cssi/SciSciGPT-SciSciNet huggingface dataset:
Most Commonly Mutated Genes in High-Grade Serous Ovarian Carcinoma Are Nonessential for Ovarian Surface Epithelial Stem Cell Transformation

Summary High-grade serous ovarian carcinoma (HGSOC) is the fifth leading cause of cancer-related deaths of women in the United States. Disease-associated mutations have been identified by the Cancer Genome Atlas Research Network. However, aside from mutations in TP53 or the RB1 pathway that are common in HGSOC, the contributions of mutation combinations are unclear. Here, we report CRISPR mutagenesis of 20 putative HGSOC driver genes to identify combinatorial disruptions of genes that transform either ovarian surface epithelium stem cells (OSE-SCs) or non-stem cells (OSE-NSs). Our results support the OSE-SC theory of HGSOC initiation and suggest that most commonly mutated genes in HGSOC have no effect on OSE-SC transformation initiation. Our results indicate that disruption of TP53 and PTEN, combined with RB1 disruption, constitutes a core set of mutations driving efficient transformation in vitro. The combined data may contribute to more accurate modeling of HGSOC development.
Reasons For Both Pessimism And Optimism: A Response To The Commentaries

We had thought that our piece presented about as bleak a picture of the current privacy climate as could be imagined. These three superb commentaries, however, suggest that we may have fallen short of plumbing the depths of the current problem. Yet, if they are, possibly, even more despairing than we are about the current state of affairs, we read these commentaries as more optimistic about the prospects for an improvement of the situation.
Secrets and Likes: The Drive for Privacy and the Difficulty of Achieving It in the Digital Age

We review different streams of social science literature on privacy with the goal of understanding consumer privacy decision making and deriving implications for policy. We focus on psychological and economic factors influencing both consumers’ desire and consumers’ ability to protect their privacy, either through individual action or the implementation of regulations applying to firms. Contrary to depictions of online sharing behaviors as careless, we show how consumers fundamentally care about online privacy, and present evidence of numerous actions they take to protect it. However, we also document how prohibitively difficult it is to attain desired, or even desirable, levels of privacy through individual action alone. The remaining instrument for privacy protection is policy intervention. However, again for both psychological and economic reasons, the collective impetus for adequate intervention is often countervailed by powerful interests that oppose it.
Performance of Temporal Artery Temperature Measurement in Ruling Out Fever: Implications for COVID-19 Screening.

The use of non-invasive temperature testing methods like temporal artery thermometers (TATs) is growing exponentially in the face of the ongoing COVID-19 pandemic. We performed a retrospective analysis of over 1.8 million emergency department electronic health records to identify assess the performance of TAT measurement using patients with near-contemporaneous temperature measurements taken via rectal or oral approaches. Using over 17,000 matched measurements, we show poor fever sensitivity using TAT. We show that sensitivity is significantly improved by lowering the fever threshold and describe limits of agreement between methods of measurement. Our findings suggest that private, public, and healthcare delivery organizations may need to reconsider how we perform high-volume screening during this time of crisis and has implications for return-to-work protocols.
Identification of Split-GAL4 Drivers and Enhancers That Allow Regional Cell Type Manipulations of the Drosophila melanogaster Intestine

The Drosophila adult midgut is a model epithelial tissue composed of a few major cell types with distinct regional identities. One of the limitations to its analysis is the lack of tools to manipulate gene expression based on these regional identities. To overcome this obstacle, we applied the intersectional split-GAL4 system to the adult midgut and report 653 driver combinations that label cells by region and cell type. We first identified 424 split-GAL4 drivers with midgut expression from ∼7300 drivers screened, and then evaluated the expression patterns of each of these 424 when paired with three reference drivers that report activity specifically in progenitor cells, enteroendocrine cells, or enterocytes. We also evaluated a subset of the drivers expressed in progenitor cells for expression in enteroblasts using another reference driver. We show that driver combinations can define novel cell populations by identifying a driver that marks a distinct subset of enteroendocrine cells expressing genes usually associated with progenitor cells. The regional cell type patterns associated with the entire set of driver combinations are documented in a freely available website, providing information for the design of thousands of additional driver combinations to experimentally manipulate small subsets of intestinal cells. In addition, we show that intestinal enhancers identified with the split-GAL4 system can confer equivalent expression patterns on other transgenic reporters. Altogether, the resource reported here will enable more precisely targeted gene expression for studying intestinal processes, epithelial cell functions, and diseases affecting self-renewing tissues.
Spectral sparsification of simplicial complexes for clustering and label propagation

As a generalization of the use of graphs to describe pairwise interactions, simplicial complexes can be used to model higher-order interactions between three or more objects in complex systems. There has been a recent surge in activity for the development of data analysis methods applicable to simplicial complexes, including techniques based on computational topology, higher-order random processes, generalized Cheeger inequalities, isoperimetric inequalities, and spectral methods. In particular, spectral learning methods (e.g. label propagation and clustering) that directly operate on simplicial complexes represent a new direction emerging from the confluence of computational topology and machine learning. To apply spectral methods in learning to massive datasets modeled as simplicial complexes, we sparsify simplicial complexes, while preserving the spectrum of the associated Laplacian operators. We show that the theory of Spielman and Srivastava for the sparsification of graphs extends to simplicial complexes via the up Laplacian. In particular, we introduce a generalized effective resistance for simplexes, provide an algorithm for sparsifying simplicial complexes at a fixed dimension, and give a specific version of the generalized Cheeger inequality for weighted simplicial complexes. Finally, we introduce higher-order generalizations of spectral clustering and label propagation for simplicial complexes and demonstrate via experiments the utility of the proposed spectral sparsification method for these applications.
Metaplasticity in Multistate Memristor Synaptic Networks

Recent studies have shown that metaplastic synapses can retain information longer than simple binary synapses and are beneficial for continual learning. In this paper, we explore the multistate metaplastic synapse characteristics in the context of high retention and reception of information. Inherent behavior of a memristor emulating the multistate synapse is employed to capture the metaplastic behavior. An integrated neural network study for learning and memory retention is performed by integrating the synapse in a 5 × 3 crossbar at the circuit level and 128 × 128 network at the architectural level. An on-device training circuitry ensures the dynamic learning in the network. In the 128 × 128 network, it is observed that the number of input patterns the multistate synapse can classify is ∼ 2.1× that of a simple binary synapse model, at a mean accuracy of > 75%.
Roman wealth and wealth inequality in comparative perspective

In 2013, Barack Obama called rising inequality “the defining challenge of our time”. Since the Financial Crisis and Great Recession of 2007-9, the gap between the haves and have-nots has attracted unprecedented attention in politics, the media and academia.1 Students of the more distant past have also begun to embrace this trend. Economists are once again looking back in time, inspired in no small measure by the broad impact of the work of Thomas Piketty.2 Historians are laboring hard to unearth and publish relevant data. Thanks to their efforts, we are now able to glimpse the contours of changes in the concentration of income and wealth over the very long run, at least in some parts of the world.3 Archaeologists have been joining the fray, gathering and analyzing plausible proxies of inequality such as house sizes.
Restrictions on parameters of partial difference sets in nonabelian groups

A partial difference set $S$ in a finite group $G$ satisfying $1 \notin S$ and $S = S^{-1}$ corresponds to an undirected strongly regular Cayley graph ${\rm Cay}(G,S)$. While the case when $G$ is abelian has been thoroughly studied, there are comparatively few results when $G$ is nonabelian. In this paper, we provide restrictions on the parameters of a partial difference set that apply to both abelian and nonabelian groups and are especially effective in groups with a nontrivial center. In particular, these results apply to $p$-groups, and we are able to rule out the existence of partial difference sets in many instances.
Executive Underreach, in Pandemics and Otherwise

Legal scholars are familiar with the problem of executive overreach, especially in emergencies. But sometimes, instead of being too audacious or extreme, a national executive's attempts to address a true threat prove far too limited and insubstantial. In this Essay, we seek to define and clarify the phenomenon of executive underreach, with special reference to the COVID-19 crisis; to outline ways in which such underreach may compromise constitutional governance and the international legal order; and to suggest a partial remedy.
Central-difference time-lapse 4D seismic full-waveform inversion

ABSTRACTRepeated seismic surveys contain valuable information regarding time-lapse (4D) changes in the subsurface. Full-waveform inversion (FWI) of seismic data can provide high-resolution estimate...
QBMMlib: A library of quadrature-based moment methods

QBMMlib is an open source Mathematica package of quadrature-based moment methods and their algorithms. Such methods are commonly used to solve fully-coupled disperse flow and combustion problems, though formulating and closing the corresponding governing equations can be complex. QBMMlib aims to make analyzing these techniques simple and more accessible. Its routines use symbolic manipulation to formulate the moment transport equations for a population balance equation and a prescribed dynamical system. However, the resulting moment transport equations are unclosed. QBMMlib trades the moments for a set of quadrature points and weights via an inversion algorithm, of which several are available. Quadratures then closes the moment transport equations. Embedded code snippets show how to use QBMMlib, with the algorithm initialization and solution spanning just 13 total lines of code. Examples are shown and analyzed for linear harmonic oscillator and bubble dynamics problems.
Cosmic Ray Driven Outflows from the Large Magellanic Cloud: Contributions to the LMC Filament

In this paper, we build from previous work (Bustard et al. 2018) and present simulations of recent (within the past Gyr), magnetized, cosmic ray driven outflows from the Large Magellanic Cloud (LMC), including our first attempts to explicitly use the derived star formation history of the LMC to seed outflow generation. We run a parameter set of simulations for different LMC gas masses and cosmic ray transport treatments, and we make preliminary comparisons to published outflow flux estimates, neutral and ionized hydrogen observations, and Faraday rotation measure maps. We additionally report on the gas mass that becomes unbound from the LMC disk and swept by ram pressure into the Trailing Magellanic Stream. We find that, even for our largest outburst, the mass contribution to the Stream is still quite small, as much of the outflow-turned-halo gas is shielded on the LMC's far-side due to the LMC's primarily face-on infall through the Milky Way halo over the past Gyr. On the LMC's near-side, past outflows have fought an uphill battle against ram pressure, with near-side halo mass being at least a factor of a few smaller than the far-side. Absorption line studies probing only the LMC foreground, then, may be severely underestimating the total mass of the LMC halo formed by outflows.
On inefficiency of markowitz-style investment strategies when drawdown is important

The focal point of this paper is the issue of “drawdown” which arises in recursive betting scenarios and related applications in the stock market. Roughly speaking, drawdown is understood to mean drops in wealth over time from peaks to subsequent lows. Motivated by the fact that this issue is of paramount concern to conservative investors, we dispense with the classical variance as the risk metric and work with drawdown and mean return as the risk-reward pair. In this setting, the main results in this paper address the so-called “efficiency” of linear time-invariant (LTI) investment feedback strategies which correspond to Markowitz-style schemes in the finance literature. Our analysis begins with the following principle which is widely used in finance: Given two investment opportunities, if one of them has higher risk and lower return, it will be deemed to be inefficient or strictly dominated and generally rejected in the marketplace. In this framework, with risk-reward pair as described above, our main result is that classical Markowitz-style strategies are inefficient. To establish this, we use a new investment strategy which involves a time-varying linear feedback block K (k), called the drawdown modulator. Using this instead of the original LTI feedback block K in the Markowitz scheme, the desired domination is obtained. As a bonus, it is also seen that the modulator assures a worst-case level of drawdown protection with probability one.
Ionization, Kinematics, and Extent of the Diffuse Ionized Gas Halo of NGC 5775

We present key results from deep spectra of the diffuse ionized gas halo of the edge-on galaxy NGC 5775. [N II] λ6583 has been detected up to z ≈ 13 kpc above the plane in one of two vertically oriented long slits—making this the spiral galaxy with the greatest spectroscopically detected halo extent in emission. Key diagnostic line ratios have been measured up to z ≈ 8 kpc, allowing the source of ionization and physical state to be probed. Ionization by a dilute radiation field from massive stars in the disk can explain some of the line ratio behavior, but departures from this picture are clearly indicated, most strongly by the rise of [O III]/Hα with z. Velocities of the gas in both slits approach the systemic velocity of the galaxy at several kiloparsecs above the plane. We interpret this trend as a decrease in rotation velocity with z, with essentially no rotation at heights of several kiloparsecs. Such a trend was observed in the edge-on galaxy NGC 891, but here much more dramatically. This falloff is presumably due to the gravitational potential changing with z, but will also depend on the hydrodynamic nature of the disk-halo cycling of gas and projection effects. More detailed modeling of the ionization and kinematics of this and other edge-ons will be presented in future papers.
Early Forecasting of Text Classification Accuracy and F-Measure with Active Learning

When creating text classification systems, one of the major bottlenecks is the annotation of training data. Active learning has been proposed to address this bottleneck using stopping methods to minimize the cost of data annotation. An important capability for improving the utility of stopping methods is to effectively forecast the performance of the text classification models. Forecasting can be done through the use of logarithmic models regressed on some portion of the data as learning is progressing. A critical unexplored question is what portion of the data is needed for accurate forecasting. There is a tension, where it is desirable to use less data so that the forecast can be made earlier, which is more useful, versus it being desirable to use more data, so that the forecast can be more accurate. We find that when using active learning it is even more important to generate forecasts earlier so as to make them more useful and not waste annotation effort. We investigate the difference in forecasting difficulty when using accuracy and F-measure as the text classification system performance metrics and we find that F-measure is more difficult to forecast. We conduct experiments on seven text classification datasets in different semantic domains with different characteristics and with three different base machine learning algorithms. We find that forecasting is easiest for decision tree learning, moderate for Support Vector Machines, and most difficult for neural networks.
Diffeomorphisms, symplectic forms and Kodaira fibrations

As was recently pointed out by McMullen and Taubes [Math. Res. Lett. 6 (1999) 681-696], there are 4-manifolds for which the diffeomorphism group does not act transitively on the deformation classes of orientation-compatible symplectic structures. This note points out some other 4-manifolds with this property which arise as the orientation-reversed versions of certain complex surfaces constructed by Kodaira [J. Analyse Math. 19 (1967) 207-215]. While this construction is arguably simpler than that of McMullen and Taubes, its simplicity comes at a price: the examples exhibited herein all have large fundamental groups.
The generalized zero-mode supersymmetry scheme and the confluent algorithm

Abstract We show the relationship between the mathematical framework used in recent papers by Rosu et al. (2014) [1–3] and the second-order confluent supersymmetric quantum mechanics. In addition, we point out several immediate generalizations of the approach taken in the latter references. Furthermore, it is shown how to apply the generalized scheme to the Dirac and to the Fokker–Planck equation.
Data Handling and Assimilation for Solar Event Prediction

The prediction of solar flares, eruptions, and high energy particle storms is of great societal importance. The data mining approach to forecasting has been shown to be very promising. Benchmark datasets are a key element in the further development of data-driven forecasting. With one or more benchmark data sets established, judicious use of both the data themselves and the selection of prediction algorithms is key to developing a high quality and robust method for the prediction of geo-effective solar activity. We review here briefly the process of generating benchmark datasets and developing prediction algorithms.
Superconformal multi-black hole moduli spaces in four dimensions

Quantum mechanics on the moduli space of N supersymmetric Reissner- Nordstrom black holes is shown to admit 4 supersymmetries using an unconventional su- permultiplet which contains 3N bosons and 4N fermions. A near-horizon limit is found in which the quantum mechanics of widely separated black holes decouples from that of strongly-interacting, near-coincident black holes. This near-horizon theory is shown to have an enhanced D(2;1;0) superconformal symmetry. The bosonic symmetries are SL(2; R) conformal symmetry and SU(2)£ SU(2) R-symmetry arising from spatial rotations and the R-symmetry ofN = 2 supergravity.
The Elliott-Halberstam conjecture implies the Vinogradov least quadratic nonresidue conjecture

For each prime p, let n(p) denote the least quadratic nonresidue modulo p. Vinogradov conjectured that n(p) = O(pe) for every fixed e > 0. This conjecture follows from the generalized Riemann hypothesis and is known to hold for almost all primes p but remains open in general. In this paper, we show that Vinogradov’s conjecture also follows from the Elliott–Halberstam conjecture on the distribution of primes in arithmetic progressions, thus providing a potential “nonmultiplicative” route to the Vinogradov conjecture. We also give a variant of this argument that obtains bounds on short centered character sums from “Type II” estimates of the type introduced recently by Zhang and improved upon by the Polymath project or from bounds on the level of distribution on variants of the higher-order divisor function. In particular, an improvement over the Burgess bound would be obtained if one had Type II estimates with level of distribution above 2 3 (when the conductor is not cube-free) or 3 4 (if the conductor is cube-free); morally, one would also obtain such a gain if one had distributional estimates on the third or fourth divisor functions τ3 or τ4 at level above 2 3 or 3 4, respectively. Some applications to the least primitive root are also given.
A Three-Dimensional Constitutive Model for Polycrystalline Shape Memory Alloys Under Large Strains Combined With Large Rotations

Shape Memory Alloys (SMAs) has been widely aware of working as actuators for active/smart morphing structures in the engineering industry. Because of the high actuation energy density of SMAs, compared to other active materials, structures integrated with SMA-based actuators has high advantage in terms of trade-offs between overall structure weight, integrity and functionality. The majority of available constitutive models for SMAs are developed within the infinitesimal strain regime. However, it was reported that particular SMAs can generate transformation strains nearly up to 8%-10%, for which the adopted infinitesimal strain assumption is no longer appropriate. Furthermore, industry applications may require SMA actuators undergo large rotation deformation at work. Combining the above two facts, a constitutive model for SMAs developed on a finite deformation framework is required. A three-dimensional constitutive model for SMAs considering large strains with large rotations is proposed in this work. This model utilizes the logarithmic strain as a finite strain measure for large deformation analysis so that its rate form hypo-elastic constitutive relation can be consistently integrated to deliver a free energy based hyper-elastic constitutive relation. The martensitic volume fraction and the second-order transformation strain tensor are chosen as the internal state variables to characterize the inelastic response exhibited by polycrystalline SMAs. The presented formulation and its numerical implementation scheme can be extended in future work for the incorporation of other inelastic phenomena such as transformation-induced plasticity, viscoplasticity and creep under large deformations.
Growth of strontium ruthenate films by hybrid molecular beam epitaxy

We report on the growth of epitaxial Sr2RuO4 films using a hybrid molecular beam epitaxy approach in which a volatile precursor containing RuO4 is used to supply ruthenium and oxygen. The use of the precursor overcomes a number of issues encountered in traditional molecular beam epitaxy that uses elemental metal sources. Phase-pure, epitaxial thin films of Sr2RuO4 are obtained. At high substrate temperatures, growth proceeds in a layer-by-layer mode with intensity oscillations observed in reflection high-energy electron diffraction. Films are of high structural quality, as documented by x-ray diffraction, atomic force microscopy, and transmission electron microscopy. The method should be suitable for the growth of other complex oxides containing ruthenium, opening up opportunities to investigate thin films that host rich exotic ground states.
Symmetries of higher dimensional black holes

We prove that if a stationary, real analytic, asymptotically flat vacuum black hole spacetime of dimension n ≥ 4 contains a non-degenerate horizon with compact cross-sections that are transverse to the stationarity generating Killing vector field then, for each connected component of the black hole's horizon, there is a Killing field which is tangent to the generators of the horizon. For the case of rotating black holes, the stationarity generating Killing field is not tangent to the horizon generators and therefore the isometry group of the spacetime is at least two dimensional. Our proof relies on significant extensions of our earlier work on the symmetries of spacetimes containing a compact Cauchy horizon, allowing now for non-closed generators of the horizon.
Privacy-Preserving Shortest Path Computation

Navigation is one of the most popular cloud computing services. But in virtually all cloud-based navigation systems, the client must reveal her location and destination to the cloud service provider in order to learn the fastest route. In this work, we present a cryptographic protocol for navigation on city streets that provides privacy for both the client’s location and the service provider’s routing data. Our key ingredient is a novel method for compressing the next-hop routing matrices in networks such as city street maps. Applying our compression method to the map of Los Angeles, for example, we achieve over tenfold reduction in the representation size. In conjunction with other cryptographic techniques, this compressed representation results in an ecient protocol suitable for fully-private real-time navigation on city streets. We demonstrate the practicality of our protocol by benchmarking it on real street map data for major cities such as San Francisco and Washington, D.C.
Pair correlation functions of strongly coupled two-temperature plasma

Using molecular dynamics simulations, we perform the first direct tests of three proposed models for the pair correlation functions of strongly coupled plasmas with species of unequal temperature. The models are all extensions of the Ornstein–Zernike/hypernetted-chain theory used to good success for equilibrium plasmas. Each theory is evaluated at several coupling strengths, temperature ratios, and mass ratios for a model plasma in which the electrons are positively charged. We show that the model proposed by Seuferling et al. [Phys. Rev. A 40, 323 (1989)] agrees well with molecular dynamics over a wide range of mass and temperature ratios, as well as over a range of coupling strength similar to that of the equilibrium hypernetted-chain (HNC) theory. The SVT model also correctly predicts the strength of interspecies correlations and exhibits physically reasonable long-wavelength limits of the static structure factors. Comparisons of the SVT model with the Yukawa one-component plasma (YOCP) model are used ...
Spectra associated to symmetric monoidal bicategories

We show how to construct a  –bicategory from a symmetric monoidal bicategory and use that to show that the classifying space is an infinite loop space upon group completion. We also show a way to relate this construction to the classic  –category construction for a permutative category. As an example, we use this machinery to construct a delooping of the K–theory of a rig category as defined by Baas, Dundas and Rognes [2].
Vorticity Budget of Weak Thermal Convection in Keplerian Disks

By employing the equations of mean-square vorticity (enstrophy) fluctuations in strong shear flows, we demonstrate that, unlike energy production of turbulent vorticity in nonrotating shear flows, the turbulent vorticity of weak convection in Keplerian disks cannot gain energy from vortex stretching/tilting by background shear unless the associated Reynolds stresses are negative. This is because the epicyclic motion is an energy sink of the radial component of mean-square turbulent vorticity in Keplerian disks when Reynolds stresses are positive. Consequently, weak convection cannot be self-sustained in Keplerian flows. This agrees with the results implied from the equations of mean-square velocity fluctuations in strong shear flows. Our analysis also sheds light on the explanation of the simulation result in which positive kinetic helicity is produced by the Balbus-Hawley instability in a vertically stratified Keplerian disk. We also comment on the possibility of outward angular momentum transport by strong convection based on azimuthal pressure perturbations and directions of energy cascade.
Distributed Robust Adaptive Frequency Control of Power Systems With Dynamic Loads

This article investigates the frequency control of multimachine power systems subject to uncertain and dynamic net loads. We propose distributed internal model controllers that coordinate synchronous generators and demand response to tackle the unpredictable nature of net loads. Frequency stability is formally guaranteed via Lyapunov analysis. Numerical simulations on the IEEE 68-bus test system demonstrate the effectiveness of the controllers.
Enzyme-based logic analysis of biomarkers at physiological concentrations: and gate with double-sigmoid "filter" response.

We report the first realization of a biomolecular AND gate function with double-sigmoid response (sigmoid in both inputs). Two enzyme biomarker inputs activate the gate output signal, which can then be used as indicating liver injury, but only when both of these inputs have elevated pathophysiological concentrations, effectively corresponding to logic-1 of the binary gate functioning. At lower, normal physiological concentrations, defined as logic-0 inputs, the liver-injury output levels are not obtained. High-quality gate functioning in handling of various sources of noise, on time scales of relevance to potential applications, is enabled by utilizing “filtering” effected by a simple added biocatalytic process. The resulting gate response is sigmoid in both inputs when proper system parameters are chosen, and the gate properties are theoretically analyzed within a model devised to evaluate its noise-handling properties.
Precise complexity guarantees for pointer analysis via Datalog with extensions

Pointer analysis is a fundamental static program analysis for computing the set of objects that an expression can refer to. Decades of research has gone into developing methods of varying precision and efficiency for pointer analysis for programs that use different language features, but determining precisely how efficient a particular method is has been a challenge in itself. For programs that use different language features, we consider methods for pointer analysis using Datalog and extensions to Datalog. When the rules are in Datalog, we present the calculation of precise time complexities from the rules using a new algorithm for decomposing rules for obtaining the best complexities. When extensions such as function symbols and universal quantification are used, we describe algorithms for efficiently implementing the extensions and the complexities of the algorithms.
A Decentralized Control Framework for Energy-Optimal Goal Assignment and Trajectory Generation

This paper proposes a decentralized approach for solving the problem of moving a swarm of agents into a desired formation. We propose a decentralized assignment algorithm which prescribes goals to each agent using only local information. The assignment results are then used to generate energy-optimal trajectories for each agent which have guaranteed collision avoidance through safety constraints. We present the conditions for optimality and discuss the robustness of the solution. The efficacy of the proposed approach is validated through a numerical case study to characterize the framework’s performance on a set of dynamic goals.
Angular Momentum in Giant Molecular Clouds. I. The Milky Way

We present a detailed analysis comparing the velocity fields in molecular clouds and the atomic gas that surrounds them in order to address the origin of the gradients. To that end, we present first-moment intensity-weighted velocity maps of the molecular clouds and surrounding atomic gas. The maps are made from high-resolution {sup 13}CO observations and 21 cm observations from the Leiden/Argentine/Bonn Galactic H I Survey. We find that (1) the atomic gas associated with each molecular cloud has a substantial velocity gradient-ranging from 0.02 to 0.07 km s{sup -1} pc{sup -1}-whether or not the molecular cloud itself has a substantial linear gradient. (2) If the gradients in the molecular and atomic gas were due to rotation, this would imply that the molecular clouds have less specific angular momentum than the surrounding H I by a factor of 1-6. (3) Most importantly, the velocity gradient position angles in the molecular and atomic gas are generally widely separated-by as much as 130 deg. in the case of the Rosette molecular cloud. This result argues against the hypothesis that molecular clouds formed by simple top-down collapse from atomic gas.
Non-Linearities in Fiscal Policy:The Role of Debt

Empirical evidence shows that fiscal multipliers depend on the state of the cycle, the nature of fiscal policy and the level of debt. In other words, evidence points to non-linearities in the effects of fiscal policy. This paper provides a framework to examine the role of the level of government debt in the assessment of consolidation policies across the business cycle, allowing for the consolidation multiplier to depend on the level of debt at the time of consolidation. The empirical analysis, which uses a panel of 13 countries between 1980 and 2014, finds that when debt is high, fiscal consolidations based on tax increases are in general self-defeating, in that they result in an increase of the debt-to-GDP ratio. Instead, cutting public expenditure has a less pronounced effect on economic activity and can stabilize debt. The initial level of debt in an economy, when a fiscal consolidation is implemented, appears to work as a channel in explaining evidence of state-dependence of the different consolidation instruments.
SiO Masers in the Galactic Bulge and Disk: Kinematics from the BAaDE Survey

We present the first results from the BAaDE (Bulge Asymmetries and Dynamic Evolution) survey. Though only a subset of the complete survey ($\sim$2700 out of $\sim$20000 final sources), our data comprise the largest radio kinematic survey to date of stellar SiO masers observed toward the Galactic bulge and plane from $-15^\circ 8$, colors consistent with Mira variables and mass losing AGB stars. We see a clean division into two kinematic populations: a kinematically cold ($\sigma \sim 50\rm\ km\ sec^{-1}$) population that we propose is in the foreground disk, consisting of giants with 2MASS $Ks 5.5$. Only the kinematically hot giants with $Ks>5.5$ include the reddest stars. Adopting 8.3 kpc to the Galactic Center, and correcting for foreground extinction, we find that most of the sources have $M_{bol} \sim -5$, consistent with their being luminous, and possibly intermediate age, AGB stars. We note some tension between the possibly intermediate age of the kinematically hot population, and its high velocity dispersion compared to the disk.
Identifying designs from incomplete, fragmented cultural heritage objects by curve-pattern matching

The study of cultural heritage objects with embellished realistic and abstract designs made up of connected and intertwined curves crosscuts a number of related disciplines, including archaeology, art history, and heritage management. However, many objects, such as pottery sherds found in the archaeological record, are fragmentary, making the underlying complete designs unknowable at the scale of the sherd fragment. The challenge to reconstruct and study complete designs is stymied because (1) most fragmentary cultural heritage objects contain only a small portion of the underlying full design, (2) in the case of a stamping application, the same design may be applied multiple times with spatial overlap on one object, and (3) curve patterns detected on an object are usually incomplete and noisy. As a result, traditional curve-pattern matching algorithms, such as Chamfer matching, may perform poorly in identifying the underlying design. We develop a new partial-to-global curve matching algorithm to address these challenges and better identify the full design from a fragmented cultural heritage object. Specifically, we develop the algorithm to identify the designs of the carved wooden paddles of the Southeastern Woodlands from unearthed pottery sherds. A set of pottery sherds, curated at Georgia Southern University, are used to test the proposed algorithm, with promising results.
Enhancement of the Magnetic Moment of the Electron due to a Topological Defect

In the framework of the theory of defects/three-dimensional gravitation, a positive correction to the magnetic moment of the electron bound to a disclination in a dielectric solid is obtained.
Big polynomial rings and Stillman’s conjecture

The purpose of this paper is to prove that certain limits of polynomial rings are themselves polynomial rings, and show how this observation can be used to deduce some interesting results in commutative algebra. In particular, we give two new proofs of Stillman's conjecture. The first is similar to that of Ananyan-Hochster, though more streamlined; in particular, it establishes the existence of small subalgebras. The second proof is completely different, and relies on a recent noetherianity result of Draisma.
RADIATION MAGNETOHYDRODYNAMIC SIMULATIONS OF PROTOSTELLAR COLLAPSE: LOW-METALLICITY ENVIRONMENTS

Among many physical processes involved in star formation, radiation transfer is one of the key processes because it dominantly controls the thermodynamics. Because metallicities control opacities, they are one of the important environmental parameters that affect star formation processes. In this work, I investigate protostellar collapse in solar-metallicity and low-metallicity (Z = 0.1 Z ☉) environments using three-dimensional radiation hydrodynamic and magnetohydrodynamic simulations. Because radiation cooling in high-density gas is more effective in low-metallicity environments, first cores are colder and have lower entropies. As a result, first cores are smaller, less massive, and have shorter lifetimes in low-metallicity clouds. Therefore, first cores would be less likely to be found in low-metallicity star forming clouds. This also implies that first cores tend to be more gravitationally unstable and susceptible to fragmentation. The evolution and structure of protostellar cores formed after the second collapse weakly depend on metallicities in the spherical and magnetized models, despite the large difference in the metallicities. Because this is due to the change of the heat capacity by dissociation and ionization of hydrogen, it is a general consequence of the second collapse as long as the effects of radiation cooling are not very large during the second collapse. On the other hand, the effects of different metallicities are more significant in the rotating models without magnetic fields, because they evolve slower than other models and therefore are more affected by radiation cooling.
On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems

Convolutional Neural Networks (CNNs) have shown a great deal of success in diverse application domains including computer vision, speech recognition, and natural language processing. However, as the size of datasets and the depth of neural network architectures continue to grow, it is imperative to design high-performance and energy-efficient computing hardware for training CNNs. In this paper, we consider the problem of designing specialized CPU-GPU based heterogeneous manycore systems for energy-efficient training of CNNs. It has already been shown that the typical on-chip communication infrastructures employed in conventional CPU-GPU based heterogeneous manycore platforms are unable to handle both CPU and GPU communication requirements efficiently. To address this issue, we first analyze the on-chip traffic patterns that arise from the computational processes associated with training two deep CNN architectures, namely, LeNet and CDBNet, to perform image classification. By leveraging this knowledge, we design a hybrid Network-on-Chip (NoC) architecture, which consists of both wireline and wireless links, to improve the performance of CPU-GPU based heterogeneous manycore platforms running the above-mentioned CNN training workloads. The proposed NoC achieves 1.8× reduction in network latency and improves the network throughput by a factor of 2.2 for training CNNs, when compared to a highly-optimized wireline mesh NoC. For the considered CNN workloads, these network-level improvements translate into 25 percent savings in full-system energy-delay-product (EDP). This demonstrates that the proposed hybrid NoC for heterogeneous manycore architectures is capable of significantly accelerating training of CNNs while remaining energy-efficient.
OFFSET ACTIVE GALACTIC NUCLEI AS TRACERS OF GALAXY MERGERS AND SUPERMASSIVE BLACK HOLE GROWTH

Offset active galactic nuclei (AGNs) are AGNs that are in ongoing galaxy mergers, which produce kinematic offsets in the AGNs relative to their host galaxies. Offset AGNs are also close relatives of dual AGNs. We conduct a systematic search for offset AGNs in the Sloan Digital Sky Survey by selecting AGN emission lines that exhibit statistically significant line-of-sight velocity offsets relative to systemic. From a parent sample of 18,314 Type 2 AGNs at z < 0.21, we identify 351 offset AGN candidates with velocity offsets of 50 km s–1 < |Δv| < 410 km s–1. When we account for projection effects in the observed velocities, we estimate that 4%-8% of AGNs are offset AGNs. We designed our selection criteria to bypass velocity offsets produced by rotating gas disks, AGN outflows, and gravitational recoil of supermassive black holes, but follow-up observations are still required to confirm our candidates as offset AGNs. We find that the fraction of AGNs that are offset candidates increases with AGN bolometric luminosity, from 0.7% to 6% over the luminosity range 43 < log (L bol) [erg s–1] <46. If these candidates are shown to be bona fide offset AGNs, then this would be direct observational evidence that galaxy mergers preferentially trigger high-luminosity AGNs. Finally, we find that the fraction of AGNs that are offset AGN candidates increases from 1.9% at z = 0.1 to 32% at z = 0.7, in step with the growth in the galaxy merger fraction over the same redshift range.
Proof of factorization using background field method of QCD

Abstract Factorization theorem plays the central role at high energy colliders to study standard model and beyond standard model physics. The proof of factorization theorem is given by Collins, Soper and Sterman to all orders in perturbation theory by using diagrammatic approach. One might wonder if one can obtain the proof of factorization theorem through symmetry considerations at the lagrangian level. In this paper we provide such a proof.
Testing Modified Dark Matter with galaxy clusters: Does dark matter know about the cosmological constant?

We discuss the possibility that the cold dark matter mass profiles contain information on the cosmological constant Λ, and that such information constrains the nature of cold dark matter (CDM). We call this approach Modified Dark Matter (MDM). In particular, we examine the ability of MDM to explain the observed mass profiles of 13 galaxy clusters. Using general arguments from gravitational thermodynamics, we provide a theoretical justification for our MDM mass profile. In order to properly fit the shape of the mass profiles in galaxy clusters, we find it necessary to generalize the MDM mass profile from the one we used previously to fit galactic rotation curves. We successfully compare it to the NFW mass profiles both on cluster and galactic scales, though differences in form appear with the change in scales. Our results suggest that indeed the CDM mass profiles contain information about the cosmological constant in a nontrivial way.
Resonance enhanced two-photon cavity ring-down spectroscopy of vibrational overtone bands: A proposal.

This paper presents an analysis of near-resonant, rovibrational two-photon spectroscopy and the use of cavity ring-down spectroscopy for its detection. Expressions are derived for the photon absorption rate of a three-level system, correct to all orders and the simpler expressions that result from various approximations. The analysis includes the angular momentum projection degeneracies and linear or circular polarization of the exciting field. Expressions are derived for the rate of two-photon power loss for light inside a resonant cavity. Explicit calculations are made for excitation of the ν3 mode of 12C16O2 for which the two-photon excitation spectrum is dominated by a single v3 = 0 → 2, Q(16) line at ν=2335.826 cm-1. This transition has an intermediate v3 = 0 → 1, P(16) one-photon transition that is off resonance by 0.093 cm-1 (2.8 GHz). At 1 Torr total pressure, the Q(16) two-photon transition is calculated to have a cross section of 2.99 × 10-38 cm4 s per CO2 molecule in the J = 16 state or 2.24 × 10-39 cm4 s per CO2 molecule at 300 K. The analysis of the sensitivity limits for 2-photon cavity ring-down spectroscopy predicts a theoretical detection limit of 32 ppq (10-15) Hz-1/2 for 12C16O2, higher sensitivity than has been realized using one-photon absorption. The analysis predicts that most polyatomic molecules will have sparse, Doppler-free two-photon absorption spectra, which will dramatically increase the selectivity of trace gas detection of samples with multiple components with overlapping absorption bands. This is demonstrated by the predicted mid-IR two-photon absorption spectrum of butadiene using theoretical spectroscopic constants.
Deep Quantum Geometry of Matrices

We employ machine learning techniques to provide accurate variational wave functions for matrix quantum mechanics, with multiple bosonic and fermionic matrices. The variational quantum Monte Carlo method is implemented with deep generative flows to search for gauge-invariant low-energy states. The ground state (and also long-lived metastable states) of an SU(N) matrix quantum mechanics with three bosonic matrices, and also its supersymmetric “mini-BMN” extension, are studied as a function of coupling and N. Known semiclassical fuzzy sphere states are recovered, and the collapse of these geometries in more strongly quantum regimes is probed using the variational wave function. We then describe a factorization of the quantum mechanical Hilbert space that corresponds to a spatial partition of the emergent geometry. Under this partition, the fuzzy sphere states show a boundary-law entanglement entropy in the large N limit.
Yang–Mills Replacement

We develop an analog of harmonic replacement in the gauge theory context. The idea behind harmonic replacement dates back to Schwarz and Perron. The technique, as introduced by Jost and further developed by Colding and Minicozzi, involves taking a map $$v:\Sigma \rightarrow M$$ defined on a surface $$\Sigma $$ and replacing its values on a small ball $$B^2\subset \Sigma $$ with a harmonic map u that has the same values as v on the boundary $$\partial B^2$$ . The resulting map on $$\Sigma $$ has lower energy, and repeating this process on balls covering $$\Sigma $$ , one can obtain a global harmonic map in the limit. We develop the analogous procedure in the gauge theory context. We take a connection B on a bundle over a four-manifold X, and replace it on a small ball $$B^4\subset X$$ with a Yang–Mills connection A that has the same restriction to the boundary $${\partial B^4}$$ as B. As in the harmonic replacement results of Colding and Minicozzi, we have bounds on the difference $$||{B-A}||_{{{L^{2}_{1}(B^4)}}}^2$$ in terms of the drop in energy, and we only require that the connection B has small energy on the ball, rather than small $$C^0$$ oscillation. Throughout, we work with connections of the lowest possible regularity $${{L^{2}_{1}(X)}}$$ , the natural choice for this context, and so our gauge transformations are in $${{L^{2}_{2}(X)}}$$ and therefore almost but not quite continuous, leading to more delicate arguments than in higher regularity.