cssi/SciSciGPT-SciSciNet huggingface dataset:
The Rise of Multiunit Firms in U.S. Manufacturing

Abstract The modern multiunit enterprise has been touted by historians and economic historians as a major and important phase of organizational change and a significant source of growth. However, most studies concerning this phenomenon have been based on a sample of the very largest enterprises. This article utilizes data on a complete sample of firms provided by the pioneering works of Thorp (1924) and Thorp et al. (1941) and the Census Bureau's Enterprise Statistics and other census sources to document and examine the rise of modern multiunit firms in U.S. manufacturing over the twentieth century. The analysis of the data suggests that the modern multiunit firm arose to take advantage of economies of marketing rather than those of scale and scope.
Social Networks and Contract Enforcement in IT Outsourcing.

Prior research on Information Technology Outsourcing has characterized the dominant governance modes as either ‘Formal’ or ‘Relational,’ which rely on stringent assumptions of either perfect foresight or about the extent to which one party can punish unilateral deviations by the other. We propose a third alternative for inter-firm contract governance. The social network capital offers a measure of reputation that can indicate to future trading partners the reduced likelihood of opportunistic behavior. The network of trading partners enables a community enforcement of contracting terms by providing safeguards that may not be offered by traditional measures. Based on a large dataset of public ITO announcements we examine the role that structural embeddedness can play in predicting contract duration. We find preliminary evidence suggesting that network position does matter in predicting contract structure over and above the traditional economic variables.
PALEOCLIMATE MODELING | Paleo-ENSO

Teleconnections, such as El Nino, are climate relationships over long distances, reflecting organized patterns of atmospheric and oceanic circulation that occur at interannual to decadal scales. Paleoclimatic data provide a longer temporal perspective on teleconnections prior to the period of modern instrumental records. This article provides an overview of the prominent teleconnections in the modern record, how different paleoclimatic proxies are used to reconstruct El Nino/Southern Oscillation and other teleconnections at different time scales, and how researchers assess the forcing mechanisms that cause variations of teleconnections in the paleoclimate record.
A Submillimeter Mission for the 1990s: SMMM

Submillimeter wavelengths hold the key to some of the most important aspects of astronomy. These range from star-forming molecular clouds and proto-planetary disks in our galaxy to infrared emitting galaxies at cosmological distances. Indeed, the essential problems of star-formation and galaxy-formation will be directly probed by the submillimeter spectral lines and continuum radiation emitted by these objects. Other fascinating topics falling into the submillimeter band include the Wien component of the cosmic background radiation, containing information on the nature of the early universe, and nearer to home, the spectroscopy of planetary atmospheres. Since the submillimeter contains fundamental information on the physics and chemistry of so many aspects of our universe, every effort should be made to provide the very best instrumentation for these astronomical studies. We should be capable of detection and analysis of even the most distant objects yet conceived.
Euler characteristics of finite homotopy colimits

In this short note, we provide a calculation of the Euler characteristic of a finite homotopy colimit of finite cell complexes, which depends only on the Euler characteristics of each space and resembles Mobius inversion. Versions of the result are known when the colimit is indexed by a finite category, but the behavior is more uniform when we index by finite quasicategories instead. The formula simultaneously generalizes the additive formula for Euler characteristic of a homotopy pushout and the multiplicative formula for Euler characteristic of a fiber bundle.
The Economics of Railroad "Captive Shipper" Legislation

EAG Discussion Papers are the primary vehicle used to disseminate research from economists in the Economic Analysis Group (EAG) of the Antitrust Division. These papers are intended to inform interested individuals and institutions of EAG’s research program and to stimulate comment and criticism on economic issues related to antitrust policy and regulation. The Antitrust Division encourages independent research by its economists. The views expressed herein are entirely those of the author and are not urported to reflect those of the United States Department of Justice. p
Preferential Control of Forward Reaction Kinetics in Hydrogels Crosslinked with Reversible Conjugate Additions

Molecular substitutions were used to demonstrate preferential control over the kinetic rate constants in a poly(ethylene glycol)-based hydrogel with two different reversible thia-conjugate addition...
Coherent optical clock down-conversion for microwave frequencies with 10-18 instability.

Optical atomic clocks are poised to redefine the Systeme International (SI) second, thanks to stability and accuracy more than 100 times better than the current microwave atomic clock standard. However, the best optical clocks have not seen their performance transferred to the electronic domain, where radar, navigation, communications, and fundamental research rely on less stable microwave sources. By comparing two independent optical-to-electronic signal generators, we demonstrate a 10-gigahertz microwave signal with phase that exactly tracks that of the optical clock phase from which it is derived, yielding an absolute fractional frequency instability of 1 × 10-18 in the electronic domain. Such faithful reproduction of the optical clock phase expands the opportunities for optical clocks both technologically and scientifically for time dissemination, navigation, and long-baseline interferometric imaging.
Omnipresent Chemicals: TSCA Preemption in the Wake of PFAS Contamination

Given the amplified concern surrounding PFAS, states are proactively filing lawsuits on behalf of their citizens and enacting legislation to combat this nation-wide contamination epidemic. However,...
Mitochondrial DNA Copy Number and Incident Heart Failure: The Atherosclerosis Risk in Communities (ARIC) Study.

ABSTRACT Background The association between mitochondrial DNA-copy number (mtDNA-CN) and incident heart failure (HF) in the general population is unclear. Methods We examined the association between mtDNA-CN and the risk of incident HF among 10,802 participants free of HF at baseline from the Atherosclerosis Risk in Communities (ARIC) study, a large bi-racial population-based cohort. mtDNA-CN was estimated using probe intensities on the Affymetrix Genome-Wide Human single nucleotide polymorphisms Array 6.0. Incident HF events were identified through hospital discharge codes from 1987 until 2005 and through adjudication by the ARIC HF Classification Committee since 2005. Results During a median follow-up of 23.1 years, there were 2,227 incident HF events (incidence rate 10.3 per 1000 person-years). In fully adjusted models, the hazard ratios (95% confidence intervals) for HF comparing the 2nd through 5th quintiles of mtDNA-CN to the 1st quintile were 0.91 (0.80–1.04), 0.82 (0.72–0.93), 0.81 (0.71–0.92), and 0.74 (0.65–0.85), respectively (P for trend Conclusions In this prospective cohort, mtDNA-CN was inversely associated with the risk of incident HF suggesting that reduced levels of mtDNA-CN, a biomarker of mitochondrial dysfunction, could reflect early susceptibility to HF.
Mode-assisted unsupervised learning of restricted Boltzmann machines

Restricted Boltzmann machines (RBMs) are a powerful class of generative models, but their training requires computing a gradient that, unlike supervised backpropagation on typical loss functions, is notoriously difficult even to approximate. Here, we show that properly combining standard gradient updates with an off-gradient direction, constructed from samples of the RBM ground state (mode), improves training dramatically over traditional gradient methods. This approach, which we call ‘mode-assisted training’, promotes faster training and stability, in addition to lower converged relative entropy (KL divergence). We demonstrate its efficacy on synthetic datasets where we can compute KL divergences exactly, as well as on a larger machine learning standard (MNIST). The proposed mode-assisted training can be applied in conjunction with any given gradient method, and is easily extended to more general energy-based neural network structures such as deep, convolutional and unrestricted Boltzmann machines. While widely adopted, contrastive divergence methods for Restricted Boltzmann Machines typically result in poor representations of the data distribution. Here, the authors propose an unsupervised training where gradient-descent is combined with the Machine’s mode samples, significantly improving the final model quality.
The value of green energy under regulation uncertainty

Abstract We examine investments in power generation projects under policy uncertainty, when the investor has the choice between two alternative technologies, a gas-fired plant and a wind plant. Increased likelihood of subsidy withdrawal reduces the payoff from and postpones investments in the wind technology. Simultaneously, it accelerates investments in gas, thereby eliminating or further postponing investments in wind capacity. We show that this substitution phenomenon can be of first order importance: it can have a significant impact on the timing of investment, the wind premium, and the probability of investing in the wind technology. Our results provide new insights about the scope and impact of green energy regulation.
The Judgment in Bauer and the Effect of the EU Charter of Fundamental Rights in Horizontal Situations

The note discusses the judgment of the Court of Justice of the European Union (CJEU) in Bauer, a preliminary reference concerning the question of the effect of the EU Charter of Fundamental Rights in horizontal situations. The note examines whether the Bauer judgment unequivocally transformed the EU Charter into an independent source of private parties’ duties, and how it can be determined which Charter provisions could impose specific duties on private parties. The note evaluates the reasoning of the CJEU and locates the Bauer judgment within the growing strand of EU case law concerning the question of horizontal effect of fundamental rights and the role of the Charter of Fundamental Rights in regulating private law situations.
Extracting Headless MWEs from Dependency Parse Trees: Parsing, Tagging, and Joint Modeling Approaches.

An interesting and frequent type of multi-word expression (MWE) is the headless MWE, for which there are no true internal syntactic dominance relations; examples include many named entities (“Wells Fargo”) and dates (“July 5, 2020”) as well as certain productive constructions (“blow for blow”, “day after day”). Despite their special status and prevalence, current dependency-annotation schemes require treating such flat structures as if they had internal syntactic heads, and most current parsers handle them in the same fashion as headed constructions. Meanwhile, outside the context of parsing, taggers are typically used for identifying MWEs, but taggers might benefit from structural information. We empirically compare these two common strategies—parsing and tagging—for predicting flat MWEs. Additionally, we propose an efficient joint decoding algorithm that combines scores from both strategies. Experimental results on the MWE-Aware English Dependency Corpus and on six non-English dependency treebanks with frequent flat structures show that: (1) tagging is more accurate than parsing for identifying flat-structure MWEs, (2) our joint decoder reconciles the two different views and, for non-BERT features, leads to higher accuracies, and (3) most of the gains result from feature sharing between the parsers and taggers.
Causal Inference using Gaussian Processes with Structured Latent Confounders

Latent confounders---unobserved variables that influence both treatment and outcome---can bias estimates of causal effects. In some cases, these confounders are shared across observations, e.g. all students taking a course are influenced by the course's difficulty in addition to any educational interventions they receive individually. This paper shows how to semiparametrically model latent confounders that have this structure and thereby improve estimates of causal effects. The key innovations are a hierarchical Bayesian model, Gaussian processes with structured latent confounders (GP-SLC), and a Monte Carlo inference algorithm for this model based on elliptical slice sampling. GP-SLC provides principled Bayesian uncertainty estimates of individual treatment effect with minimal assumptions about the functional forms relating confounders, covariates, treatment, and outcome. Finally, this paper shows GP-SLC is competitive with or more accurate than widely used causal inference techniques on three benchmark datasets, including the Infant Health and Development Program and a dataset showing the effect of changing temperatures on state-wide energy consumption across New England.
The Gursky–Streets equations

Gursky–Streets introduced a formal Riemannian metric on the space of conformal metrics in a fixed conformal class of a compact Riemannian four-manifold in the context of the $$\sigma _2$$-Yamabe problem. The geodesic equation of Gursky–Streets’ metric is a fully nonlinear degenerate elliptic equation. Using this geometric structure and the geodesic equation, Gursky–Streets proved an important result in conformal geometry, that the solution of the $$\sigma _2$$-Yamabe problem is unique (the existence of such a solution was known more than a decade ago). A key ingredient is the convexity of Chang–Yang’s $${{\mathcal {F}}}$$-functional along the (smooth) geodesic. However Gursky–Streets have only proved uniform $$C^{0, 1}$$ regularity for a perturbed equation and it turns out that the uniform $$C^{1, 1}$$ regularity is very delicate. Without such a uniform $$C^{1, 1}$$ regularity, Gursky–Streets arguments of the uniqueness theorem are very complicated. In this paper we establish the uniform $$C^{1, 1}$$ regularity of the Gursky–Streets equation. In the course of deriving regularity, we also obtain very interesting and new convexity regarding matrices in $$\Gamma _2^+$$. As an application, we can establish strictly the convexity of $${{\mathcal {F}}}$$-functional along $$C^{1, 1}$$ geodesic. This gives a straightforward proof of the uniqueness of solutions of $$\sigma _2$$-Yamabe problem.
Twisted Fourier–Mukai partners of Enriques surfaces

Bridgeland and Maciocia showed that a complex Enriques surface X has no Fourier–Mukai partners apart from itself: that is, if $$D^b(X) \cong D^b(Y)$$ then $$X \cong Y$$ . We extend this to twisted Fourier–Mukai partners: if $$\alpha $$ is the non-trivial element of $${{\,\mathrm{Br}\,}}(X) = {\mathbb {Z}}/2$$ and $$D^b(X,\alpha ) \cong D^b(Y,\beta )$$ , then $$X \cong Y$$ and $$\beta $$ is non-trivial. Our main tools are twisted topological K-theory and twisted Mukai lattices.
Variation in Maize Chlorophyll Biosynthesis Alters Plant Architecture.

Chlorophyll is a tetrapyrrole metabolite essential for photosynthesis in plants. The first committed step of chlorophyll biosynthesis is catalyzed by a multimeric enzyme, magnesium chelatase, the subunit I of which is encoded by the oil yellow1 (oy1) gene in maize (Zea mays). A range of chlorophyll contents and net CO2 assimilation rates can be achieved in maize by combining a semidominant mutant allele of oy1 (Oy1-N1989) and a cis-regulatory modifier named very oil yellow1 (vey1) that varies between different inbred lines. We previously demonstrated that these allelic interactions can delay reproductive maturity. In this study, we demonstrate that multiple gross morphological traits respond to a reduction in chlorophyll. We found that stalk width, number of lateral branches (tillers), and branching of the inflorescence decline with a decrease in chlorophyll level. Chlorophyll deficit suppressed tillering in multiple maize mutants, including teosinte branched1, Tillering1, and grassy tillers1. In contrast to these traits, plant height showed a nonlinear response to chlorophyll levels. Weak suppression of Oy1-N1989 by vey1B73 resulted in a significant increase in mutant plant height. By contrast, enhancement of the severity of the Oy1-N1989 phenotype by the vey1Mo17 allele resulted in reduced plant height. We demonstrate that the effects of reduced chlorophyll contents on plant growth and development are complex and depend on the trait being measured. We propose that the lack of chlorophyll exerts growth control via energy balance sensing, which is upstream of the known genetic networks for branching and architecture.
HX-POL - a balloon-borne hard X-ray polarimeter

We report on the conceptual design and estimated performance of a balloon-borne hard X-ray polarimeter called HX-POL. The experiment uses a combination of Si and Cadmium Zinc Telluride detectors to measure the polarization of 50 keV-500 keV X-rays from cosmic sources through the dependence of the angular distribution of Compton scattered photons on the polarization direction. On a one-day balloon flight, HX-POL would allow us to measure the polarization of strong Crab-like sources for polarization degrees down to 5%. On a longer (15–30 day) flight from Australia or Antarctica, HX-POL would be be able to measure the polarization of strong sources down to polarization degrees of 1%. Hard X-ray polarization measurements provide unique venues for the study of particle acceleration processes by compact objects. In this contribution, we discuss the overall instrument design and performance. Furthermore, we present results from laboratory tests of the Si and CZT detectors.
Global well-posedness for the Euler alignment system with mildly singular interactions

We consider the Euler alignment system with mildly singular interaction kernels. When the local repulsion term is of the fractional type, global in time existence of smooth solutions was proved in [16, 22–24]. Here, we consider a class of less singular interaction kernels and establish the global regularity of solutions as long as the interaction kernels are not integrable. The proof relies on modulus of continuity estimates for a class of parabolic integro-differential equations with a drift and mildly singular kernels.
Coordinated Control of UAVs for Human-Centered Active Sensing of Wildfires

Fighting wildfires is a precarious task, imperiling the lives of engaging firefighters and those who reside in the fire's path. Firefighters need online and dynamic observation of the firefront to anticipate a wildfire's unknown characteristics, such as size, scale, and propagation velocity, and to plan accordingly. In this paper, we propose a distributed control framework to coordinate a team of unmanned aerial vehicles (UAVs) for a human-centered active sensing of wildfires. We develop a dual-criterion objective function based on Kalman uncertainty residual propagation and weighted multi-agent consensus protocol, which enables the UAVs to actively infer the wildfire dynamics and parameters, track and monitor the fire transition, and safely manage human firefighters on the ground using acquired information. We evaluate our approach relative to prior work, showing significant improvements by reducing the environment's cumulative uncertainty residual by more than $ 10^2 $ and $ 10^5 $ times in firefront coverage performance to support human-robot teaming for firefighting. We also demonstrate our method on physical robots in a mock firefighting exercise.
FTRANS: energy-efficient acceleration of transformers using FPGA

In natural language processing (NLP), the "Transformer" architecture was proposed as the first transduction model replying entirely on self-attention mechanisms without using sequence-aligned recurrent neural networks (RNNs) or convolution, and it achieved significant improvements for sequence to sequence tasks. The introduced intensive computation and storage of these pre-trained language representations has impeded their popularity into computation and memory constrained devices. The field-programmable gate array (FPGA) is widely used to accelerate deep learning algorithms for its high parallelism and low latency. However, the trained models are still too large to accommodate to an FPGA fabric. In this paper, we propose an efficient acceleration framework, Ftrans, for transformer-based large scale language representations. Our framework includes enhanced block-circulant matrix (BCM)-based weight representation to enable model compression on large-scale language representations at the algorithm level with few accuracy degradation, and an acceleration design at the architecture level. Experimental results show that our proposed framework significantly reduce the model size of NLP models by up to 16 times. Our FPGA design achieves 27.07× and 81 × improvement in performance and energy efficiency compared to CPU, and up to 8.80× improvement in energy efficiency compared to GPU.
Baseline estimation of commercial building HVAC fan power using tensor completion

Abstract Commercial building heating, ventilation, and air conditioning (HVAC) systems have been studied for providing ancillary services to power grids via demand response (DR). One critical issue is to estimate the counterfactual baseline power consumption that would have prevailed without DR. Baseline methods have been developed based on whole building electric load profiles. New methods are necessary to estimate the baseline power consumption of HVAC sub-components (e.g., supply and return fans), which have different characteristics compared to that of the whole building. Tensor completion can estimate the unobserved entries of multi-dimensional tensors describing complex data sets. It exploits high-dimensional data to capture granular insights into the problem. This paper proposes to use it for baselining HVAC fan power, by utilizing its capability of capturing dominant fan power patterns. The tensor completion method is evaluated using HVAC fan power data from several buildings at the University of Michigan, and compared with several existing methods. The tensor completion method generally outperforms the benchmarks.
Spacecraft Attitude Determination Using Terrestrial Illumination Matching

An algorithm to conduct spacecraft attitude determination via terrestrial illumination matching (TIM) is presented consisting of a novel method that uses terrestrial lights as a surrogate for star fields. Although star sensors represent a highly accurate means of attitude determination with considerable spaceflight heritage, TIM provides a potentially viable alternative in the event of star sensor malfunction or performance degradation. The research defines a catalog of terrestrial light “constellations,” which are then implemented within the TIM algorithm for position acquisition of a generic spacecraft bus. With the algorithm relying on terrestrial lights rather than the establish standard of star fields, a series of sensitivity studies are showcased to determine performance during specified operating constraints, to include varying orbital altitude and cloud cover conditions. Also, a comparison of relative accuracy will be presented for TIM with a generic star sensor.
A new algorithm to determine the creation or depletion term of parabolic equations from boundary measurements

Abstract We propose a robust numerical method to find the coefficient of the creation or depletion term of parabolic equations from the measurement of the lateral Cauchy information of their solutions. Most papers in the field study this nonlinear and severely ill-posed problem using optimal control. The main drawback of this widely used approach is the need of some advanced knowledge of the true solution. In this paper, we propose a new method that opens a door to solve nonlinear inverse problems for parabolic equations without any initial guess of the true coefficient. This claim is confirmed numerically. The key point of the method is to derive a system of nonlinear elliptic equations for the Fourier coefficients of the solution to the governing equation with respect to a special basis of L 2 . We then solve this system by a predictor–corrector process, in which our computation to obtain the first and second predictors is effective. The desired solution to the inverse problem under consideration follows.
Self domain adapted network

Domain shift is a major problem for deploying deep networks in clinical practice. Network performance drops significantly with (target) images obtained differently than its (source) training data. Due to a lack of target label data, most work has focused on unsupervised domain adaptation (UDA). Current UDA methods need both source and target data to train models which perform image translation (harmonization) or learn domain-invariant features. However, training a model for each target domain is time consuming and computationally expensive, even infeasible when target domain data are scarce or source data are unavailable due to data privacy. In this paper, we propose a novel self domain adapted network (SDA-Net) that can rapidly adapt itself to a single test subject at the testing stage, without using extra data or training a UDA model. The SDA-Net consists of three parts: adaptors, task model, and auto-encoders. The latter two are pre-trained offline on labeled source images. The task model performs tasks like synthesis, segmentation, or classification, which may suffer from the domain shift problem. At the testing stage, the adaptors are trained to transform the input test image and features to reduce the domain shift as measured by the auto-encoders, and thus perform domain adaptation. We validated our method on retinal layer segmentation from different OCT scanners and T1 to T2 synthesis with T1 from different MRI scanners and with different imaging parameters. Results show that our SDA-Net, with a single test subject and a short amount of time for self adaptation at the testing stage, can achieve significant improvements.
Structural basis of ClpXP recognition and unfolding of ssrA-tagged substrates

When ribosomes fail to complete normal translation, all cells have mechanisms to ensure degradation of the resulting partial proteins to safeguard proteome integrity. In Escherichia coli and other eubacteria, the tmRNA system rescues stalled ribosomes and adds an ssrA tag or degron to the C-terminus of the incomplete protein, which directs degradation by the AAA+ ClpXP protease. Here, we present cryo-EM structures of ClpXP bound to the ssrA degron. C-terminal residues of the ssrA degron initially bind in the top of an otherwise closed ClpX axial channel and subsequently move deeper into an open channel. For short-degron protein substrates, we show that unfolding can occur directly from the initial closed-channel complex. For longer degron substrates, our studies illuminate how ClpXP transitions from specific recognition into a nonspecific unfolding and translocation machine. Many AAA+ proteases and protein-remodeling motors are likely to employ similar multistep recognition and engagement strategies.
On the Berry-Esseen bound for the Student statistic

New Berry–Esseen-type bounds, with explicit constant factors, for the distribution of the Student statistic and, equivalently, for that of the self-normalized sum of independent zero-mean random variables are obtained. These bounds are compared with the corresponding existing results.
PSR J1306-40: An X-Ray Luminous Redback with an Evolved Companion

PSR J1306--40 is a millisecond pulsar binary with a non-degenerate companion in an unusually long $\sim$1.097 day orbit. We present new optical photometry and spectroscopy of this system, and model these data to constrain fundamental properties of the binary such as the component masses and distance. The optical data imply a minimum neutron star mass of $1.75\pm0.09\,M_{\odot}$ (1-sigma) and a high, nearly edge-on inclination. The light curves suggest a large hot spot on the companion, suggestive of a portion of the pulsar wind being channeled to the stellar surface by the magnetic field of the secondary, mediated via an intrabinary shock. The H$\alpha$ line profiles switch rapidly from emission to absorption near companion inferior conjunction, consistent with an eclipse of the compact emission region at these phases. At our optically-inferred distance of $4.7\pm0.5$ kpc, the X-ray luminosity is $\sim$10$^{33}$ erg s$^{\textrm{-1}}$, brighter than nearly all known redbacks in the pulsar state. The long period, subgiant-like secondary, and luminous X-ray emission suggest this system may be part of the expanding class of millisecond pulsar binaries that are progenitors to typical field pulsar--white dwarf binaries.
Resummed photon spectra for WIMP annihilation

We construct an effective field theory (EFT) description of the hard photon spectrum for heavy WIMP annihilation. This facilitates precision predictions relevant for line searches, and allows the incorporation of non-trivial energy resolution effects. Our framework combines techniques from non-relativistic EFTs and soft-collinear effective theory (SCET), as well as its multi-scale extensions that have been recently introduced for studying jet substructure. We find a number of interesting features, including the simultaneous presence of SCETI and SCETII modes, as well as collinear-soft modes at the electroweak scale. We derive a factorization formula that enables both the resummation of the leading large Sudakov double logarithms that appear in the perturbative spectrum, and the inclusion of Sommerfeld enhancement effects. Consistency of this factorization is demonstrated to leading logarithmic order through explicit calculation. Our final result contains both the exclusive and the inclusive limits, thereby providing a unifying description of these two previously-considered approximations. We estimate the impact on experimental sensitivity, focusing for concreteness on an SU(2) W triplet fermion dark matter — the pure wino — where the strongest constraints are due to a search for gamma-ray lines from the Galactic Center. We find numerically significant corrections compared to previous results, thereby highlighting the importance of accounting for the photon spectrum when interpreting data from current and future indirect detection experiments.
Rényi entropies as a measure of the complexity of counting problems

Counting problems such as determining how many bit strings satisfy a given Boolean logic formula are notoriously hard. In many cases, even getting an approximate count is difficult. Here we propose that entanglement, a common concept in quantum information theory, may serve as a telltale of the difficulty of counting exactly or approximately. We quantify entanglement by using Renyi entropies S(q), which we define by bipartitioning the logic variables of a generic satisfiability problem. We conjecture that S(q→0) provides information about the difficulty of counting solutions exactly, while S(q>0) indicates the possibility of carrying out an efficient approximate counting. We test this conjecture by employing a matrix computing scheme to numerically solve #2SAT problems for a large number of uniformly distributed instances. We find that all Renyi entropies scale linearly with the number of variables in the case of the #2SAT problem; this is consistent with the fact that neither exact nor efficient approximate algorithms are known for this problem. However, for the negated (disjunctive) form of the problem, S(q→0) scales linearly while S(q>0) tends to zero when the number of variables is large. These results are consistent with the existence of fully polynomial-time randomized approximate algorithms for counting solutions of disjunctive normal forms and suggest that efficient algorithms for the conjunctive normal form may not exist.
The Case for a Low Mass Black Hole in the Low Mass X-Ray Binary V1408 Aquilae (= 4U 1957+115)

There are few confirmed black holes with a mass of less and no neutron stars with masses greater than , creating a gap in the observed distribution of compact star masses. We present new optical photometry of the Low mass X-ray binary V1408 Aql, which is a persistent X-ray source thought to contain a black hole. The optical light curve of V1408 Aql shows nearly sinusoidal modulations at the orbital period, superimposed on large night-to-night variations. We combined this photometry with previously published photometry to derive a more precise orbital period of days. The orbital light curve agrees with a model in which the modulation is caused by the changing aspect of the heated face of the secondary. The lack of eclipses rules out orbital inclinations . Our best models favor inclinations near and black hole masses near with a 90% upper bound of , and a lower bound of imposed solely by the maximum mass of neutron stars. We favor a black hole primary over a neutron star based on evidence from the X-ray spectra, the high spin of the compact object, and the lack of any observed type I X-ray bursts. Although uncertainties in the data allow for higher masses, the compact star in V1408 Aql is a candidate for a black hole lying in the mass gap.
Theory of bipolar outflows from high-mass young stellar objects

Abstract There is a growing number of observational indicators for the presence of bipolar outflows in massive, young stellar objects that are still accreting mass as part of their formation process. In particular, there is evidence that the outflows from these objects can attain higher velocities and kinetic luminosities than their lower-mass counterparts. Furthermore, the higher-mass objects appear to smoothly continue the correlation found in T Tauri stars between outflow and accretion signatures, and in several cases there are direct clues to the existence of a circumstellar disk from optical and infrared imaging and spectroscopy as well as from millimeter-wavelength interferometry. These results suggest that the disk-outflow connection found in low-mass pre-main-sequence stars extends to more massive objects, and that a similar physical mechanism may drive the outflows in both cases. We examine the observational basis for this hypothesis and consider how the commonly invoked centrifugally driven wind models of bipolar outflows in low-mass stars would be affected by the various physical processes (such as photoionization, photoevaporation, radiation pressure, and stellar wind ram pressure) that operate in higher-mass stars. We then list some of the interesting questions that one could hope to address as this young field of research continues to develop.
Examining and contrasting the cognitive activities engaged in undergraduate research experiences and lab courses

Comparison of cognitive activities students use in undergraduate research experiences and lab courses to those required for experimental research.
Topological Index Theory for surfaces in 3-manifolds

The disk complex of a surface in a 3‐manifold is used to define its topological index. Surfaces with well-defined topological index are shown to generalize well known classes, such as incompressible, strongly irreducible and critical surfaces. The main result is that one may always isotope a surface H with topological index n to meet an incompressible surface F so that the sum of the indices of the components of HnN.F/ is at most n. This theorem and its corollaries generalize many known results about surfaces in 3‐manifolds, and often provides more efficient proofs. The paper concludes with a list of questions and conjectures, including a natural generalization of Hempel’s distance to surfaces with topological index 2. 57M99
Vortex states in Archimedean tiling pinning arrays

We numerically study vortex ordering and pinning in Archimedean tiling substrates composed of square and triangular plaquettes. The two different plaquettes become occupied at different vortex densities, producing commensurate peaks in the magnetization at non-integer matching fields. We find that as the field increases, in some cases the fraction of occupied pins can decrease due to the competition between fillings of the different plaquette types. We also identify a number of different types of vortex orderings as a function of the field at integer and non-integer commensurate fillings.
AGN All the Way Down? AGN-like Line Ratios are Common In the Lowest-Mass Isolated Quiescent Galaxies

Author(s): Dickey, CMK; Geha, M; Wetzel, A; El-Badry, K | Abstract: We investigate the lowest-mass quiescent galaxies known to exist in isolated environments (M* = 109.0-9.5 M⊙; 1.5 Mpc from a more massive galaxy). This population may represent the lowest stellar mass galaxies in which internal feedback quenches galaxy-wide star formation. We present a Keck/Echelle Spectrograph and Imager longslit spectroscopy for 27 isolated galaxies in this regime (20 quiescent galaxies and 7 star-forming galaxies). We measure emission line strengths as a function of radius and place galaxies on the Baldwin Phillips Terlevich (BPT) diagram. Remarkably, 16 of 20 quiescent galaxies in our sample host central active galactic nucleus (AGN)- like line ratios. Only five of these quiescent galaxies were identified as AGN-like in the Sloan Digital Sky Survey due to a lower spatial resolution and signal-to-noise ratio. We find that many of the quiescent galaxies in our sample have spatially extended emission across the non-star-forming regions of BPT-space. While quenched galaxies in denser environments in this mass range often show no evidence for AGN activity, a significant fraction of quiescent galaxies in isolation host AGNs despite their overall passive appearances.
Investigating competition in financial markets: a sparse autologistic model for dynamic network data

ABSTRACTWe develop a sparse autologistic model for investigating the impact of diversification and disintermediation strategies in the evolution of financial trading networks. In order to induce sparsity in the model estimates and address substantive questions about the underlying processes the model includes an L1 regularization penalty. This makes implementation feasible for complex dynamic networks in which the number of parameters is considerably greater than the number of observations over time. We use the model to characterize trader behavior in the NYMEX natural gas futures market, where we find that disintermediation and not diversification or momentum tend to drive market microstructure.
High Temperature Asymptotics of Orthogonal Mean-Field Spin Glasses

We evaluate the high temperature limit of the free energy of spin glasses on the hypercube with Hamiltonian \(H_N({\underline{\sigma }}) = {\underline{\sigma }}^T J {\underline{\sigma }}\), where the coupling matrix J is drawn from certain symmetric orthogonally invariant ensembles. Our derivation relates the annealed free energy of these models to a spherical integral, and expresses the limit of the free energy in terms of the limiting spectral measure of the coupling matrix J. As an application, we derive the limiting free energy of the random orthogonal model at high temperatures, which confirms non-rigorous calculations of Marinari et al. (J Phys A 27:7647, 1994). Our methods also apply to other well-known models of disordered systems, including the SK and Gaussian Hopfield models.
Why are fluid densities so low in carbon nanotubes

The equilibrium density of fluids under nanoconfinement can differ substantially from their bulk density. Using a mean-field approach to describe the energetic landscape near the carbon nanotube (CNT) wall, we obtain analytical results describing the lengthscales associated with the layering observed at the interface of a Lennard-Jones fluid and a CNT. We also show that this approach can be extended to describe the multiple-ring structure observed in larger CNTs. When combined with molecular simulation results for the fluid density in the first two rings, this approach allows us to derive a closed-form prediction for the overall equilibrium fluid density as a function of CNT radius that is in excellent agreement with molecular dynamics simulations. We also show how aspects of this theory can be extended to describe some features of water confinement within CNTs and find good agreement with results from the literature.
Stochastic modified equations for the asynchronous stochastic gradient descent

We propose a stochastic modified equations (SME) for modeling the asynchronous stochastic gradient descent (ASGD) algorithms. The resulting SME of Langevin type extracts more information about the ASGD dynamics and elucidates the relationship between different types of stochastic gradient algorithms. We show the convergence of ASGD to the SME in the continuous time limit, as well as the SME's precise prediction to the trajectories of ASGD with various forcing terms. As an application of the SME, we propose an optimal mini-batching strategy for ASGD via solving the optimal control problem of the associated SME.
Radio Transients from the Accretion-induced Collapse of White Dwarfs

It has long been expected that in some scenarios when a white dwarf (WD) grows to the Chandrasekhar limit, it can undergo an accretion-induced collapse (AIC) to form a rapidly rotating neutron star. Nevertheless, the detection of such events has so far evaded discovery, likely because the optical, supernova-like emission is expected to be dim and short-lived. Here we propose a novel signature of AIC: a transient radio source lasting for a few months. Rapid rotation along with flux freezing and dynamo action can grow the WD's magnetic field to magnetar strengths during collapse. The spin-down of this newly born magnetar generates a pulsar wind nebula (PWN) within the ~10^(–3)-10^(–1) M_☉ of ejecta surrounding it. Our calculations show that synchrotron emission from the PWN may be detectable in the radio, even if the magnetar has a rather modest magnetic field of ~2 × 10^(14) G and an initial spin period of ~10 ms. An all-sky survey with a detection limit of 1 mJy at 1.4 GHz would see ~4(ƒ/10^(–2)) above threshold at any given time, where f is the ratio of the AIC rate to Type Ia supernova rate. A similar scenario may result from binary neutron stars if some mergers produce massive neutron stars rather than black holes. We conclude with a discussion of the detectability of these types of transient radio sources in an era of facilities with high mapping speeds.
Representations of Each Number Type That Differ by Scale Factors

For each type of number, structures that differ by arbitrary scaling factors and are isomorphic to one another are described. The scaling of number values in one structure, relative to the values in another structure, must be compensated for by scaling of the basic operations and relations (if any) in the structure. The scaling must be such that one structure satisfies the relevant number type axioms if and only if the other structure does.
Sliding Window Algorithms for k-Clustering Problems

The sliding window model of computation captures scenarios in which data is arriving continuously, but only the latest $w$ elements should be used for analysis. The goal is to design algorithms that update the solution efficiently with each arrival rather than recomputing it from scratch. In this work, we focus on $k$-clustering problems such as $k$-means and $k$-median. In this setting, we provide simple and practical algorithms that offer stronger performance guarantees than previous results. Empirically, we show that our methods store only a small fraction of the data, are orders of magnitude faster, and find solutions with costs only slightly higher than those returned by algorithms with access to the full dataset.
MISO Broadcast Channel With Hybrid CSIT: Beyond Two Users

We study the impact of heterogeneity of channel-state-information available at the transmitters (CSIT) on the capacity of broadcast channels with a multiple-antenna transmitter and $k$ single-antenna receivers (MISO BC). In particular, we consider the $k$ -user MISO BC, where the CSIT with respect to each receiver can be either instantaneous/perfect, delayed, or not available; and we study the impact of this heterogeneity of CSIT on the degrees-of-freedom (DoFs) of such network. We first focus on the three-user MISO BC, and we completely characterize the DoF region for all possible heterogeneous CSIT configurations, assuming linear encoding strategies at the transmitters. The result shows that the state-of-the-art achievable schemes in the literature are indeed sum-DoF optimal, when restricted to linear encoding schemes. To prove the result, we develop a novel bound, called interference decomposition bound , which provides a lower bound on the interference dimension at a receiver which supplies delayed CSIT based on the average dimension of constituents of that interference, thereby decomposing the interference into its individual components. Furthermore, we extend our outer bound on the DoF region to the general $k$ -user MISO BC, and demonstrate that it leads to an approximate characterization of linear sum-DoF to within an additive gap of 0.5 for a broad range of CSIT configurations. Moreover, for the special case where only one receiver supplies delayed CSIT, we completely characterize the linear sum-DoF.
Gamma-Ray Burst Spectra and Light Curves as Signatures of a Relativistically Expanding Plasma

Temporal and spectral characteristics of prompt emission of gamma-ray burst (GRB) pulses are the primary observations for constraining the energizing and emission mechanisms. In spite of very complex temporal behavior of the GRBs, several patterns have been discovered in how some spectral characteristics change during the decaying phase of individual, well-defined long (greater than a few seconds) pulses. In this paper we compare these observed signatures with those expected from a relativistically expanding, shock-heated, and radiation-emitting plasma shell. Within the internal shock model and assuming a short cooling time, we show that the angular dependence in arrival time from a spherical expanding shell can explain the general characteristics of some well-defined long GRB pulses. This includes the pulse shape, with a fast rise and a slower decay, ∝(1 + t/τ)2, where τ is a time constant, and the spectral evolution, which can be described by the hardness-intensity correlation (HIC), with the intensity being proportional to the square of the hardness measured by the value of the peak, e.g., Ep of the νFν spectrum. A variation of the relevant timescales involved (the angular spreading and the dynamic) can explain the broad, observed dispersion of the HIC index. Reasonable estimates of physical parameters lead to situations where the HIC relation deviates from a pure power law, features that are indeed present in the observations. Depending on the relative values of the rise and decay times of the intrinsic light curve, the spectral/temporal behavior, as seen by an observer, will produce the hard-to-soft evolution and the so-called tracking pulses. In our model the observed spectrum is a superposition of many intrinsic spectra arriving from different parts of the fireball shell with varying spectral shifts. Therefore, it will be broader than the emitted spectrum and its spectral parameters could have complex relations with the intrinsic ones. Furthermore, we show that the softening of the low-energy power-law index, that has been observed in some pulses, can be explained by geometric effects and does not need to be an intrinsic behavior.