cssi/SciSciGPT-SciSciNet huggingface dataset:
Going It Alone: Competition Increases the Attractiveness of Minority Status

Abstract Past research demonstrates that people prefer to affiliate with others who resemble them demographically. However, we posit that when competing for scarce opportunities, strategic considerations moderate the strength of this tendency toward homophily. Across six experiments, we find that anticipated competition weakens people’s desire to join groups that include similar others. When expecting to compete against fellow group members, women are more willing to join all-male groups and Black participants are more willing to join all-White groups than in the absence of competition. We show that this effect is mediated by the belief that being distinct will lead your performance to stand out. Our findings offer a new perspective to enrich past research on homophily, shedding light on the instances when minorities are more likely to join groups in which they will be underrepresented.
A Macroscopic Model of an Interactive Computing System

The development of effective performance evaluation techniques for interactive systems is a complex problem [1,2]. Numerous papers have presented evaluation models based upon queuing theory [3,4]. This paper presents an alternative model which is quite general since it is independent of the microscopic properties of any given interactive system. By supplying to the model from four to seven experimentally determined parameters for a given interactive system, we can compute a numerical throughput optimization factor, and also a demand optimization factor in the case of time-dependent demands from the terminals. Additionally, for systems meeting a small number of restrictions, the model predicts quantitative relationships between the throughput and the implementation of techniques such as that of dynamically varying the scheduling algorithm.
CHAPTER 5 – The Compactness Theorem and the Existence of Area-Minimizing Surfaces

Publisher Summary This chapter explains the compactness theorem and the existence of area-minimizing surfaces. The compactness theorem deserves to be known as the fundamental theorem of geometric measure theory. It guarantees solutions to a wide class of variational problems in general dimensions. It says that a certain set F of surfaces is compact in a natural topology. The two main lemmas are the deformation theorem and the closure theorem. The deformation theorem approximates an integral current T by deforming it onto a grid of mesh 2ɛ > 0. The resulting approximation, P, is automatically a polyhedral chain. The main error term is ∂S, where S is the surface through which T is deformed. There is a secondary error term, Q, because of moving ∂T into the skeleton of the grid. The chapter presents the proof of the existence of an area-minimizing surface with given boundary B, where it is necessary to keep surfaces under consideration inside some large ball B(0, A). This is accomplished by projecting everything outside the ball onto its surface.
Systemic credit freezes in financial lending networks

This paper develops a network model of interbank lending, in which banks decide to extend credit to their potential borrowers. Borrowers are subject to shocks that may force them to default on their loans. In contrast to much of the previous literature on financial networks, we focus on how anticipation of future defaults may result in ex ante “credit freezes,” whereby banks refuse to extend credit to one another. We first characterize the terms of the interbank contracts and the patterns of interbank lending that emerge in equilibrium. We then study how shifts in the distribution of shocks can result in complex credit freezes that travel throughout the network. We use this framework to analyze the effects of various policy interventions on systemic credit freezes.
Effective virtual and residual properties of some arithmetic hyperbolic 3–manifolds

We give an effective upper bound, for certain arithmetic hyperbolic 3-manifold groups obtained from a quadratic form construction, on the minimal index of a subgroup that embeds in a fixed 6-dimensional right-angled reflection group, stabilizing a totally geodesic subspace. In particular, for manifold groups in any fixed commensurability class we show that the index of such a subgroup is asymptotically smaller than any fractional power of the volume of the manifold. We also give effective bounds on the geodesic residual finiteness growths of closed hyperbolic manifolds that totally geodesically immerse in non-compact right-angled reflection orbifolds, extending work of the third author from the compact case. The first result gives examples to which the second applies, and for these we give explicit bounds on geodesic residual finiteness growth.
Numerical Modeling of Hypersonic Weakly Ionized External Flowfields with Poisson’s Equation

A seven-species air model is used to numerically simulate and analyze the flowfield of an air plasma. Previous numerical models have employed different electric field approximations that assume amb...
Discussion of “Prediction, Estimation, and Attribution” by Bradley Efron

Professor Efron has presented us with a thought-provoking paper on the relationship between prediction, estimation, and attribution in the modern era of data science. While we appreciate many of hi...
A Note on Complex-Hyperbolic Kleinian Groups

Let $$\varGamma $$ be a discrete group of isometries acting on the complex hyperbolic n-space $$\mathbb {H}^n_\mathbb {C}$$ . In this note, we prove that if $$\varGamma $$ is convex-cocompact, torsion-free, and the critical exponent $$\delta (\varGamma )$$ is strictly lesser than 2, then the complex manifold $$\mathbb {H}^n_\mathbb {C}/\varGamma $$ is Stein. We also discuss several related conjectures.
Discourse-Aware Neural Extractive Text Summarization

Recently BERT has been adopted for document encoding in state-of-the-art text summarization models. However, sentence-based extractive models often result in redundant or uninformative phrases in the extracted summaries. Also, long-range dependencies throughout a document are not well captured by BERT, which is pre-trained on sentence pairs instead of documents. To address these issues, we present a discourse-aware neural summarization model - DiscoBert. DiscoBert extracts sub-sentential discourse units (instead of sentences) as candidates for extractive selection on a finer granularity. To capture the long-range dependencies among discourse units, structural discourse graphs are constructed based on RST trees and coreference mentions, encoded with Graph Convolutional Networks. Experiments show that the proposed model outperforms state-of-the-art methods by a significant margin on popular summarization benchmarks compared to other BERT-base models.
Analysis of stochastic timing of intracellular events with gene switching

An important step in execution of several cellular processes is accumulation of a regulatory protein up to a specific threshold level. Since production of a protein is inherently stochastic, the time at which its level crosses a threshold exhibits cell-to-cell variation. A problem of interest is to characterize how the statistics of event timing is affected by various steps of protein expression. Our previous work studied this problem by considering a gene expression model where gene was always active. Here we extend our analysis to a scenario where gene stochastically switches between active and inactive states. We formulate event timing as the first-passage time for a protein’s level to cross a threshold and investigate how the rates of gene activation/inactivation affect the distribution and moments of the first-passage time. Our results show that both the time-scale of gene switching with respect to the protein degradation rate as well as the ratio of the gene inactivation to gene activation rates are important parameters in shaping the event-timing distribution.
A simple model for learning in volatile environments

Sound principles of statistical inference dictate that uncertainty shapes learning. In this work, we revisit the question of learning in volatile environments, in which both the first and second-order statistics of observations dynamically evolve over time. We propose a new model, the volatile Kalman filter (VKF), which is based on a tractable state-space model of uncertainty and extends the Kalman filter algorithm to volatile environments. The proposed model is algorithmically simple and encompasses the Kalman filter as a special case. Specifically, in addition to the error-correcting rule of Kalman filter for learning observations, the VKF learns volatility according to a second error-correcting rule. These dual updates echo and contextualize classical psychological models of learning, in particular hybrid accounts of Pearce-Hall and Rescorla-Wagner. At the computational level, compared with existing models, the VKF gives up some flexibility in the generative model to enable a more faithful approximation to exact inference. When fit to empirical data, the VKF is better behaved than alternatives and better captures human choice data in two independent datasets of probabilistic learning tasks. The proposed model provides a coherent account of learning in stable or volatile environments and has implications for decision neuroscience research.
A hardness of approximation result in metric geometry

We show that it is $${\mathsf {NP}}$$ -hard to approximate the hyperspherical radius of a triangulated manifold up to an almost-polynomial factor.
Volumetric particle tracking velocimetry (PTV) uncertainty quantification

We introduce the first comprehensive approach to determine the uncertainty in volumetric Particle Tracking Velocimetry (PTV) measurements. Volumetric PTV is a state-of-the-art non-invasive flow measurement technique, which measures the velocity field by recording successive snapshots of the tracer particle motion using a multi-camera set-up. The measurement chain involves reconstructing the three-dimensional particle positions by a triangulation process using the calibrated camera mapping functions. The non-linear combination of the elemental error sources during the iterative self-calibration correction and particle reconstruction steps increases the complexity of the task. Here, we first estimate the uncertainty in the particle image location, which we model as a combination of the particle position estimation uncertainty and the reprojection error uncertainty. The latter is obtained by a gaussian fit to the histogram of disparity estimates within a sub-volume. Next, we determine the uncertainty in the camera calibration coefficients. As a final step, the previous two uncertainties are combined using an uncertainty propagation through the volumetric reconstruction process. The uncertainty in the velocity vector is directly obtained as a function of the reconstructed particle position uncertainty. The framework is tested with synthetic vortex ring images. The results show good agreement between the predicted and the expected RMS uncertainty values. The prediction is consistent for seeding densities tested in the range of 0.01–0.1 particles per pixel. Finally, the methodology is also successfully validated for an experimental test case of laminar pipe flow velocity profile measurement where the predicted uncertainty in the streamwise component is within 9% of the RMS error value.
The shibboleth of human rights in public health.

Human rights discourse has greatly influenced advocacy for justice in public health. Yet, beyond rhetorical claims, how can we employ human rights to achieve the aspiration of health with justice? Without human rights education to support public health practice, human rights have become a shibboleth of public health—raised frequently to signal devotion to justice, but employed rarely in policy, programming, or practice. As advocates respond to the public health injustices of populist nationalism during an unprecedented pandemic, human rights education must be an essential foundation to hold governments accountable for implementing rights to safeguard public health.
Finite-Blocklength Performance of Sequential Transmission over BSC with Noiseless Feedback

In this paper, we consider the problem of sequential transmission over the binary symmetric channel (BSC) with full, noiseless feedback. Naghshvar et al. proposed a one-phase encoding scheme, for which we refer to as the small-enough difference (SED) encoder, which can achieve capacity and Burnashev’s optimal error exponent for symmetric binary-input channels. They also provided a non-asymptotic upper bound on the average blocklength, which implies an achievability bound on rates. However, their achievability bound is loose compared to the simulated performance of SED encoder, and even lies beneath Polyanskiy’s achievability bound of a system limited to stop feedback. This paper significantly tightens the achievability bound by using a Markovian analysis that leverages both the submartingale and Markov properties of the transmitted message. Our new non-asymptotic lower bound on achievable rate lies above Polyanskiy’s bound and is close to the actual performance of the SED encoder over the BSC.
Detecting selection with a genetic cross.

Distinguishing which traits have evolved under natural selection, as opposed to neutral evolution, is a major goal of evolutionary biology. Several tests have been proposed to accomplish this, but these either rely on false assumptions or suffer from low power. Here, I introduce an approach to detecting selection that makes minimal assumptions and only requires phenotypic data from ∼10 individuals. The test compares the phenotypic difference between two populations to what would be expected by chance under neutral evolution, which can be estimated from the phenotypic distribution of an F2 cross between those populations. Simulations show that the test is robust to variation in the number of loci affecting the trait, the distribution of locus effect sizes, heritability, dominance, and epistasis. Comparing its performance to the QTL sign test—an existing test of selection that requires both genotype and phenotype data—the new test achieves comparable power with 50- to 100-fold fewer individuals (and no genotype data). Applying the test to empirical data spanning over a century shows strong directional selection in many crops, as well as on naturally selected traits such as head shape in Hawaiian Drosophila and skin color in humans. Applied to gene expression data, the test reveals that the strength of stabilizing selection acting on mRNA levels in a species is strongly associated with that species’ effective population size. In sum, this test is applicable to phenotypic data from almost any genetic cross, allowing selection to be detected more easily and powerfully than previously possible.
Support Constrained Generator Matrices of Gabidulin Codes in Characteristic Zero

Gabidulin codes over fields of characteristic zero were recently constructed by Augot et al., whenever the Galois group of the underlying field extension is cyclic. In parallel, the interest in sparse generator matrices of Reed–Solomon and Gabidulin codes has increased lately, due to applications in distributed computations. In particular, a certain condition pertaining to the intersection of zero entries at different rows, was shown to be necessary and sufficient for the existence of the sparsest possible generator matrix of Gabidulin codes over finite fields. In this paper we complete the picture by showing that the same condition is also necessary and sufficient for Gabidulin codes over fields of characteristic zero.Our proof builds upon and extends tools from the finite-field case, combines them with a variant of the Schwartz–Zippel lemma over automorphisms, and provides a simple randomized construction algorithm whose probability of success can be arbitrarily close to one. In addition, potential applications for low-rank matrix recovery are discussed.
Genomic Signatures of Honey Bee Association in an Acetic Acid Symbiont.

Recent declines in the health of the honey bee have startled researchers and lay people alike as honey bees are agriculture's most important pollinator. Honey bees are important pollinators of many major crops and add billions of dollars annually to the US economy through their services. One factor that may influence colony health is the microbial community. Indeed, the honey bee worker digestive tract harbors a characteristic community of bee-specific microbes, and the composition of this community is known to impact honey bee health. However, the honey bee is a superorganism, a colony of eusocial insects with overlapping generations where nestmates cooperate, building a hive, gathering and storing food, and raising brood. In contrast to what is known regarding the honey bee worker gut microbiome, less is known of the microbes associated with developing brood, with food stores, and with the rest of the built hive environment. More recently, the microbe Bombella apis was identified as associated with nectar, with developing larvae, and with honey bee queens. This bacterium is related to flower-associated microbes such as Saccharibacter floricola and other species in the genus Saccharibacter, and initial phylogenetic analyses placed it as sister to these environmental bacteria. Here, we used comparative genomics of multiple honey bee-associated strains and the nectar-associated Saccharibacter to identify genomic changes that may be associated with the ecological transition to honey bee association. We identified several genomic differences in the honey bee-associated strains, including a complete CRISPR/Cas system. Many of the changes we note here are predicted to confer upon Bombella the ability to survive in royal jelly and defend themselves against mobile elements, including phages. Our results are a first step towards identifying potential function of this microbe in the honey bee superorganism.
Why Aren’t More Theories Named After Women? Teaching Women’s History in Physics

Barriers to women’s education and employment in Europe and the United States in the 19th century made it unlikely that any women would be among the few physicists whose ideas are taught in high school and college courses. This paper explores the social settings in which three influential physicists worked—James Clerk Maxwell, Robert Millikan, and Albert Einstein—to better understand the limited opportunities available to women. By acknowledging and explaining why there weren’t more women among these founding physicists, instructors may help students understand the barriers that still exist and feel more empowered to overcome them and pursue physics as a career.
Dynamic Emergence of Nanostructure and Transport Properties in Perfluorinated Sulfonic Acid Ionomers

The role of fluoropolymer physicochemical properties in the dynamic evolution of nanostructure and ionic conductivity in perfluorinated sulfonic acid ionomer thin films was investigated by in situ ...
PhyDOSE: Design of follow-up single-cell sequencing experiments of tumors.

The combination of bulk and single-cell DNA sequencing data of the same tumor enables the inference of high-fidelity phylogenies that form the input to many important downstream analyses in cancer genomics. While many studies simultaneously perform bulk and single-cell sequencing, some studies have analyzed initial bulk data to identify which mutations to target in a follow-up single-cell sequencing experiment, thereby decreasing cost. Bulk data provide an additional untapped source of valuable information, composed of candidate phylogenies and associated clonal prevalence. Here, we introduce PhyDOSE, a method that uses this information to strategically optimize the design of follow-up single cell experiments. Underpinning our method is the observation that only a small number of clones uniquely distinguish one candidate tree from all other trees. We incorporate distinguishing features into a probabilistic model that infers the number of cells to sequence so as to confidently reconstruct the phylogeny of the tumor. We validate PhyDOSE using simulations and a retrospective analysis of a leukemia patient, concluding that PhyDOSE’s computed number of cells resolves tree ambiguity even in the presence of typical single-cell sequencing errors. We also conduct a retrospective analysis on an acute myeloid leukemia cohort, demonstrating the potential to achieve similar results with a significant reduction in the number of cells sequenced. In a prospective analysis, we demonstrate the advantage of selecting cells to sequence across multiple biopsies and that only a small number of cells suffice to disambiguate the solution space of trees in a recent lung cancer cohort. In summary, PhyDOSE proposes cost-efficient single-cell sequencing experiments that yield high-fidelity phylogenies, which will improve downstream analyses aimed at deepening our understanding of cancer biology.
During the second wave of COVID-19, don't forget about influenza: a call to action.

Having lived through the havoc of COVID-19 in a hospital situated in one of the hardest hit zip codes in the United States, the thought that another wave could loom in the fall is bracing. Further, we are acutely aware of the herculean effort it took to reorganize the service to accommodate the needs of women infected with this new pathogen.
Where Are the Extrasolar Mercuries

We utilize observations of 16 white dwarf stars to calculate and analyze the oxidation states of the parent bodies accreting onto the stars. Oxygen fugacity, a measure of overall oxidation state for rocks, is as important as pressure and temperature in determining the structure of a planet. We find that most of the extrasolar rocky bodies formed under oxidizing conditions, but approximately 1/4 of the polluted white dwarfs have compositions consistent with more reduced parent bodies. The difficulty in constraining the oxidation states of relatively reduced bodies is discussed and a model for the time-dependent evolution of the apparent oxygen fugacity for a hypothetical reduced body engulfed by a WD is investigated. Differences in diffusive fluxes of various elements through the WD envelope yield spurious inferred bulk elemental compositions and oxidation states of the accreting parent bodies under certain conditions. The worst case for biasing against detection of reduced bodies occurs for high effective temperatures. For moderate and low effective temperatures, evidence for relatively reduced parent bodies is preserved under most circumstances for at least several characteristic lifetimes of the debris disk.
Schema2QA: High-Quality and Low-Cost Q&A Agents for the Structured Web

Building a question-answering agent currently requires large annotated datasets, which are prohibitively expensive. This paper proposes Schema2QA, an open-source toolkit that can generate a Q&A system from a database schema augmented with a few annotations for each field. The key concept is to cover the space of possible compound queries on the database with a large number of in-domain questions synthesized with the help of a corpus of generic query templates. The synthesized data and a small paraphrase set are used to train a novel neural network based on the BERT pretrained model. We use Schema2QA to generate Q&A systems for five Schema.org domains, restaurants, people, movies, books and music, and obtain an overall accuracy between 64% and 75% on crowdsourced questions for these domains. Once annotations and paraphrases are obtained for a Schema.org schema, no additional manual effort is needed to create a Q&A agent for any website that uses the same schema. Furthermore, we demonstrate that learning can be transferred from the restaurant to the hotel domain, obtaining a 64% accuracy on crowdsourced questions with no manual effort. Schema2QA achieves an accuracy of 60% on popular restaurant questions that can be answered using Schema.org. Its performance is comparable to Google Assistant, 7% lower than Siri, and 15% higher than Alexa. It outperforms all these assistants by at least 18% on more complex, long-tail questions.
Speaker Discrimination in Humans and Machines: Effects of Speaking Style Variability.

Does speaking style variation affect humans' ability to distinguish individuals from their voices? How do humans compare with automatic systems designed to discriminate between voices? In this paper, we attempt to answer these questions by comparing human and machine speaker discrimination performance for read speech versus casual conversations. Thirty listeners were asked to perform a same versus different speaker task. Their performance was compared to a state-of-the-art x-vector/PLDA-based automatic speaker verification system. Results showed that both humans and machines performed better with style-matched stimuli, and human performance was better when listeners were native speakers of American English. Native listeners performed better than machines in the style-matched conditions (EERs of 6.96% versus 14.35% for read speech, and 15.12% versus 19.87%, for conversations), but for style-mismatched conditions, there was no significant difference between native listeners and machines. In all conditions, fusing human responses with machine results showed improvements compared to each alone, suggesting that humans and machines have different approaches to speaker discrimination tasks. Differences in the approaches were further confirmed by examining results for individual speakers which showed that the perception of distinct and confused speakers differed between human listeners and machines.
A new positivity condition for the curvature of Hermitian manifolds

In this note, we introduce a new type of positivity condition for the curvature of a Hermitian manifold, which generalizes the notion of nonnegative quadratic orthogonal bisectional curvature to the non-Kahler case. We derive a Bochner formula for closed (1, 1)-forms from which this condition appears naturally and prove that if a Hermitian manifold satisfies our positivity condition, then any class $$\alpha \in H^{1, 1}_{BC}(X)$$ can be represented by a closed (1, 1)-form which is parallel with respect to the Bismut connection. Lastly, we show that such a curvature positivity condition holds on certain generalized Hopf manifolds and on certain Vaisman manifolds.
Recent Work on Gravitational Waves From a Generic Standard Model-like Effective Higgs Potential

I present recent work on gravitational waves (GWs) from a generic Standard Model-like effective potential for the electroweak phase transition. We derive a semi-analytic expression for the approximate tunneling temperature, and analytic and approximate expressions for the two GW parameters α and β. A quick summary of our analysis and general results, as well as a list of some specific models which easily fit into this framework, are presented. The work presented here has been done in collaboration with Stefano Profumo.
Conformal superalgebras via tractor calculus

We use the manifestly conformally invariant description of a Lorentzian conformal structure in terms of a parabolic Cartan geometry in order to introduce a superalgebra structure on the space of twistor spinors and normal conformal vector fields formulated in purely algebraic terms on parallel sections in tractor bundles. Via a fixed metric in the conformal class, one reproduces a conformal superalgebra structure that has been considered in the literature before. The tractor approach, however, makes clear that the failure of this object to be a Lie superalgebra in certain cases is due to purely algebraic identities on the spinor module and to special properties of the conformal holonomy representation. Moreover, it naturally generalizes to higher signatures. This yields new formulas for constructing new twistor spinors and higher order normal conformal Killing forms out of existing ones, generalizing the well-known spinorial Lie derivative. Moreover, we derive restrictions on the possible dimension of the space of twistor spinors in any metric signature.
Studies of single-photoelectron response and of performance in magnetic field of a H8500C-03 photomultiplier tube

We studied the single-photoelectron detection capabilities of a multianode photomultiplier tube H8500C-03 and its performance in high magnetic field. Our results show that the device can readily resolve signals at the single photoelectron level making it suitable for photon detection in both threshold and ring imaging Cherenkov detectors. We also found that a large longitudinal magnetic field, up to 300 Gauss, induces a change in the relative output of at most 55% for an edge pixel, and of at most 15% for a central pixel. The H8500C-03 signal loss in transverse magnetic fields it is significantly more pronounced than for the longitudinal case. Our studies of single photoelectron reduction in magnetic fields point to the field induced misfocusing of the photoelectron extracted from the photocathode as primary cause of signal loss. With appropriate shielding this PMT could function in high magnetic field environments.
Section rings of $\mathbb{Q}$-divisors on minimal rational surfaces

We give bounds on the degree of generation and relations of section rings associated to arbitrary $\mathbb{Q}$-divisors on projective spaces of all dimensions and Hirzebruch surfaces. For section rings of effective $\mathbb{Q}$-divisors on projective spaces, we find the best possible bound on the degrees of generators and relations.
Enumeration of finite inverse semigroups

We give an efficient algorithm for the enumeration up to isomorphism of the inverse semigroups of order n, and we count the number S(n) of inverse semigroups of order $$n\le 15$$. This improves considerably on the previous highest-known value S(9). We also give a related algorithm for the enumeration up to isomorphism of the finite inverse semigroups S with a given underlying semilattice of idempotents E, a given restriction of Green’s $$\mathrel {\mathcal {D}}$$-relation on S to E, and a given list of maximal subgroups of S associated to the elements of E.
Characterization of an x-ray hybrid CMOS detector with low interpixel capacitive crosstalk

We present the results of x-ray measurements on a hybrid CMOS detector that uses a H2RG ROIC and a unique bonding structure. The silicon absorber array has a 36μm pixel size, and the readout array has a pitch of 18μm; but only one readout circuit line is bonded to each 36x36μm absorber pixel. This unique bonding structure gives the readout an effective pitch of 36μm. We find the increased pitch between readout bonds significantly reduces the interpixel capacitance of the CMOS detector reported by Bongiorno et al. 20101 and Kenter et al. 2005.2
A numerical dressing method for the nonlinear superposition of solutions of the KdV equation

In this paper we present the unification of two existing numerical methods for the construction of solutions of the Korteweg?de Vries (KdV) equation. The first method is used to solve the Cauchy initial-value problem on the line for rapidly decaying initial data. The second method is used to compute finite-genus solutions of the KdV equation. The combination of these numerical methods allows for the computation of exact solutions that are asymptotically (quasi-)periodic finite-gap solutions and are a nonlinear superposition of dispersive, soliton and (quasi-)periodic solutions in the finite (x, t)-plane. Such solutions are referred to as superposition solutions. We compute these solutions accurately for all values of x and t.
Uniqueness of Ground States for Short-Range Spin Glasses in the Half-Plane

We consider the Edwards-Anderson Ising spin glass model on the half-plane \({\mathbb{Z} \times \mathbb{Z}^+}\) with zero external field and a wide range of choices, including mean zero Gaussian for the common distribution of the collection J of i.i.d. nearest neighbor couplings. The infinite-volume joint distribution \({\mathcal{K}(J,\alpha)}\) of couplings J and ground state pairs α with periodic (respectively, free) boundary conditions in the horizontal (respectively, vertical) coordinate is shown to exist without need for subsequence limits. Our main result is that for almost every J, the conditional distribution \({\mathcal{K}(\alpha\,|\,J)}\) is supported on a single ground state pair.
Inferences About the Magnetic Field Structure of a CME with Both In Situ and Faraday Rotation Constraints

On 2012 August 2, two CMEs (CME-1 and CME-2) erupted from the west limb of the Sun as viewed from Earth, and were observed in images from the white light coronagraphs on the SOHO and STEREO spacecraft. These events were also observed by the Very Large Array (VLA), which was monitoring the Sun at radio wavelengths, allowing time-dependent Faraday rotation observations to be made of both events. We use the white-light imaging and radio data to model the 3-D field geometry of both CMEs, assuming a magnetic flux rope geometry. For CME-2, we also consider 1 au in situ field measurements in the analysis, as this CME hits STEREO-A on August~6, making this the first CME with observational constraints from stereoscopic coronal imaging, radio Faraday rotation, and in situ plasma measurements combined. The imaging and in situ observations of CME-2 provide two clear predictions for the radio data; namely that VLA should observe positive rotation measures (RMs) when the radio line of sight first encounters the CME, and that the sign should reverse to negative within a couple hours. The initial positive RMs are in fact observed. The expected sign reversal is not, but the VLA data unfortunately end too soon to be sure of the significance of this discrepancy. We interpret an RM increase prior to the expected occultation time of the CME as a signature of a sheath region of deflected field ahead of the CME itself.
Dirbe minus 2mass: confirming the cosmic infrared background at 2.2 microns

Stellar fluxes from the Two Micron All Sky Survey catalog are used to remove the contribution owing to Galactic stars from the intensity measured by the Diffuse Infrared Background Experiment in four regions in the north and south Galactic polar caps. After subtracting the interplanetary and Galactic foregrounds, a consistent residual intensity of 14.8 ± 4.6 kJy sr-1 or 20.2 ± 6.3 nW m-2 sr-1 at 2.2 μm is found. At 1.25 μm the residuals show more scatter and are a much smaller fraction of the foreground, leading to a weak limit on the cosmic infrared background of 12.0 ± 6.8 kJy sr-1 or 28.9 ± 16.3 nW m-2 sr-1 (1 σ).
An Optimal Coordination Framework for Connected and Automated Vehicles in two Interconnected Intersections

In this paper, we provide a decentralized optimal control framework for coordinating connected and automated vehicles (CAVs) in two interconnected intersections. We formulate a control problem and provide a solution that can be implemented in real time. The solution yields the optimal acceleration/deceleration of each CAV under the safety constraint at “conflict zones,” where there is a chance of potential collision. Our objective is to minimize travel time for each CAV. If no such solution exists, then each CAV solves an energy-optimal control problem. We evaluate the effectiveness of the efficiency of the proposed framework through simulation.
Interface studies of molecular beam epitaxy (MBE) grown ZnSe–GaAs heterovalent structures

Comprehensive investigations on ZnSe/GaAs and GaAs/ZnSe interfaces were carried out by photoluminescence and transmission electron microscopy as a part of realizing high quality ZnSe–GaAs (100) hetero-valent structures (HS). The nature of the ZnSe/GaAs interface under different surface terminations of GaAs was examined. The ZnSe/Ga-terminated GaAs was found to have a superior optical and microstructural quality, with a chemical interface consisting of a mixture of both GaAs and ZnSe atomic constituents. For GaAs/ZnSe interface studies, a low-temperature migration enhanced epitaxy (LT-MEE) growth technique was used to grow GaAs layers under the conditions compatible to the growth of ZnSe. Both Ga and As-initialized LT-MEE GaAs/ZnSe interfaces were investigated. A defective transition layer was observed along the As-initialized GaAs/ZnSe interface, which may be attributed to the formation of the Zn 3As 2 compound. The correlation between the observed optical as well as structural properties of both (GaAs/ZnSe and ZnSe/GaAs) interfaces and growth conditions used in this study is discussed in detail. This study could provide a valuable insight into the interface nature of the ZnSe–GaAs HS.
Community detection using fast low-cardinality semidefinite programming

Modularity maximization has been a fundamental tool for understanding the community structure of a network, but the underlying optimization problem is nonconvex and NP-hard to solve. State-of-the-art algorithms like the Louvain or Leiden methods focus on different heuristics to help escape local optima, but they still depend on a greedy step that moves node assignment locally and is prone to getting trapped. In this paper, we propose a new class of low-cardinality algorithm that generalizes the local update to maximize a semidefinite relaxation derived from max-k-cut. This proposed algorithm is scalable, empirically achieves the global semidefinite optimality for small cases, and outperforms the state-of-the-art algorithms in real-world datasets with little additional time cost. From the algorithmic perspective, it also opens a new avenue for scaling-up semidefinite programming when the solutions are sparse instead of low-rank.
Regularizing Matrix Factorization with User and Item Embeddings for Recommendation

Following recent successes in exploiting both latent factor and word embedding models in recommendation, we propose a novel Regularized Multi-Embedding (RME) based recommendation model that simultaneously encapsulates the following ideas via decomposition: (1) which items a user likes, (2) which two users co-like the same items, (3) which two items users often co-liked, and (4) which two items users often co-disliked. In experimental validation, the RME outperforms competing state-of-the-art models in both explicit and implicit feedback datasets, significantly improving Recall@5 by 5.9~7.0%, NDCG@20 by 4.3~5.6%, and MAP@10 by 7.9~8.9%. In addition, under the cold-start scenario for users with the lowest number of interactions, against the competing models, the RME outperforms NDCG@5 by 20.2% and 29.4% in MovieLens-10M and MovieLens-20M datasets, respectively. Our datasets and source code are available at: https://github.com/thanhdtran/RME.git.
Correlation between Student Collaboration Network Centrality and Academic Performance.

The benefits of student collaboration in upper-division physics courses are not automatically transferred to exam performance, but rather depends on the structure of the course and exams.
Energy-Efficient Power Adaptation for Cognitive Radio Systems under Imperfect Channel Sensing

In this paper, energy efficient power adaptation is considered in sensing-based spectrum sharing cognitive radio systems in which secondary users first perform channel sensing and then initiate data transmission with two power levels based on the sensing decisions (e.g., idle or busy). It is assumed that spectrum sensing is performed by the cognitive secondary users, albeit with possible errors. In this setting, the optimization problem of maximizing the energy efficiency (EE) subject to peak/average transmission power constraints and average interference constraints is considered. The circuit power is taken into account for total power consumption. By exploiting the quasiconcave property of the EE maximization problem, the original problem is transformed into an equivalent parameterized concave problem and Dinkelbach's method-based iterative power adaptation algorithm is proposed. The impact of sensing performance, peak/average transmit power constraints and average interference constraint on the energy efficiency of cognitive radio systems is analyzed.
AIOps for a Cloud Object Storage Service

With the growing reliance on the ubiquitous availability of IT systems and services, these systems become more global, scaled, and complex to operate. To maintain business viability, IT service providers must put in place reliable and cost efficient operations support. Artificial Intelligence for IT Operations (AIOps) is a promising technology for alleviating operational complexity of IT systems and services. AIOps platforms utilize big data, machine learning and other advanced analytics technologies to enhance IT operations with proactive actionable dynamic insight. In this paper we share our experience applying the AIOps approach to a production cloud object storage service to get actionable insights into system's behavior and health. We describe a real-life production cloud scale service and its operational data, present the AIOps platform we have created, and show how it has helped us resolving operational pain points.
Effective predictions of event shapes: factorized, resummed and gapped angularity distributions

Using soft-collinear effective theory (SCET), which provides a unified framework for factorization, resummation of logarithms, and incorporation of universal nonperturbative functions in hard-scattering QCD cross-sections, we present a new prediction of angularity distributions in e+e− annihilation. Angularities τa are an infinite class of event shapes which vary in their sensitivity to the substructure of jets in the final state, controlled by a continuous parameter a < 2. We calculate angularity distributions for all a < 1 to first order in the strong coupling αs and resum large logarithms in these distributions to next-to-leading logarithmic (NLL) accuracy. Our expressions for the next-to-leading order (NLO) (αs) partonic jet and soft functions in the factorization theorem for angularity distributions are given for the first time. We employ a model for the nonperturbative soft function with a gap parameter which cancels the renormalon ambiguity in the partonic soft function. We explore the relation between the SCET approach to resummation and past approaches in QCD, and discuss the advantages of the effective theory approach. In addition, we draw from the NLO calculations of the jet and soft functions an intuitive lesson about how factorization breaks down in the effective theory as a → 1.
Acceleration from Modified Gravity: Lessons from Worked Examples

I examine how two specific examples of modified gravity explanations of cosmic acceleration help us understand some general problems confronting cosmological tests of gravity: how do we distinguish modified gravity from dark energy if they can be made formally equivalent? how do we parameterize deviations according to physical principles with sufficient generality, yet focus cosmological tests into areas that complement our existing knowledge of gravity? how do we treat the dynamics of modifications which necessarily involve non-linearities that preclude superposition of forces? The modified action f ( R ) and DGP braneworld models provide insight on these question as fully-worked examples whose expansion history, linear perturbation theory, and most recently, non-linear N-body and force-modification field dynamics of cosmological simulations are available for study.
The Shape and Orientation of NGC 3379: Implications for Nuclear Decoupling

The intrinsic shape and orientation of the elliptical galaxy NGC 3379 are estimated by dynamical modeling. The maximal-ignorance shape estimate, an average over the parameter space, is axisymmetric and oblate in the inner parts, with an outward triaxiality gradient. The 1 σ limits on total mass triaxiality T are T < 0.13 at 0.33 kpc and T = 0.08 ± 0.07 at 3.5 kpc from the center. The luminous short-to-long axis ratio cL = 0.79 inside 0.82 kpc, flattening to cL = 0.66 at 1.9 kpc. The results are similar if the galaxy is assumed to rotate about its short axis. Estimates for cL are robust, but those for T are dependent on whether the internal rotation field is disklike or spheroid-like. Short-axis inclinations i between 30° and 50° are preferred for nearly axisymmetric models, but triaxial models in high inclination are also allowed, which can affect central black hole mass estimates. The available constraints on orientation rule out the possibility that the nuclear dust ring at R ≈ 15 is in a stable equilibrium in one of the galaxy's principal planes. The ring is thus a decoupled nuclear component not linked to the main body of the galaxy. It may be connected with ionized gas that extends to larger radii, since the projected gas rotation axis is near the minor axis of the ring. The gas and dust may both be part of a strongly warped disk; however, if caused by differential precession, the warp will wind up on itself in a few times 107 yr. The decoupling with the stellar component suggests that the gas has an external origin, but no obvious source is present.
The Technologies Required for Fusing HPC and Real-Time Data to Support Urgent Computing

The use of High Performance Computing (HPC) to compliment urgent decision making in the event of disasters is an important future potential use of supercomputers. However, the usage modes involved are rather different from how HPC has been used traditionally. As such, there are many obstacles that need to be overcome, not least the unbounded wait times in the batch system queues, to make the use of HPC in disaster response practical. In this paper, we present how the VESTEC project plans to overcome these issues and develop a working prototype of an urgent computing control system. We describe the requirements for such a system and analyse the different technologies available that can be leveraged to successfully build such a system. We finally explore the design of the VESTEC system and discuss ongoing challenges that need to be addressed to realise a production level system.
Time and thermodynamics extended discussion on “Time & clocks: A thermodynamic approach”

Abstract In the paper, “Time & clocks: A thermodynamic approach” Lucia and Grisolia describe the connections between the physical nature of time and macroscopic irreversibility in thermodynamics. They also discuss the possibility of constructing a thermodynamic clock that links the two, through an approach based on the behaviour of a black body. Their work primarily focuses on the macroscopic irreversibilty, and their attempt to define ‘thermodynamic time’ is grounded on the concepts from non-equilibrium thermodynamics such as, entropy generation and time-dependent thermodynamic fluxes - in and out of the system. In this letter, we present a first principles approach based on the Maupertuis principle to describe the connection between time and thermodynamics for equilibrium phenomena. Our novel interpretation of the temperature as a functional allows us to extend our formalism to irreversible processes when the local equilibrium hypothesis is satisfied. Through our framework we also establish a functional relationship between equilibrium and non-equilibrium time-scales while distinguishing between the two.
Pre-string theory

In this note, I recollect a two-week period in September 1968 when I factorized the Veneziano model using string variables in Chicago. Professor Yoichiro Nambu went on to calculate the N-particle dual resonance model and then to factorize it on an exponential degeneracy of states. That was in 1968 and the following year 1969 he discovered the string action. I also include some other reminiscences of Nambu who passed away on July 5, 2015.
Antisymmetry: Fundamentals and Applications

Symmetry is fundamental to understanding our physical world. An antisymmetry operation switches between two different states of a trait, such as two time states, position states, charge states, spi...
AN INDEX THEOREM FOR END-PERIODIC OPERATORS

We extend the Atiyah, Patodi, and Singer index theorem for first-order differential operators from the context of manifolds with cylindrical ends to manifolds with periodic ends. This theorem provides a natural complement to Taubes’ Fredholm theory for general end-periodic operators. Our index theorem is expressed in terms of a new periodic eta-invariant that equals the Atiyah–Patodi–Singer eta-invariant in the cylindrical setting. We apply this periodic eta-invariant to the study of moduli spaces of Riemannian metrics of positive scalar curvature.