cssi/SciSciGPT-SciSciNet huggingface dataset:
Group trisections and smooth 4–manifolds

A trisection of a smooth, closed, oriented 4 –manifold is a decomposition into three 4 –dimensional 1 –handlebodies meeting pairwise in 3 –dimensional 1 –handlebodies, with triple intersection a closed surface. The fundamental groups of the surface, the 3 –dimensional handlebodies, the 4 –dimensional handlebodies and the closed 4 –manifold, with homomorphisms between them induced by inclusion, form a commutative diagram of epimorphisms, which we call a trisection of the 4 –manifold group. A trisected 4 –manifold thus gives a trisected group; here we show that every trisected group uniquely determines a trisected 4 –manifold. Together with Gay and Kirby’s existence and uniqueness theorem for 4 –manifold trisections, this gives a bijection from group trisections modulo isomorphism and a certain stabilization operation to smooth, closed, connected, oriented 4 –manifolds modulo diffeomorphism. As a consequence, smooth 4 –manifold topology is, in principle, entirely group-theoretic. For example, the smooth 4 –dimensional Poincare conjecture can be reformulated as a purely group-theoretic statement.
Null geodesics and wave front singularities in the Gödel space–time

We explore wave fronts of null geodesics in the Godel metric emitted from point sources both at, and away from, the origin. For constant time wave fronts emitted by sources away from the origin, we find cusp ridges as well as blue sky metamorphoses where spatially disconnected portions of the wave front appear, connect to the main wave front, and then later break free and vanish. These blue sky metamorphoses in the constant time wave fronts highlight the non-causal features of the Godel metric. We introduce a concept of physical distance along the null geodesics, and show that for wave fronts of constant physical distance, the reorganization of the points making up the wave front leads to the removal of cusp ridges.
Long-time behavior of $3$–dimensional Ricci flow, C: $3$–manifold topology and combinatorics of simplicial complexes in $3$–manifolds

In the third part of this series of papers, we establish several topological results that will become important for studying the long-time behavior of Ricci flows with surgery. In the first part of this paper we recall some elementary observations in the topology of 3–manifolds. The main part is devoted to the construction of certain simplicial complexes in a given 3–manifold that exhibit useful intersection properties with embedded, incompressible solid tori. This paper is purely topological in nature and Ricci flows will not be used.
Invariant prime ideals in quantizations of nilpotent Lie algebras

De Concini, Kac and Procesi defined a family of subalgebras U + of a quantized universal enveloping algebra Uq(g), associated to the elements of the corresponding Weyl group W . They are deformations of the universal enveloping algebras U(n+ ∩ Adw(n−)) where n± are the nilradicals of a pair of dual Borel subalgebras. Based on results of Gorelik and Joseph and an interpretation of U + as quantized algebras of functions on Schubert cells, we construct explicitly the H invariant prime ideals of each U + and show that the corresponding poset is isomorphic to W, where H is the group of group-like elements of Uq(g). Moreover, for each H-prime of U w + we construct a generating set in terms of Demazure modules related to fundamental representations. Using results of Ramanathan and Kempf we prove similar theorems for vanishing ideals of closures of torus orbits of symplectic leaves of related Poisson structures on Schubert cells in flag varieties.
Raman topography and strain uniformity of large-area epitaxial graphene.

We report results of Raman spectroscopy studies of large-area epitaxial graphene grown on SiC. Our work reveals unexpectedly large variation in Raman shift resulting from graphene strain inhomogeneity, which is shown to be correlated with physical topography by coupling Raman spectroscopy with atomic force microscopy. We show that graphene strain can vary over a distance shorter than 300 nm and may be uniform only over roughly 1 μm. We show that nearly strain-free graphene is possible even in epitaxial graphene.
s.Baer and s.Rickart Modules

In this paper, we study module theoretic definitions of the Baer and related ring concepts. We say a module is s.Baer if the right annihilator of a nonempty subset of the module is generated by an idempotent in the ring. We show that s.Baer modules satisfy a number of closure properties. Under certain conditions, a torsion theory is established for the s.Baer modules, and we provide examples of s.Baer torsion modules and modules with a nonzero s.Baer radical. The other principal interest of this paper is to provide explicit connections between s.Baer modules and projective modules. Among other results, we show that every s.Baer module is an essential extension of a projective module. Additionally, we prove, with limited and natural assumptions, that in a generalized triangular matrix ring every s.Baer submodule of the ring is projective. As an application, we show that every prime ring with a minimal right ideal has the strong summand intersection property. Numerous examples are provided to illustrate, motivate, and delimit the theory.
The Geodesic Ray Transform on Riemannian Surfaces with Conjugate Points

We study the geodesic X-ray transform X on compact Riemannian surfaces with conjugate points. Regardless of the type of the conjugate points, we show that we cannot recover the singularities and, therefore, this transform is always unstable (ill-posed). We describe the microlocal kernel of X and relate it to the conjugate locus. We present numerical examples illustrating the cancellation of singularities. We also show that the attenuated X-ray transform is well posed if the attenuation is positive and there are no more than two conjugate points along each geodesic; but it is still ill-posed if there are three or more conjugate points. Those results follow from our analysis of the weighted X-ray transform.
A Technique to Derive Improved Proper Motions for Kepler Objects of Interest

We outline an approach yielding proper motions with higher precision than exists in present catalogs for a sample of stars in the Kepler field. To increase proper-motion precision, we combine first-moment centroids of Kepler pixel data from a single season with existing catalog positions and proper motions. We use this astrometry to produce improved reduced-proper-motion diagrams, analogous to a Hertzsprung–Russell (H-R) diagram, for stars identified as Kepler objects of interest. The more precise the relative proper motions, the better the discrimination between stellar luminosity classes. Using UCAC4 and PPMXL epoch 2000 positions (and proper motions from those catalogs as quasi-Bayesian priors), astrometry for a single test Channel (21) and Season (0) spanning 2 yr yields proper motions with an average per-coordinate proper-motion error of 1.0 mas yr^(−1), which is over a factor of three better than existing catalogs. We apply a mapping between a reduced-proper-motion diagram and an H-R diagram, both constructed using Hubble Space Telescope parallaxes and proper motions, to estimate Kepler object of interest K-band absolute magnitudes. The techniques discussed apply to any future small-field astrometry as well as to the rest of the Kepler field.
Thermoelectric properties of intermetallic semiconducting RuIn3 and metallic IrIn3

Low temperature (<400 K) thermoelectric properties of semiconducting RuIn3 and metallic IrIn3 are reported. RuIn3 is a narrow band gap semiconductor with a large n-type Seebeck coefficient at room temperature (S(290K)≈−400μV/K), but the thermoelectric figure of merit (ZT(290K)≈0.007) is small because of high electrical resistivity and thermal conductivity (κ(290 K) ∼ 2.0 W/m K). IrIn3 is a metal (n(290K)≈1021cm−3) with low thermopower at room temperature (S(290K)≈−20μV/K). Iridium substitution on the ruthenium site has a dramatic effect on transport properties, which leads to a large improvement in the power factor (S2ρ(390K)∼−207μWm K2) and corresponding figure of merit (ZT(380 K) = 0.053), improving the efficiency of the material by almost an order of magnitude.
Path properties of atmospheric transitions: Illustration with a low-order sudden stratospheric warming model

AbstractMany rare weather events, including hurricanes, droughts, and floods, dramatically impact human life. To accurately forecast these events and characterize their climatology requires special...
Covariantly functorial wrapped Floer theory on Liouville sectors

We introduce a class of Liouville manifolds with boundary which we call Liouville sectors. We define the wrapped Fukaya category, symplectic cohomology, and the open-closed map for Liouville sectors, and we show that these invariants are covariantly functorial with respect to inclusions of Liouville sectors. From this foundational setup, a local-to-global principle for Abouzaid’s generation criterion follows.
STATIC POTENTIAL AND A NEW GENERALIZED CONNECTION IN THREE DIMENSIONS

For a recently proposed pure gauge theory in three dimensions, without a Chern–Simons term, we calculate the static interaction potential within the structure of the gauge-invariant variables formalism. As a consequence, a confining potential is obtained. This result displays a marked qualitative departure from the usual Maxwell–Chern–Simons theory.
Random defect lines in conformal minimal models

We analyze the effect of adding quenched disorder along a defect line in the 2D conformal minimal models using replicas. The disorder is realized by a random applied magnetic field in the Ising model, by fluctuations in the ferromagnetic bond coupling in the tricritical Ising model and tricritical three-state Potts model (the φ12 operator), etc. We find that for the Ising model, the defect renormalizes to two decoupled half-planes without disorder, but that for all other models, the defect renormalizes to a disorder-dominated fixed point. Its critical properties are studied with an expansion in ϵ∝1/m for the mth Virasoro minimal model. The decay exponents XN=N21−9(3N−4)4(m+1)2+O3m+13 of the Nth moment of the two-point function of φ12 along the defect are obtained to 2-loop order, exhibiting multifractal behavior. This leads to a typical decay exponent Xtyp=121+9(m+1)2+O3m+13. One-point functions are seen to have a non-self-averaging amplitude. The boundary entropy is larger than that of the pure system by order 1/m3. As a byproduct of our calculations, we also obtain to 2-loop order the exponent XN=N1−29π2(3N−4)(q−2)2+O(q−2)3 of the Nth moment of the energy operator in the q-state Potts model with bulk bond disorder.
Automated lattice data generation

The process of generating ensembles of gauge configurations (and measuring various observables over them) can be tedious and error-prone when done “by hand”. In practice, most of this procedure can be automated with the use of a workflow manager. We discuss how this automation can be accomplished using Taxi, a minimal Python-based workflow manager built for generating lattice data. We present a case study demonstrating this technology.
Scalar charges and scaling relations in massless scalar-Tensor theories

The timing of binary pulsars allows us to place some of the tightest constraints on modified theories of gravity. Perhaps some of the most interesting and well-motivated extensions to General Relativity are scalar-tensor theories, in which gravity is mediated by the metric tensor and a scalar field. These theories predict large deviations from General Relativity in the presence of neutron stars through a phenomenon known as scalarization. Neutron stars in scalar-tensor theories develop scalar charges, which directly enter the timing model for binary pulsars. In this paper, we calculate and tabulate these scalar charges in two popular, massless scalar tensor theories for a collection of neutron star equations of state that are compatible with constraints placed by the recent, gravitational wave observations of a binary neutron star coalescence. We then study these scalar charges and explore analytic scaling relations that allow us to predict their value in a large region of parameter space. Our results allow for the quick evaluation of the scalar charge in a large region of scalar-tensor theory parameter space, which has applications for gravitational wave tests of scalar-tensor theories, as well as binary pulsar experiments.
The Goldston-Pintz-Yildirim sieve and maximal gaps

One field of particular interest in Number Theory concerns the gaps between consecutive primes. Within the last few years, very important results have been achieved on how small these gaps can be. The strongest of these results were obtained by Dan Goldston, Janos Pintz and Cem Yalcin Yildirim. The present work begins by generalizing their results so that they can be applied to related problems in a more direct manner. Additionally, we improve the bound for $F_2$ (concerning the maximal gap in a block of three primes) obtained by the authors' first paper with our generalization.
A Remark on CFT Realization of Quantum Doubles of Subfactors. Case Index< 4

It is well known that the quantum double $${D(N\subset M)}$$ of a finite depth subfactor $${N\subset M}$$ , or equivalently the Drinfeld center of the even part fusion category, is a unitary modular tensor category. It is big open conjecture that all (unitary) modular tensor categories arise from conformal field theory. We show that for every subfactor $${N\subset M}$$ with index $${[M:N] < 4}$$ the quantum double $${D(N\subset M)}$$ is realized as the representation category of a completely rational conformal net. In particular, the quantum double of $${E_6}$$ can be realized as a $${\mathbb{Z}_2}$$ -simple current extension of $${{{\rm SU}(2)}_{10} \times {{\rm Spin}(11)}_1}$$ and thus is not exotic in any sense. As a byproduct, we obtain a vertex operator algebra for every such subfactor. We obtain the result by showing that if a subfactor $${N\subset M }$$ arises from $${\alpha}$$ -induction of completely rational nets $${\mathcal{A}\subset \mathcal{B}}$$ and there is a net $${\tilde{\mathcal{A}}}$$ with the opposite braiding, then the quantum $${D(N\subset M)}$$ is realized by completely rational net. We construct completely rational nets with the opposite braiding of $${{{\rm SU}(2)}_k}$$ and use the well-known fact that all subfactors with index $${[M:N] < 4}$$ arise by $${\alpha}$$ -induction from $${{{\rm SU}(2)}_k}$$ .
Axiomatic Conformal Theory in Dimensions >2 and AdS/CT Correspondence

We formulate axioms of conformal theory (CT) in dimensions >2 modifying Segal’s axioms for two-dimensional CFT. (In the definition of higher-dimensional CFT, one includes also a condition of existence of energy-momentum tensor.) We use these axioms to derive the AdS/CT correspondence for local theories on AdS. We introduce a notion of weakly local quantum field theory and construct a bijective correspondence between conformal theories on the sphere Sd and weakly local quantum field theories on \({H^{d+1}}\) that are invariant with respect to isometries. (Here \({H^{d+1}}\) denotes hyperbolic space = Euclidean AdS space.) We give an expression of AdS correlation functions in terms of CT correlation functions. The conformal theory has conserved energy-momentum tensor iff the AdS theory has graviton in its spectrum.
Optimized design of antisense oligomers for targeted rRNA depletion

RNA sequencing (RNA-seq) is extensively used to quantify gene expression transcriptome-wide. Although often paired with polyadenylate (poly(A)) selection to enrich for messenger RNA (mRNA), many applications require alternate approaches to counteract the high proportion of ribosomal RNA (rRNA) in total RNA. Recently, digestion using RNaseH and antisense DNA oligomers tiling target rRNAs has emerged as an alternative to commercial rRNA depletion kits. Here, we present a streamlined, more economical RNaseH-mediated rRNA depletion with substantially lower up-front costs, using shorter antisense oligos only sparsely tiled along the target RNA in a 5-min digestion reaction. We introduce a novel Web tool, Oligo-ASST, that simplifies oligo design to target regions with optimal thermodynamic properties, and additionally can generate compact, common oligo pools that simultaneously target divergent RNAs, e.g. across different species. We demonstrate the efficacy of these strategies by generating rRNA-depletion oligos for Xenopus laevis and for zebrafish, which expresses two distinct versions of rRNAs during embryogenesis. The resulting RNA-seq libraries reduce rRNA to <5% of aligned reads, on par with poly(A) selection, and also reveal expression of many non-adenylated RNA species. Oligo-ASST is freely available at https://mtleelab.pitt.edu/oligo to design antisense oligos for any taxon or to target any abundant RNA for depletion.
A Unified Approach to Translate Classical Bandit Algorithms to the Structured Bandit Setting

We consider a finite-armed structured bandit problem in which mean rewards of different arms are known functions of a common hidden parameter $\theta ^{*}$ . Since we do not place any restrictions on these functions, the problem setting subsumes several previously studied frameworks that assume linear or invertible reward functions. We propose a novel approach to gradually estimate the hidden $\theta ^{*}$ and use the estimate together with the mean reward functions to substantially reduce exploration of sub-optimal arms. This approach enables us to fundamentally generalize any classical bandit algorithm including UCB and Thompson Sampling to the structured bandit setting. We prove via regret analysis that our proposed UCB-C algorithm (structured bandit versions of UCB) pulls only a subset of the sub-optimal arms $\mathrm {O}(\log T)$ times while the other sub-optimal arms (referred to as non-competitive arms) are pulled O(1) times. As a result, in cases where all sub-optimal arms are non-competitive, which can happen in many practical scenarios, the proposed algorithm achieves bounded regret. We also conduct simulations on the MOVIELENS recommendations dataset to demonstrate the improvement of the proposed algorithms over existing structured bandit algorithms.
The effects of exposure to predators on personality and plasticity

Past experiences are known to affect average behavior but effects on "animal personality", and plasticity are less well studied. To determine whether experience with predators influences these aspects, we compared the behavior of Gryllodes sigillatus before and after exposure to live predators. We found that emergence from shelter and distance moved during open-field trials (activity) changed after exposure, with individuals becoming less likely to emerge from shelters but more active when deprived of shelter. We also found that plasticity in activity increased after exposure to predators and some indications that differences among individuals (i.e. "personality") in emergence from shelter and the amount of an arena investigated increased after exposure. Our results demonstrate that experience with predators affects not only the average behavior of individuals but also how individuals differ from each other--and their own prior behavior--even when all individuals have the same experiences.
The effect of a ketogenic diet and synergy with rapamycin in a mouse model of breast cancer.

Background The effects of diet in cancer, in general, and breast cancer in particular, are not well understood. Insulin inhibition in ketogenic, high fat diets, modulate downstream signaling molecules and are postulated to have therapeutic benefits. Obesity and diabetes have been associated with higher incidence of breast cancer. Addition of anti-cancer drugs together with diet is also not well studied. Methods Two diets, one ketogenic, the other standard mouse chow, were tested in a spontaneous breast cancer model in 34 mice. Subgroups of 3–9 mice were assigned, in which the diet were implemented either with or without added rapamycin, an mTOR inhibitor and potential anti-cancer drug. Results Blood glucose and insulin concentrations in mice ingesting the ketogenic diet (KD) were significantly lower, whereas beta hydroxybutyrate (BHB) levels were significantly higher, respectively, than in mice on the standard diet (SD). Growth of primary breast tumors and lung metastases were inhibited, and lifespans were longer in the KD mice compared to mice on the SD (p<0.005). Rapamycin improved survival in both mouse diet groups, but when combined with the KD was more effective than when combined with the SD. Conclusions The study provides proof of principle that a ketogenic diet a) results in serum insulin reduction and ketosis in a spontaneous breast cancer mouse model; b) can serve as a therapeutic anti-cancer agent; and c) can enhance the effects of rapamycin, an anti-cancer drug, permitting dose reduction for comparable effect. Further, the ketogenic diet in this model produces superior cancer control than standard mouse chow whether with or without added rapamycin.
Unsteady wing surface pressures in the wake of a propeller

The unsteady nature of the propeller slipstream interacting with a wing has been studied by flow visualization and unsteady wing surface pressure measurements. Flow visualization was performed by marking the propeller tip vortex with smoke. Unsteady wing surface pressures were measured by traversing a wing instrumented with a chordwise array of 16 microphones in a spanwise direction through the propeller wake. This work yielded information on the motion of the propeller wake as it passes over the wing. As the propeller wake passed over the wing: the propeller tip vortex experienced an inviscid interaction at the leading edge; viscous action at the leading edge severed the propeller tip vortex; the propeller tip vortex experienced significant spanwise and chordwise displacements and then deformed in order to reconnect at the trailing edge; axial velocity in the vortex core caused the helical vortex to thicken or stretch near the wing surface; and, the magnitude of the pressure fluctuations decreased in magnitude with distance traveled along the chord.
Document Structure Extraction Using Prior Based High Resolution Hierarchical Semantic Segmentation

Structure extraction from document images has been a long-standing research topic due to its high impact on a wide range of practical applications. In this paper, we share our findings on employing a hierarchical semantic segmentation network for this task of structure extraction. We propose a prior based deep hierarchical CNN network architecture that enables document structure extraction using very high resolution (\(1800 \times 1000\)) images. We divide the document image into overlapping horizontal strips such that the network segments a strip and uses its prediction mask as prior for predicting the segmentation of the subsequent strip. We perform experiments establishing the effectiveness of our strip based network architecture through ablation methods and comparison with low-resolution variations. Further, to demonstrate our network’s capabilities, we train it on only one type of documents (Forms) and achieve state-of-the-art results over other general document datasets. We introduce our new human-annotated forms dataset and show that our method significantly outperforms different segmentation baselines on this dataset in extracting hierarchical structures. Our method is currently being used in Adobe’s AEM Forms for automated conversion of paper and PDF forms to modern HTML based forms.
Evidence of Superior and Inferior Sinoatrial Nodes in the Mammalian Heart

Abstract Objectives This study sought to investigate the shift of leading pacemaker locations in healthy and failing mammalian hearts over the entire range of physiological heart rates (HRs), and t...
Changing Reward Expectation Transforms Spatial Encoding and Retrieval in the Hippocampus

Internal states of reward expectation play a central role in influencing the strength of spatial memories. At the cellular level, spatial memories are represented through the firing dynamics of hippocampal place cells. However, it remains unclear how internal states of reward expectation influence place cell dynamics and exert their effects on spatial memories. Here we show that when reward expectation is altered, the same environment becomes encoded by a distinct ensemble of place cells at all locations. Further, when reward expectation is high versus low, place cells demonstrate enhanced reliability during navigation and greater stability across days at all locations within the environment. These findings reveal that when rewards are expected, neuromodulatory circuits that represent internal reward expectation support and strengthen the encoding and retrieval of spatial information by place cells at all locations that lead to reward. This enhanced spatial memory can be used to guide future decisions about which locations are most likely to lead to rewards that are crucial for survival.
Shears for quasisymmetric maps

We give an elementary proof of a theorem that characterizes quasisymmetric maps of the unit circle in terms of shear coordinates on the Farey tesselation. The proof only uses the normal family argument for quasisymmetric maps and some elementary hyperbolic geometry.
Spectral Design of Active Mechanical and Electrical Metamaterials

Active matter is ubiquitous in biology and becomes increasingly more important in materials science. While numerous active systems have been investigated in detail both experimentally and theoretically, general design principles for functional active materials are still lacking. Building on a recently developed linear response optimization (LRO) framework, we here demonstrate that the spectra of nonlinear active mechanical and electric circuits can be designed similarly to those of linear passive networks.
Spherical Shell Cosmological Model and Uniformity of Cosmic Microwave Background Radiation

Considered is spherical shell as a model for visible universe and parameters that such model must have to comply with the observable data. The topology of the model requires that motion of all galaxies and light must be confined inside a spherical shell. Consequently the observable universe cannot be defined as a sphere centered on the observer, rather it is an arc length within the volume of the spherical shell. The radius of the shell is 4.46 ± 0.06 Gpc, which is for factor π smaller than radius of a corresponding 3-sphere. However the event horizon, defined as the arc length inside the shell, has the size of 14.0 ± 0.2 Gpc, which is in agreement with the observable data. The model predicts, without inflation theory, the isotropy and uniformity of the CMB. It predicts the correct value for the Hubble constant H_0 = 67.26 ± 0.90 km/s/Mpc, the cosmic expansion rate H(z), and the speed of the event horizon in agreement with observations. The theoretical suport for shell model comes from general relativity, curvature of space by mass, and from holographic principle. The model explains the reason for the established discrepancy between the non-covariant version of the holographic principle and the calculated dimensionless entropy (S/k) for the visible universe, which exceeds the entropy of a black hole. The model is in accordance with the distribution of radio sources in space, type Ia data, and data from the Hubble Ultra Deep Field optical and near-infrared survey.
A survey of loss functions for semantic segmentation

Image Segmentation has been an active field of research as it has a wide range of applications, ranging from automated disease detection to self driving cars. In the past five years, various papers came up with different objective loss functions used in different cases such as biased data, sparse segmentation, etc. In this paper, we have summarized some of the well-known loss functions widely used for Image Segmentation and listed out the cases where their usage can help in fast and better convergence of a model. Furthermore, we have also introduced a new log-cosh dice loss function and compared its performance on NBFS skull-segmentation open source data-set with widely used loss functions. We also showcased that certain loss functions perform well across all data-sets and can be taken as a good baseline choice in unknown data distribution scenarios.
Polymer informatics: Current status and critical next steps

Abstract Artificial intelligence (AI) based approaches are beginning to impact several domains of human life, science and technology. Polymer informatics is one such domain where AI and machine learning (ML) tools are being used in the efficient development, design and discovery of polymers. Surrogate models are trained on available polymer data for instant property prediction, allowing screening of promising polymer candidates with specific target property requirements. Questions regarding synthesizability, and potential (retro)synthesis steps to create a target polymer, are being explored using statistical means. Data-driven strategies to tackle unique challenges resulting from the extraordinary chemical and physical diversity of polymers at small and large scales are being explored. Other major hurdles for polymer informatics are the lack of widespread availability of curated and organized data, and approaches to create machine-readable representations that capture not just the structure of complex polymeric situations but also synthesis and processing conditions. Methods to solve inverse problems, wherein polymer recommendations are made using advanced AI algorithms that meet application targets, are being investigated. As various parts of the burgeoning polymer informatics ecosystem mature and become integrated, efficiency improvements, accelerated discoveries and increased productivity can result. Here, we review emergent components of this polymer informatics ecosystem and discuss imminent challenges and opportunities.
Higher-genus wall-crossing in the gauged linear sigma model

We introduce a technique for proving all-genus wall-crossing formulas in the gauged linear sigma model as the stability parameter varies, without assuming factorization properties of the virtual class. Implementing this technique to the gauged linear sigma model associated to a complete intersection in weighted projective space, we obtain a uniform proof of the wall-crossing formula in both the geometric and the Landau–Ginzburg phase.
Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction

Recent advances in unbiased learning to rank (LTR) count on Inverse Propensity Scoring (IPS) to eliminate bias in implicit feedback. Though theoretically sound in correcting the bias introduced by treating clicked documents as relevant, IPS ignores the bias caused by (implicitly) treating non-clicked ones as irrelevant. In this work, we first rigorously prove that such use of click data leads to unnecessary pairwise comparisons between relevant documents, which prevent unbiased ranker optimization. Based on the proof, we derive a simple yet well justified new weighting scheme, called Propensity Ratio Scoring (PRS), which provides treatments on both clicks and non-clicks. Besides correcting the bias in clicks, PRS avoids relevant-relevant document comparisons in LTR training and enjoys a lower variability. Our extensive empirical evaluations confirm that PRS ensures a more effective use of click data and improved performance in both synthetic data from a set of LTR benchmarks, as well as in the real-world large-scale data from GMail search.
Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes.

While visual object detection with deep learning has received much attention in the past decade, cases when heavy intra-class occlusions occur have not been studied thoroughly. In this work, we propose a Non-Maximum-Suppression (NMS) algorithm that dramatically improves the detection recall while maintaining high precision in scenes with heavy occlusions. Our NMS algorithm is derived from a novel embedding mechanism, in which the semantic and geometric features of the detected boxes are jointly exploited. The embedding makes it possible to determine whether two heavily-overlapping boxes belong to the same object in the physical world. Our approach is particularly useful for car detection and pedestrian detection in urban scenes where occlusions often happen. We show the effectiveness of our approach by creating a model called SG-Det (short for Semantics and Geometry Detection) and testing SG-Det on two widely-adopted datasets, KITTI and CityPersons for which it achieves state-of-the-art performance. Our code is available at https://github.com/ChenhongyiYang/SG-NMS.
A Time-Power Series Based Semi-Analytical Approach for Power System Simulation

Time-domain simulation is the basis of dynamic security assessment for power systems. Traditionally, numerical integration methods are adopted by simulation software to solve nonlinear power system dynamics for any given contingency under a specific operating condition. An alternative simulation approach promising for online applications is to offline derive a semi-analytical solution (SAS) for power system differential equations and then online evaluate the SAS over consecutive time windows regarding the operating condition and contingency until the simulation result over a desired period is obtained. This paper proposes a general semi-analytical approach that derives and evaluates an SAS in the form of a power series in time to approximate the true solution. This paper provides an error-rate upper bound of the SAS for reliable use of adaptive time windows in evaluation of the SAS. To extend the semi-analytical approach for solving general power system differential-algebraic equations, this paper also proposes a dynamic bus method to efficiently link the SAS for dynamic components with the numerical solution of the network algebraic equations. Case studies on the New England 39-bus system and the Polish 2383-bus system test the performance of the proposed approach, compare it with other methods, and show the potentials of the proposed semi-analytical approach for online simulation.
Conditional Density Estimation, Latent Variable Discovery, and Optimal Transport

A framework is proposed that addresses both conditional density estimation and latent variable discovery. The objective function maximizes explanation of variability in the data, achieved through the optimal transport barycenter generalized to a collection of conditional distributions indexed by a covariate --either given or latent-- in any suitable space. Theoretical results establish the existence of barycenters, a minimax formulation of optimal transport maps, and a general characterization of variability via the optimal transport cost. This framework leads to a family of non-parametric neural network-based algorithms, the BaryNet, with a supervised version that estimates conditional distributions and an unsupervised version that assigns latent variables. The efficacy of BaryNets is demonstrated by tests on both artificial and real-world data sets. A parallel drawn between autoencoders and the barycenter framework leads to the Barycentric autoencoder algorithm (BAE).
Formal Test Synthesis for Safety-Critical Autonomous Systems based on Control Barrier Functions

The prolific rise in autonomous systems has led to questions regarding their safe instantiation in real-world scenarios. Failures in safety-critical contexts such as humanrobot interactions or even autonomous driving can ultimately lead to loss of life. In this context, this paper aims to provide a method by which one can algorithmically test and evaluate an autonomous system. Given a black-box autonomous system with some operational specifications, we construct a minimax problem based on control barrier functions to generate a family of test parameters designed to optimally evaluate whether the system can satisfy the specifications. To illustrate our results, we utilize the Robotarium as a case study for an autonomous system that claims to satisfy waypoint navigation and obstacle avoidance simultaneously. We demonstrate that the proposed test synthesis framework systematically finds those sequences of events (tests) that identify points of system failure.
Patent transactions in the marketplace: Lessons from the USPTO Patent Assignment Dataset

Transaction records involving U.S. patent documents have been maintained by the United States Patent and Trademark Office (USPTO) for over 40 years, but have not been extensively used by scholars. One explanation is that these data have not been in a form amenable for research. To help remedy this deficiency and to foster scholarship, the USPTO Office of Chief Economist is curating internal agency records to release a series of datasets in research‐ready formats. This article describes the USPTO Patent Assignment Dataset (UPAD), a relational database of roughly 6 million assignments, licenses, securitizations, and other conveyances involving about 10 million U.S. patents and patent applications, recorded 1970–2014. To promote research uses, this article provides a comprehensive data description and presents stylized facts derived from the records. Although this article discusses several limitations inherent in using these data, the release of the UPAD creates opportunities to conduct original research, particularly relating to intellectual property collateralization and the markets for technology and innovation.
Asleep at the Wheel (Again)? Bank Audits During the Lead‐Up to the Financial Crisis

We present the first large-sample empirical evidence on U.S. auditors' responses to changes in entity-level audit risk during 2006–2007, the period leading up to the financial crisis of 2008–2009. Treating fiscal year 2005 engagements as a pre-crisis benchmark, we find that audit attention during fiscal year 2006 and 2007 bank audit engagements shifted in line with the shifting audit risks. One implication of these findings is that auditors were able to recognize and respond to financial statement impacts of the macroeconomic shocks that unfolded during the lead-up to the crisis. Another implication is that auditors' failure to issue advance warnings of increasing auditee riskiness during the time leading up to the financial crisis more likely reflects limitations of extant accounting and auditing rules rather than a lack of auditor awareness or attention to those risks.
Voluntary disclosure incentives: Evidence from the municipal bond market

Abstract I investigate the trade-off between capital market incentives, reputational concerns, and administrative costs in the public disclosure decisions of municipal bond issuers. After Ambac׳s bankruptcy, issuers of insured debt increase disclosure relative to issuers of uninsured debt. After local per capita income declines or expenditures increase, issuers, particularly those with strong electoral incentives and weak voter oversight, reduce disclosure. After the implementation of an online filing repository, issuers with few dissemination channels increase disclosure relative to other issuers. Overall, my findings support a positive relationship between voluntary disclosure, risk, and low-cost dissemination, to the extent reputational capital is not threatened.
Antitrust in the New Economy

Concern has been expressed that U. S. antitrust law may not be well suited to regulating the "new economy." Doctrines developed to deal with competition and monopoly in smokestack industries are not well adapted, it is argued, to dealing with the dynamic economy of the 21st century. The industries differ markedly from most of the industries in which modern antitrust doctrine emerged, and particularly from industries that manufacture traditional physical goods, such as steel, automobiles, pipe, wire, aluminium, railroad cars, road building materials, and cigarettes. One of the sources of the quality problem is that in most states the attorney general runs for office independent of the governor and is thus not part of the governor's administration and as a result does not receive much support from the governor in negotiating for appropriations from the legislature. The difficult factual questions presented by new-economy antitrust cases are not limited to technical areas, unfortunately.
Implied volatility dynamics among exchange-traded funds and their largest component stocks

The authors implement a new model for time-variation in implied volatilities and the correlations among them to look for common factors both at the aggregate market level and also within industries. The securities under consideration are ETFs and the largest of their component stocks. Krause and Lien find strong evidence of both market and industry factors in individual stock implied volatilities, with the latter being about one-third the size of the former and mean-reverting more quickly. They then explore how the amount of volatility spillover from the ETF to its components is influenced by option trading volume and the relative importance of the individual stock in the ETF portfolio.
Economic policy of a free society

Liberalism correctly understood is little more than the persistent and consistent applications of the principles of economics of the affairs of men be they domestic or international. These include mutually beneficial exchange, the absence of political privilege, and toleration. The institutional precondition of these principles is the rule of law, private property, and freedom of contract. Since the collapse of communism, however, the gains in human progress that have followed from economic and political liberalization are being increasingly questioned and critiqued. To counter these criticisms of liberalism, I contend, requires tireless and varied iterations of the basic principles. In order to prevent the invisible hand of the market process from being captured by the visible hand of political privilege, political economists must stress how the creative powers of a free civilization erode poverty, inequality, and monopoly privilege through the spontaneous order of market process.
Is competition always good

Competition is the backbone of US economic policy. Competition advocacy is also thriving internationally. Promoting competition is broadly accepted as the best available tool for promoting consumer well-being. Competition officials, who regularly try to protect the public from anticompetitive special interest legislation, are justifiably jaded about complaints of excess competition. Although the economic crisis has prompted some policymakers to reconsider basic assumptions, the virtues of competition are not among them. Nonetheless to effectively advocate competition, officials must understand when competition itself is the problem’s cause, not its cure. Market competition, while harming some participants, often benefits society. But does competition always benefit society? This is antitrust’s blind spot. After outlining the virtues of competition, and discussing some well-accepted exceptions to competition law, this article addresses four scenarios where competition yields suboptimal results.
Toward an Integrative Theory of Counterproductive Workplace Behavior: A Causal Reasoning Perspective

Over the past decade, there has been an increase in attention to counterproductive workplace behaviors including violence, stealing, dishonesty, volitional absenteeism, drug and alcohol abuse, and aggression, many of which have been addressed in this special issue. Accompanying the attention to these specific types of behaviors has been a proliferation of theories developed to explain, understand, and manage counterproductive behavior. While these theories have addressed many apparently divergent types of behaviors, many similarities exist between and among these various perspectives. In this article, we integrate these various perspectives into a causal reasoning framework, proposing that individuals’ attributions about the causal dimensions of workplace events are a primary factor motivating both the emotions and behaviors that result in counterproductive workplace behaviors.
THE USE OF NEUTRALITIES IN INTERNATIONAL TAX POLICY

This paper analyzes the use of neutrality conditions, such as capital export neutrality, capital import neutrality, capital ownership neutrality, and market neutrality, in international tax policy. Neutralities are not appropriate tools for designing tax policy. They each identify a possible margin where taxation may distort business activities. Because these neutralities cannot be all satised simultaneously, however, they do not allow analysts to determine the appropriate trade-os of these distortions, unlike deadweight loss measures used in other areas of tax policy. International tax policy should instead be tied directly to the reasons for taxing capital income, reasons which are derived from optimal tax or similar models.
THE ABSENCE OF MUSLIM WOMEN IN SHAPING ISLAMIC THOUGHT: FOUNDATIONS OF MUSLIMS' PEACEFUL AND JUST CO-EXISTENCE

This paper explores the ethical and legal pedagogy of the current debates on “reforming” Muslim societies, whether they claim to reform social and legal systems, reform educational institutions, or liberate Muslim women. Since these debates claim to achieve balance in global or domestic conflicts, I address the foundations of these debates by answering three questions:Are the rationales for American and/or European governments' interventions justified?;Can the discipline of civil law help in rethinking Islam for Muslims; andAre Muslims themselves ready to critically address the use and misuse of Islam's primary sources (the Qur'an and particularly the Hadith) in their rethinking of Islam?I argue that rather than seeking to “reform others,” in this case Muslims with an elitist attitude and sometimes violent interventions, we scholars of law and religion, scholars of Islam, policy-makers, and social justice researchers would be better off if:we thought of Islam as a religio-moral rational worldview, rather than a set of laws,we recognized Muslims as subject to historical transformation, like any other religious groups, and understood how they developed their present views of Islam, andwe considered our own real responsibilities to address the forms of global injustices as powerful shapers of world politics, particularly the politics of difference—the view that the “other” is inferior, and women's role as mostly complementary to men.
Co-ranking mates: Assortative matching in marriage markets

Abstract We show that co-ranking is the necessary and sufficient condition for assortative matching with strictly nontransferable utility. This condition is equivalent to the GID condition in Legros and Newman (2007) and is a weakening of existing conditions for equilibrium uniqueness.
Unconventional Methods for a Traditional Setting: The Use of Virtual Reality to Reduce Implicit Racial Bias in the Courtroom

The presumption of innocence and the right to a fair trial lie at the core of the United States justice system. While existing rules and practices serve to uphold these principles, the administration of justice is significantly compromised by a covert but influential factor: namely, implicit racial biases. These biases can lead to automatic associations between race and guilt, as well as impact the way in which judges and jurors interpret information throughout a trial. Despite the well-documented presence of implicit racial biases, few steps have been taken to ameliorate the problem in the courtroom setting. This Article discusses the potential of virtual reality to reduce these biases among judges and jurors. Through analyzing the various ethical and legal considerations, this Article contends that implementing virtual reality training with judges and jurors would be justifiable and advisable should effective means become available. Given that implicit racial biases can seriously undermine the fairness of the justice system, this Article ultimately asserts that unconventional debiasing methods warrant legitimate attention and consideration.