cssi/SciSciGPT-SciSciNet huggingface dataset:
Geometric control of active collective motion

Recent experimental studies have shown that confinement can profoundly affect self-organization in semi-dilute active suspensions, leading to striking features such as the formation of steady and spontaneous vortices in circular domains and the emergence of unidirectional pumping motions in periodic racetrack geometries. Motivated by these findings, we analyze the two-dimensional dynamics in confined suspensions of active self-propelled swimmers using a mean-field kinetic theory where conservation equations for the particle configurations are coupled to the forced Navier-Stokes equations for the self-generated fluid flow. In circular domains, a systematic exploration of the parameter space casts light on three distinct states: equilibrium with no flow, stable vortex, and chaotic motion, and the transitions between these are explained and predicted quantitatively using a linearized theory. In periodic racetracks, similar transitions from equilibrium to net pumping to traveling waves to chaos are observed in agreement with experimental observations and are also explained theoretically. Our results underscore the subtle effects of geometry on the morphology and dynamics of emerging patterns in active suspensions and pave the way for the control of active collective motion in microfluidic devices.
Hamilton-Jacobi reachability: A brief overview and recent advances

Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for guaranteeing performance and safety properties of dynamical systems; it has been applied to many small-scale systems in the past decade. Its advantages include compatibility with general nonlinear system dynamics, formal treatment of bounded disturbances, and the availability of well-developed numerical tools. The main challenge is addressing its exponential computational complexity with respect to the number of state variables. In this tutorial, we present an overview of basic HJ reachability theory and provide instructions for using the most recent numerical tools, including an efficient GPU-parallelized implementation of a Level Set Toolbox for computing reachable sets. In addition, we review some of the current work in high-dimensional HJ reachability to show how the dimensionality challenge can be alleviated via various general theoretical and application-specific insights.
A boundary integral equation method for mode elimination and vibration confinement in thin plates with clamped points

We consider the bi-Laplacian eigenvalue problem for the modes of vibration of a thin elastic plate with a discrete set of clamped points. A high-order boundary integral equation method is developed for efficient numerical determination of these modes in the presence of multiple localized defects for a wide range of two-dimensional geometries. The defects result in eigenfunctions with a weak singularity that is resolved by decomposing the solution as a superposition of Green’s functions plus a smooth regular part. This method is applied to a variety of regular and irregular domains and two key phenomena are observed. First, careful placement of clamping points can entirely eliminate particular eigenvalues and suggests a strategy for manipulating the vibrational characteristics of rigid bodies so that undesirable frequencies are removed. Second, clamping of the plate can result in partitioning of the domain so that vibrational modes are largely confined to certain spatial regions. This numerical method gives a precision tool for tuning the vibrational characteristics of thin elastic plates.
Rigidity of Nonnegatively Curved Surfaces Relative to a Curve

We prove that any properly oriented $C^{2,1}$ isometric immersion of a positively curved Riemannian surface M into Euclidean 3-space is uniquely determined, up to a rigid motion, by its values on any curve segment in M. A generalization of this result to nonnegatively curved surfaces is presented as well under suitable conditions on their parabolic points. Thus we obtain a local version of Cohn-Vossen's rigidity theorem for convex surfaces subject to a Dirichlet condition. The proof employs in part Hormander's unique continuation principle for elliptic PDEs. Our approach also yields a short proof of Cohn-Vossen's theorem.
A polynomial bound for the arithmetic $k$-cycle removal lemma in vector spaces

Abstract For each k ≥ 3 , Green proved an arithmetic k-cycle removal lemma for any abelian group G. The best known bounds relating the parameters in the lemma for general G are of tower-type. For k > 3 , even in the case G = F 2 n no better bounds were known prior to this paper. This special case has received considerable attention due to its close connection to property testing of boolean functions. For every k ≥ 3 , we prove a polynomial bound relating the parameters for G = F p n , where p is any fixed prime. This extends the result for k = 3 by the first two authors. Due to substantial issues with generalizing the proof of the k = 3 case, a new strategy is developed in order to prove the result for k > 3 .
The toric Frobenius morphism and a conjecture of Orlov

We combine the Bondal–Uehara method for producing exceptional collections on toric varieties with a result of the first author and Favero to expand the set of varieties satisfying Orlov’s Conjecture on derived dimension.
Multivariate Gaussian network structure learning

Abstract We consider a graphical model where a multivariate normal vector is associated with each node of the underlying graph and estimate the graphical structure. We minimize a loss function obtained by regressing the vector at each node on those at the remaining ones under a group penalty. We show that the proposed estimator can be computed by a fast convex optimization algorithm. We show that as the sample size increases, the estimated regression coefficients and the correct graphical structure are correctly estimated with probability tending to one. By extensive simulations, we show the superiority of the proposed method over comparable procedures. We apply the technique on two real datasets. The first one is to identify gene and protein networks showing up in cancer cell lines, and the second one is to reveal the connections among different industries in the US.
Cotangent Bundles of Partial Flag Varieties and Conormal Varieties of their Schubert Divisors

Let P be a parabolic subgroup in G = SLn(k), for k an algebraically closed field. We show that there is a G-stable closed subvariety of an affine Schubert variety in an affine partial flag variety which is a natural compactification of the cotangent bundle T*G/P. Restricting this identification to the conormal variety N*X(w) of a Schubert divisor X(w) in G/P, we show that there is a compactification of N*X(w) as an affine Schubert variety. It follows that N*X(w) is normal, Cohen–Macaulay, and Frobenius split.
The peak region of the extragalactic background radiation

The Cosmic X-ray background carries the information of cosmic accretion onto super-massive black holes. The intensity at its peak can be used to constrain the integrated space density of highly obscured AGNs. Determining the shape and intensity of the Cosmic X-ray background radiation represents, however, a first step towards the understanding of the population of Comptonthick AGNs. The study of AGNs in the local and more distant Universe allows to understand the whole picture. In this talk, I will review the current understanding of generation of the Cosmic X-ray background at its peak. I will focus on the recent measurements of the Cosmic X-ray background and I will discuss the recent advancements in the understanding of AGNs in both the local and more distant Universe. Finally, I will also discuss open issues and future prospects.
Set-Difference Range Queries

We introduce the problem of performing set-difference range queries, where answers to queries are set-theoretic symmetric differences between sets of items in two geometric ranges. We describe a general framework for answering such queries based on a novel use of data-streaming sketches we call signed symmetric-difference sketches. We show that such sketches can be realized using invertible Bloom filters (IBFs), which can be composed, differenced, and searched so as to solve set-difference range queries in a wide range of scenarios. ∗Dept. of Comp. Sci., U. of CA, Irvine, eppstein(at)uci.edu †Dept. of Comp. Sci., U. of CA, Irvine, goodrich(at)uci.edu ‡Dept. of Comp. Sci., U. of CA, Irvine, jsimons(at)uci.edu 0 ar X iv :1 30 6. 34 82 v1 [ cs .D S] 1 4 Ju n 20 13 (a) (b) Figure 1: Illustrating the set-difference range query problem. The images in (a) and (b) have four major differences, three of which are inside the common query range. The image (a) is a public-domain engraving of an astronomer by Albrecht Durer, from the title page of Messahalah, De scientia motus orbis (1504).
TRIFECTA: Security, Energy Efficiency, and Communication Capacity Comparison for Wireless IoT Devices

The widespread proliferation of sensor nodes in the era of the Internet of Things (IoT), coupled with increasing sensor fidelity and data acquisition modality, is expected to generate 30+ Exabytes of data per month by 2020. Since most of these IoT devices will be wirelessly connected at the last few feet, wireless communication is an integral part of the future IoT scenario. The ever-shrinking size of unit computation (Moores law) and continued improvements in efficient communication (Shannons law) are expected to harness the true potential of the IoT revolution and produce a dramatic societal impact. However, reducing the size of IoT nodes and the slow improvement in energy storage density leads to reduced energy availability. Moreover, smaller size and less energy means fewer resources available for securing IoT nodes, making the energy-sparse low-cost leaf nodes of the network prime targets for attackers. In this article, we survey six prominent wireless technologies with respect to three dimensions: security, energy efficiency, and communication capacity. We point out the state of the art, open issues, and the road ahead for promising research directions.
Distributed Secret Dissemination Across a Network

Shamir's $(n,k)$ threshold secret sharing is an important component of several cryptographic protocols, such as those for secure multiparty-computation and key management. These protocols typically assume the presence of direct communication links from the dealer to all participants, in which case the dealer can directly pass the shares of the secret to each participant. In this paper, we consider the problem of secret sharing when the dealer does not have direct communication links to all the participants, and instead, the dealer and the participants form a general network. Existing methods are based on separate secure message transmissions from the dealer to each participant, requiring considerable coordination and communication in the network. We present a distributed algorithm for disseminating shares over a network, which we call the “SNEAK” algorithm, requiring each node to know only the identities of its one-hop neighbors. While SNEAK imposes a stronger condition on the network by requiring the dealer to be what we call $k$ -propagating rather than $k$ -connected as required by the existing solutions, we show that in addition to being distributed, it achieves significant reduction in the amount of communication and the randomness required. We also derive information-theoretic lower bounds on the amount of communication for secret sharing over networks, which may be of independent interest.
BNP-Seq: Bayesian Nonparametric Differential Expression Analysis of Sequencing Count Data

ABSTRACTWe perform differential expression analysis of high-throughput sequencing count data under a Bayesian nonparametric framework, removing sophisticated ad hoc pre-processing steps commonly required in existing algorithms. We propose to use the gamma (beta) negative binomial process, which takes into account different sequencing depths using sample-specific negative binomial probability (dispersion) parameters, to detect differentially expressed genes by comparing the posterior distributions of gene-specific negative binomial dispersion (probability) parameters. These model parameters are inferred by borrowing statistical strength across both the genes and samples. Extensive experiments on both simulated and real-world RNA sequencing count data show that the proposed differential expression analysis algorithms clearly outperform previously proposed ones in terms of the areas under both the receiver operating characteristic and precision-recall curves. Supplementary materials for this article are avai...
CSGNet: Neural Shape Parser for Constructive Solid Geometry

We present a neural architecture that takes as input a 2D or 3D shape and outputs a program that generates the shape. The instructions in our program are based on constructive solid geometry principles, i.e., a set of boolean operations on shape primitives defined recursively. Bottom-up techniques for this shape parsing task rely on primitive detection and are inherently slow since the search space over possible primitive combinations is large. In contrast, our model uses a recurrent neural network that parses the input shape in a top-down manner, which is significantly faster and yields a compact and easy-to-interpret sequence of modeling instructions. Our model is also more effective as a shape detector compared to existing state-of-the-art detection techniques. We finally demonstrate that our network can be trained on novel datasets without ground-truth program annotations through policy gradient techniques.
Does the Healthcare Educational Market Respond to Short-Run Local Demand?

Abstract The Patient Protection and Affordable Care Act (ACA) increased demand for healthcare across the U.S., but it is unclear if or how the supply side has responded to meet this demand. In this paper, we take advantage of plausibly exogenous geographical heterogeneity in the ACA to examine the healthcare education sector's response to increased demand for healthcare services. We look across educational fields, types of degrees, and types of institutions, paying particular attention to settings where our conceptual model predicts heightened responses. We find no statistically significant evidence of increases in graduates and can rule out fairly modest effects. This implies that healthcare production may have adjusted to increased demand from insurance expansion in other ways rather than primarily through new graduates of local healthcare educational markets.
Reaction Mechanisms of Pol IV, RDR2, and DCL3 Drive RNA Channeling in the siRNA-Directed DNA Methylation Pathway

In eukaryotes with multiple small RNA pathways, the mechanisms that channel RNAs within specific pathways are unclear. Here, we reveal the reactions that account for channeling in the small interfering RNA (siRNA) biogenesis phase of the Arabidopsis RNA-directed DNA methylation pathway. The process begins with template DNA transcription by NUCLEAR RNA POLYMERASE IV (Pol IV), whose atypical termination mechanism, induced by nontemplate DNA base-pairing, channels transcripts to the associated RNA-dependent RNA polymerase RDR2. RDR2 converts Pol IV transcripts into double-stranded RNAs and then typically adds an extra untemplated 3' terminal nucleotide to the second strands. The dicer endonuclease DCL3 cuts resulting duplexes to generate 24- and 23-nt siRNAs. The 23-nt RNAs bear the untemplated terminal nucleotide of the RDR2 strand and are underrepresented among ARGONAUTE4-associated siRNAs. Collectively, our results provide mechanistic insights into Pol IV termination, Pol IV-RDR2 coupling, and RNA channeling, from template DNA transcription to siRNA strand discrimination.
Rectification in Spin-Orbit Materials Using Low-Energy-Barrier Magnets

The authors predict multiterminal rectification arising in a spin-orbit material when it is coupled to a ferromagnet with a low energy barrier. The proposed all-metallic device can rectify arbitrarily small signals within a frequency band dictated by an angular-momentum conservation principle, which points to applications in ``passive'' microwave or rf detection and energy harvesting from weak ambient signals.
A direct mixed–enriched Galerkin method on quadrilaterals for two-phase Darcy flow

We develop a locally conservative, finite element method for the simulation of two-phase flow on quadrilateral meshes that minimize the number of degrees of freedom (DoFs) subject to accuracy requirements and the DoF continuity constraints. We use a mixed finite element method (MFEM) for the flow problem and an enriched Galerkin method (EG) for the transport, stabilized with an entropy viscosity. Standard elements for MFEM lose accuracy on quadrilaterals, so we use the newly developed AC elements which have our desired properties. Standard tensor product spaces used in EG have many excess DoFs, so we would like to use the minimal DoF serendipity elements. However, the standard elements lose accuracy on quadrilaterals, so we use the newly developed direct serendipity elements. We use the Hoteit-Firoozabadi formulation, which requires a capillary flux. We compute this in a novel way that does not break down when one of the saturations degenerate to its residual value. Extension to three dimensions is described. Numerical tests show that accurate results are obtained.
Look-up and Adapt: A One-shot Semantic Parser.

Computing devices have recently become capable of interacting with their end users via natural language. However, they can only operate within a limited “supported” domain of discourse and fail drastically when faced with an out-of-domain utterance, mainly due to the limitations of their semantic parser. In this paper, we propose a semantic parser that generalizes to out-of-domain examples by learning a general strategy for parsing an unseen utterance through adapting the logical forms of seen utterances, instead of learning to generate a logical form from scratch. Our parser maintains a memory consisting of a representative subset of the seen utterances paired with their logical forms. Given an unseen utterance, our parser works by looking up a similar utterance from the memory and adapting its logical form until it fits the unseen utterance. Moreover, we present a data generation strategy for constructing utterance-logical form pairs from different domains. Our results show an improvement of up to 68.8% on one-shot parsing under two different evaluation settings compared to the baselines.
Flexibly Scalable High Performance Architectures with Embedded Photonics

Computing systems are critically challenged to meet the performance demands of applications particularly driven by the explosive growth in data analytics. Data movement, dominated by energy costs and limited ‘chip-escape’ bandwidth densities, is a key physical layer roadblock to these systems' scalability. Integrated silicon photonics with deeply embedded optical connectivity is on the cusp of enabling revolutionary data movement and extreme performance capabilities. Beyond alleviating the bandwidth/energy bottlenecks, embedded photonics can enable new disaggregated architectures that leverage the distance independence of optical transmission. We will discuss how the envisioned modular system interconnected by a unified photonic fabric can be flexibly composed to create custom architectures tailored for specific applications.
Managerial entrenchment and capital structure: The effect of diversification

Abstract This paper empirically examines how diversification influences the relation between corporate governance and capital structure. Consistent with the creditor alignment hypothesis, we find a positive relation between managerial entrenchment and leverage in diversified firms. In contrast, we find a negative relation between managerial entrenchment and leverage in focused firms, which supports the managerial entrenchment hypothesis. These effects are stronger or only exist in samples with low excess values, which supports the agency channel through which governance influences leverage decisions. Our results are robust to different measures of leverage, diversification, and governance, and continue to hold when we attempt to account for selection bias and the joint endogeneity of leverage, diversification, and governance.
Model Selection for Contextual Bandits

We introduce the problem of model selection for contextual bandits, where a learner must adapt to the complexity of the optimal policy while balancing exploration and exploitation. Our main result is a new model selection guarantee for linear contextual bandits. We work in the stochastic realizable setting with a sequence of nested linear policy classes of dimension $d_1 < d_2 < \ldots$, where the $m^\star$-th class contains the optimal policy, and we design an algorithm that achieves $\tilde{O}l(T^{2/3}d^{1/3}_{m^\star})$ regret with no prior knowledge of the optimal dimension $d_{m^\star}$. The algorithm also achieves regret $\tilde{O}(T^{3/4} + \sqrt{Td_{m^\star}})$, which is optimal for $d_{m^{\star}}\geq{}\sqrt{T}$. This is the first model selection result for contextual bandits with non-vacuous regret for all values of $d_{m^\star}$, and to the best of our knowledge is the first positive result of this type for any online learning setting with partial information. The core of the algorithm is a new estimator for the gap in the best loss achievable by two linear policy classes, which we show admits a convergence rate faster than the rate required to learn the parameters for either class.
Racial Disparities in Voting Wait Times: Evidence from Smartphone Data

Equal access to voting is a core feature of democratic government. Using data from hundreds of thousands of smartphone users, we quantify a racial disparity in voting wait times across a nationwide...
Thermodynamics of Benford's first digit law

According to Benford's first digit law, the frequency of appearance of the first digit d taken from various sets of data is log ( 1 + ( 1 / d ) ) where d = 1, 2,…9. I present a thermodynamic derivation of this law that follows from the unbiased partitioning of a conserved quantity whose pieces may fragment and combine.
Edge coloring signed graphs

Abstract We define a method for edge coloring signed graphs and what it means for such a coloring to be proper. Our method has many desirable properties: it specializes to the usual notion of edge coloring when the signed graph is all-negative, it has a natural definition in terms of vertex coloring of a line graph, and the minimum number of colors required for a proper coloring of a signed simple graph is bounded above by Δ + 1 in parallel with Vizing’s Theorem. In fact, Vizing’s Theorem is a special case of the more difficult theorem concerning signed graphs.
A local to global argument on low dimensional manifolds

For an oriented manifold $M$ whose dimension is less than $4$, we use the contractibility of certain complexes associated to its submanifolds to cut $M$ into simpler pieces in order to do local to global arguments. In particular, in these dimensions, we give a different proof of a deep theorem of Thurston in foliation theory which says that the natural map between classifying spaces $\mathrm{B}\text{Homeo}^{\delta}(M)\to \mathrm{B}\text{Homeo}(M)$ induces a homology isomorphism where $\text{Homeo}^{\delta}(M)$ denotes the group of homeomorphisms of $M$ made discrete. Our proof shows that in low dimensions, Thurston's theorem can be proved without using foliation theory. Finally, we show that this technique gives a new perspective on the homotopy type of homeomorphism groups in low dimensions. In particular, we give a different proof of Hacher's theorem that the homeomorphism groups of Haken $3$-manifolds with boundary are homotopically discrete without using his disjunction techniques.
Antisymmetric Couplings Enable Direct Observation of Chirality in Nuclear Magnetic Resonance Spectroscopy

Here we demonstrate that a term in the nuclear spin Hamiltonian, the antisymmetric J-coupling, is fundamentally connected to molecular chirality. We propose and simulate a nuclear magnetic resonance (NMR) experiment to observe this interaction and differentiate between enantiomers without adding any additional chiral agent to the sample. The antisymmetric J-coupling may be observed in the presence of molecular orientation by an external electric field. The opposite parity of the antisymmetric coupling tensor and the molecular electric dipole moment yields a sign change of the observed coupling between enantiomers. We show how this sign change influences the phase of the NMR spectrum and may be used to discriminate between enantiomers.
On the dimension spectrum of infinite subsystems of continued fractions

In this paper we study the dimension spectrum of continued fractions with coefficients restricted to infinite subsets of natural numbers. We prove that if $E$ is any arithmetic progression, the set of primes, or the set of squares $\{n^2\}_{n \in \mathbb{N}}$, then the continued fractions whose digits lie in $E$ have full dimension spectrum, which we denote by $DS(\mathcal{CF}_E)$. Moreover we prove that if $E$ is an infinite set of consecutive powers then the dimension spectrum $DS(\mathcal{CF}_E)$ always contains a non trivial interval. We also show that there exists some $E \subset \mathbb{N}$ and two non-trivial intervals $I_1, I_2$, such that $DS(\mathcal{CF}_E) \cap I_1=I_1$ and $DS(\mathcal{CF}_E) \cap I_2$ is a Cantor set. On the way we employ the computational approach of Falk and Nussbaum in order to obtain rigorous effective estimates for the Hausdorff dimension of continued fractions whose entries are restricted to infinite sets.
Two‐sample test based on classification probability

Abstract Robust classification algorithms have been developed in recent years with great success. We take advantage of this development and recast the classical two‐sample test problem in the frame...
Single layer MoS 2 band structure and transport

Ultrathin two dimensional materials have significant potential for application in nano-electronic devices. Graphene is a popular two-dimensional material due to its intrinsic high mobility. However, Graphene does not have any band gap, which makes it hard to be used for field effect transistors (FET)[1]. On the other hand, monolayer Molybdenum Disulfide (MoS 2 ) is a thin two dimensional material with large intrinsic band gap. These characteristics and recent successful fabrication of transistors [1] make it a promising candidate for future device applications. In this paper, the band structure of monolayer MoS 2 is calculated by density functional theory (DFT) using the abinit [2] package with the local density approximation (LDA) and GW approximation. The newly computed GW band structure and effective masses are different from previously reported LDA results in the literature. Using the new band structure we simulate a short gate length field FET and report initial results.
Short-term exposures to particulate matter gamma radiation activities and biomarkers of systemic inflammation and endothelial activation in COPD patients.

Abstract Background We hypothesized that particulate matter (PM) gamma activity (gamma radiation associated with PM) is associated with systemic effects. Objective Examine short-term relationships between ambient and indoor exposures to PM gamma activities with systemic inflammation and endothelial activation in chronic obstructive pulmonary disease (COPD) patients. Methods In 85 COPD patients from Eastern Massachusetts, USA from 2012 to 2014, plasma C-reactive protein (CRP), interleukin-6 (IL-6), and soluble vascular cell adhesion molecule-1 (sVCAM-1) were measured seasonally up to four times. We used US EPA RadNet data measuring ambient gamma radiation attached to PM adjusted for background radiation, and estimated in-home gamma radiation exposures using the ratio of in-home-to-ambient sulfur in PM2.5. Linear mixed-effects regression models were used to determine associations between moving averages of PM gamma activities through the week before phlebotomy with these biomarkers. We explored ambient and indoor PM2.5, black carbon (BC), and NO2 as confounders. Results Ambient and indoor PM gamma activities measured as energy spectra classes 3 through 9 were positively associated with CRP and IL-6. For example, averaged from phlebotomy day through previous 6 days, each IQR increase in indoor PM gamma activity for each spectra class, was associated with an CRP increase ranging from 7.45% (95%CI: 2.77, 12.4) to 13.4% (95%CI: 5.82, 21.4) and for ambient exposures were associated with an increase of 8.75% (95%CI: −0.57, 18.95) to 14.8% (95%CI: 4.5, 26.0). Indoor exposures were associated with IL-6 increase of 3.56% (95%CI: 0.31, 6.91) to 6.46% (95%CI:1.33, 11.85) and ambient exposures were associated with an increase of 0.03% (95%CI: −6.37, 6.87) to 3.50% (95%CI: −3.15, 10.61). There were no positive associations with sVCAM-1. Sensitivity analyses using two-pollutant models showed similar effects. Conclusions Our results demonstrate that short-term exposures to environmental PM gamma radiation activities were associated with systemic inflammation in COPD patients.
Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis

Time-varying networks are fast emerging in a wide range of scientific and business applications. Most existing dynamic network models are limited to a single-subject and discrete-time setting. In t...
A dimension-free Hermite–Hadamard inequality via gradient estimates for the torsion function

Let $\Omega \subset \mathbb{R}^n$ be a convex domain and let $f:\Omega \rightarrow \mathbb{R}$ be a subharmonic function, $\Delta f \geq 0$, which satisfies $f \geq 0$ on the boundary $\partial \Omega$. Then $$ \int_{\Omega}{f ~dx} \leq |\Omega|^{\frac{1}{n}} \int_{\partial \Omega}{f ~d\sigma}.$$ Our proof is based on a new gradient estimate for the torsion function, $\Delta u = -1$ with Dirichlet boundary conditions, which is of independent interest.
The kernel of the monodromy of the universal family of degree d smooth plane curves

We consider the parameter space &#x1d4b0;d of smooth plane curves of degree d. The universal smooth plane curve of degree d is a fiber bundle ℰd →&#x1d4b0;d with fiber diffeomorphic to a surface Σg. This bundle gi...
A positive fraction mutually avoiding sets theorem

Abstract Two sets A and B of points in the plane are mutually avoiding if no line generated by any two points in A intersects the convex hull of B , and vice versa. In 1994, Aronov, Erdős, Goddard, Kleitman, Klugerman, Pach, and Schulman showed that every set of n points in the plane in general position contains a pair of mutually avoiding sets each of size at least n ∕ 12 . As a corollary, their result implies that, for every set of n points in the plane in general position, one can find at least n ∕ 12 segments, each joining two of the points, such that these segments are pairwise crossing. In this note, we prove a fractional version of their theorem: for every k > 0 there is a constant e k > 0 such that any sufficiently large point set P in the plane contains 2 k subsets A 1 , … , A k , B 1 , … , B k , each of size at least e k | P | , such that every pair of sets A = { a 1 , … , a k } and B = { b 1 , … , b k } , with a i ∈ A i and b i ∈ B i , are mutually avoiding. Moreover, we show that e k = Ω ( 1 ∕ k 4 ) . Similar results are obtained in higher dimensions.
Resolvent Analysis of Compressible Laminar and Turbulent Cavity Flows

The present work demonstrates the use of a resolvent analysis to obtain physical insights for open-cavity flows. A resolvent analysis identifies the flow response to harmonic forcing, given a stead...
Examples of mirror partners arising from integrable systems

Abstract In this Note we present pairs of hyperkahler orbifolds which satisfy two different versions of mirror symmetry. On the one hand, we show that their Hodge numbers (or more precisely, stringy E -polynomials) are equal. On the other hand, we show that they satisfy the prescription of Strominger, Yau, and Zaslow (which in the present case goes back to Bershadsky, Johansen, Sadov and Vafa): that a Calabi–Yau and its mirror should fiber over the same real manifold, with special Lagrangian fibers which are tori dual to each other. Our examples arise as moduli spaces of local systems on a curve with structure group SL (n) ; the mirror is the corresponding space with structure group PGL (n) . The special Lagrangian tori come from an algebraically completely integrable Hamiltonian system: the Hitchin system.
Information Geometry of Orthogonal Initializations and Training

Recently mean field theory has been successfully used to analyze properties of wide, random neural networks. It gave rise to a prescriptive theory for initializing feed-forward neural networks with orthogonal weights, which ensures that both the forward propagated activations and the backpropagated gradients are near `2 isometries and as a consequence training is orders of magnitude faster. Despite strong empirical performance, the mechanisms by which critical initializations confer an advantage in the optimization of deep neural networks are poorly understood. Here we show a novel connection between the maximum curvature of the optimization landscape (gradient smoothness) as measured by the Fisher information matrix (FIM) and the spectral radius of the input-output Jacobian, which partially explains why more isometric networks can train much faster. Furthermore, given that orthogonal weights are necessary to ensure that gradient norms are approximately preserved at initialization, we experimentally investigate the benefits of maintaining orthogonality throughout training, and we conclude that manifold optimization of weights performs well regardless of the smoothness of the gradients. Moreover, we observe a surprising yet robust behavior of highly isometric initializations— even though such networks have a lower FIM condition number at initialization, and therefore by analogy to convex functions should be easier to optimize, experimentally they prove to be much harder to train with stochastic gradient descent. We propose an explanation for this phenomenon by exploting connections between Fisher geometry and the recently introduced Neural Tangent Kernel.
Resonant microwave-mediated interactions between distant electron spins.

Nonlocal qubit interactions are a hallmark of advanced quantum information technologies1–5. The ability to transfer quantum states and generate entanglement over distances much larger than qubit length scales greatly increases connectivity and is an important step towards maximal parallelism and the implementation of two-qubit gates on arbitrary pairs of qubits6. Qubit-coupling schemes based on cavity quantum electrodynamics2,7,8 also offer the possibility of using high-quality-factor resonators as quantum memories3,9. Extending qubit interactions beyond the nearest neighbour is particularly beneficial for spin-based quantum computing architectures, which are limited by short-range exchange interactions10. Despite the rapidly maturing device technology for silicon spin qubits11–16, experimental progress towards achieving long-range spin–spin coupling has so far been restricted to interactions between individual spins and microwave photons17–20. Here we demonstrate resonant microwave-mediated coupling between two electron spins that are physically separated by more than four millimetres. An enhanced vacuum Rabi splitting is observed when both spins are tuned into resonance with the cavity, indicating a coherent interaction between the two spins and a cavity photon. Our results imply that microwave-frequency photons may be used to generate long-range two-qubit gates between spatially separated spins. Microwave-mediated coupling of electron spins separated by more than 4 mm is demonstrated, suggesting the possibility of using photons at microwave frequencies to create long-range two-qubit gates between distant spins.
Tankyrase inhibition sensitizes cells to CDK4 blockade

Tankyrase (TNKS) 1/2 are positive regulators of WNT signaling by controlling the activity of the s-catenin destruction complex. TNKS inhibitors provide an opportunity to suppress hyperactive WNT signaling in tumors, however, they have shown limited anti-proliferative activity as a monotherapy in human cancer cell lines. Here we perform a kinome-focused CRISPR screen to identify potential effective drug combinations with TNKS inhibition. We show that the loss of CDK4, but not CDK6, synergizes with TNKS1/2 blockade to drive G1 cell cycle arrest and senescence. Through precise modelling of cancer-associated mutations using cytidine base editors, we show that this therapeutic approach is absolutely dependent on suppression of canonical WNT signaling by TNKS inhibitors and is effective in cells from multiple epithelial cancer types. Together, our results suggest that combined WNT and CDK4 inhibition might provide a potential therapeutic strategy for difficult-to-treat epithelial tumors.
Improved Parallel Construction of Wavelet Trees and Rank/Select Structures

Abstract Existing parallel algorithms for wavelet tree construction have a work complexity of O ( n log ⁡ σ ) . This paper presents parallel algorithms for the problem with improved work complexity. Our first algorithm is based on parallel integer sorting and has either O ( n log ⁡ log ⁡ n ⌈ log ⁡ σ / log ⁡ n log ⁡ log ⁡ n ⌉ ) work and polylogarithmic depth, or O ( n ⌈ log ⁡ σ / log ⁡ n ⌉ ) work and sub-linear depth. We also describe another algorithm that has O ( n ⌈ log ⁡ σ / log ⁡ n ⌉ ) work and O ( σ + log ⁡ n ) depth. We then show how to use similar ideas to construct variants of wavelet trees (arbitrary-shaped binary trees and multiary trees) as well as wavelet matrices in parallel with lower work complexity than prior algorithms. Finally, we show that the rank and select structures on binary sequences and multiary sequences, which are stored on wavelet tree nodes, can be constructed in parallel with improved work bounds, matching those of the best existing sequential algorithms for constructing rank and select structures.
Characterizing Adult Cochlear Supporting Cell Transcriptional Diversity Using Single-Cell RNA-Seq: Validation in the Adult Mouse and Translational Implications for the Adult Human Cochlea

Hearing loss is a problem that impacts a significant proportion of the adult population. Cochlear hair cell (HC) loss due to loud noise, chemotherapy and aging is the major underlying cause. A significant proportion of these individuals are dissatisfied with available treatment options which include hearing aids and cochlear implants. An alternative approach to restore hearing would be to regenerate HCs. Such therapy would require a recapitulation of the complex architecture of the organ of Corti, necessitating regeneration of both mature HCs and supporting cells (SCs). Transcriptional profiles of the mature cell types in the cochlea are necessary to can provide a metric for eventual regeneration therapies. To assist in this effort, we sought to provide the first single-cell characterization of the adult cochlear SC transcriptome. We performed single-cell RNA-Seq on FACS-purified adult cochlear SCs from the LfngEGFP adult mouse, in which SCs express GFP. We demonstrate that adult cochlear SCs are transcriptionally distinct from their perinatal counterparts. We establish cell-type-specific adult cochlear SC transcriptome profiles, and we validate these expression profiles through a combination of both fluorescent immunohistochemistry and in situ hybridization co-localization and quantitative polymerase chain reaction (qPCR) of adult cochlear SCs. Furthermore, we demonstrate the relevance of these profiles to the adult human cochlea through immunofluorescent human temporal bone histopathology. Finally, we demonstrate cell cycle regulator expression in adult SCs and perform pathway analyses to identify potential mechanisms for facilitating mitotic regeneration (cell proliferation, differentiation, and eventually regeneration) in the adult mammalian cochlea. Our findings demonstrate the importance of characterizing mature as opposed to perinatal SCs.
Poly(methylene ditelluride)

Preparation par reduction du bis(trichlorotelluro) methane. Proprietes physiques et chimiques du polymere incluant la conductivite electrique en fonction de la temperature et de la pression
Non-simplicity of Isocontact Embeddings in All Higher Dimensions

In this article we show that in any dimension there exist infinitely many pairs of formally contact isotopic isocontact embeddings into the standard contact sphere which are not contact isotopic. This is the first example of rigidity for contact submanifolds in higher dimensions. The contact embeddings are constructed via contact push-offs of higher-dimensional Legendrian submanifolds, a construction that generalizes the union of the positive and negative transverse push-offs of a Legendrian knot to higher dimensions.
Within and between-person correlates of the temporal dynamics of resting EEG microstates

Microstates reflect transient brain states resulting from the synchronous activity of brain networks that predominate in the broadband EEG. There has been increasing interest in how the functional organization of the brain varies across individuals, or the extent to which its spatiotemporal dynamics are state dependent. However, little research has examined within and between-person correlates of microstate temporal parameters in healthy populations. In the present study, neuroelectric activity recorded during eyes-closed rest and during simple visual fixation was segmented into a time series of transient microstate intervals. It was found that five data-driven microstate configurations explained the preponderance of topographic variance in the EEG time series of the 374 recordings (from 187 participants) included in the study. We observed that the temporal dynamics of microstates varied within individuals to a greater degree than they differed between persons, with within-person factors explaining a large portion of the variance in mean microstate duration and occurrence rate. Nevertheless, several individual differences were found to predict the temporal dynamics of microstates. Of these, age and gender were the most reliable. These findings not only suggest that the rich temporal dynamics of whole-brain neuronal networks vary considerably within individuals, but that microstates appear to differentiate persons based on trait individual differences. Rather than focusing exclusively on between-person differences in microstates as measures of brain function, researchers should turn their attention towards understanding the factors contributing to within-person variation.
Direct-Write Ion Beam Irradiated Josephson Junctions

We highlight the reproducibility and level of control over the electrical properties of YBa 2 Cu 3 O 7 Josephson junctions fabricated with irradiation from a focused helium ion beam. Specifically we show the results of electrical transport properties for several junctions fabricated using a large range of irradiation doses. At the lower end of this range, junctions exhibit superconductor-normal metal-superconductor (SNS) Josephson junction properties. However, as dose increases there is a transition to electrical characteristics consistent with superconductor-insulator-superconductor (SIS) junctions. To investigate the uniformity of large numbers of helium ion Josephson junctions we fabricate arrays of both SNS and SIS Josephson junctions containing 20 connected in series. Electrical transport properties for these arrays reveal very uniform junctions with no appreciable spread in critical current or resistance.
On a conjecture of Lynch

We comment on a conjecture of Lynch on annihilators of local cohomology.Communicated by Lawrence Ein
CNCC: an analysis tool to determine genome-wide DNA break end structure at single-nucleotide resolution.

DNA double-stranded breaks (DSBs) are potentially deleterious events in a cell. The end structures (blunt, 3′- and 5′-overhangs) at DSB sites contribute to the fate of their repair and provide critical information concerning the consequences of the damage. Therefore, there has been a recent eruption of DNA break mapping and sequencing methods that aim to map at single-nucleotide resolution where breaks are generated genome-wide. These methods provide high resolution data for the location of DSBs, which can encode the type of end-structure present at these breaks. However, genome-wide analysis of the resulting end structures has not been investigated following these sequencing methods. To address this analysis gap, we develop the use of a coverage-normalized cross correlation analysis (CNCC) to process the high-precision genome-wide break mapping data, and determine genome-wide break end structure distributions at single-nucleotide resolution. We take advantage of the single-nucleotide position and the knowledge of strandness from every mapped break to analyze the relative shifts between positive and negative strand encoded break nucleotides. By applying CNCC we can identify the most abundant end structures captured by a break mapping technique, and further can make comparisons between different samples and treatments. We validate our analysis with restriction enzyme digestions of genomic DNA and establish the sensitivity of the analysis using end structures that only exist as a minor fraction of total breaks. Finally, we demonstrate the versatility of our analysis by applying CNCC to the breaks resulting after treatment with etoposide and study the variety of resulting end structures. For the first time, on a genome-wide scale, our analysis revealed the increase in the 5′ to 3′ end resection following etoposide treatment, and the global progression of the resection. Furthermore, our method distinguished the change in the pattern of DSB end structure with increasing doses of the drug. The ability of this method to determine DNA break end structures without a priori knowledge of break sequences or genomic position should have broad applications in understanding genome instability.
Genetic structure is stronger across human-impacted habitats than among islands in the coral Porites lobata

We examined genetic structure in the lobe coral Porites lobata among pairs of highly variable and high-stress nearshore sites and adjacent less variable and less impacted offshore sites on the islands of Oahu and Maui, Hawaii. Using an analysis of molecular variance framework, we tested whether populations were more structured by geographic distance or environmental extremes. The genetic patterns we observed followed isolation by environment, where nearshore and adjacent offshore populations showed significant genetic structure at both locations (AMOVA F ST = 0.04∼0.19, P < 0.001), but no significant isolation by distance between islands. Strikingly, corals from the two nearshore sites with higher levels of environmental stressors on different islands over 100 km apart with similar environmentally stressful conditions were genetically closer (FST = 0.0, P = 0.73) than those within a single location less than 2 km apart (FST = 0.04∼0.08, P < 0.01). In contrast, a third site with a less impacted nearshore site (i.e., less pronounced environmental gradient) showed no significant structure from the offshore comparison. Our results show much stronger support for environment than distance separating these populations. Our finding suggests that ecological boundaries from human impacts may play a role in forming genetic structure in the coastal environment, and that genetic divergence in the absence of geographical barriers to gene flow might be explained by selective pressure across contrasting habitats.