cssi/SciSciGPT-SciSciNet huggingface dataset:
Nonlinear interaction of impulsive gravitational waves for the vacuum Einstein equations

In this paper, we study the problem of the nonlinear interaction of impulsive gravitational waves for the Einstein vacuum equations. The problem is studied in the context of a characteristic initial value problem with data given on two null hypersurfaces and containing curvature delta singularities. We establish an existence and uniqueness result for the spacetime arising from such data and show that the resulting spacetime represents the interaction of two impulsive gravitational waves germinating from the initial singularities. In the spacetime, the curvature delta singularities propagate along 3-dimensional null hypersurfaces intersecting to the future of the data. To the past of the intersection, the spacetime can be thought of as containing two independent, non-interacting impulsive gravitational waves and the intersection represents the first instance of their nonlinear interaction. Our analysis extends to the region past their first interaction and shows that the spacetime still remains smooth away from the continuing propagating individual waves. The construction of these spacetimes are motivated in part by the celebrated explicit solutions of KhanPenrose and Szekeres. The approach of this paper can be applied to an even larger class of characteristic data and in particular implies an extension of the theorem on formation of trapped surfaces by Christodoulou and Klainerman-Rodnianski, allowing non-trivial data on the initial incoming hypersurface.
Threats and promises in bargaining

Abstract If, prior to bargaining, bargainers can make commitments that have some chance of binding their bargaining behavior, they may want to threaten to reject low offers, promise to accept high offers, or both. We show that the timing of commitment attempts influences the goal of the commitments and the likelihood that incompatible threats result in impasse. Sequential commitments enable the player who commits first to make a moderate threat that convinces the second mover not to respond with a threat himself. The moderate threat requires a promise to not renege on the offer if the committed player would otherwise have incentives to deviate. This combination of tactics is not feasible when commitments are made simultaneously.
Hadwiger Integration of Random Fields

Hadwiger integrals employ the intrinsic volumes as measures for integration of real-valued functions. We provide a formula for the expected values of Hadwiger integrals of Gaussian-related random fields. The expected Hadwiger integrals of random fields are both theoretically interesting and potentially useful in applications such as sensor networks, image processing, and cell dynamics. Furthermore, combining the expected integrals with a functional version of Hadwiger's theorem, we obtain expected values of more general valuations on Gaussian-related random fields.
On the Moduli Description of Local Models for Ramified Unitary Groups

Local models are schemes which are intended to model the etalelocal structure of p-adic integral models of Shimura varieties. Pappas and Zhu have recently given a general group-theoretic construction of flat local models with parahoric level structure for any tamely ramified group, but it remains an interesting problem to characterize the local models, when possible, in terms of an explicit moduli problem. In the setting of local models for ramified, quasi-split GUn, work towards an explicit moduli description was initiated in the general framework of Rapoport and Zink’s book and was subsequently advanced by Pappas and Pappas–Rapoport. In this paper we propose a further refinement to their moduli problem, which we show is both necessary and sufficient to characterize the (flat) local model in a certain special maximal parahoric case with signature (n− 1, 1).
Diagnosing Heterogeneous Dynamics in Single-Molecule/Particle Trajectories with Multiscale Wavelets

We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large data sets generated in single-molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw data to locally match dynamics of interest. This is accomplished using statistically adaptive universal thresholding, whose advantage is to avoid a single arbitrary threshold that might conceal individual variability across populations. How to implement this multiscale method is described, focusing on local confined diffusion separated by transient transport periods or hopping events, with three specific examples: in cell biology, biotechnology, and glassy colloid dynamics. The discussion is generalized within the framework of continuous time random walk. This computationally efficient method can run routinely on hundreds of millions of data points analyzed within an hour on a desktop personal computer.
The accessible lasso models

ABSTRACTA new line of research [Lee et al. Exact post-selection inference with the lasso. arXiv preprint arXiv:1311.6238 (2013)] on the lasso [Tibshirani. Regression shrinkage and selection via the lasso. J R Stat Soc Ser B (Methodological). 1996;267–288] exploits the beautiful geometric fact that the lasso fit is the residual from projecting the response vector y onto a certain convex polytope [Tibshirani et al. Degrees of freedom in lasso problems. Ann Stat. 2012;40:1198–1232]. This geometric picture also allows an exact geometric description of the set of accessible lasso models for a given design matrix, that is, which configurations of the signs of the coefficients it is possible to realize with some choice of y. In particular, the accessible lasso models are those that correspond to a face of the convex hull of all the feature vectors together with their negations. This convex hull representation then permits the enumeration and bounding of the number of accessible lasso models, which in turn provid...
A fixed point theorem for branched covering maps of the plane

It is known that every homeomorphism of the plane which admits an invariant non-separating continuum has a fixed point in the continuum. In this paper we show that any branched covering map of the plane of degree d, |d| ≤ 2, which has an invariant, non-separating continuum Y , either has a fixed point in Y , or is such that Y contains a minimal (by inclusion among invariant continua), fully invariant, non-separating subcontinuum X. In the latter case, f has to be of degree −2 and X has exactly three fixed prime ends, one corresponding to an outchannel and the other two to inchannels.
A Contract Design Approach for Phantom Demand Response

We design an optimal contract between a demand response aggregator (DRA) and power grid customers for incentive-based demand response. We consider a setting in which the customers are asked to reduce their electricity consumption by the DRA and they are compensated for this demand curtailment. However, given that the DRA must supply every customer with as much power as she desires, a strategic customer can temporarily increase her base load in order to report a larger reduction as part of the demand response event. The DRA wishes to incentivize the customers both to make costly effort to reduce load and to not falsify the reported load reduction. We model this problem as a contract design problem and present a solution. The proposed contract consists of two parts: a part that depends on (the possibly inflated) load reduction as measured by the DRA and another that provides a share of the profit that accrues to the DRA through the demand response event to the customers. Since this profit accrues due to the total load reduction because of the actions taken by all the customers, the interaction among the customers also needs to be carefully included in the contract design. The contract design and its properties are presented and illustrated through examples.
Network Design with Coverage Costs

We study network design with a cost structure motivated by redundancy in data traffic. We are given a graph, g groups of terminals, and a universe of data packets. Each group of terminals desires a subset of the packets from its respective source. The cost of routing traffic on any edge in the network is proportional to the total size of the distinct packets that the edge carries. Our goal is to find a minimum cost routing. We focus on two settings. In the first, the collection of packet sets desired by source-sink pairs is laminar. For this setting, we present a primal-dual based 2-approximation, improving upon a logarithmic approximation due to Barman and Chawla (2012){BC12}. In the second setting, packet sets can have non-trivial intersection. We focus on the case where each packet is desired by either a single terminal group or by all of the groups. This setting does not admit an O(log^{{1}/{4} - gamma} g)-approximation for any constant gamma under a standard assumption; we present an O(log g)-approximation when the graph is unweighted. Our approximation for the second setting is based on a novel spanner-type construction in unweighted graphs that, given a collection of g vertex subsets, finds a subgraph of cost only a constant factor more than the minimum spanning tree of the graph, such that every subset in the collection has a Steiner tree in the subgraph of cost at most O(log g) that of its minimum Steiner tree in the original graph. We call such a subgraph a group spanner.
Social welfare and profit maximization from revealed preferences

Consider the seller’s problem of finding optimal prices for her n (divisible) goods when faced with a set of m consumers, given that she can only observe their purchased bundles at posted prices, i.e., revealed preferences. We study both social welfare and profit maximization with revealed preferences. Although social welfare maximization is a seemingly non-convex optimization problem in prices, we show that (i) it can be reduced to a dual convex optimization problem in prices, and (ii) the revealed preferences can be interpreted as supergradients of the concave conjugate of valuation, with which subgradients of the dual function can be computed. We thereby obtain a simple subgradient-based algorithm for strongly concave valuations and convex cost, with query complexity \(O(m^2/\epsilon ^2)\), where \(\epsilon \) is the additive difference between the social welfare induced by our algorithm and the optimum social welfare. We also study social welfare maximization under the online setting, specifically the random permutation model, where consumers arrive one-by-one in a random order. For the case where consumer valuations can be arbitrary continuous functions, we propose a price posting mechanism that achieves an expected social welfare up to an additive factor of \(O(\sqrt{mn})\) from the maximum social welfare. Finally, for profit maximization (which may be non-convex in simple cases), we give nearly matching upper and lower bounds on the query complexity for separable valuations and cost (i.e., each good can be treated independently).
Vizing’s conjecture: A two-thirds bound for claw-free graphs

Abstract We show that for any claw-free graph G and any graph H , γ ( G □ H ) ≥ 2 3 γ ( G ) γ ( H ) , where γ ( G ) is the domination number of G .
Adjusting for unmeasured spatial confounding with distance adjusted propensity score matching

Propensity score matching is a common tool for adjusting for observed confounding in observational studies, but is known to have limitations in the presence of unmeasured confounding. In many settings, researchers are confronted with spatially-indexed data where the relative locations of the observational units may serve as a useful proxy for unmeasured confounding that varies according to a spatial pattern. We develop a new method, termed distance adjusted propensity score matching (DAPSm) that incorporates information on units' spatial proximity into a propensity score matching procedure. We show that DAPSm can adjust for both observed and some forms of unobserved confounding and evaluate its performance relative to several other reasonable alternatives for incorporating spatial information into propensity score adjustment. The method is motivated by and applied to a comparative effectiveness investigation of power plant emission reduction technologies designed to reduce population exposure to ambient ozone pollution. Ultimately, DAPSm provides a framework for augmenting a "standard" propensity score analysis with information on spatial proximity and provides a transparent and principled way to assess the relative trade-offs of prioritizing observed confounding adjustment versus spatial proximity adjustment.
AB initio study of size and strain effects on the electronic properties of Si nanowires

We have applied density-functional theory (DFT) based calculations to investigate the size and strain effects on the electronic properties, such as band structures, energy gaps and effective masses of the electron and the hole, in Si nanowires along the 〈110〉 direction with diameters up to 5 nm. Under uniaxial strain, we find that the band gap varies with strain and this variation is size dependent. For the 1–2 nm wire, the band gap is a linear function of strain, while for the 2–4 nm wire the gap variation with strain shows nearly parabolic behaviour. This size dependence of the gap variation with strain is explained on the basis of orbital characters of the band edges. In addition we find that the expansive strain increases the effective mass of the hole, while compressive strain increases the effective mass of the electron. The study of size and strain effects on effective masses shows that effective masses of the electron and the hole can be reduced by tuning the diameter of the wire and applying appropriate strain.
Naive entropy of dynamical systems

We study an invariant of dynamical systems called naive entropy, which is defined for both measurable and topological actions of any countable group. We focus on nonamenable groups, in which case the invariant is two-valued, with every system having naive entropy either zero or infinity. Bowen has conjectured that when the acting group is sofic, zero naive entropy implies sofic entropy at most zero for both types of systems. We prove the topological version of this conjecture by showing that for every action of a sofic group by homeomorphisms of a compact metric space, zero naive entropy implies sofic entropy at most zero. This result and the simple definition of naive entropy allow us to show that the generic action of a free group on the Cantor set has sofic entropy at most zero. We observe that a distal Γ-system has zero naive entropy in both senses, if Γ has an element of infinite order. We also show that the naive entropy of a topological system is greater than or equal to the naive measure entropy of the same system with respect to any invariant measure.
TRANSFINITE RECURSION IN HIGHER REVERSE MATHEMATICS

In this paper we investigate the reverse mathematics of higher-order analogues of the theory remains robust at higher types. Our main result is the separation of open and clopen determinacy for reals, using a variant of Steel’s tagged tree forcing; in the presentation of this result, we develop a new, more flexible framework for Steel-type forcing.
Exploiting Commutativity For Practical Fast Replication

Traditional approaches to replication require client requests to be ordered before making them durable by copying them to replicas. As a result, clients must wait for two round-trip times (RTTs) before updates complete. In this paper, we show that this entanglement of ordering and durability is unnecessary for strong consistency. Consistent Unordered Replication Protocol (CURP) allows clients to replicate requests that have not yet been ordered, as long as they are commutative. This strategy allows most operations to complete in 1 RTT (the same as an unreplicated system). We implemented CURP in the Redis and RAMCloud storage systems. In RAMCloud, CURP improved write latency by ~2x (13.8 us -> 7.3 us) and write throughput by 4x. Compared to unreplicated RAMCloud, CURP's latency overhead for 3-way replication is just 0.4 us (6.9 us vs 7.3 us). CURP transformed a non-durable Redis cache into a consistent and durable storage system with only a small performance overhead.
Parameters for generalized Hecke algebras in type B

The irreducible representations of full support in the rational Cherednik category &#x1d4aa;c(W) attached to a Coxeter group W are in bijection with the irreducible representations of an associated Iwahori...
A century-long commitment to assessing artificial intelligence and its impact on society

A series of reports promises the general public a technologically accurate view of the state of AI and its societal implications.
A new semidirect product for association schemes

Abstract We propose a new definition for the semidirect product of association schemes, generalizing work of Bang, Hirasaka, and Song. We define an action of one scheme on another, and show how one can use such an action to construct all semidirect products satisfying a certain technical condition.
Chermak–Delgado simple groups

This paper provides the first steps in classifying the finite solvable groups having Property A, which is a property involving abelian normal subgroups. We see that this classification is reduced t...
Multimodal Storytelling via Generative Adversarial Imitation Learning

Deriving event storylines is an effective summarization method to succinctly organize extensive information, which can significantly alleviate the pain of information overload. The critical challenge is the lack of widely recognized definition of storyline metric. Prior studies have developed various approaches based on different assumptions about users' interests. These works can extract interesting patterns, but their assumptions do not guarantee that the derived patterns will match users' preference. On the other hand, their exclusiveness of single modality source misses cross-modality information. This paper proposes a method, multimodal imitation learning via generative adversarial networks(MIL-GAN), to directly model users' interests as reflected by various data. In particular, the proposed model addresses the critical challenge by imitating users' demonstrated storylines. Our proposed model is designed to learn the reward patterns given user-provided storylines and then applies the learned policy to unseen data. The proposed approach is demonstrated to be capable of acquiring the user's implicit intent and outperforming competing methods by a substantial margin with a user study.
Convex Relaxations for Nonlinear Stochastic Optimal Control Problems

This article presents a new method for computing guaranteed convex and concave relaxations of nonlinear stochastic optimal control problems with final-time expected-value cost functions. This method is motivated by similar methods for deterministic optimal control problems, which have been successfully applied within spatial branch-and-bound (B&B) techniques to obtain guaranteed global optima. Relative to those methods, a key challenge here is that the expected-value cost function cannot be expressed analytically in closed form. Nonetheless, the presented relaxations provide rigorous lower and upper bounds on the optimal objective value with no sample-based approximation error. In principle, this enables the use of spatial B&B global optimization techniques, but we leave the details of such an algorithm for future work.
On normal variance–mean mixtures

Abstract We study shape properties of normal variance–mean mixtures, in both the univariate and multivariate cases, and determine conditions for unimodality and log-concavity of the density functions. We also interpret such results in practical terms and discuss discrete analogues.
New normality constructions for continued fraction expansions

Abstract Text Adler, Keane, and Smorodinsky showed that if one concatenates the finite continued fraction expansions of the sequence of rationals 1 2 , 1 3 , 2 3 , 1 4 , 2 4 , 3 4 , 1 5 , ⋯ into an infinite continued fraction expansion, then this new number is normal with respect to the continued fraction expansion. We show a variety of new constructions of continued fraction normal numbers, including one generated by the subsequence of rationals with prime numerators and denominators: 2 3 , 2 5 , 3 5 , 2 7 , 3 7 , 5 7 , ⋯ . Video For a video summary of this paper, please visit https://youtu.be/L7uyAQ7hS74 .
On the Motion of a Compressible Gravity Water Wave with Vorticity

We prove a priori estimates for the compressible Euler equations modeling the motion of a liquid with moving physical vacuum boundary with unbounded initial domain. The liquid is under influence of gravity but without surface tension. Our fluid is not assumed to be irrotational. But the physical sign condition needs to be assumed on the free boundary. We generalize the method used in Lindblad and Luo (Commun Pure Appl Math, 2008) to prove the energy estimates in an unbounded domain up to arbitrary order. In addition to that, the a priori energy estimates are in fact uniform in the sound speed $$\kappa $$ . As a consequence, we obtain the convergence of solutions of compressible Euler equations with a free boundary to solutions of the incompressible equations, generalizing the result of Lindblad and Luo (2008) to when you have an unbounded domain. On the other hand, we prove that there are initial data satisfying the compatibility condition in some weighted Sobolev spaces, and this will propagate within a short time interval, which is essential for proving long time existence for slightly compressible irrotational water waves.
Equation Parsing: Mapping Sentences to Grounded Equations

Identifying mathematical relations expressed in text is essential to understanding a broad range of natural language text from election reports, to financial news, to sport commentaries to mathematical word problems. This paper focuses on identifying and understanding mathematical relations described within a single sentence. We introduce the problem of Equation Parsing -- given a sentence, identify noun phrases which represent variables, and generate the mathematical equation expressing the relation described in the sentence. We introduce the notion of projective equation parsing and provide an efficient algorithm to parse text to projective equations. Our system makes use of a high precision lexicon of mathematical expressions and a pipeline of structured predictors, and generates correct equations in $70\%$ of the cases. In $60\%$ of the time, it also identifies the correct noun phrase $\rightarrow$ variables mapping, significantly outperforming baselines. We also release a new annotated dataset for task evaluation.
Privacy Under Hard Distortion Constraints

We study the problem of data disclosure with privacy guarantees, wherein the utility of the disclosed data is ensured via a hard distortion constraint. Unlike average distortion, hard distortion provides a deterministic guarantee of fidelity. For the privacy measure, we use a tunable information leakage measure, namely maximal $\alpha$- leakage $(\alpha \in [1, \infty$ and formulate the privacy-utility tradeoff problem. The resulting solution highlights that under a hard distortion constraint, the nature of the solution remains unchanged for both local and non-local privacy requirements. More precisely, we show that both the optimal mechanism and the optimal tradeoff are invariant for any $\alpha \gt 1$; i.e., the tunable leakage measure only behaves as either of the two extrema, i.e., mutual information for $\alpha=1$ and maximal leakage for $\alpha=\infty$.
Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering

Many vision and language tasks require commonsense reasoning beyond data-driven image and natural language processing. Here we adopt Visual Question Answering (VQA) as an example task, where a system is expected to answer a question in natural language about an image. Current state-of-the-art systems attempted to solve the task using deep neural architectures and achieved promising performance. However, the resulting systems are generally opaque and they struggle in understanding questions for which extra knowledge is required. In this paper, we present an explicit reasoning layer on top of a set of penultimate neural network based systems. The reasoning layer enables reasoning and answering questions where additional knowledge is required, and at the same time provides an interpretable interface to the end users. Specifically, the reasoning layer adopts a Probabilistic Soft Logic (PSL) based engine to reason over a basket of inputs: visual relations, the semantic parse of the question, and background ontological knowledge from word2vec and ConceptNet. Experimental analysis of the answers and the key evidential predicates generated on the VQA dataset validate our approach.
An empirical model for the galaxy luminosity and star formation rate function at high redshift

Using the most recent measurements of the ultraviolet (UV) luminosity functions (LFs) and dust estimates of early galaxies, we derive updated dust-corrected star-formation rate functions (SFRFs) at z~4-8, which we model to predict the evolution to higher redshifts, z>8. We employ abundance matching techniques to calibrate a relation between galaxy star formation rate (SFR) and host halo mass M$_{h}$ by mapping the shape of the observed SFRFs at z~4-8 to that of the halo mass function. The resulting scaling law remains roughly constant over this redshift range. We apply the average SFR-M$_{h}$ relation to reproduce the observed SFR functions at 4 10 indicate that JWST will be able to detect galaxies out to z~15 with an extensive treasury sized program. We also derive the redshift evolution of the star formation rate density and associated reionization history by galaxies. Models which integrate down to the current HUDF12/XDF detection limit (M$_{UV}$ ~ -17.7 mag) result in a SFRD that declines as (1+z)$^{-10.4\pm0.3}$ at high redshift and fail to reproduce the observed CMB electron scattering optical depth, $\tau$ ~ 0.066, to within 1$\sigma$. On the other hand, we find that the inclusion of galaxies with SFRs well below the current detection limit (M$_{UV}$ < -5.7 mag) leads to a fully reionized universe by z ~ 6.5 and an optical depth of $\tau$ ~ 0.054, consistent with the recently derived Planck value at the 1$\sigma$ level.
Formation of a giant component in the intersection graph of a random chord diagram

Abstract We study the number of chords and the number of crossings in the largest component of a random chord diagram when the chords are sparsely crossing. This is equivalent to studying the number of vertices and the number of edges in the largest component of the random intersection graph. Denoting the number of chords by n and the number of crossings by m, when m / ( n log ⁡ n ) tends to a limit in ( 0 , 2 / π 2 ) , we show that the chord diagram chosen uniformly at random from all the diagrams with given parameters has a component containing almost all the crossings and a positive fraction of chords. On the other hand, when m ≤ n / 14 , the size of the largest component is of order O ( log ⁡ n ) . One of the key analytical ingredients is an asymptotic expression for the number of chord diagrams with parameters n and m for m ( 2 / π 2 ) n log ⁡ n , based on the Touchard–Riordan formula and the Jacobi identity for the generating function of Euler partition function.
How a User’s Personality Influences Content Engagement in Social Media

Social media presents an opportunity for people to share content that they find to be significant, funny, or notable. No single piece of content will appeal to all users, but are there systematic variations between users that can help us better understand information propagation? We conducted an experiment exploring social media usage during disaster scenarios, combining electroencephalogram (EEG), personality surveys, and prompts to share social media, we show how personality not only drives willingness to engage with social media, but also helps to determine what type of content users find compelling. As expected, extroverts are more likely to share content. In contrast, one of our central results is that individuals with depressive personalities are the most likely cohort to share informative content, like news or alerts. Because personality and mood will generally be highly correlated between friends via homophily, our results may be an import factor in understanding social contagion.
Intrinsically motivated multimodal structure learning

We present a long-term intrinsically motivated structure learning method for modeling transition dynamics during controlled interactions between a robot and semipermanent structures in the world. These structures serve as the basis for a number of possible future tasks defined as Markov Decision Processes (MDPs). We apply a structure learning technique to a multimodal affordance representation that yields a population of forward models for use in planning. We evaluate the approach using experiments on a bimanual mobile manipulator (uBot-6) that show the performance of model acquisition as the number of transition actions increases.
Counting using Hall algebras I. Quivers

Abstract We survey some results on counting the rational points of moduli spaces of quiver representations. We then make generalizations to Grassmannians and flags of quiver representations. These results have nice applications to the cluster algebra. Along the way, we use the full Hopf structure of the Hall algebra of a quiver.
Pattern avoidance in extensions of comb-like posets

This paper investigates pattern avoidance in linear extensions of particular partially ordered sets (posets). Since the problem of enumerating pattern avoiding linear extensions of posets without any additional restrictions is a very hard one, we focus on the class of posets called combs. Combs consist of a fully ordered spine and several fully ordered teeth, where an element of each tooth coincides with a corresponding element of the spine, as described in Section 2. We consider two natural assignments of integers to elements of the combs; we refer to the resulting integer posets as type-α and type-β combs, as described in Section 3. In this paper, we enumerate the linear extensions of type-α and type-β combs that avoid some of the length-three patterns w ∈ S3. Most notably, the number of linear extensions of type-β combs that avoid 312 is shown to be the same as the number 1 st+1 ( s(t+1) s ) of (t + 1)-ary trees on s nodes, where t is the length of each tooth and s is the length of the comb spine or, equivalently, the number of its teeth. We also investigate the enumeration of linear extensions of type-α and type-β combs that avoid multiple length-three patterns simultaneously. 1 ar X iv :1 31 0. 29 79 v2 [ m at h. C O ] 3 0 Ja n 20 14
Novel phenomena in dilute electron systems in two dimensions

Based on theory and experiments in weakly interacting electron systems, it was believed for many years that no metallic phase is possible in two dimensions. The unexpected observation of metallic-like behavior in strongly interacting electron systems has thus drawn considerable attention. Following background material and a brief history, we review the dramatic response of these 2D systems to in-plane magnetic fields, and the evidence this provides for a possible quantum phase transition.
A Learning-Based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles

Vehicle-to-vehicle communication has a great potential to improve reaction accuracy of different driver assistance systems in critical driving situations. Cooperative adaptive cruise control (CACC), which is an automated application, provides drivers with extra benefits such as traffic throughput maximization and collision avoidance. CACC systems must be designed in a way that are sufficiently robust against all special maneuvers, such as cutting-into the CACC platoons by interfering vehicles or hard braking by leading cars. To address this problem, a neural-network-based cut-in detection and trajectory prediction scheme is proposed in the first part of this paper. Next, a probabilistic framework is developed in which the cut-in probability is calculated based on the output of the mentioned cut-in prediction block. Finally, a specific stochastic model predictive controller is designed which incorporates this cut-in probability to enhance its reaction against the detected dangerous cut-in maneuver. The overall system is implemented, and its performance is evaluated using realistic driving scenarios from safety pilot model deployment.
XJ-BP: Express Journey Belief Propagation Decoding for Polar Codes

This paper presents a novel belief propagation (BP) based decoding algorithm for polar codes. The proposed algorithm facilitates belief propagation by utilizing the specific constituent codes that exist in the factor graph, which results in an express journey (XJ) for belief information to propagate in each decoding iteration. In addition, this XJ-BP decoder employs a novel round-trip message passing scheduling method for the increased efficiency. The proposed method simplifies min-sum (MS) BP decoder by 40.6\%. Along with the round-trip scheduling, the XJ-BP algorithm reduces the computational complexity of MS BP decoding by 90.4\%; this enables an energy-efficient hardware implementation of BP decoding in practice.
Hindman’s theorem and idempotent types

Motivated by a question of Di Nasso, we show that Hindman’s theorem is equivalent to the existence of idempotent types in countable complete extensions of Peano Arithmetic.
Optical magnetism in planar metamaterial heterostructures

Harnessing artificial optical magnetism has previously required complex two- and three-dimensional structures, such as nanoparticle arrays and split-ring metamaterials. By contrast, planar structures, and in particular dielectric/metal multilayer metamaterials, have been generally considered non-magnetic. Although the hyperbolic and plasmonic properties of these systems have been extensively investigated, their assumed non-magnetic response limits their performance to transverse magnetic (TM) polarization. We propose and experimentally validate a mechanism for artificial magnetism in planar multilayer metamaterials. We also demonstrate that the magnetic properties of high-index dielectric/metal hyperbolic metamaterials can be anisotropic, leading to magnetic hyperbolic dispersion in certain frequency regimes. We show that such systems can support transverse electric polarized interface-bound waves, analogous to their TM counterparts, surface plasmon polaritons. Our results open a route for tailoring optical artificial magnetism in lithography-free layered systems and enable us to generalize the plasmonic and hyperbolic properties to encompass both linear polarizations.
Correlation manipulating circuits for stochastic computing

Stochastic computing (SC) is an emerging computing technique that promises high density, low power, and error tolerant solutions. In SC, values are encoded as unary bitstreams and SC arithmetic circuits operate on one or more bitstreams. In many cases, the input bitstreams must be correlated or uncorrelated for SC arithmetic to produce accurate results. As a result, a key challenge for designing SC accelerators is manipulating the impact of correlation across SC operations. This paper presents and evaluates a set of novel correlation manipulating circuits to manage correlation in SC computation: a synchronizer, desynchronizer, and decorrelator. We then use these circuits to propose improved SC maximum, minimum, and saturating adder designs. Compared to existing correlation manipulation techniques, our circuits are more accurate and up to 3× more energy efficient. In the context of an image processing pipeline, these circuits can reduce the total energy consumption by up to 24%.
PARTON SHOWERS BEYOND THE LEADING ORDER: A FACTORIZATION APPROACH

We discuss recent work on methods for incorporating nonleading QCD corrections in parton shower algorithms.
Network Model Selection Using Task-Focused Minimum Description Length

Networks are fundamental models for data used in practically every application domain. In most instances, several implicit or explicit choices about the network definition impact the translation of underlying data to a network representation, and the subsequent question(s) about the underlying system being represented. Users of downstream network data may not even be aware of these choices or their impacts. We propose a task-focused network model selection methodology which addresses several key challenges. Our approach constructs network models from underlying data and uses minimum description length (MDL) criteria for selection. Our methodology measures efficiency, a general and comparable measure of the network's performance of a local (i.e. node-level) predictive task of interest. Selection on efficiency favors parsimonious (e.g. sparse) models to avoid overfitting and can be applied across arbitrary tasks and representations. We show stability, sensitivity, and significance testing in our methodology.
A dynamical systems approach to energy disaggregation

Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task of separating aggregate energy data for a whole building into the energy data for individual appliances. Studies have shown that simply providing disaggregated data to the consumer improves energy consumption behavior. However, placing individual sensors on every device in a home is not presently a practical solution. Disaggregation provides a feasible method for providing energy usage behavior data to the consumer which utilizes currently existing infrastructure. In this paper, we present a novel framework to perform the energy disaggregation task. We model each individual device as a single-input, single-output system, where the output is the power consumed by the device and the input is the device usage. In this framework, the task of disaggregation translates into finding inputs for each device that generates our observed power consumption. We describe an implementation of this framework, and show its results on simulated data as well as data from a small-scale experiment.
Time-Periodic Einstein-Klein-Gordon Bifurcations of Kerr

We construct one-parameter families of solutions to the Einstein–Klein–Gordon equations bifurcating off the Kerr solution such that the underlying family of spacetimes are each an asymptotically flat, stationary, axisymmetric, black hole spacetime, and such that the corresponding scalar fields are non-zero and time-periodic. An immediate corollary is that for these Klein–Gordon masses, the Kerr family is not asymptotically stable as a solution to the Einstein–Klein–Gordon equations.
DENSE PGL-ORBITS IN PRODUCTS OF GRASSMANNIANS

Abstract In this paper, we find some necessary and sufficient conditions on the dimension vector d = ( d 1 , … , d k ; n ) so that the diagonal action of P GL ( n ) on ∏ i = 1 k Gr ( d i ; n ) has a dense orbit. Consequently, we obtain some algorithms for finding dense and sparse dimension vectors and classify dense dimension vectors with small length or size. We also classify dimension vectors where | d i − d j | 3 for all i , j generalizing a theorem of Popov [11] .
First stability eigenvalue of singular minimal hypersurfaces in spheres

In this short note we extend an estimate due to J. Simons on the first stability eigenvalue of minimal hypersurfaces in spheres to the singular setting. Specifically, we show that any singular minimal hypersurface in $${\mathbf {S}}^{n+1}$$ , which is not totally geodesic and satisfies the $$\alpha $$ -structural hypothesis, has first stability eigenvalue at most $$-\,2n$$ , with equality if and only if it is a product of two round spheres. The equality case was settled independently in the classical setting by Wu and Perdomo.
Diagonal-preserving isomorphisms of étale groupoid algebras

Abstract Work of Jean Renault shows that, for topologically principal etale groupoids, a diagonal-preserving isomorphism of reduced C ⁎ -algebras yields an isomorphism of groupoids. Several authors have proved analogues of this result for ample groupoid algebras over integral domains under suitable hypotheses. In this paper, we extend the known results by allowing more general coefficient rings and by weakening the hypotheses on the groupoids. Our approach has the additional feature that we only need to impose conditions on one of the two groupoids. Applications are given to Leavitt path algebras.
Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net

Parsing articulated objects, e.g. humans and animals, into semantic parts (e.g. head, body and arms, etc.) from natural images is a challenging and fundamental problem in computer vision. A big difficulty is the large variability of scale and location for objects and their corresponding parts. Even limited mistakes in estimating scale and location will degrade the parsing output and cause errors in boundary details. To tackle this difficulty, we propose a “Hierarchical Auto-Zoom Net” (HAZN) for object part parsing which adapts to the local scales of objects and parts. HAZN is a sequence of two “Auto-Zoom Nets” (AZNs), each employing fully convolutional networks for two tasks: (1) predict the locations and scales of object instances (the first AZN) or their parts (the second AZN); (2) estimate the part scores for predicted object instance or part regions. Our model can adaptively “zoom” (resize) predicted image regions into their proper scales to refine the parsing. We conduct extensive experiments over the PASCAL part datasets on humans, horses, and cows. In all the three categories, our approach significantly outperforms alternative state-of-the-arts by more than \(5\,\%\) mIOU and is especially better at segmenting small instances and small parts. In summary, our strategy of first zooming into objects and then zooming into parts is very effective. It also enables us to process different regions of the image at different scales adaptively so that we do not need to waste computational resources scaling the entire image.
Far infrared edge photoresponse and persistent edge transport in an inverted InAs/GaSb heterostructure

Direct current (DC) transport and far infrared photoresponse were studied an InAs/GaSb double quantum well with an inverted band structure. The DC transport depends systematically upon the DC bias configuration and operating temperature. Surprisingly, it reveals robust edge conduction despite prevalent bulk transport in our device of macroscopic size. Under 180 GHz far infrared illumination at oblique incidence, we measured a strong photovoltaic response. We conclude that quantum spin Hall edge transport produces the observed transverse photovoltages. Overall, our experimental results support a hypothesis that the photoresponse arises from direct coupling of the incident radiation field to edge states.
Updated Compositional Models of the TRAPPIST-1 Planets

After publication of our initial mass-radius-composition models for the TRAPPIST-1 system in Unterborn et al. (2018), the planet masses were updated in Grimm et al. (2018). We had originally adopted the data set of Wang et al., 2017 who reported different densities than the updated values. The differences in observed density change the inferred volatile content of the planets. Grimm et al. (2018) report TRAPPIST-1 b, d, f, g, and h as being consistent with <5 wt% water and TRAPPIST-1 c and e has having largely rocky interiors. Here, we present updated results recalculating water fractions and potential alternative compositions using the Grimm et al., 2018 masses. Overall, we can only reproduce the results of Grimm et al., 2018 of planets b, d and g having small water contents if the cores of these planets are small (<23 wt%). We show that, if the cores for these planets are roughly Earth-sized (33 wt%), significant water fractions up to 40 wt% are possible. We show planets c, e, f, and h can have volatile envelopes between 0-35 wt% that are also consistent with being totally oxidized and lacking an Fe-core entirely. We note here that a pure MgSiO$_3$ planet (Fe/Mg = 0) is not the true lowest density end-member mass-radius curve for determining the probability of a planet containing volatiles. All planets that are rocky likely contain some Fe, either within the core or oxidized in the mantle. We argue the true low density end-member for oxidizing systems is instead a planet with the lowest reasonable Fe/Mg and completely core-less. Using this logic, we assert that planets b, d and g likely must have significant volatile layers because the end-member planet models produce masses too high even when uncertainties in both mass and radius are taken into account.
Perfect Symmetric Rings of Quotients

Perfect Gabriel filters of right ideals and their corresponding right rings of quotients have the desirable feature that every module of quotients is determined solely by the right ring of quotients. On the other hand, symmetric rings of quotients have a symmetry that mimics the commutative case. In this paper, we study rings of quotients that combine these two desirable properties. We define the symmetric versions of a right perfect ring of quotients and a right perfect Gabriel filter — the perfect symmetric ring of quotients and the perfect symmetric Gabriel filter and study their properties. Then we prove that the standard construction of the total right ring of quotients can be adapted to the construction of the largest perfect symmetric ring of quotients — the total symmetric ring of quotients . We also demonstrate that Morita's construction of can be adapted to the construction of .
Smartphone microendoscopy for high resolution fluorescence imaging

High resolution optical endoscopes are increasingly used in diagnosis of various medical conditions of internal organs, such as the cervix and gastrointestinal (GI) tracts, but they are too expensive for use in resource-poor settings. On the other hand, smartphones with high resolution cameras and Internet access have become more affordable, enabling them to diffuse into most rural areas and developing countries in the past decade. In this paper, we describe a smartphone microendoscope that can take fluorescence images with a spatial resolution of 3.1 μm. Images collected from ex vivo, in vitro and in vivo samples using the device are also presented. The compact and cost-effective smartphone microendoscope may be envisaged as a powerful tool for detecting pre-cancerous lesions of internal organs in low and middle-income countries (LMICs).
TrafficNet: An open naturalistic driving scenario library

The enormous efforts spent on collecting naturalistic driving data in the recent years has resulted in an expansion of publicly available traffic datasets, which has the potential to assist the development of the self-driving vehicles. However, we found that many of the attempts to utilize these datasets have failed in practice due to a lack of usability concern from the organizations that host these collected data. For example, extracting data associated with certain critical conditions from naturalistic driving data organized in chronological order may not be convenient for a vehicle engineer that doesn't have big data analytics experiences. To address the general usability challenges of these publicly available traffic datasets, we propose TrafficNet, a large-scale and extensible library of naturalistic driving scenarios, aiming at bridging the gap between research datasets and practically usable information for vehicle engineers and researchers. The proposed web-based driving scenario database preprocesses massive raw traffic data collected in chronological order into an organized scenario-based dataset by applying a set of categorization algorithms to label the naturalistic driving data with six different critical driving scenarios. TrafficNet opens not only the scenario library but also the source code of these categorization methods to the public, which will foster more sophisticated and accurate scenario-based categorization algorithms to advance the intelligent transportation research. The source code and the scenario database can be accessed at https://github.com/TrafficNet.