cssi/SciSciGPT-SciSciNet huggingface dataset:
Multiple-rank modification of symmetric eigenvalue problem.

Abstract Rank-1 modifications applied k-times (k?>?1) often are performed to achieve a rank-k modification. We propose a rank- k modification for enhancing computational efficiency. As the first step toward a rank- k modification, an algorithm to perform a rank-2 modification is proposed and tested. The computation cost of our proposed algorithm is in O ( n 2 ) where n is the cardinality of the matrix of interest. We also propose a general rank-k update algorithm based on the Sturm Theorem, and compare our results to those of the direct eigenvalue decomposition and of a perturbation method.
Duality pairs and stable module categories

Abstract Let R be a commutative ring . We show that any complete duality pair gives rise to a theory of relative homological algebra , analogous to Gorenstein homological algebra. Indeed Gorenstein homological algebra over a commutative Noetherian ring of finite Krull dimension can be recovered from the duality pair ( F , I ) where F is the class of flat R-modules and I is the class of injective R-modules. For a general R, the AC-Gorenstein homological algebra of Bravo–Gillespie–Hovey is the one coming from the duality pair ( L , A ) where L is the class of level R-modules and A is class of absolutely clean R-modules. Indeed we show here that the work in [1] can be extended to obtain similar abelian model structures on R-Mod from any a complete duality pair ( L , A ) . It applies in particular to the original duality pairs constructed by Holm–Jorgensen.
Fast algorithms for finding pattern avoiders and counting pattern occurrences in permutations

Given a set $\Pi$ of permutation patterns of length at most $k$, we present an algorithm for building $S_{\le n}(\Pi)$, the set of permutations of length at most $n$ avoiding the patterns in $\Pi$, in time $O(|S_{\le n - 1}(\Pi)| \cdot k + |S_{n}(\Pi)|)$. Additionally, we present an $O(n!k)$-time algorithm for counting the number of copies of patterns from $\Pi$ in each permutation in $S_n$. Surprisingly, when $|\Pi| = 1$, this runtime can be improved to $O(n!)$, spending only constant time per permutation. Whereas the previous best algorithms, based on generate-and-check, take exponential time per permutation analyzed, all of our algorithms take time at most polynomial per outputted permutation. If we want to solve only the enumerative variant of each problem, computing $|S_{\le n}(\Pi)|$ or tallying permutations according to $\Pi$-patterns, rather than to store information about every permutation, then all of our algorithms can be implemented in $O(n^{k+1}k)$ space. Using our algorithms, we generated $|S_5(\Pi)|, \ldots, |S_{16}(\Pi)|$ for each $\Pi \subseteq S_4$ with $|\Pi| > 4$, and analyzed OEIS matches. We obtained a number of potentially novel pattern-avoidance conjectures. Our algorithms extend to considering permutations in any set closed under standardization of subsequences. Our algorithms also partially adapt to considering vincular patterns.
Principal subspaces of twisted modules for certain lattice vertex operator algebras

This is the third in a series of papers studying the vertex-algebraic structure of principal subspaces of twisted modules for lattice vertex operator algebras. We focus primarily on lattices L whos...
A Cambrian Framework for the Oriented Cycle

This paper completes the project of constructing combinatorial models (called frameworks) for the exchange graph and $\mathbf{g}$-vector fan associated to any exchange matrix $B$ whose Cartan companion is of finite or affine type, using the combinatorics and geometry of Coxeter-sortable elements and Cambrian lattices/fans. Specifically, we construct a framework in the unique non-acyclic affine case, the cyclically oriented $n$-cycle. In the acyclic affine case, a framework was constructed by combining a copy of the Cambrian fan for $B$ with an antipodal copy of the Cambrian fan for $-B$. In this paper, we extend this "doubled Cambrian fan'' construction to the oriented $n$-cycle, using a more general notion of sortable elements for quivers with cycles.
Properties of Mean Value Sets: Angle Conditions, Blowup Solutions, and Nonconvexity

We study the mean values sets of the second order divergence form elliptic operator with principal coefficients defined as $$a^{ij}_{k}(x):= \left\{\begin{array}{llll} \alpha_{k} \delta^{ij}(x) &x_{n}>0 \\ \beta_{k} \delta^{ij}(x) &x_{n}<0. \end{array}\right. $$ In particular, we will show that the mean value sets associated to such an operator need not be convex as αk and βk converge to 1. This example then leads to an example of nonconvex mean value sets for smooth aij(x).
BC type z-measures and determinantal point processes

Abstract The (BC type) z-measures are a family of four parameter z , z ′ , a , b probability measures on the path space of the nonnegative Gelfand–Tsetlin graph with Jacobi-edge multiplicities. We can interpret the z-measures as random point processes P z , z ′ , a , b on the punctured positive real line X = R > 0 ∖ { 1 } . Our main result is that these random processes are determinantal and moreover we compute their correlation kernels explicitly in terms of hypergeometric functions. For very special values of the parameters z , z ′ , the processes P z , z ′ , a , b on X are essentially scaling limits of Racah orthogonal polynomial ensembles and their correlation kernels can be computed simply from some limits of the Racah polynomials. Thus, in the language of random matrices, we study certain analytic continuations of processes that are limits of Racah ensembles, and such that they retain the determinantal structure. Another interpretation of our results, and the main motivation of this paper, is the representation theory of big groups. In representation-theoretic terms, this paper solves a natural problem of harmonic analysis for several infinite-dimensional symmetric spaces.
Modulation of time-mean and turbulent flow by suspended sediment

Experiments are conducted to study the effects of suspended sediment on flow dynamics in a mixing box. Results from particle image velocimetry, providing the velocity of the sediment and fluid phases separately, demonstrate the formation of a stratified layer where turbulent modulation increases.
The Kikuchi Hierarchy and Tensor PCA

For the tensor PCA (principal component analysis) problem, we propose a new hierarchy of increasingly powerful algorithms with increasing runtime. Our hierarchy is analogous to the sum-of-squares (SOS) hierarchy but is instead inspired by statistical physics and related algorithms such as belief propagation and AMP (approximate message passing). Our level-t algorithm can be thought of as a linearized message-passing algorithm that keeps track of t-wise dependencies among the hidden variables. Specifically, our algorithms are spectral methods based on the Kikuchi Hessian, which generalizes the well-studied Bethe Hessian to the higher-order Kikuchi free energies. It is known that AMP, the flagship algorithm of statistical physics, has substantially worse performance than SOS for tensor PCA. In this work we 'redeem' the statistical physics approach by showing that our hierarchy gives a polynomial-time algorithm matching the performance of SOS. Our hierarchy also yields a continuum of subexponential-time algorithms, and we prove that these achieve the same (conjecturally optimal) tradeoff between runtime and statistical power as SOS. Our proofs are much simpler than prior work, and also apply to the related problem of refuting random k-XOR formulas. The results we present here apply to tensor PCA for tensors of all orders, and to k-XOR when k is even. Our methods suggest a new avenue for systematically obtaining optimal algorithms for Bayesian inference problems, and our results constitute a step toward unifying the statistical physics and sum-of-squares approaches to algorithm design.
Fast objective coupled planar illumination microscopy.

Among optical imaging techniques light sheet fluorescence microscopy is one of the most attractive for capturing high-speed biological dynamics unfolding in three dimensions. The technique is potentially millions of times faster than point-scanning techniques such as two-photon microscopy. However light sheet microscopes are limited by volume scanning rate and/or camera speed. We present speed-optimized Objective Coupled Planar Illumination (OCPI) microscopy, a fast light sheet technique that avoids compromising image quality or photon efficiency. Our fast scan system supports 40 Hz imaging of 700 μm-thick volumes if camera speed is sufficient. We also address the camera speed limitation by introducing Distributed Planar Imaging (DPI), a scaleable technique that parallelizes image acquisition across cameras. Finally, we demonstrate fast calcium imaging of the larval zebrafish brain and find a heartbeat-induced artifact, removable when the imaging rate exceeds 15 Hz. These advances extend the reach of fluorescence microscopy for monitoring fast processes in large volumes. Light sheet microscopy holds potential for imaging dynamics in 3D biological specimens, but is limited by scan speed and camera acquisition rate. Here the authors address both issues by developing speed-optimized Objective Coupled Planar Illumination and parallelizing image acquisition across cameras to achieve 40 Hz imaging over thick samples.
MRAM-Based Stochastic Oscillators for Adaptive Non-Uniform Sampling of Sparse Signals in IoT Applications

Recent advances to hardware integration and realization of highly-efficient Compressive Sensing (CS) approaches have inspired novel circuit and architectural-level approaches. These embrace the challenge to design more optimal nonuniform CS solutions that consider device-level constraints for IoT applications wherein lifetime energy, device area, and manufacturing costs are highly-constrained, but meanwhile, the sensing environment is rapidly changing. In this manuscript, we develop a novel adaptive hardware-based approach for non-uniform compressive sampling of sparse and time-varying signals. The proposed Adaptive Sampling of Sparse IoT signals via STochastic-oscillators (ASSIST) approach intelligently generates the CS measurement matrix by distributing the sensing energy among coefficients by considering the signal characteristics such as sparsity rate and noise level obtained in the previous time step. In our proposed approach, Magnetic Random Access Memory (MRAM)-based stochastic oscillators are utilized to generate the random bitstreams used in the CS measurement matrix. SPICE and MATLAB circuit-algorithm simulation results indicate that ASSIST efficiently achieves the desired non-uniform recovery of the original signals with varying sparsity rates and noise levels.
New Constructions of Hinting PRGs, OWFs with Encryption, and More

Over the last few years, there has been a surge of new cryptographic results, including laconic oblivious transfer [13, 16], (anonymous/ hierarchical) identity-based encryption [9], trapdoor functions [19, 20], chosen-ciphertext security transformations [32, 33], designated-verifier zero-knowledge proofs [30, 34, 37], due to a beautiful framework recently introduced in the works of Cho et al. [13], and Dottling and Garg [14]. The primitive of one-way function with encryption (OWFE) [19, 20] and its relatives (chameleon encryption, one-time signatures with encryption, hinting PRGs, trapdoor hash encryption, batch encryption) [9, 14, 16, 17, 33] have been a centerpiece in all these results.
Strengthening children’s roots of resilience: Trauma-responsive early learning

Abstract With the majority of children in the United States attending early care and education (ECE) prior to kindergarten (National Survey of Early Care and Education, 2016), the opportunity to reach children early, and strengthen resilience in the context of everyday life, is profound. Yet, ECE teachers often lack professional supports to meet the needs of children impacted by trauma (Cummings, Addante, Swindell, & Meadan, 2017; Loomis, 2018). The Roots of Resilience program was designed to address this issue through an online course and video-based coaching. Recognizing the importance of feasibility and of balancing rigor with relevance to create wide-spread change (Glasgow & Chambers, 2012), this preliminary study of Roots of Resilience focuses on feasibility and examines teachers’ learning and application of practices consistent with trauma-responsive care. Seventeen ECE teachers from family child care homes, centers, and Head Start programs participated. The majority (69%) had less than a Bachelor’s-level education. Qualitative and quantitative data sources included teacher surveys, quizzes, discussion board entries, workbook entries, coach ratings, and observations. Findings indicate that the program is feasible for ECE teachers and offer preliminary evidence that it may help teachers strengthen their knowledge and application of practices to identify and respond to children’s needs. An iterative development process and a strengths-based approach were identified as critical program attributes.
The Moral Asymmetry of Juvenile and Adult Offenders

Many commentators agree that the trend to try juveniles as adults fails to recognize that there should be an asymmetry in our treatment of juvenile and adult crime such that all else being equal juvenile crime deserves less punishment than does adult crime. This essay explores different rationales for this asymmetry. A political rationale claims that the disenfranchisement of juveniles compromises the state’s democratic authority to punish juveniles in the same way it is permitted to punish adults. A developmental rationale claims that juveniles deserve to be punished less than adults because their immaturity makes them less responsible and, hence, less culpable for their wrongdoing. Gideon Yaffe’s new book The Age of Culpability expresses skepticism about the developmental rationale and defends a version of the political rationale. By contrast, this essay finds important limits to the political rationale and defends a qualified version of the developmental rationale. In the process, it argues against treating the asymmetry between juvenile and adult crime as a categorical one.
Polystore++: Accelerated Polystore System for Heterogeneous Workloads

Modern real-time business analytic consist of heterogeneous workloads (e.g., database queries, graph processing, and machine learning). These analytic applications need programming environments that can capture all aspects of the constituent workloads (including data models they work on and movement of data across processing engines). Polystore systems suit such applications; however, these systems currently execute on CPUs and the slowdown of Moore's Law means they cannot meet the performance and efficiency requirements of modern workloads. We envision Polystore++, an architecture to accelerate existing polystore systems using hardware accelerators (e.g., FPGAs, CGRAs, and GPUs). Polystore++ systems can achieve high performance at low power by identifying and offloading components of a polystore system that are amenable to acceleration using specialized hardware. Building a Polystore++ system is challenging and introduces new research problems motivated by the use of hardware accelerators (e.g., optimizing and mapping query plans across heterogeneous computing units and exploiting hardware pipelining and parallelism to improve performance). In this paper, we discuss these challenges in detail and list possible approaches to address these problems.
Codon use and aversion is largely phylogenetically conserved across the tree of life.

Abstract Using parsimony, we analyzed codon usages across 12,337 species and 25,727 orthologous genes to rank specific genes and codons according to their phylogenetic signal. We examined each codon within each ortholog to determine the codon usage for each species. In total, 890,814 codons were parsimony informative. Next, we compared species that used a codon with species that did not use the codon. We assessed each codon's congruence with species relationships provided in the Open Tree of Life (OTL) and determined the statistical probability of observing these results by random chance. We determined that 25,771 codons had no parallelisms or reversals when mapped to the OTL. Codon usages from orthologous genes spanning many species were 1109× more likely to be congruent with species relationships in the OTL than would be expected by random chance. Using the OTL as a reference, we show that codon usage is phylogenetically conserved within orthologous genes in archaea, bacteria, plants, mammals, and other vertebrates. We also show how to use our provided framework to test different tree hypotheses by confirming the placement of turtles as sister taxa to archosaurs.
The Power of Duality — Exact Results in 4D SUSY Field Theory

Recently the vacuum structure of a large class of four-dimensional (supersymmetric) quantum field theories was determined exactly. These theories exhibit a wide range of interesting new physical phenomena. One of the main new insights is the role of "electric–magnetic duality." In its simplest form it describes the long distance behavior of some strongly coupled, and hence complicated, "electric theories" in terms of weakly coupled "magnetic theories." This understanding sheds new light on confinement and the Higgs mechanism and uncovers new phases of four-dimensional gauge theories. We review these developments and speculate on the outlook.
Non-Kähler Ricci flow singularities modeled on Kähler–Ricci solitons

We investigate Riemannian (non-Kahler) Ricci flow solutions that develop finite-time Type-I singularities and present evidence in favor of a conjecture that parabolic rescalings at the singularities converge to singularity models that are shrinking Kahler-Ricci solitons. Specifically, the singularity model for these solutions is expected to be the "blowdown soliton" discovered in [FIK03]. Our partial results support the conjecture that the blowdown soliton is stable under Ricci flow, as well as the conjectured stability of the subspace of Kahler metrics under Ricci flow.
Parametric Resynthesis With Neural Vocoders

Noise suppression systems generally produce output speech with compromised quality. We propose to utilize the high quality speech generation capability of neural vocoders for noise suppression. We use a neural network to predict clean mel-spectrogram features from noisy speech and then compare two neural vocoders, WaveNet and WaveGlow, for synthesizing clean speech from the predicted mel spectrogram. Both WaveNet and WaveGlow achieve better subjective and objective quality scores than the source separation model Chimera++. Further, WaveNet and WaveGlow also achieve significantly better subjective quality ratings than the oracle Wiener mask. Moreover, we observe that between WaveNet and WaveGlow, WaveNet achieves the best subjective quality scores, although at the cost of much slower waveform generation.
Diversifying seeds and audience in social influence maximization

Influence maximization (IM) has been extensively studied for better viral marketing. However, previous works put less emphasis on how balancedly the audience are affected across different communities and how diversely the seed nodes are selected. In this paper, we incorporate audience diversity and seed diversity into the IM task. From the model perspective, in order to characterize both influence spread and diversity in our objective function, we adopt three commonly used utilities in economics (i.e., Perfect Substitutes, Perfect Complements and Cobb-Douglas). We validate our choices of these three functions by showing their nice properties. From the algorithmic perspective, we present various approximation strategies to maximize the utilities. In audience diversification, we propose a solution-dependent approximation algorithm to circumvent the hardness results. In seed diversification, we prove a (1/e --- ϵ) approximation ratio based on non-monotonic submodular maximization. Experimental results show that our framework outperforms other natural heuristics both in utility maximization and result diversification.
A large-scale empirical study of geotagging behavior on Twitter

Geotagging on social media has become an important proxy for understanding people's mobility and social events. Research that uses geotags to infer public opinions relies on several key assumptions about the behavior of geotagged and non-geotagged users. However, these assumptions have not been fully validated. Lack of understanding the geotagging behavior prohibits people further utilizing it. In this paper, we present an empirical study of geotagging behavior on Twitter based on more than 40 billion tweets collected from 20 million users. There are three main findings that may challenge these common assumptions. Firstly, different groups of users have different geotagging preferences. For example, less than 3% of users speaking in Korean are geotagged, while more than 40% of users speaking in Indonesian use geotags. Secondly, users who report their locations in profiles are more likely to use geotags, which may affects the generability of those location prediction systems on non-geotagged users. Thirdly, strong homophily effect exists in users' geotagging behavior, that users tend to connect to friends with similar geotagging preferences.
Pseudomonas aeruginosa lasR mutant fitness in microoxia is supported by an Anr-regulated oxygen-binding hemerythrin.

Pseudomonas aeruginosa strains with loss-of-function mutations in the transcription factor LasR are frequently encountered in the clinic and the environment. Among the characteristics common to LasR-defective (LasR−) strains is increased activity of the transcription factor Anr, relative to their LasR+ counterparts, in low-oxygen conditions. One of the Anr-regulated genes found to be highly induced in LasR− strains was PA14_42860 (PA1673), which we named mhr for microoxic hemerythrin. Purified P. aeruginosa Mhr protein contained the predicted di-iron center and bound molecular oxygen with an apparent Kd of ∼1 µM. Both Anr and Mhr were necessary for fitness in lasR+ and lasR mutant strains in colony biofilms grown in microoxic conditions, and the effects were more striking in the lasR mutant. Among genes in the Anr regulon, mhr was most closely coregulated with the Anr-controlled high-affinity cytochrome c oxidase genes. In the absence of high-affinity cytochrome c oxidases, deletion of mhr no longer caused a fitness disadvantage, suggesting that Mhr works in concert with microoxic respiration. We demonstrate that Anr and Mhr contribute to LasR− strain fitness even in biofilms grown in normoxic conditions. Furthermore, metabolomics data indicate that, in a lasR mutant, expression of Anr-regulated mhr leads to differences in metabolism in cells grown on lysogeny broth or artificial sputum medium. We propose that increased Anr activity leads to higher levels of the oxygen-binding protein Mhr, which confers an advantage to lasR mutants in microoxic conditions.
Usefulness and applicability of next generation sequencing in neuroendocrine neoplasms.

626Background: Neuroendocrine neoplasms (NENs) are rare tumors that can arise anywhere in the body and treatment options are limited due to their rarity. Knowledge of their mutational status might ...
Beyond Redistribution: In-Stream Habitat Restoration Increases Capacity for Young-of-the-Year Chinook Salmon and Steelhead in the Entiat River, Washington

We conducted snorkel surveys for juvenile salmonids in reaches of the Entiat River (Washington, USA) treated with engineered log jams (ELJs), and in reaches without treatments, to determine if habitat-unit-scale observations can identify whether restoration has increased the habitat capacity of a reach. The conceptual basis and field methodology emphasize fish density data (fish/habitat area in m2) from unrestored habitat within a reach treated with ELJs compared to surveys in 1) unrestored habitat in untreated reaches and 2) restored habitat in treated reaches. A Bayesian generalized linear model enabled us to quantify density differences among habitat types using advanced computational statistics. Modal density of young-of-the-year Chinook salmon (Oncorhynchus tschawytscha) and steelhead (O. mykiss) was at least 3.1-fold and 2.7-fold greater, respectively, in restored habitat compared with unrestored habitat for all treated reaches examined. To distinguish the density differences in those reaches as capacity increases rather than redistribution from poor habitat to good habitat, we compared density in unrestored habitat in both treated and untreated reaches. Here we found no differences for either species, confirming that the increased density in restored habitat units did not come from depletion of unrestored habitat in the same reach. We thus concluded that restoration increased the habitat capacity of the reach at the scale of pools created by ELJs.
Degree Tables for Secure Distributed Matrix Multiplication

We consider the problem of secure distributed matrix multiplication (SDMM) in which a user wishes to compute the product of two matrices with the assistance of honest but curious servers. We construct polynomial codes for SDMM by studying a recently introduced combinatorial tool called the degree table. Maximizing the download rate of a polynomial code for SDMM is equivalent to minimizing N, the number of distinct elements in the corresponding degree table. We propose new constructions of degree tables with a low number of distinct elements. These new constructions lead to a general family of polynomial codes for SDMM, which we call $GASP_{r}$ (Gap Additive Secure Polynomial codes) parametrized by an integer r. $GASP_{r}$ outperforms all previously known polynomial codes for SDMM. We also present lower bounds on N and show that $GASP_{r}$ achieves the lower bounds in the case of no server collusion.
A parametric study to understand the adhesion failure mechanism of asphalt sealant

Adhesive strength of sealant was investigated by utilizing a new test setup developed from modification of Texas Overlay Test. Direct tension to sealant- asphalt concrete substrate was applied without any specialized sealant testing machine. Type I and Type IV (recommended for use in hot and cold climate respectively) sealants were tested at four temperatures on two different joint thicknesses. Type IV sealant fails in adhesion irrespective of temperature or thickness. Depending on the temperature, the failure pattern of Type I is cohesive or mix mode. A correlation between dynamic shear modulus of sealants and adhesive strength for both the sealants at each thickness were established with R2 values over 0.90. A general trend of the effect of thickness was observed and was explained by proposing a hypothesis that there exists a certain modulus for each sealant type at which the bond strength remains same irrespective of its thickness.
How Biased Is Your Model? Concentration Inequalities, Information and Model Bias

We derive tight and computable bounds on the bias of statistical estimators, or more generally of quantities of interest, when evaluated on a baseline model $P$ rather than on the typically unknown true model $Q$ . Our proposed method combines the scalable information inequality derived by P. Dupuis, K.Chowdhary, the authors and their collaborators together with classical concentration inequalities (such as Bennett’s and Hoeffding-Azuma inequalities). Our bounds are expressed in terms of the Kullback-Leibler divergence $R(Q\|P)$ of model $Q$ with respect to $P$ and the moment generating function for the statistical estimator under $P$ . Furthermore, concentration inequalities, i.e. bounds on moment generating functions, provide tight and computationally inexpensive model bias bounds for quantities of interest. Finally, they allow us to derive rigorous confidence bands for statistical estimators that account for model bias and are valid for an arbitrary amount of data.
A Rigorous Path Integral Construction in any Dimension

A rigorous path integral construction for a wide class of Weyl evolution operators is based on a pseudo-differential Ω-calculus on flat phase spaces of finite and infinite dimensions.
Average sampling and average splines on combinatorial graphs

In the setting of a weighted combinatorial finite or infinite countable graph G we introduce functional Paley-Wiener spaces P W ω (L), ω > 0, defined in terms of the spectral resolution of the combinatorial Laplace operator L in the space L 2 (G). It is shown that functions in certain P W ω (L), ω > 0, are uniquely defined by their averages over some families of "small" subgraphs which form a cover of G. Reconstruction methods for reconstruction of an f ∈ P W ω (L) from appropriate set of its averages are introduced. One method is using language of Hilbert frames. Another one is using average variational interpolating splines which are constructed in the setting of combinatorial graphs.
Integral forms in vertex operator algebras, a survey

We give a brief survey of recent work on integral forms in vertex operator algebras (VOAs).
The adversarial mindset.

Many social outcomes are reached by means of competitions between opposing actors. While the positive effects of competition are beyond dispute, this paper contends that competitive situations also trigger a particular psychological mindset that can distort contestants’ judgment and lead to suboptimal courses of action. The paper presents a theoretical framework that consists of a myside bias, by which people adopt a self-serving view of the competition, evaluate themselves favorably, and evaluate their counterpart unfavorably. The framework also proposes the construct of otherside bias, by which people impute to their counterparts distortions that are similar, but opposite, to their own. The combined effect of these biases is to fuel conflict-promoting behavior. Next, the paper presents two experiments designed to test this framework. Using minimalistic experimental treatments, we find that participants assigned to adversarial roles display the myside and otherside biases. The primary objective of this paper is to offer a comprehensive account of the psychological mindset evoked by competitive situations. We integrate findings established across a variety of research fields into a unifying theoretical framework and demonstrate their joint impact on this important domain of human judgment and behavior. Second, we propose that coherence-based reasoning serves as the cognitive backbone of the framework, in that the array of judgments are intricately interconnected and organized in a coherence maximizing representational structure both within and between the myside and otherside biases. Third, we discuss the framework’s implications for a variety of legal domains, including negotiations, litigation, expert testimony, and police investigations.
Irreversible heat flow across phase boundaries in phase-separated manganites

Abstract We have investigated the change in entropy with direct measurements of heat flow as a function of magnetic field at fixed temperatures across the entire phase diagram of the phase-separated (PS) compound La0.25Pr0.375Ca0.375MnO3 (LPCMO). At this composition, the compound shows competing charge-ordered/antiferromagnetic (CO/AF) ground states. Under a fixed temperature, we observed an increase in hysteresis in the entropy as a function of the applied field. The heat flux shows progressively irreversible hysteresis, which characterizes the energy barriers between the two competing ground states, as the temperature is lowered. The increase in the heat loss correlates with the increase in magnetic viscosity in the phase-separated state.
Trust Estimation of Historical Social Harm Events in Indianapolis Metro Area

Social harm involves incidents resulting in physical, financial, and emotional hardships such as crime, drug overdoses and abuses, traffic accidents, and suicides. These incidents require various law-enforcement and emergencyresponding agencies to coordinate together for mitigating their impact on society. In this paper, we discuss the enhancements made to Community Data Analytic for Social Harm Prevention (CDASH) - a system that we have created for analyzing historical social harm events. CDASH predicts `hot-spots’ and displays them graphically to law-enforcement officials. The enhanced system, called Trusted-CDASH (T-CDASH), superimposes a trust estimation framework on top of CDASH. We discuss the importance and necessity of associating a degree of trust with each social harm incident reported to T-CDASH. We also describe different trust models that can be incorporated for assigning trust while examining their impact on prediction accuracy of future social harm events. To validate the trust models, we run simulations on historical social harm data of Indianapolis metro area, illustrating the behavior of each trust model and exploring their significance.
A 1 Gb/s Mixed-Signal Baseband Analog Front-End for a 60 GHz Wireless Receiver

Alow-power mixed-signal baseband analog front-end for 60 GHz, 1 Gb/s wireless communications has been implemented in a standard 90 nm CMOS process. The receiver is capable of operating under indoor multipath scenarios, resolving channels with up to 32 ns multipath delay spread. It uses mixed-signal equalization and carrier recovery in order to minimize the dynamic range requirements of the analog-to-digital converter circuitry. A new mixed-signal carrier phase recovery architecture, utilizing a replica tuning scheme employing Gilbert quad variable-gain amplifiers is introduced. The analog-to-digital converters use an active averaging technique that decouples the preamplifier gain from the averager input range, enabling enhanced suppression of mismatch-induced nonlinearities. These techniques enable a front-end with 6-bit linearity and dynamic range, while dissipating a low power consumption of 55 mW.
Pathfinder Mission to Mars

Mission and Spacecraft Overview Science Instruments and Objectives Lander Site Location Keywords: Pathfinder mission to Mars; cruise phase (of Mars)
Macroscopic optomechanical superposition via periodic qubit flipping

We propose a scheme to generate macroscopic superpositions of well-distinguishable coherent states in an optomechanical system via periodic qubit flipping. Our scheme does not require the single-photon strong-coupling rate of an optomechanical system. The generated mechanical superposition state can be reconstructed using mechanical quantum-state reconstruction. The proposed scheme relies on recycling of an atom, fast atomic qubit flipping, and coherent state mapping between a single-photon superposition state and an atomic superposition state. We discuss the experimental feasibility of our proposal under current technology.
A Complex Adaptive Systems-Based Enterprise Knowledge Sharing Model

This article describes a complex adaptive system (CAS)-based enterprise knowledge-sharing (KnS) model. The CAS-based enterprise KnS model consists of a CAS-based KnS framework and a multi-agent simulation model. Enterprise knowledge sharing is modeled as the emergent behavior of knowledge workers interacting with the KnS environment and other knowledge workers. The CAS-based enterprise KnS model is developed to aid knowledge management (KM) leadership and other KnS researchers in gaining an enhanced understanding of KnS behavior and its influences. A premise of this research is that a better understanding of KnS influences can result in enhanced decision-making of KnS interventions that can result in improvements in KnS behavior.
Unraveling yields inefficient matchings: evidence from post-season college football bowls

Many markets have “unraveled” and experienced inefficient, early, dispersed transactions, and subsequently developed institutions to delay transaction timing. It has previously proved difficult, however, to measure and identify the resulting efficiency gains. Prior to 1992, college football teams were matched for post-season play up to several weeks before the end of the regular season. Since 1992, the market has reorganized to postpone this matching. We show that the matching of teams affects efficiency as measured by the resulting television viewership, and that the reorganization promoted more efficient matching, chiefly as a result of the increased ability of later matching to produce “championship” games.
Differential Information and Dynamic Behavior of Stock Trading Volume

This article develops a multiperiod rational expectations model of stock trading in which investors have differential information concerning the underlying value of the stock. Investors trade competitively in the stock market based on their private information and the information revealed by the market-clearing prices, as well as other public news. We examine how trading volume is related to the information flow in the market and how investors' trading reveals their private information. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
A mechanism for the production of planetary nebulae

C12 stars in the range 1.04–1.55M ⊙ are evolved to simulate the core evolution of the possible precursors of planetary nebulae. The nuclear shell burning in stars above 1.2M ⊙ advances to within about 0.2M ⊙ of the surface, where the intense radiation interacts with the surface matter and causes mass loss. Comparison between our theoretical results and observations suggests that this may be a mechanism by which planetary nebulae are formed.
Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study.

Background Over 40 000 patients with COVID-19 have been hospitalised in New York City (NY, USA) as of April 28, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed. Methods This prospective observational cohort study took place at two NewYork-Presbyterian hospitals affiliated with Columbia University Irving Medical Center in northern Manhattan. We prospectively identified adult patients (aged ≥18 years) admitted to both hospitals from March 2 to April 1, 2020, who were diagnosed with laboratory-confirmed COVID-19 and were critically ill with acute hypoxaemic respiratory failure, and collected clinical, biomarker, and treatment data. The primary outcome was the rate of in-hospital death. Secondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal replacement therapy, and time to in-hospital clinical deterioration following admission. The relation between clinical risk factors, biomarkers, and in-hospital mortality was modelled using Cox proportional hazards regression. Follow-up time was right-censored on April 28, 2020 so that each patient had at least 28 days of observation. Findings Between March 2 and April 1, 2020, 1150 adults were admitted to both hospitals with laboratory-confirmed COVID-19, of which 257 (22%) were critically ill. The median age of patients was 62 years (IQR 51-72), 171 (67%) were men. 212 (82%) patients had at least one chronic illness, the most common of which were hypertension (162 [63%]) and diabetes (92 [36%]). 119 (46%) patients had obesity. As of April 28, 2020, 101 (39%) patients had died and 94 (37%) remained hospitalised. 203 (79%) patients received invasive mechanical ventilation for a median of 18 days (IQR 9-28), 170 (66%) of 257 patients received vasopressors and 79 (31%) received renal replacement therapy. The median time to in-hospital deterioration was 3 days (IQR 1-6). In the multivariable Cox model, older age (adjusted hazard ratio [aHR] 1·31 [1·09-1·57] per 10-year increase), chronic cardiac disease (aHR 1·76 [1·08-2·86]), chronic pulmonary disease (aHR 2·94 [1·48-5·84]), higher concentrations of interleukin-6 (aHR 1·11 [95%CI 1·02-1·20] per decile increase), and higher concentrations of D-dimer (aHR 1·10 [1·01-1·19] per decile increase) were independently associated with in-hospital mortality. Interpretation Critical illness among patients hospitalised with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extrapulmonary organ dysfunction, and substantial in-hospital mortality. Funding National Institute of Allergy and Infectious Diseases and the National Center for Advancing Translational Sciences, National Institutes of Health, and the Columbia University Irving Institute for Clinical and Translational Research.
Multimodal Fusion of Imaging and Genomics for Lung Cancer Recurrence Prediction

Lung cancer has a high rate of recurrence in early-stage patients. Predicting the post-surgical recurrence in lung cancer patients has traditionally been approached using single modality information of genomics or radiology images. We investigate the potential of multimodal fusion for this task. By combining computed tomography (CT) images and genomics, we demonstrate improved prediction of recurrence using linear Cox proportional hazards models with elastic net regularization. We work on a recent non-small cell lung cancer (NSCLC) radiogenomics dataset of 130 patients and observe an increase in concordance-index values of up to 10%. Employing non-linear methods from the neural network literature, such as multi -layer perceptrons and visual-question answering fusion modules, did not improve performance consistently. This indicates the need for larger multimodal datasets and fusion techniques better adapted to this biological setting.
The Relative Tax Gap Hypothesis: An Exploratory Analysis and Application to U.S. Financial Markets

This study empirically investigates the “relative tax gap hypothesis,” which posits that the greater the size of the relative tax gap, the greater the degree to which the U.S. Treasury must borrow from domestic and/or other credit markets and hence the higher the ex ante real interest rate yield on the Bellwether 30 year U.S. Treasury bond. The study uses the most current data available for computing what is referred to here as the “relative tax gap,” which is the ratio of the aggregate tax gap (the loss in federal income tax revenue resulting from personal income tax evasion) to the GDP level. For each year of the study period, the nominal value of the tax gap is scaled by the nominal GDP level and expressed as a percentage. The study period runs from 1982 through 2016, reflecting data availability for all of the variables. The estimation results provide strong support for the hypothesis. In addition, in separate estimations, evidence is provided that the relative tax gap also acts to elevate the ex ante real interest rate yield on Moody’s Baa-rated long-term corporate bonds. It logically follows, then, that to the extent that a greater relative tax gap leads to higher ex ante real interest rates, it may contribute to the crowding out of corporate investment in new plant equipment associated heretofore with government budget deficits per se.
Variability and Fidelity Limits of Silicon Quantum Gates Due to Random Interface Charge Traps

Silicon offers an attractive material platform for hardware realization of quantum computing. In this study, a microscopic stochastic simulation method is developed to model the effect of random interface charge traps in silicon metal-oxide-semiconductor (MOS) quantum gates. The statistical results show that by using a fast two-qubit gate in isotopically purified silicon, the two-qubit silicon-based quantum gates have the fidelity >98% with a probability of 75% for the state-of-the-art MOS interface quality. By using a composite gate pulse, the fidelity can be further improved to >99.5% with the 75% probability. The variations between the quantum gate devices, however, are largely due to the small number of traps per device. The results highlight the importance of variability consideration due to random charge traps and potential to improve fidelity in silicon-based quantum computing.
Sequential Cooperative Bayesian Inference

Cooperation is often implicitly assumed when learning from other agents. Cooperation implies that the agent selecting the data, and the agent learning from the data, have the same goal, that the learner infer the intended hypothesis. Recent models in human and machine learning have demonstrated the possibility of cooperation. We seek foundational theoretical results for cooperative inference by Bayesian agents through sequential data. We develop novel approaches analyzing consistency, rate of convergence and stability of Sequential Cooperative Bayesian Inference (SCBI). Our analysis of the effectiveness, sample efficiency and robustness show that cooperation is not only possible in specific instances but theoretically well-founded in general. We discuss implications for human-human and human-machine cooperation.
FDA: Fourier Domain Adaptation for Semantic Segmentation

We describe a simple method for unsupervised domain adaptation, whereby the discrepancy between the source and target distributions is reduced by swapping the low-frequency spectrum of one with the other. We illustrate the method in semantic segmentation, where densely annotated images are aplenty in one domain (synthetic data), but difficult to obtain in another (real images). Current state-of-the-art methods are complex, some requiring adversarial optimization to render the backbone of a neural network invariant to the discrete domain selection variable. Our method does not require any training to perform the domain alignment, just a simple Fourier Transform and its inverse. Despite its simplicity, it achieves state-of-the-art performance in the current benchmarks, when integrated into a relatively standard semantic segmentation model. Our results indicate that even simple procedures can discount nuisance variability in the data that more sophisticated methods struggle to learn away.
Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies

Standard reinforcement learning (RL) aims to find an optimal policy that identifies the best action for each state. However, in healthcare settings, many actions may be near-equivalent with respect to the reward (e.g., survival). We consider an alternative objective -- learning set-valued policies to capture near-equivalent actions that lead to similar cumulative rewards. We propose a model-free algorithm based on temporal difference learning and a near-greedy heuristic for action selection. We analyze the theoretical properties of the proposed algorithm, providing optimality guarantees and demonstrate our approach on simulated environments and a real clinical task. Empirically, the proposed algorithm exhibits good convergence properties and discovers meaningful near-equivalent actions. Our work provides theoretical, as well as practical, foundations for clinician/human-in-the-loop decision making, in which humans (e.g., clinicians, patients) can incorporate additional knowledge (e.g., side effects, patient preference) when selecting among near-equivalent actions.
Large second-order nonlinearity in asymmetric metallic quantum wells

Investigation of new plasmonic material platforms with large optical nonlinearity is crucial for the continued development of nonlinear optics and its applications. Here, we report an enhanced second-order nonlinear effect in metallic quantum wells (QWs), where the intersubband transition plays a dominant role. Centrosymmetry in these metallic QWs is broken by forming multilayers with chemically and structurally distinct barrier oxides above and below a metal nanofilm. For Au-based QWs, we show that a large χ(2) around 229.6 pm/V in the near infrared was achieved in an asymmetric metallic QW of SiO2|Au|HfO2 on a fused silica substrate.