cssi/SciSciGPT-SciSciNet huggingface dataset:
Stationary Ca2+ nanodomains in the presence of buffers with two binding sites

Abstract We examine closed-form approximations for the equilibrium Ca2+ and buffer concentrations near a point Ca2+ source representing a Ca2+ channel, in the presence of a mobile buffer with two Ca2+ binding sites activated sequentially and possessing distinct binding affinities and kinetics. This allows us to model the impact on Ca2+ nanodomains of realistic endogenous Ca2+ buffers characterized by cooperative Ca2+ binding, such as calretinin. The approximations we present involve a combination or rational and exponential functions, whose parameters are constrained using the series interpolation method that we recently introduced for the case of simpler Ca2+ buffers with a single Ca2+ binding site. We conduct extensive parameter sensitivity analysis and show that the obtained closed-form approximations achieve reasonable qualitative accuracy for a wide range of buffer’s Ca2+ binding properties and other relevant model parameters. In particular, the accuracy of the derived approximants exceeds that of the rapid buffering approximation in large portions of the relevant parameter space.
Can Nondeterminism Help Complementation

Complementation and determinization are two fundamental notions in automata theory. The close relationship between the two has been well observed in the literature. In the case of nondeterministic finite automata on finite words (NFA), complementation and determinization have the same state complexity, namely Θ(2) where n is the state size. The same similarity between determinization and complementation was found for Buchi automata, where both operations were shown to have 2 lg n) state complexity. An intriguing question is whether there exists a type of ω-automata whose determinization is considerably harder than its complementation. In this paper, we show that for all common type ω-automata, the determinization problem has the same state complexity as the corresponding complementation problem at the granularity of 2Θ(·).
Minimum Mean-Squared-Error autocorrelation processing in coprime arrays

Abstract Coprime arrays enable Direction-of-Arrival (DoA) estimation of an increased number of sources. To that end, the receiver estimates the autocorrelation matrix of a larger virtual uniform linear array (coarray), by applying selection or averaging to the physical array's autocorrelation estimates, followed by spatial-smoothing. Both selection and averaging have been designed under no optimality criterion and attain arbitrary (suboptimal) Mean-Squared-Error (MSE) estimation performance. In this work, we design a novel coprime array receiver that estimates the coarray autocorrelation with Minimum-MSE (MMSE), for any probability distribution of the source DoAs. Our extensive numerical evaluation illustrates that the proposed MMSE approach returns superior autocorrelation estimates which, in turn, enable higher DoA estimation performance compared to standard counterparts.
Space Charge and Current in Alternating Corona

1. The physical nature of ionization in a corona discharge in air is studied; by means of the corona spectrum, the saturation current in air around the corona voltage, and the influence of the material of the wire on the saturation current. The results indicate that nitrogen only is ionized in a corona discharge in air; that the ionization of the nitrogen results in the separation of an electron from the nitrogen molecule; and that the electron quickly attaches to a molecule or group of molecules, probably water or oxygen, to form an ion. 2. The free charge in the neighborhood of the wire called the space charge, is found to be alternating in character and to have a definite boundary. The space charge formed on any half-wave returns to the wire on the next succeeding half-wave. 3. The mobility of the ions is calculated from the boundary of the space charge. A limiting value of about 10 cm./sec. per volt/cm. is indicated for the positive ions. The negative ions show no sign of a limiting value and the mobility varies from about 1.6 to 10 cm./sec. per volt/cm. as the maximum impressed voltage rises from the corona voltage to twice the corona voltage. 4. Ionization is found to occur at lower voltages on the positive half-waves than on the negative half-waves and the ionization on the positive half-waves becomes much more copious with the beginning of ionization on the negative half-waves. 5.
Star factorizations and noncrossing partitions

Abstract We develop the relationship between minimal transitive star factorizations and noncrossing partitions. This gives a new combinatorial proof of a result by Irving and Rattan, and a specialization of a result of Kreweras. It also arises in a poset on the symmetric group whose definition is motivated by the Subword Property of the Bruhat order.
Directional Laplacian Centrality for Cyber Situational Awareness

Cyber operations is drowning in diverse, high-volume, multi-source data. In order to get a full picture of current operations and identify malicious events and actors analysts must see through data generated by a mix of human activity and benign automated processes. Although many monitoring and alert systems exist, they typically use signature-based detection methods. We introduce a general method rooted in spectral graph theory to discover patterns and anomalies without a priori knowledge of signatures. We derive and propose a new graph-theoretic centrality measure based on the derivative of the graph Laplacian matrix in the direction of a vertex. While our proposed Directional Laplacian Centrality may be applied to any graph, we study its effectiveness in identifying important Internet Protocol addresses in network flow data. Using both real and synthetic network flow data, we conduct several experiments to test our measure's sensitivity to two types of injected attack profiles.
Using multiple imputation to classify potential outcomes subgroups.

With medical tests becoming increasingly available, concerns about over-testing, over-treatment and health care cost dramatically increase. Hence, it is important to understand the influence of tes...
Quantified Facial Temporal-Expressiveness Dynamics for Affect Analysis

The quantification of visual affect data (e.g. face images) is essential to build and monitor automated affect modeling systems efficiently. Considering this, this work proposes quantified facial Temporal-expressiveness Dynamics (TED) to quantify the expressiveness of human faces. The proposed algorithm leverages multimodal facial features by incorporating static and dynamic information to enable accurate measurements of facial expressiveness. We show that TED can be used for high-level tasks such as summarization of unstructured visual data, and expectation from and interpretation of automated affect recognition models. To evaluate the positive impact of using TED, a case study was conducted on spontaneous pain using the UNBC-McMaster spontaneous shoulder pain dataset. Experimental results show the efficacy of using TED for quantified affect analysis.
Learning Complexity of Simulated Annealing.

Simulated annealing is an effective and general means of optimization. It is in fact inspired by metallurgy, where the temperature of a material determines its behavior in thermodynamics. Likewise, in simulated annealing, the actions that the algorithm takes depend entirely on the value of a variable which captures the notion of temperature. Typically, simulated annealing starts with a high temperature, which makes the algorithm pretty unpredictable, and gradually cools the temperature down to become more stable. A key component that plays a crucial role in the performance of simulated annealing is the criteria under which the temperature changes namely, the cooling schedule. Motivated by this, we study the following question in this work: "Given enough samples to the instances of a specific class of optimization problems, can we design optimal (or approximately optimal) cooling schedules that minimize the runtime or maximize the success rate of the algorithm on average when the underlying problem is drawn uniformly at random from the same class?" We provide positive results both in terms of sample complexity and simulation complexity. For sample complexity, we show that $\tilde O(\sqrt{m})$ samples suffice to find an approximately optimal cooling schedule of length $m$. We complement this result by giving a lower bound of $\tilde \Omega(m^{1/3})$ on the sample complexity of any learning algorithm that provides an almost optimal cooling schedule. These results are general and rely on no assumption. For simulation complexity, however, we make additional assumptions to measure the success rate of an algorithm. To this end, we introduce the monotone stationary graph that models the performance of simulated annealing. Based on this model, we present polynomial time algorithms with provable guarantees for the learning problem.
Hierarchical low-rank structure of parameterized distributions

This note shows that the matrix forms of several one-parameter distribution families satisfy a hierarchical low-rank structure. Such families of distributions include binomial, Poisson, and $\chi^2$ distributions. The proof is based on a uniform relative bound of a related divergence function. Numerical results are provided to confirm the theoretical findings.
Around Which Stars Can TESS Detect Earth-like Planets? The Revised TESS Habitable Zone Catalog

In the search for life in the cosmos, NASA's Transiting Exoplanet Survey Satellite (TESS) mission has already monitored about 74% of the sky for transiting extrasolar planets, including potentially habitable worlds. However, TESS only observed a fraction of the stars long enough to be able to find planets like Earth. We use the primary mission data - the first two years of observations - and identify 4,239 stars within 210pc that TESS observed long enough to see 3 transits of an exoplanet that receives similar irradiation to Earth: 738 of these stars are located within 30pc. We provide reliable stellar parameters from the TESS Input Catalog that incorporates Gaia DR2 and also calculate the transit depth and radial velocity semi-amplitude for an Earth-analog planet. Of the 4,239 stars in the Revised TESS HZ Catalog, 9 are known exoplanet hosts - GJ 1061, GJ 1132, GJ 3512, GJ 685, Kepler-42, LHS 1815, L98-59, RR Cae, TOI 700 - around which TESS could identify additional Earth-like planetary companions. 37 additional stars host yet unconfirmed TESS Objects of Interest: three of these orbit in the habitable zone - TOI 203, TOI 715, and TOI 2298. For a subset of 614 of the 4,239 stars, TESS has observed the star long enough to be able to observe planets throughout the full temperate, habitable zone out to the equivalent of Mars' orbit. Thus, the Revised TESS Habitable Zone Catalog provides a tool for observers to prioritize stars for follow-up observation to discover life in the cosmos. These stars are the best path towards the discovery of habitable planets using the TESS mission data.
Does environmental compliance pay

This paper examines the relationship between environmental compliance and financial performance of large US companies. The environmental performance is measured in penalties assessed for violations of environmental regulations. The financial performance is represented by the profit margins. The regression models developed in this paper suggest that the degrees of environmental compliance have a positive influence on the profit margins. Conventional economic wisdom is that regulations impose costs and restrictions and therefore put companies at a competitive disadvantage. However, this paper is consistent with the proponents of environmental regulations who argue that tough regulations force companies to be innovative and as a result make them more productive.
New views of black holes from computational imaging

The unique challenges associated with imaging a black hole motivated the development of new computational imaging algorithms. As the Event Horizon Telescope continues to expand, these algorithms will need to evolve to keep pace with the increasingly demanding volume and dimensionality of the data.
Deep S 3 PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models

This paper introduces and solves the simultaneous source separation and phase retrieval (S3PR) problem. S3PR is an important but largely unsolved problem in a number application domains, including microscopy, wireless communication, and imaging through scattering media, where one has multiple independent coherent sources whose phase is difficult to measure. In general, S3PR is highly under-determined, non-convex, and difficult to solve. In this work, we demonstrate that by restricting the solutions to lie in the range of a deep generative model, we can constrain the search space sufficiently to solve S3PR.Code associated with this work is available at https://github.com/computational-imaging/DeepS3PR. An extended version of this work is available at https://arxiv.org/abs/2002.05856.
On Hamiltonian Berge cycles in [3]-uniform hypergraphs

Abstract Given a set R, a hypergraph is R-uniform if the size of every hyperedge belongs to R. A hypergraph H is called covering if every vertex pair is contained in some hyperedge in H . In this note, we show that every covering [3]-uniform hypergraph on n ≥ 6 vertices contains a Berge cycle C s for any 3 ≤ s ≤ n . As an application, we determine the maximum Lagrangian of k-uniform Berge- C t -free hypergraphs and Berge- P t -free hypergraphs.
OSSE Observations of the Crab Pulsar

We present results of the Compton Gamma-Ray Observatory (CGRO) Oriented Scintillation Spectrometer Experiment (OSSE) observations of the Crab pulsar, made during MJD 48373-48406 (1991 April 27 - 1991 May 30) and MJD 48798-48804 (1992 June 25 - 1992 July 1). Pulsar light curves and spectra over the approximately 0.05 to 10 MeV range are presented. The arrival time of the gamma-ray peak and the radio peak agree to within 30 microsec which is better than the approximately 300 microsec accuracy of the measurements. The overall pulse phase averaged spectrum in the 0.1 - 10 MeV range is well-fit by a power law of the form 0.05 x (E/0.13 MeV)exp(-(1.99 +/- 0.03)) photons/sq cm/s. The outer-gap model (with gap parameter equal to 0.46) provided to us by Ho agrees with the data to better than 20%. The spectra of the bridge and second peak are slightly harder than the first peak as measured by the hardness ratio (approximately 110 - 220 keV)/(approximately 50 - 105 keV): P1 = 0.54 +/- 0.01, P2 = 0.63 +/- 0.01, bridge = 0.68 +/- 0.03. The phase of the two peaks in the light curve is constant over the 50 - 550 keV range to within the accuracy of the measurements (better than 0.02 in phase). No evidence was found for variability of the light curve on timescales from 2 minutes (less than a factor of 1.8) to 1 year (less than a factor of 1.06), where these are 3 sigma upper limits. However, when we examine the historical database, we find, in agreement with Nolan et al. (1993), that there is evidence for a 13 year variation in the ratio of the intensity of peak 2 to peak 1. We show that if this is interpreted as being due to precession (which changes the relative view of the intrinsic gamma-ray pulse as seen on earth), the variation is consistent with models of neutron star structure. The optical data may be in conflict with the interpretation however. We found no statistically significant lines in the 50 - 550 keV range in the spectrum. The average 3 sigma upper limits in 10(exp -3) photons/sq cm/s for lines at 0.073, 0.078, 0.4, 0.44, 0.511, and 0.545 MeV are 0.3, 0.5, 0.6, 0.5, and 0.1.
Liver Fibrosis And NAS Scoring From CT Images Using Self-Supervised Learning And Texture Encoding

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver diseases (CLD) which can progress to liver cancer. The severity and treatment of NAFLD is determined by NAFLD Activity Scores (NAS) and liver fibrosis stage, which are usually obtained from liver biopsy. However, biopsy is invasive in nature and involves risk of procedural complications. Current methods to predict the fibrosis and NAS scores from noninvasive CT images rely heavily on either a large annotated dataset or transfer learning using pretrained networks. However, the availability of a large annotated dataset cannot be always ensured and there can be domain shifts when using transfer learning. In this work, we propose a self-supervised learning method to address both problems. As the NAFLD causes changes in the liver texture, we also propose to use texture encoded inputs to improve the performance of the model. Given a relatively small dataset with 30 patients, we employ a self-supervised network which achieves better performance than a network trained via transfer learning. The code is publicly available 1.
Where to locate COVID-19 mass vaccination facilities?

The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new Biden administration is launching mass vaccination sites across the country, raising the obvious question of where to locate these clinics to maximize the effectiveness of the vaccination campaign. This paper tackles this question with a novel data-driven approach to optimize COVID-19 vaccine distribution. We first augment a state-of-the-art epidemiological model, called DELPHI, to capture the effects of vaccinations and the variability in mortality rates across age groups. We then integrate this predictive model into a prescriptive model to optimize the location of vaccination sites and subsequent vaccine allocation. The model is formulated as a bilinear, nonconvex optimization model. To solve it, we propose a coordinate descent algorithm that iterates between optimizing vaccine distribution and simulating the dynamics of the pandemic. As compared to benchmarks based on demographic and epidemiological information, the proposed optimization approach increases the effectiveness of the vaccination campaign by an estimated 20%, saving an extra 4000 extra lives in the United States over a 3-month period. The proposed solution achieves critical fairness objectives—by reducing the death toll of the pandemic in several states without hurting others—and is highly robust to uncertainties and forecast errors—by achieving similar benefits under a vast range of perturbations.
Simple and fast derandomization from very hard functions: eliminating randomness at almost no cost

Extending the classical “hardness-to-randomness” line-of-works, Doron, Moshkovitz, Oh, and Zuckerman (FOCS 2020) recently proved that derandomization with near-quadratic time overhead is possible, under the assumption that there exists a function in DTIME[2n] that cannot be computed by randomized SVN circuits of size 2(1−є)· n for a small є. In this work we extend their inquiry and answer several open questions that arose from their work. For a time function T(n), consider the following assumption: Non-uniformly secure one-way functions exist, and for δ=δ(є) and k=kT(є) there exists a problem in DTIME[2k· n] that is hard for algorithms that run in time 2(k−δ)· n and use 2(1−δ)· n bits of advice. Under this assumption, we show that: 1. (Worst-case derandomization.) Probabilistic algorithms that run in time T(n) can be deterministically simulated in time n· T(n)1+є. 2. (Average-case derandomization.) For polynomial time functions T(n)=poly(n), we can improve the derandomization time to nє· T(n) if we allow the derandomization to succeed only on average, rather than in the worst-case. 3. (Conditional optimality.) For worst-case derandomization, the multiplicative time overhead of n is essentially optimal, conditioned on a counting version of the non-deterministic strong exponential-time hypothesis (i.e., on #NSETH). Lastly, we present an alternative proof for the result of Doron, Moshkovitz, Oh, and Zuckerman that is simpler and more versatile. In fact, we show how to simplify the analysis not only of their construction, but of any construction that “extracts randomness from a pseudoentropic string”.
Diffraction of the Aharonov–Bohm Hamiltonian

In this paper, we compute the diffractive wave propagator of the Aharonov–Bohm effect (Aharonov and Bohm, Phys Rev 115(3):485, 1959) on $${\mathbf {R}}^2$$ with a single solenoid using a technique of moving solenoid location. In addition, we compute the corresponding diffraction coefficient which is the principal symbol of the diffractive propagator. This paper proves the propagation of singularities of the Aharonov–Bohm Hamiltonian.
Stable subgroups and Morse subgroups in mapping class groups

For a finitely generated group, there are two recent generalizations of the notion of a quasiconvex subgroup of a word-hyperbolic group, namely a stable subgroup and a Morse or strongly quasiconvex...
Assessment of an unstructured-grid method for predicting 3-D turbulent viscous flows

A method Is presented for solving turbulent flow problems on three-dimensional unstructured grids. Spatial discretization Is accomplished by a cell-centered finite-volume formulation using an accurate lin- ear reconstruction scheme and upwind flux differencing. Time is advanced by an implicit backward- Euler time-stepping scheme. Flow turbulence effects are modeled by the Spalart-Allmaras one-equation model, which is coupled with a wall function to reduce the number of cells in the sublayer region of the boundary layer. A systematic assessment of the method is presented to devise guidelines for more strategic application of the technology to complex problems. The assessment includes the accuracy In predictions of skin-friction coefficient, law-of-the-wall behavior, and surface pressure for a flat-plate turbulent boundary layer, and for the ONERA M6 wing under a high Reynolds number, transonic, separated flow condition.
Plasma polymerization of an ethylene-nitrogen gas mixture

A procedure has been developed whereby nitrogen can be incorporated into an organic film from an ethylene-nitrogen gas mixture using an internal electrode capacitively coupled radio frequency reactor. The presence of nitrogen has been shown directly by infrared transmittance spectra and electron spectroscopic chemical analysis data, and further indirect evidence was provided by dielectric measurements and by the reverse osmosis properties of the film. Preparation of a nitrogen containing film did not require vapor from an organic nitrogen containing liquid monomer. Some control over the bonding and stoichiometry of the polymer film was provided by the added degree of freedom of the nitrogen partial pressure in the gas mixture. This new parameter strongly affected the dielectric properties of the plasma polymerized film and could affect the reverse osmosis behavior.
Shortest paths with a cost constraint: A probabilistic analysis

Abstract We consider a constrained version of the shortest path problem on the complete graphs whose edges have independent random lengths and costs. We establish the asymptotic value of the minimum length as a function of the cost-budget within a wide range.
Statistical Inference and Feasibility Determination: A Nonasymptotic Approach

We develop non-asymptotically justified methods for hypothesis testing about the $p-$dimensional coefficients $\theta^{*}$ in (possibly nonlinear) regression models. Given a function $h:\,\mathbb{R}^{p}\mapsto\mathbb{R}^{m}$, we consider the null hypothesis $H_{0}:\,h(\theta^{*})\in\Omega$ against the alternative hypothesis $H_{1}:\,h(\theta^{*})\notin\Omega$, where $\Omega$ is a nonempty closed subset of $\mathbb{R}^{m}$ and $h$ can be nonlinear in $\theta^{*}$. Our (nonasymptotic) control on the Type I and Type II errors holds for fixed $n$ and does not rely on well-behaved estimation error or prediction error; in particular, when the number of restrictions in $H_{0}$ is large relative to $p-n$, we show it is possible to bypass the sparsity assumption on $\theta^{*}$ (for both Type I and Type II error control), regularization on the estimates of $\theta^{*}$, and other inherent challenges in an inverse problem. We also demonstrate an interesting link between our framework and Farkas' lemma (in math programming) under uncertainty, which points to some potential applications of our method outside traditional hypothesis testing.
Identification of Utility-Scale Renewable Energy Penetration Threshold in a Dynamic Setting

Integration of renewable energy resources with the electric grid is necessary for a sustainable energy future. However, increased penetration of inverter based resources (IBRs) reduce grid inertia, which might then compromise power system reliability. Therefore, power utilities are often interested in identifying the maximum IBR penetration limit for their system. The proposed research presents a methodology to identify the IBR penetration threshold beyond which voltage, frequency, and tie-line limits will be exceeded. The sensitivity of the IBR penetration threshold to momentary cessation due to low voltages, transmission versus distribution connected solar generation, and stalling of induction motors are also analyzed. Dynamic simulation studies conducted on a 24,000-bus model of the Western Interconnection (WI) demonstrate the practicality of the proposed approach.
FAPIS: A Few-shot Anchor-free Part-based Instance Segmenter

This paper is about few-shot instance segmentation, where training and test image sets do not share the same object classes. We specify and evaluate a new few-shot anchor-free part-based instance segmenter (FAPIS). Our key novelty is in explicit modeling of latent object parts shared across training object classes, which is expected to facilitate our few-shot learning on new classes in testing. We specify a new anchor-free object detector aimed at scoring and regressing locations of foreground bounding boxes, as well as estimating relative importance of latent parts within each box. Also, we specify a new network for delineating and weighting latent parts for the final instance segmentation within every detected bounding box. Our evaluation on the benchmark COCO-20i dataset demonstrates that we significantly outperform the state of the art.
Chiral edge modes in Helmholtz-Onsager vortex systems

Low-energy point vortices in a two-dimensional domain accumulate at boundaries. The resulting statistical edge modes are robust, persisting in non-convex domains at large vortex numbers.
Discovering Multi-Hardware Mobile Models via Architecture Search

Hardware-aware neural architecture designs have been predominantly focusing on optimizing model performance on single hardware and model development complexity, where another important factor, model deployment complexity, has been largely ignored. In this paper, we argue that, for applications that may be deployed on multiple hardware, having different single-hardware models across the deployed hardware makes it hard to guarantee consistent outputs across hardware and duplicates engineering work for debugging and fixing. To minimize such deployment cost, we propose an alternative solution, multi-hardware models, where a single architecture is developed for multiple hardware. With thoughtful search space design and incorporating the proposed multi-hardware metrics in neural architecture search, we discover multi-hardware models that give state-of-the-art (SoTA) performance across multiple hardware in both average and worse case scenarios. For performance on individual hardware, the single multi-hardware model yields similar or better results than SoTA performance on accelerators like GPU, DSP and EdgeTPU which was achieved by different models, while having similar performance with MobilenetV3 Large Minimalistic model on mobile CPU. 1
Distribution Properties for t-Hooks in Partitions

Partitions, the partition function p(n), and the hook lengths of their Ferrers–Young diagrams are important objects in combinatorics, number theory, and representation theory. For positive integers n and t, we study $$p_t^\mathrm{e}(n)$$ (resp. $$p_t^\mathrm{o}(n)$$ ), the number of partitions of n with an even (resp. odd) number of t-hooks. We study the limiting behavior of the ratio $$p_t^\mathrm{e}(n)/p(n)$$ , which also gives $$p_t^\mathrm{o}(n)/p(n)$$ , since $$p_t^\mathrm{e}(n) + p_t^\mathrm{o}(n) = p(n)$$ . For even t, we show that $$\begin{aligned} \lim \limits _{n \rightarrow \infty } \dfrac{p_t^\mathrm{e}(n)}{p(n)} = \dfrac{1}{2}, \end{aligned}$$ and for odd t, we establish the non-uniform distribution $$\begin{aligned} \lim \limits _{n \rightarrow \infty } \dfrac{p^\mathrm{e}_t(n)}{p(n)} = {\left\{ \begin{array}{ll} \dfrac{1}{2} + \dfrac{1}{2^{(t+1)/2}} &{} \text {if } 2 \mid n, \\ \\ \dfrac{1}{2} - \dfrac{1}{2^{(t+1)/2}} &{} \text {otherwise.} \end{array}\right. } \end{aligned}$$ Using the Rademacher circle method, we find an exact formula for $$p_t^\mathrm{e}(n)$$ and $$p_t^\mathrm{o}(n)$$ , and this exact formula yields these distribution properties for large n. We also show that for sufficiently large n, the sign of $$p_t^\mathrm{e}(n) - p_t^\mathrm{o}(n)$$ is periodic.
Sequence-specific minimizers via polar sets.

MOTIVATION Minimizers are efficient methods to sample k-mers from genomic sequences that unconditionally preserve sufficiently long matches between sequences. Well-established methods to construct efficient minimizers focus on sampling fewer k-mers on a random sequence and use universal hitting sets (sets of k-mers that appear frequently enough) to upper bound the sketch size. In contrast, the problem of sequence-specific minimizers, which is to construct efficient minimizers to sample fewer k-mers on a specific sequence such as the reference genome, is less studied. Currently, the theoretical understanding of this problem is lacking, and existing methods do not specialize well to sketch specific sequences. RESULTS We propose the concept of polar sets, complementary to the existing idea of universal hitting sets. Polar sets are k-mer sets that are spread out enough on the reference, and provably specialize well to specific sequences. Link energy measures how well spread out a polar set is, and with it, the sketch size can be bounded from above and below in a theoretically sound way. This allows for direct optimization of sketch size. We propose efficient heuristics to construct polar sets, and via experiments on the human reference genome, show their practical superiority in designing efficient sequence-specific minimizers. AVAILABILITY AND IMPLEMENTATION A reference implementation and code for analyses under an open-source license are at https://github.com/kingsford-group/polarset. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Genetic architecture of floral traits in bee- and hummingbird-pollinated sister species of Aquilegia (columbine).

Interactions with animal pollinators have helped shape the stunning diversity of flower morphologies across the angiosperms. A common evolutionary consequence of these interactions is that some flowers have converged on suites of traits, or pollination syndromes, that attract and reward specific pollinator groups. Determining the genetic basis of these floral pollination syndromes can help us understand the processes that contributed to the diversification of the angiosperms. Here, we characterize the genetic architecture of a bee-to-hummingbird pollination shift in Aquilegia (columbine) using QTL mapping of 17 floral traits encompassing color, nectar composition, and organ morphology. In this system, we find that the genetic architectures underlying differences in floral color are quite complex, and we identify several likely candidate genes involved in anthocyanin and carotenoid floral pigmentation. Most morphological and nectar traits also have complex genetic underpinnings; however, one of the key floral morphological phenotypes, nectar spur curvature, is shaped by a single locus of large effect. This article is protected by copyright. All rights reserved.
Dual-energy CT imaging with limited-angular-range data.

In dual-energy computed tomography (DECT), low- and high-kVp data are collected often over a full-angular range (FAR) of 360○. While there exists strong interest in DECT with low- and high-kVp data acquired over limited-angular ranges (LARs), there remains little investigation of image reconstruction in DECT with LAR data. Objective: We investigate image reconstruction with minimized LAR artifacts from low- and high-kVp data over LARs of ≤180○ by using a directional-total-variation (DTV) algorithm. Methods: Image reconstruction from LAR data is formulated as a convex optimization problem in which data-l2 is minimized with constraints on image's DTVs along orthogonal axes. We then achieve image reconstruction by applying the DTV algorithm to solve the optimization problem. We conduct numerical studies from data generated over arcs of LARs, ranging from 14○ to 180○, and perform visual inspection and quantitative analysis of images reconstructed. Results: Monochromatic images of interest obtained with the DTV algorithm from LAR data show substantially reduced artifacts that are observed often in images obtained with existing algorithms. The improved image quality also leads to accurate estimation of physical quantities of interest, such as effective atomic number and iodine-contrast concentration. Conclusion: Our study reveals that from LAR data of low- and high-kVp, monochromatic images can be obtained that are visually, and physical quantities can be estimated that are quantitatively, comparable to those obtained in FAR DECT. Significance: As LAR DECT is of high practical application interest, the results acquired in the work may engender insights into the design of DECT with LAR scanning configurations of practical application significance.
Does Face Recognition Error Echo Gender Classification Error

This paper is the first to explore the question of whether images that are classified incorrectly by a face analytics algorithm (e.g., gender classification) are any more or less likely to participate in an image pair that results in a face recognition error. We analyze results from three different gender classification algorithms (one open-source and two commercial), and two face recognition algorithms (one open-source and one commercial), on image sets representing four demographic groups (African-American female and male, Caucasian female and male). For impostor image pairs, our results show that pairs in which one image has a gender classification error have a better impostor distribution than pairs in which both images have correct gender classification, and so are less likely to generate a false match error. For genuine image pairs, our results show that individuals whose images have a mix of correct and incorrect gender classification have a worse genuine distribution (increased false non-match rate) compared to individuals whose images consistently have correct gender classification. Thus, compared to images that generate correct gender classification, images with gender classification error have a lower false match rate and a higher false non-match rate.
Role of intercellular coupling and delay on the synchronization of genetic oscillators

Living cells encode diverse biological clocks for circadian timekeeping and formation of rhythmic structures during embryonic development. A key open question is how these clocks synchronize across cells through intercellular coupling mechanisms. To address this question, we leverage the classical motif for genetic clocks the Goodwin oscillator where a gene product inhibits its own synthesis via time-delayed negative feedback. More specifically, we consider an interconnected system of two identical Goodwin oscillators (each operating in a single cell), where state information is conveyed between cells via a signaling pathway whose dynamics is modeled as a first-order system. In essence, the interaction between oscillators is characterized by an intercellular coupling strength and an intercellular time delay that represents the signaling response time. Systematic stability analysis characterizes the parameter regimes that lead to oscillatory dynamics, with high coupling strength found to destroy sustained oscillations. Within the oscillatory parameter regime we find both in-phase and anti-phase oscillations with the former more likely to occur for small intercellular time delays. Finally, we consider the stochastic formulation of the model with low-copy number fluctuations in biomolecular components. Interestingly, stochasticity leads to qualitatively different behaviors where in-phase oscillations are susceptible to inherent fluctuations but not the anti-phase oscillations. In the context of the segmentation clock, such synchronized in-phase oscillations between cells are critical for the proper generation of repetitive segments during embryo development that eventually leads to the formation of the vertebral column.
Assessment and Comparison of Two Different Methods to Extract Nucleic Acids From Individual Honey Bees

The honey bee is an excellent model system to study behavior ecology, behavioral genetics, and sociogenomics. Nucleic acid based analyses enable a broad scope of research in functional genomics, disease diagnostics, mutant screening, and genetic breeding. Multiple levels of analysis lead to a more comprehensive understanding of the causes of phenotypic variation by integrating genomic variation, transcriptomic profiles, and epigenomic information. One limitation, however, is the sample preparation procedures to obtain high quality DNA and RNA simultaneously, particularly from small amounts of material, such as tissues of individual bees. We demonstrate that it is feasible to perform dual extractions of DNA and RNA from a single individual bee and compare the quality and quantity of the extracted nucleic acids using two different types of methods (column based versus ethanol precipitation). We obtained a higher yield of both DNA and RNA with one of the extraction methods over the other, although the quality of the DNA and RNA was not significantly different between methods. We describe here the first validated method for dual extraction of DNA and RNA specifically from individual honey bees.
Zero-Error Tracking for Autonomous Vehicles through Epsilon-Trajectory Generation

This paper presents a control method for vehicles with first-order nonholonomic constraints that guarantees asymptotic convergence to a time-indexed trajectory. To overcome the nonholonomic constraint, a fixed point in front of the vehicle can be controlled to track a desired trajectory, albeit with a steady-state error. To eliminate steady state error, a sufficiently smooth trajectory is reformulated for the new reference point such that, when tracking the new trajectory, the vehicle asymptotically converges to the original trajectory. The results of the control method are evaluated to view the effects of errors due to estimation and initial conditions.
Wake-foil interactions and energy harvesting efficiency in tandem oscillating foils

Oscillating foils in synchronized pitch and heave motion can harvest hydrokinetic energy while leaving behind a distinct trail of alternating signed vortices. This work correlates the specific foil kinematics (frequency, pitch, and heave amplitude) with the resulting wake structure by defining three modes within the energy harvesting kinematic regime. Using an array of two tandem oscillating foils, the performance of the trailing foil is modeled by analyzing the wake between the two oscillating foils. The resulting efficiency of the trailing foil is redefined by accounting for the steady and unsteady components of the local flow, yielding a closer match to the single foil efficiency curve.
Understanding the Effects of Dielectric Property, Separation Distance, and Band Alignment on Interlayer Excitons in 2D Hybrid MoS2/WSe2 Heterostructures

Two dimensional (2D) van der Waals heterostructures from transition metal dichalcogenide (TMDC) semiconductors show a new class of spatially separate excitons with extraordinary properties. The interlayer excitons (XI) have been studied extensively, yet the mechanisms that modulate XI are still not well understood. Here, we introduce several organic-layer-embedded hybrid heterostructures, MoS2/organic/WSe2, to study the binding energy of XI. We discover that the dielectric screening of the quasi-particle is reduced with organic molecules due to decreased dielectric constant and greater separation distance between the TMDC layers. As a result, a distinct blueshift is observed in interlayer emission. We also find that the band alignment at the heterointerface is critical. When the organic layer provides a staggered energy state, interlayer charge transfer can transition from tunneling to band-assisted transfer, further increasing XI emission energies due to a stronger dipolar interaction. The formation of XI may also be significantly suppressed with electron or hole trapping molecules. These findings should be useful in realizing XI-based optoelectronics.
RepairSig: Deconvolution of DNA damage and repair contributions to the mutational landscape of cancer

Summary Cancer genomes accumulate a large number of somatic mutations resulting from a combination of stochastic errors in DNA processing, cancer-related aberrations of the DNA repair machinery, or carcinogenic exposures; each mutagenic process leaves a characteristic mutational signature. A key challenge is understanding the interactions between signatures, particularly as DNA repair deficiencies often modify the effects of other mutagens. Here, we introduce RepairSig, a computational method that explicitly models additive primary mutagenic processes; non-additive secondary processes, which interact with the primary processes; and a mutation opportunity, that is, the distribution of sites across the genome that are vulnerable to damage or preferentially repaired. We demonstrate that RepairSig accurately recapitulates experimentally identified signatures, identifies autonomous signatures of deficient DNA repair processes, and explains mismatch repair deficiency in breast cancer by de novo inference of both primary and secondary signatures from patient data. RepairSig is freely available for download at https://github.com/ncbi/RepairSig .
Household expectations and the release of macroeconomic statistics

Abstract Households were surveyed in the days immediately before and after the June release of the Consumer Price Index (CPI). The CPI release was associated with an 11 percentage point increase in the likelihood that a respondent heard news about inflation, with a larger increase for highly-numerate respondents. Inflation expectations only of highly-numerate respondents rose with the CPI release.
Bariatric Surgery is Safe for Patients After Recovery from COVID-19.

Abstract Background Studies of patients who have undergone surgery while infected with COVID-19 have shown increased risks for adverse outcomes in both pulmonary complications and mortality. It has become clear that the risk of complications from perioperative COVID-19 infection must be weighed against the risk from delayed surgical treatment. Studies have also shown that prior bariatric surgery conveys protection against mortality from COVID-19 and that obesity is the biggest risk factor for mortality from COVID-19 infection in adults under 45 years of age. Studies in patients who have fully recovered from COVID-19 and underwent elective surgery have not become widely available yet. Objectives This multi-institutional case series is presented to highlight patients who developed COVID-19, fully recovered, and subsequently underwent elective bariatric surgery with 30-day outcomes available. Setting Nine bariatric surgery centers located across the United States. Methods This multicenter case series is a retrospective chart review of patients who developed COVID-19, recovered, and subsequently underwent bariatric surgery. Fifty-three patients are included, and 30-day morbidity and mortality were analyzed. Results Thirty-day complications included esophageal spasm, dehydration, and ileus. There were no cardiovascular, venous thromboembolism (VTE) or respiratory events reported. There were no 30- day mortalities. Conclusions Bariatric surgery has been safely performed in patients who made a full recovery from COVID-19 without increased complications due to cardiovascular, pulmonary, venous thromboembolism, or increased mortality rates.
TAPER: Pinpointing errors in multiple sequence alignments despite varying rates of evolution

Erroneous data can creep into sequence datasets for reasons ranging from contamination to annotation and alignment mistakes. These errors can reduce the accuracy of downstream analyses such as tree inference and will diminish the confidence of the community in the results even when they do not impact the analysis. As datasets keep getting larger, it has become difficult to visually check for errors, and thus, automatic error detection methods are needed more than ever before. Alignment masking methods, which are widely used, completely remove entire aligned sites. Therefore, they may reduce signal as much as or more than they reduce the noise. An alternative is designing targeted methods that look for errors in small species-specific stretches of the alignment by detecting outliers. Crucially, such a method should attempt to distinguish the real heterogeneity, which includes signal, from errors. This type of error filtering is surprisingly under-explored. In this paper, we introduce TAPER, an automatic algorithm that looks for small stretches of error in sequence alignments. Our results show that TAPER removes very little data yet finds much of the error and cleans up the alignments.
A Conventional Liner Acoustic/Drag Interaction Benchmark Database

The aerodynamic drag of acoustic liners has become a significant topic in the design of such for aircraft noise applications. In order to evaluate the benefits of concepts designed to reduce liner drag, it is necessary to establish the baseline performance of liners employing the typical design features of conventional configurations. This paper details a set of experiments in the NASA Langley Grazing Flow Impedance Tube to quantify the relative drag of a number of perforate-over-honeycomb liner configurations at flow speeds of M=0.3 and 0.5. These conventional liners are investigated to determine their resistance factors using a static pressure drop approach. Comparison of the resistance factors gives a relative measurement of liner drag. For these same flow conditions, acoustic measurements are performed with tonal excitation from 400 to 3000 Hz at source sound pressure levels of 140 and 150 dB. Educed impedance and attenuation spectra are used to determine the interaction between acoustic performance and drag.
Control of Plasmons in Topological Insulators via Local Perturbations

We use a fully quantum mechanical approach to demonstrate control of plasmonic excitations in prototype models of topological insulators by molecule-scale perturbations. Strongly localized surface plasmons are present in the host systems, arising from the topologically nontrivial single-particle edge states. A numerical evaluation of the random phase approximation equations for the perturbed systems reveals how the positions and the internal electronic structure of the added molecules affect the degeneracy of the locally confined collective excitations, i.e., shifting the plasmonic energies of the host system and changing their spatial charge density profile. In particular, we identify conditions under which significant charge transfer from the host system to the added molecules occurs. Furthermore, the induced field energy density in the perturbed topological systems due to external electric fields is determined.