cssi/SciSciGPT-SciSciNet huggingface dataset:
Bond Strengths in ChCl3-and ChOCl3-(Ch = S, Se, Te): Experiment and Theory

The strengths of the SeCl2−Cl-, SeOCl2−Cl-, SeBr2−Br-, and TeCl2−Cl- bonds have been measured to be 133 ± 9, 150 ± 10, 110 ± 6, and 170 ± 7 kJ mol-1, respectively, by determining thresholds for collision-induced dissociation in a flowing afterglow-tandem mass spectrometer. These values are stronger than the previously measured D(SCl2−Cl-) and D(SOCl2−Cl-), both 85 ± 8 kJ mol-1. Bond energies and other properties for these molecules and TeOCl3- have also been computed by several high-level computational techniques, including B3LYP/aug-cc-pVTZ. There is excellent agreement between the experimental and computational energetics for SeCl3-, SeOCl3-, and TeCl3-. The bond strengths increase in the order S < Se < Te.
Predicting evolutionarily stable strategies from functional responses of Sonoran Desert annuals to precipitation

For many decades, researchers have studied how plants use bet-hedging strategies to insure against unpredictable, unfavourable conditions. We improve upon earlier analyses by explicitly accounting for how variable precipitation affects annual plant species' bet-hedging strategies. We consider how the survival rates of dormant seeds (in a 'seed bank') interact with precipitation responses to influence optimal germination strategies. Specifically, we incorporate how response to resource availability (i.e. the amount of offspring (seeds) generated per plant in response to variation in desert rainfall) influences the evolution of germination fractions. Using data from 10 Sonoran Desert annual plants, we develop models that explicitly include these responses to model fitness as a function of precipitation. For each of the species, we identify the predicted evolutionarily stable strategies (ESSs) for the fraction of seeds germinating each year and then compare our estimated ESS values to the observed germination fractions. We also explore the relative importance of seed survival and precipitation responses in shaping germination strategies by regressing ESS values and observed germination fractions against these traits. We find that germination fractions are lower for species with higher seed survival, with lower reproductive success in dry years, and with better yield responses in wet years. These results illuminate the evolution of bet-hedging strategies in an iconic system, and provide a framework for predicting how current and future environmental conditions may reshape those strategies.
Two comparisons of the performance of positional scanning and deletion synthesis for the identification of active constituents in mixture combinatorial libraries.

Two libraries of 120 compounds each were prepared as individual compounds and as full mixtures. The corresponding scanning and deletion synthesis deconvolution libraries were prepared and tested (L-1210, IC50) alongside the individual compounds and mixture libraries. This testing, where the properties of each compound in the mixtures were known, was used to compare the performance of scanning and deletion deconvolution libraries. Each has its own intrinsic strengths, with the former being capable of identifying multiple hits at the expense of accurately identifying the most potent library member, while the latter typically is more sensitive to identifying the most potent hit but at the expense of differentiating weaker activities. The protocols complement one another and together more thoroughly identify potent library members.
Structure revision of the APHEs through synthesis

An attempt to synthesize APHE-3 (3-methylpyrazolo[1,5-b]isoquinolin-9(1H)-one, 3) gave the tautomer 3-methylpyrazolo[1,5-b]isoquinolin-9(4H)-one (9) instead, and led to a reconsideration of the structures assigned to the APHEs. The structures of the APHEs have now been reformulated as 15–18, known natural products, whose spectra are in close agreement with those reported for the APHEs.
Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats.

Background Resistant starch is a prebiotic metabolized by the gut bacteria. It has been shown to attenuate chronic kidney disease (CKD) progression in rats. Previous studies employed taxonomic analysis using 16S rRNA sequencing and untargeted metabolomics profiling. Here we expand these studies by metaproteomics, gaining new insight into the host-microbiome interaction.
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data

What learning algorithms can be run directly on compressively-sensed data? In this work, we consider the question of accurately and efficiently computing low-rank matrix or tensor factorizations given data compressed via random projections. We examine the approach of first performing factorization in the compressed domain, and then reconstructing the original high-dimensional factors from the recovered (compressed) factors. In both the matrix and tensor settings, we establish conditions under which this natural approach will provably recover the original factors. While it is well-known that random projections preserve a number of geometric properties of a dataset, our work can be viewed as showing that they can also preserve certain solutions of non-convex, NP-Hard problems like non-negative matrix factorization. We support these theoretical results with experiments on synthetic data and demonstrate the practical applicability of compressed factorization on real-world gene expression and EEG time series datasets.
Stereocontrolled synthesis of syn- and anti-diol epoxide metabolites of triphenylene

The synthesis of both syn- and anti-diol epoxide metabolites of triphenylene has been achieved under complete stereochemical control commencing with commercially available 9-phenanthrol in 18% (9 steps) and 37% (8 steps) overall yields, respectively. The exceptionally high stereoselectivity of the dimethyldioxirane oxidation of trans-dihydrodiol having the quasi-diaxially disposed hydroxyl groups is particularly noteworthy.
Selection Signatures Underlying Dramatic Male Inflorescence Transformation During Modern Hybrid Maize Breeding

Inflorescence capacity plays a crucial role in reproductive fitness in plants, and in production of hybrid crops. Maize is a monoecious species bearing separate male and female flowers (tassel and ear, respectively). The switch from open-pollinated populations of maize to hybrid-based breeding schemes in the early 20th century was accompanied by a dramatic reduction in tassel size, and the trend has continued with modern breeding over the recent decades. The goal of this study was to identify selection signatures in genes that may underlie this dramatic transformation. Using a population of 942 diverse inbred maize accessions and a nested association mapping population comprising three 200-line biparental populations, we measured 15 tassel morphological characteristics by manual and image-based methods. Genome-wide association studies identified 242 single nucleotide polymorphisms significantly associated with measured traits. We compared 41 unselected lines from the Iowa Stiff Stalk Synthetic (BSSS) population to 21 highly selected lines developed by modern commercial breeding programs, and found that tassel size and weight were reduced significantly. We assayed genetic differences between the two groups using three selection statistics: cross population extended haplotype homozogysity, cross-population composite likelihood ratio, and fixation index. All three statistics show evidence of selection at genomic regions associated with tassel morphology relative to genome-wide null distributions. These results support the tremendous effect, both phenotypic and genotypic, that selection has had on maize male inflorescence morphology.
Calorimetric measurement of the kinetics of slow reactions

A brief review of the application of calorimetry to measurement of the kinetics of slow processes is presented. Processes degrading or otherwise changing the properties of materials often occur too slowly to be readily measured by conventional chemical analyses but can be measured in a relatively short period of time by heat conduction calorimetry. Instrument selection and derivation of rate laws from calorimetric data are discussed, and illustrative examples are presented.
The synthesis of geminal diphosphonates via phenyl selenide transfer radical addition

Abstract Geminal diphosphonates have been synthesized through the photochemical radical addition of tetraethyl phenylselenomethylenediphosphonate to a variety of monosubstituted alkenes.
Convolutional Dictionary Learning: A Comparative Review and New Algorithms

Convolutional sparse representations are a form of sparse representation with a dictionary that has a structure that is equivalent to convolution with a set of linear filters. While effective algorithms have recently been developed for the convolutional sparse coding problem, the corresponding dictionary learning problem is substantially more challenging. Furthermore, although a number of different approaches have been proposed, the absence of thorough comparisons between them makes it difficult to determine which of them represents the current state of the art. The present work both addresses this deficiency and proposes some new approaches that outperform existing ones in certain contexts. A thorough set of performance comparisons indicates a very wide range of performance differences among the existing and proposed methods, and clearly identifies those that are the most effective.
A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

Abnormal activity of cyclin-dependent kinase 8 (CDK8) along with its partner protein cyclin C (CycC) is a common feature of many diseases including colorectal cancer. Using molecular dynamics (MD) simulations, this study determined the dynamics of the CDK8-CycC system and we obtained detailed breakdowns of binding energy contributions for four type-I and five type-II CDK8 inhibitors. We revealed system motions and conformational changes that will affect ligand binding, confirmed the essentialness of CycC for inclusion in future computational studies, and provide guidance in development of CDK8 binders. We employed unbiased all-atom MD simulations for 500 ns on twelve CDK8-CycC systems, including apoproteins and protein–ligand complexes, then performed principal component analysis (PCA) and measured the RMSF of key regions to identify protein dynamics. Binding pocket volume analysis identified conformational changes that accompany ligand binding. Next, H-bond analysis, residue-wise interaction calculations, and MM/PBSA were performed to characterize protein–ligand interactions and find the binding energy. We discovered that CycC is vital for maintaining a proper conformation of CDK8 to facilitate ligand binding and that the system exhibits motion that should be carefully considered in future computational work. Surprisingly, we found that motion of the activation loop did not affect ligand binding. Type-I and type-II ligand binding is driven by van der Waals interactions, but electrostatic energy and entropic penalties affect type-II binding as well. Binding of both ligand types affects protein flexibility. Based on this we provide suggestions for development of tighter-binding CDK8 inhibitors and offer insight that can aid future computational studies.
Genome-Wide Transcriptional Response to Varying RpoS Levels in Escherichia coli K-12.

The alternative sigma factor RpoS is a central regulator of many stress responses in Escherichia coli. The level of functional RpoS differs depending on the stress. The effect of these differing concentrations of RpoS on global transcriptional responses remains unclear. We investigated the effect of RpoS concentration on the transcriptome during stationary phase in rich media. We found that 23% of genes in the E. coli genome are regulated by RpoS, and we identified many RpoS-transcribed genes and promoters. We observed three distinct classes of response to RpoS by genes in the regulon: genes whose expression changes linearly with increasing RpoS level, genes whose expression changes dramatically with the production of only a little RpoS (“sensitive” genes), and genes whose expression changes very little with the production of a little RpoS (“insensitive”). We show that sequences outside the core promoter region determine whether an RpoS-regulated gene is sensitive or insensitive. Moreover, we show that sensitive and insensitive genes are enriched for specific functional classes and that the sensitivity of a gene to RpoS corresponds to the timing of induction as cells enter stationary phase. Thus, promoter sensitivity to RpoS is a mechanism to coordinate specific cellular processes with growth phase and may also contribute to the diversity of stress responses directed by RpoS.
Synthesis of highly substituted 1,3-dienes, 1,3,5-trienes, and 3,6-disubstituted cyclohexenes by the palladium-catalyzed coupling of organic halides, internal alkynes or 1,3-cyclohexadienes, and organoboranes

A number of highly substituted 1,3-dienes and 1,3,5-trienes have been stereoselectively prepared in moderate to good yields by the coupling of vinylic iodides, internal alkynes, and organoboranes in the presence of a palladium catalyst. Optimal reaction conditions for different organoboron substrates have been developed. The analogous three-component coupling of aryl halides, 1,3-cyclohexadiene, and boronic acids provides a synthetically useful route to 3,6-disubstituted cyclohexenes. These methods are very efficient and provide an expeditious way to synthesize the indicated alkenes, dienes, and trienes, whose preparation would normally require multi-step synthesis.
A DIRECT SYNTHESIS OF AFLATOXIN M2

A six-step synthesis of aflatoxin M2 starting from 1,3,5-trimethoxybenzene is described. The key step is the addition of dichloromethyllithium.
Models of the Bis-Histidine-Ligated Electron-Transferring Cytochromes. Comparative Geometric and Electronic Structure of Low-Spin Ferro- and Ferrihemes

The word “cytochrome” was coined more than 100 years ago, in 1884 by McMunn, to describe the colored substances in cells.1 Later, many of these “cytochromes” were found to contain hemes, that is to say, porphyrins complexed to iron.2,3 The cytochromes a, b, c, d, f, and o are heme proteins that are involved in electron transfer; the iron cycles between Fe(III) and Fe(II) to allow the transfer of electrons from and to the redox cofactors of each of these cytochromes. The letter names in general are indicative of a common set of substituents on the periphery of the heme that give rise to particular optical spectral features when complexed to pyridine in their reduced (Fe(II)) state, sometimes called the “pyridine hemochrome” spectra. The names (heme a, b, c, d, d1, o) are very old, and in some cases how they arose defies explanation. Only cytochromes c have the heme covalently attached to the protein, although in recent years a number of cases of modified hemes having unique types of covalent attachments to their proteins and unique spectral features have been reported. The heme of cytochrome f is a c hemesit is the axial ligands that give cytochrome f its particular spectroscopic features. Another class of proteins that carries the name “cytochrome” is that of the enzymes called the cytochromes P450. These enzymes are monooxygenases that insert one atom of a dioxygen molecule into a substrate that is often, but not always, an organic molecule (including steroids, unsaturated hydrocarbons (to produce epoxides), xenobiotics, and a very * E-mail: awalker@u.arizona.edu. Tel.: (520) 621-8645. Fax: (520) 626-9300. 589 Chem. Rev. 2004, 104, 589−615
Synthesis of Nonracemic Dimethyl α-(Hydroxyfarnesyl)phosphonates via Oxidation of Dimethyl Farnesylphosphonate with (Camphorsulfonyl)oxaziridines

Several strategies for synthesis of nonracemic dimethyl α-(hydroxyfarnesyl)phosphonate and the parent phosphonic acid have been explored. Separation of diastereomeric derivatives prepared by esterification of racemic α-hydroxy phosphonate with (S)-(+)-O-methylmandelic acid was possible, and these diastereomers could be assigned absolute stereochemistry on the basis of literature precedent. However, hydrolysis to the α-hydroxy phosphonic acid was accompanied by extensive isomerization. Addition of a nonracemic phosphonamidite to farnesal also gave nonracemic material, but again hydrolysis was problematic. Oxidation of dimethyl farnesylphosphonate anion with nonracemic (camphorsulfonyl)oxaziridines was shown to be regio- and stereoselective for formation of the α-hydroxy phosphonate. Enantiomeric excess of ∼70% ee was established by conversion of the oxidation products to their (S)-(+)-O-methylmandelate derivatives. Although hydrolysis of these methyl esters was accompanied by extensive racemization, both e...
Recent Progress in Lattice QCD Thermodynamics

This review gives a critical assessment of the current state of lattice simulations of QCD thermodynamics and what it teaches us about hot hadronic matter. It outlines briefly lattice methods for studying QCD at nonzero temperature and zero baryon number density with particular emphasis on assessing and reducing cutoff effects. It discusses a variety of difficulties with methods for determining the transition temperature. It uses results reported recently in the literature and at this conference for illustration, especially those from a major study carried out by the HotQCD collaboration.
Chern classes and the periods of mirrors

We show how Chern classes of a Calabi Yau hypersurface in a toric Fano manifold can be expressed in terms of the holomorphic at a maximal degeneracy point period of its mirror. We also consider the relation between Chern classes and the periods of mirrors for complete intersections in Grassmanian Gr(2,5).
Computational Insights into Avidity of Polymeric Multivalent Binders

Multivalent binding interactions are commonly found throughout biology to enhance weak monovalent binding such as between glycoligands and protein receptors. Designing multivalent polymers to bind to viruses and toxic proteins is a promising avenue for inhibiting their attachment and subsequent infection of cells. Several studies have focused on oligomeric multivalent inhibitors and how changing parameters such as ligand shape, size, linker length, and flexibility affect binding. However, experimental studies of how larger structural parameters of multivalent polymers, such as degree of polymerization, affect binding avidity to targets have mixed results, with some finding an improvement with longer polymers and some finding no effect. Here, we use Brownian dynamics simulations to provide a theoretical understanding of how the degree of polymerization affects the binding avidity of multivalent polymers. We show that longer polymers increase binding avidity to multivalent targets but reach a limit in binding avidity at high degrees of polymerization. We also show that when interacting with multiple targets simultaneously, longer polymers are able to use intertarget interactions to promote clustering and improve binding efficiency. We expect our results to narrow the design space for optimizing the structure and effectiveness of multivalent inhibitors as well as be useful to understand biological design strategies for multivalent binding.
Detecting Weak but Hierarchically-Structured Patterns in Networks

The ability to detect weak distributed activation patterns in networks is critical to several applications, such as identifying the onset of anomalous activity or incipient congestion in the Internet, or faint traces of a biochemical spread by a sensor network. This is a challenging problem since weak distributed patterns can be invisible in per node statistics as well as a global networkwide aggregate. Most prior work considers situations in which the activation/non-activation of each node is statistically independent, but this is unrealistic in many problems. In this paper, we consider structured patterns arising from statistical dependencies in the activation process. Our contributions are three-fold. First, we propose a sparsifying transform that succinctly represents structured activation patterns that conform to a hierarchical dependency graph. Second, we establish that the proposed transform facilitates detection of very weak activation patterns that cannot be detected with existing methods. Third, we show that the structure of the hierarchical dependency graph governing the activation process, and hence the network transform, can be learnt from very few (logarithmic in network size) independent snapshots of network activity.
Quantum groups, quantum tori, and the Grothendieck–Springer resolution

Abstract We construct an algebra embedding of the quantum group U q ( g ) into a central extension of the quantum coordinate ring O q [ G w 0 , w 0 / H ] of the reduced big double Bruhat cell in G. This embedding factors through the Heisenberg double H q of the quantum Borel subalgebra U ≥ 0 , which we relate to O q [ G ] via twisting by the longest element of the quantum Weyl group. Our construction is inspired by the Poisson geometry of the Grothendieck–Springer resolution studied in [10] , and the quantum Beilinson–Bernstein theorem investigated in [2] and [36] .
Band Assignment in Dual Band Systems: A Learning-Based Approach

We consider the band assignment problem in dual band systems, where the base-station (BS) chooses one of the two available frequency bands (centimeter-wave and millimeterwave bands) to communicate data to the mobile station (MS). While the millimeter-wave band offers higher data rate when it is available, there is a significant probability of outage during which the communication should be carried on the centimeter-wave band. In this work, we use a machine learning framework to provide an efficient and practical solution to the band assignment problem. In particular, the BS trains a Neural Network (NN) to predict the right band assignment decision using observed channel information. We study the performance of the NN in two environments: (i) A stochastic channel model with correlated bands, and (ii) microcellular outdoor channels obtained by simulations with a commercial ray-tracer. For the former case, for sake of comparison we also develop a threshold based band assignment that relies on the optimal mean square error estimator of the best band. In addition, we study the performance of the NN-based solution with different NN structures and different observed parameters (position, field strength, etc.). We compare the achieved performance to linear and logistic regression based solutions as well as the threshold based solution. Under practical constraints, the learning based band assignment shows competitive or superior performance in both environments.
Extended de Finetti theorems for boolean independence and monotone independence

We construct several new spaces of quantum sequences and their quantum families of maps in sense of Soltan. Then, we introduce noncommutative distributional symmetries associated with these quantum maps and study simple relations between them. We will focus on studying two kinds of noncommutative distributional symmetries: monotone spreadability and boolean spreadability. We provide an example of a spreadable sequence of random variables for which the usual unilateral shift is an unbounded map. As a result, it is natural to study bilateral sequences of random objects, which are indexed by integers, rather than unilateral sequences. In the end of the paper, we will show Ryll-Nardzewski type theorems for monotone independence and boolean independence: Roughly speaking, an infinite bilateral sequence of random variables is monotonically(boolean) spreadable if and only if the variables are identically distributed and monotone(boolean) with respect to the conditional expectation onto its tail algebra. For an infinite sequence of noncommutative random variables, boolean spreadability is equivalent to boolean exchangeability.
Unsupervised Learning for Surgical Motion by Learning to Predict the Future

We show that it is possible to learn meaningful representations of surgical motion, without supervision, by learning to predict the future. An architecture that combines an RNN encoder-decoder and mixture density networks (MDNs) is developed to model the conditional distribution over future motion given past motion. We show that the learned encodings naturally cluster according to high-level activities, and we demonstrate the usefulness of these learned encodings in the context of information retrieval, where a database of surgical motion is searched for suturing activity using a motion-based query. Future prediction with MDNs is found to significantly outperform simpler baselines as well as the best previously-published result for this task, advancing state-of-the-art performance from an F1 score of \(0.60 \pm 0.14\) to \(0.77 \pm 0.05\).
A Copy-Augmented Sequence-to-Sequence Architecture Gives Good Performance on Task-Oriented Dialogue

Task-oriented dialogue focuses on conversational agents that participate in dialogues with user goals on domain-specific topics. In contrast to chatbots, which simply seek to sustain open-ended meaningful discourse, existing task-oriented agents usually explicitly model user intent and belief states. This paper examines bypassing such an explicit representation by depending on a latent neural embedding of state and learning selective attention to dialogue history together with copying to incorporate relevant prior context. We complement recent work by showing the effectiveness of simple sequence-to-sequence neural architectures with a copy mechanism. Our model outperforms more complex memory-augmented models by 7% in per-response generation and is on par with the current state-of-the-art on DSTC2, a real-world task-oriented dialogue dataset.
Symmetry problems 2

Some symmetry problems are formulated and solved. New simple proofs are given for some symmetry problems studied earlier. One of the results is as follows: if a single-layer potential of a surface, homeomorphic to a sphere, with a constant charge density, is equal to c=jxj for all suciently large jxj, where c > 0 is a constant, then the surface is a sphere.
On the heteroclinic connection problem for multi-well gradient systems

Abstract We revisit the existence problem of heteroclinic connections in R N associated with Hamiltonian systems involving potentials W : R N → R having several global minima. Under very mild assumptions on W we present a simple variational approach to first find geodesics minimizing length of curves joining any two of the potential wells, where length is computed with respect to a degenerate metric having conformal factor W . Then we show that when such a minimizing geodesic avoids passing through other wells of the potential at intermediate times, it gives rise to a heteroclinic connection between the two wells. This work improves upon the approach of [22] and represents a more geometric alternative to the approaches of e.g. [5] , [10] , [14] , [17] for finding such connections.
Inhomogeneous hypergraph clustering with applications

Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics. A widely used method for hypergraph partitioning relies on minimizing a normalized sum of the costs of partitioning hyperedges across clusters. Algorithmic solutions based on this approach assume that different partitions of a hyperedge incur the same cost. However, this assumption fails to leverage the fact that different subsets of vertices within the same hyperedge may have different structural importance. We hence propose a new hypergraph clustering technique, termed inhomogeneous hypergraph partitioning, which assigns different costs to different hyperedge cuts. We prove that inhomogeneous partitioning produces a quadratic approximation to the optimal solution if the inhomogeneous costs satisfy submodularity constraints. Moreover, we demonstrate that inhomogenous partitioning offers significant performance improvements in applications such as structure learning of rankings, subspace segmentation and motif clustering.
Asymptotics of the maximal and the typical dimensions of isotypic components of tensor representations of the symmetric group

Vershik and Kerov gave asymptotical bounds for the maximal and the typical dimensions of irreducible representations of symmetric groups S n . It was conjectured by Olshanski that the maximal and the typical dimensions of the isotypic components of tensor representations of the symmetric group admit similar asymptotical bounds. The main result of this article is the proof of this conjecture. Consider the natural representation of S n on ( C N ) � n . Its isotypic components are parametrized by Young diagrams with n cells and at most N rows. Biane found the limit shape of Young diagrams when n � ∞ , n / N � c . By showing that this limit shape is the unique solution to a variational problem, it is proven here, that after scaling, the maximal and the typical dimensions of isotypic components lie between positive constants. A new proof of Biane's limit-shape theorem is obtained.
WELL-POSEDNESS FOR THE EULER–NORDSTRÖM SYSTEM WITH COSMOLOGICAL CONSTANT

In this paper, the author considers the motion of a relativistic perfect fluid with self-interaction mediated by Nordstrom's scalar theory of gravity. The evolution of the fluid is determined by a quasilinear hyperbolic system of PDEs, and a cosmological constant is introduced in order to ensure the existence of nonzero constant solutions. Accordingly, the initial value problem for a compact perturbation of an infinitely extended quiet fluid is studied. Although the system is neither symmetric hyperbolic nor strictly hyperbolic, Christodoulou's constructive results on the existence of energy currents for equations derivable from a Lagrangian can be adapted to provide energy currents that can be used in place of the standard energy principle available for first-order symmetric hyperbolic systems. After providing such energy currents, the author uses them to prove that the Euler–Nordstrom system with a cosmological constant is well-posed in a suitable Sobolev space.
Devising superconvergent HDG methods with symmetric approximate stresses for linear elasticity by M-decompositions

We propose a new tool, which we call $M$-decompositions, for devising superconvergent hybridizable discontinuous Galerkin (HDG) methods and hybridized-mixed methods for linear elasticity with strongly symmetric approximate stresses on unstructured polygonal/polyhedral meshes. We show that for an HDG method, when its local approximation space admits an $M$-decomposition, optimal convergence of the approximate stress and superconvergence of an element-by-element postprocessing of the displacement field are obtained. The resulting methods are locking-free. Moreover, we explicitly construct approximation spaces that admit $M$-decompositions on general polygonal elements. We display numerical results on triangular meshes validating our theoretical findings.
Univalence for inverse EI diagrams

We construct a new model category presenting the homotopy theory of presheaves on "inverse EI $(\infty,1)$-categories", which contains universe objects that satisfy Voevodsky's univalence axiom. In addition to diagrams on ordinary inverse categories, as considered in previous work of the author, this includes a new model for equivariant algebraic topology with a compact Lie group of equivariance. Thus, it offers the potential for applications of homotopy type theory to equivariant homotopy theory.
Maximized exoEarth candidate yields for starshades

The design and scale of a future mission to directly image and characterize potentially Earth-like planets will be impacted, to some degree, by the expected yield of such planets. Recent efforts to increase the estimated yields, by creating observation plans optimized for the detection and characterization of Earth-twins, have focused solely on coronagraphic instruments; starshade-based missions could benefit from a similar analysis. Here we explore how to prioritize observations for a starshade given the limiting resources of both fuel and time, present analytic expressions to estimate fuel use, and provide efficient numerical techniques for maximizing the yield of starshades. We implemented these techniques to create an approximate design reference mission code for starshades and used this code to investigate how exoEarth candidate yield responds to changes in mission, instrument, and astrophysical parameters for missions with a single starshade. We find that a starshade mission operates most efficiently somewhere between the fuel- and exposuretime-limited regimes and, as a result, is less sensitive to photometric noise sources as well as parameters controlling the photon collection rate in comparison to a coronagraph. We produced optimistic yield curves for starshades, assuming our optimized observation plans are schedulable and future starshades are not thrust-limited. Given these yield curves, detecting and characterizing several dozen exoEarth candidates requires either multiple starshades or an ηEarth≳0.3.
Sparse Feature Selection in Kernel Discriminant Analysis via Optimal Scoring

We consider the two-group classification problem and propose a kernel classifier based on the optimal scoring framework. Unlike previous approaches, we provide theoretical guarantees on the expected risk consistency of the method. We also allow for feature selection by imposing structured sparsity using weighted kernels. We propose fully-automated methods for selection of all tuning parameters, and in particular adapt kernel shrinkage ideas for ridge parameter selection. Numerical studies demonstrate the superior classification performance of the proposed approach compared to existing nonparametric classifiers.
Distributed PCP Theorems for Hardness of Approximation in P

We present a new distributed} model of probabilistically checkable proofs (PCP). A satisfying assignment x &#x220A; \{0,1\}^n to a CNF formula \phi is shared between two parties, where Alice knows x_1, \dots, x_{n/2, Bob knows x_{n/2+1},\dots,x_n, and both parties know \phi. The goal is to have Alice and Bob jointly write a PCP that x satisfies \phi, while exchanging little or no information. Unfortunately, this model as-is does not allow for nontrivial query complexity. Instead, we focus on a non-deterministic} variant, where the players are helped by Merlin, a third party who knows all of x.Using our framework, we obtain, for the first time, PCP-like reductions from the Strong Exponential Time Hypothesis (SETH) to approximation problems in \P. In particular, under SETH we show that %(assuming SETH) there are no truly-subquadratic approximation algorithms for %the following problems: Maximum Inner Product over \{0,1\}-vectors, LCS Closest Pair over permutations, Approximate Partial Match, Approximate Regular Expression Matching, and Diameter in Product Metric. All our inapproximability factors are nearly-tight. In particular, for the first three problems we obtain nearly-polynomial factors of 2^{(log n)^{1-o(1)}};only (1+o(1))-factor lower bounds (under SETH) were known before.As an additional feature of our reduction, we obtain new SETH lower bounds for the exact} monochromatic Closest Pair problem in the Euclidean, Manhattan, and Hamming metrics.
Longest alignment with edits in data streams

Analyzing patterns in data streams generated by network traffic, sensor networks, or satellite feeds is a challenge for systems in which the available storage is limited. In addition, real data is noisy, which makes designing data stream algorithms even more challenging. Motivated by such challenges, we study algorithms for detecting the similarity of two data streams that can be read in sync. Two strings S, T ∊ ∑n form a d-near-alignment if the distance between them in some given metric is at most d. We study the problem of identifying a longest substring of S and T that forms a d-near-alignment under the edit distance, in the simultaneous streaming model. In this model, symbols of strings S and T are streamed at the same time, and the amount of available processing space is sublinear in the length of the strings. We give several algorithms, including an exact one-pass algorithm that uses O (d2 + d log n) bits of space. We couple these results with comparable lower bounds.
Role of Subgraphs in Epidemics over Finite-Size Networks under the Scaled SIS Process

In previous work, we developed the scaled SIS process, which models the dynamics of SIS epidemics over networks. With the scaled SIS process, we can consider networks that are finite-sized and of arbitrary topology (i.e., we are not restricted to specific classes of networks). We derived for the scaled SIS process a closed-form expression for the time-asymptotic probability distribution of the states of all the agents in the network. This closed-form solution of the equilibrium distribution explicitly exhibits the underlying network topology through its adjacency matrix. This paper determines which network configuration is the most probable. We prove that, for a range of epidemics parameters, this combinatorial problem leads to a submodular optimization problem, which is exactly solvable in polynomial time. We relate the most-probable configuration to the network structure, in particular, to the existence of high density subgraphs. Depending on the epidemics parameters, subset of agents may be more likely to be infected than others; these more-vulnerable agents form subgraphs that are denser than the overall network. We illustrate our results with a 193 node social network and the 4941 node Western US power grid under different epidemics parameters.
Generalized Line Spectral Estimation via Convex Optimization

Line spectral estimation is the problem of recovering the frequencies and amplitudes of a mixture of a few sinusoids from equispaced samples. However, in a variety of signal processing problems arising in imaging, radar, and localization, we do not have access directly to such equispaced samples. Rather, we only observe a severely undersampled version of these observations through linear measurements. This paper is about such generalized line spectral estimation problems. We reformulate these problems as sparse signal recovery problems over a continuously indexed dictionary, which can be solved via a convex program. We prove that the frequencies and amplitudes of the components of the mixture can be recovered perfectly from a near-minimal number of observations via this convex program. This result holds provided the frequencies are sufficiently separated, and the linear measurements obey natural conditions that are satisfied in a variety of applications.
On mutual information estimation for mixed-pair random variables

Abstract We study the mutual information estimation for mixed-pair random variables. One random variable is discrete and the other one is continuous. We develop a kernel method to estimate the mutual information between the two random variables. The estimates enjoy a central limit theorem under some regular conditions on the distributions. The theoretical results are demonstrated by simulation study.
On spaces with connected Higson coronas

Abstract In this paper, we characterise metric spaces which have topologically connected Higson coronas. The characterisation is given by a natural categorical condition applied in the coarse category. We also give a characterisation in terms of coarse cohomology, and consider the special case of finitely generated groups and the more general case of abstract coarse spaces. Along the way, we exhibit some connections to the notion of ω -excisive decomposition introduced by Higson, Roe and Yu, and give a categorical characterisation of such decompositions.
Wide-field Fourier ptychographic microscopy using laser illumination source

Fourier ptychographic (FP) microscopy is a coherent imaging method that can synthesize an image with a higher bandwidth using multiple low-bandwidth images captured at different spatial frequency regions. The method’s demand for multiple images drives the need for a brighter illumination scheme and a high-frame-rate camera for a faster acquisition. We report the use of a guided laser beam as an illumination source for an FP microscope. It uses a mirror array and a 2-dimensional scanning Galvo mirror system to provide a sample with plane-wave illuminations at diverse incidence angles. The use of a laser presents speckles in the image capturing process due to reflections between glass surfaces in the system. They appear as slowly varying background fluctuations in the final reconstructed image. We are able to mitigate these artifacts by including a phase image obtained by differential phase contrast (DPC) deconvolution in the FP algorithm. We use a 1-Watt laser configured to provide a collimated beam with 150 mW of power and beam diameter of 1 cm to allow for the total capturing time of 0.96 seconds for 96 raw FPM input images in our system, with the camera sensor’s frame rate being the bottleneck for speed. We demonstrate a factor of 4 resolution improvement using a 0.1 NA objective lens over the full camera field-of-view of 2.7 mm by 1.5 mm.
Equivariant cohomology and the Varchenko–Gelfand filtration

Abstract The cohomology of the configuration space of n points in R 3 is isomorphic to the regular representation of the symmetric group, which acts by permuting the points. We give a new proof of this fact by showing that the cohomology ring is canonically isomorphic to the associated graded of the Varchenko–Gelfand filtration on the cohomology of the configuration space of n points in R 1 . Along the way, we give a presentation of the equivariant cohomology ring of the R 3 configuration space with respect to a circle acting on R 3 via rotation around a fixed line. We extend our results to the settings of arbitrary real hyperplane arrangements (the aforementioned theorems correspond to the braid arrangement) as well as oriented matroids.
Tamely ramified subfields of division algebras

For any number field K, it is unknown which finite groups appear as Galois groups of extensions L/K such that L is a maximal subfield of a division algebra with center K (a K-division algebra). For K=Q, the answer is described by the long standing Q-admissibility conjecture. We extend a theorem of Neukirch on embedding problems with local constraints in order to determine for every number field K, what finite solvable groups G appear as Galois groups of tamely ramified maximal subfields of K-division algebras, generalizing Liedahlʼs theorem for metacyclic G and Sonnʼs solution of the Q-admissibility conjecture for solvable groups.
The geometric structure of max-plus hemispaces

Abstract Given a set S endowed with a convexity structure, a hemispace is a convex subset of S which has convex complement. We recall that R max n is a semimodule over the max-plus semifield ( R max : = R ∪ { − ∞ } , max ⁡ , + ) . A convexity structure of current interest is provided by R max n naturally endowed with the max-plus (or tropical) convexity. In this paper we provide a geometric description of a max-plus hemispace in R max n . We show that a max-plus hemispace has a conical decomposition as a finite union of disjoint max-plus cones. These cones can be interpreted as faces of several max-plus hyperplanes. Briec and Horvath proved that the closure of a max-plus hemispace is bounded by a max-plus hyperplane. Given a hyperplane, we give a simple condition for the assignment of the faces between a pair of complementary max-plus hemispaces. Our result allows for counting and enumeration of the associated max-plus hemispaces. We recall that an n-dimensional max-plus hyperplane is called strictly affine and nondegenerate if it has a linear equation that contains all variables x 1 , x 2 , … , x n and a free term. We prove that the number of max-plus hemispaces in R max n , supported by strictly affine nondegenerate hyperplanes centered in the origin, is twice the n-th ordered Bell number. Our work can be viewed as a complement to the recent results of Katz, Nitica, and Sergeev, who described generating sets for max-plus hemispaces, and the results of Briec and Horvath, who proved that closed/open max-plus hemispaces are max-plus closed/open halfspaces.
Improved Optimization for the Cluster Jastrow Antisymmetric Geminal Power and Tests on Triple-Bond Dissociations.

We present a novel specialization of the variational Monte Carlo linear method for the optimization of the recently introduced cluster Jastrow antisymmetric geminal power ansatz, achieving a lower-order polynomial cost scaling than would be possible with a naive application of the linear method and greatly improving optimization performance relative to that of the previously employed quasi-Newton approach. We test the methodology on highly multireference triple-bond stretches, achieving accuracy superior to those of the traditional coupled cluster theory and multireference perturbation theory in both the typical example of N2 and the transition-metal-oxide example of [ScO]+.
Almost-invariant and essentially-invariant halfspaces

Abstract In this paper we study sufficient conditions for an operator to have an almost-invariant half-space. As a consequence, we show that if X is an infinite-dimensional complex Banach space then every operator T ∈ L ( X ) admits an essentially-invariant half-space. We also show that whenever a closed algebra of operators possesses a common AIHS, then it has a common invariant half-space as well.
Logical and information aspects in surface science: friction, capillarity, and superhydrophobicity

Logical and information aspects of friction and wetting (including the adhesion, capillarity, and superhydrophobicity) are discussed. Friction involves paradoxes, such as the Painleve paradoxes of ...
Comparing Fifty Natural Languages and Twelve Genetic Languages Using Word Embedding Language Divergence (WELD) as a Quantitative Measure of Language Distance

Author(s): Asgari, Ehsaneddin; Mofrad, Mohammad RK | Abstract: We introduce a new measure of distance between languages based on word embedding, called word embedding language divergence (WELD). WELD is defined as divergence between unified similarity distribution of words between languages. Using such a measure, we perform language comparison for fifty natural languages and twelve genetic languages. Our natural language dataset is a collection of sentence-aligned parallel corpora from bible translations for fifty languages spanning a variety of language families. Although we use parallel corpora, which guarantees having the same content in all languages, interestingly in many cases languages within the same family cluster together. In addition to natural languages, we perform language comparison for the coding regions in the genomes of 12 different organisms (4 plants, 6 animals, and two human subjects). Our result confirms a significant high-level difference in the genetic language model of humans/animals versus plants. The proposed method is a step toward defining a quantitative measure of similarity between languages, with applications in languages classification, genre identification, dialect identification, and evaluation of translations.
Stillman's Question for Exterior Algebras and Herzog's Conjecture on Betti Numbers of Syzygy Modules

Abstract Let K be a field of characteristic 0 and consider exterior algebras of finite dimensional K-vector spaces. In this short paper we exhibit principal quadric ideals in a family whose Castelnuovo–Mumford regularity is unbounded. This negatively answers the analogue of Stillman's Question for exterior algebras posed by I. Peeva. We show that, via the Bernstein–Gel'fand–Gel'fand correspondence, these examples also yields counterexamples to a conjecture of J. Herzog on the Betti numbers in the linear strand of syzygy modules over polynomial rings.