cssi/SciSciGPT-SciSciNet huggingface dataset:
Products derived from oxidations of 3,4‐dimethyl‐1‐phenylphosphole‐1‐oxide: A 3‐phenyl‐5,6‐dimethyl‐2,3‐oxaphosphabicyclo[2.2.2]octene‐3‐oxide derivative as a precursor of phenyl metaphosphonic anhydride

Oxidation of 3,4-dimethyl-1-phenylphosphole with peracids or peroxides gives a relatively stable P-oxide, which can be used in Diels-Alder reactions to give derivatives with the 7-phosphanorbornene framework. Oxygen insertion into a C–P bond of this framework occurs smoothly with m- chloroperbenzoic acid (MCPBA) providing derivatives of the 2,3-oxaphosphabicyclo [2.2.2] octene ring system. The phosphole can be converted to this system in a one-pot synthesis by reaction with excess MCPBA in the presence of N-phenylmaleimide as dienophile. The phosphole oxide undergoes mono-epoxidation with MCPBA. Thermal or photochemical fragmentation of the 2,3-oxaphosphabicyclo [2.2.2] ocetene is a useful source of the 3-coordinate species Ph–PO2, a meta-anhydride of phenylphosphonic acid. This species was trapped successfully with a variety of alcohols.
Total synthesis of (±)-stemonamide and (±)-isostemonamide

Two different approaches to the alkaloids stemonamide and isostemonamide using N-acyliminium chemistry are described. The approach using an aldol spirocyclization to construct the second contiguous spirocenter was successful. The total synthesis of these products was completed by 1,4-addition of an appropriate side chain, α-methylenation by Mannich reaction, double bond isomerization and closure of the azepine ring.
Comparison of vibrotactile and joint-torque feedback in a myoelectric upper-limb prosthesis

Despite the technological advancements in myoelectric prostheses, body-powered prostheses remain a popular choice for amputees, in part due to the natural sensory advantage they provide. Research on haptic feedback in myoelectric prostheses has delivered mixed results. Furthermore, there is limited research comparing various haptic feedback modalities in myoelectric prostheses. In this paper, we present a comparison of the feedback intrinsically present in body-powered prostheses (joint-torque feedback) to a commonly proposed feedback modality for myoelectric prostheses (vibrotactile feedback). In so doing, we seek to understand whether the advantages of kinesthetic feedback present in body-powered prostheses translate to myoelectric prostheses, and whether there are differences between kinesthetic and cutaneous feedback in prosthetic applications. We developed an experimental testbed that features a cable-driven, voluntary-closing 1-DoF prosthesis, a capstan-driven elbow exoskeleton, and a vibrotactile actuation unit. The system can present grip force to users as either a flexion moment about the elbow or vibration on the wrist. To provide an equal comparison of joint-torque and vibrotactile feedback, a stimulus intensity matching scheme was utilized. Non-amputee participants (n=12) were asked to discriminate objects of varying stiffness with the prosthesis in three conditions: no haptic feedback, vibrotactile feedback, and joint-torque feedback. Results indicate that haptic feedback increased discrimination accuracy over no haptic feedback, but the difference between joint-torque feedback and vibrotactile feedback was not significant. In addition, our results highlight nuanced differences in performance depending on the objects’ stiffness, and suggest that participants likely pay less attention to incidental cues with the addition of haptic feedback. Even when haptic feedback is not modality matched to the task, such as in the case of vibrotactile feedback, performance with a myoelectric prosthesis can improve significantly. This implies it is possible to achieve the same benefits with vibrotactile feedback, which is cheaper and easier to implement than other forms of feedback.
A General Approach to Angucyclines: Synthesis of Hatomarubigin A, Rubiginone B2, Antibiotic X-1488E, 6-Hydroxytetrangulol, and Tetrangulol

Abstract Hatomarubigin A was prepared in 41% yield in a single procedure from acyl naphthoquinone 15 and 5-methylcyclohexane-1,3-dione (16). The net reaction consists of Michael addition to an acyl quinone followed by intramolecular aldol condensation. Hatomarubigin A then served as a common intermediate in syntheses of the angucyclinone antibiotics rubiginone B2, antibiotic X-1488E, 6-hydroxytetrangulol, and tetrangulol.
Synthesis of Alkylarylcarbinols via the Reaction of Organoboranes with Arylmethyl Chlorides

(α-Chloroaryl)methyl anions, generated in situ by the deprotonation of arylmethyl chlorides with dicyclohexylamide, readily react with either trialkylboranes or alkylboronic esters to produce alkylarylcarbinols in good yields after oxidation. This reaction provides a very facile procedure for the synthesis of alkylarylcarbinols.
Utilizing random regression models for genomic prediction of a longitudinal trait derived from high-throughput phenotyping.

The accessibility of high-throughput phenotyping platforms in both the greenhouse and field, as well as the relatively low cost of unmanned aerial vehicles, has provided researchers with an effective means to characterize large populations throughout the growing season. These longitudinal phenotypes can provide important insight into plant development and responses to the environment. Despite the growing use of these new phenotyping approaches in plant breeding, the use of genomic prediction models for longitudinal phenotypes is limited in major crop species. The objective of this study was to demonstrate the utility of random regression (RR) models using Legendre polynomials for genomic prediction of shoot growth trajectories in rice (Oryza sativa). An estimate of shoot biomass, projected shoot area (PSA), was recorded over a period of 20 days for a panel of 357 diverse rice accessions using an image-based greenhouse phenotyping platform. A RR that included a fixed second-order Legendre polynomial, a random second-order Legendre polynomial for the additive genetic effect, a first-order Legendre polynomial for the environmental effect, and heterogeneous residual variances was used to model PSA trajectories. The utility of the RR model over a single time point (TP) approach, where PSA is fit at each time point independently, is shown through four prediction scenarios. In the first scenario, the RR and TP approaches were used to predict PSA for a set of lines lacking phenotypic data. The RR approach showed a 11.6% increase in prediction accuracy over the TP approach. Much of this improvement could be attributed to the greater additive genetic variance captured by the RR approach. The remaining scenarios focused forecasting future phenotypes using a subset of early time points for known lines with phenotypic data, as well new lines lacking phenotypic data. In all cases, PSA could be predicted with high accuracy (r: 0.79 to 0.89 and 0.55 to 0.58 for known and unknown lines, respectively). This study provides the first application of RR models for genomic prediction of a longitudinal trait in rice and demonstrates that RR models can be effectively used to improve the accuracy of genomic prediction for complex traits compared to a TP approach.
Learning Naturalistic Temporal Structure in the Posterior Medial Network.

The posterior medial network is at the apex of a temporal integration hierarchy in the brain, integrating information over many seconds of viewing intact, but not scrambled, movies. This has been i...
Iron(II)-Catalyzed Sulfimidation and [2,3]-Sigmatropic Rearrangement of Propargyl Sulfides with tert-Butoxycarbonyl Azide. Access to N-Allenylsulfenimides

The iron(II)-catalyzed Bach reaction of tert-butoxycarbonyl azide (BocN(3)) and allyl sulfides has been extended to include propargyl sulfides, which give N-allenylsulfenimide products. Using 10 mol % dppeFeCl(2) as catalyst the reaction proceeds at 0 degrees C with a number of different propargyl sulfides in 31-73% isolated yield. The reaction is limited by product instability toward catalyst and termination of the catalytic cycle by excess BocN(3). N-Allenylsulfenimide 2b smoothly undergoes catalytic hydrogenation and a Diels-Alder reaction with cyclopentadiene.
Methane activation in homogeneous systems

Abstract Homogeneous approaches to methane conversion, including organometallic, biological and biomimetic systems, present attractive opportunities for overcoming limitations on direct methane conversion via traditional, high-temperature heterogeneous catalysis. At the same time, of course, they are subject to their own special problems. The chemistry of these systems, their potential advantages and disadvantages, and prospects for practical applications are discussed.
The Guanidinium Group in Molecular Recognition: Design and Synthetic Approaches

The guanidinium group is found in many natural products and has been extensively incorporated into various drug designs as well as artificial receptor structures. In this paper we critically review the various synthetic routes to guanidiniums and describe a novel approach that allows the mild formation of multi-substituted derivatives.
Influence of hyaluronic acid transitions in tumor microenvironment on glioblastoma malignancy and invasive behavior

The extracellular matrix (ECM) is critical in tumor growth and invasive potential of cancer cells. In glioblastoma tumors, some components of the native brain ECM such as hyaluronic acid (HA) have been suggested as key regulators of processes associated with poor patient outlook such as invasion and therapeutic resistance. Given the importance of cell-mediated remodeling during invasion, it is likely that the molecular weight of available HA polymer may strongly influence GBM progression. Biomaterial platforms therefore provide a unique opportunity to systematically examine the influence of the molecular weight distribution of HA on GBM cell activity. Here we report the relationship between the molecular weight of matrix-bound HA within a methacrylamidefunctionalized gelatin (GelMA) hydrogel, the invasive phenotype of a patient-derived xenograft GBM population that exhibits significant in vivo invasivity, and the local production of soluble HA during GBM cell invasion. Hyaluronic acid of different molecular weights spanning a range associated with cell-mediated remodeling (10, 60, and 500 kDa) was photopolymerized into GelMA hydrogels, with cell activity compared to GelMA only conditions (-HA). Polymerization conditions were tuned to create a homologous series of GelMA hydrogels with conserved poroelastic properties (i.e., shear modulus, Poisson's ratio, and diffusivity). GBM migration was strongly influenced by HA molecular weight; while markers associated with active remodeling of HA (hyaluronan synthase and hyaluronidase) were found to be uninfluenced. These results provide new information regarding the importance of local hyaluronic acid content on the invasive phenotype of GBM.
Self-propagating metathesis routes to metastable group 4 phosphides

Group 4 phosphides, which are typically prepared at high temperatures (> 800 degrees C) over several days, are synthesized in self-propagating metathesis (exchange) reactions in seconds. These reactions produce cubic forms of zirconium phosphide (ZrP) and hafnium phosphide (HfP) which are normally made at temperatures greater than 1425 degrees C and 1600 degrees C, respectively. To test whether the high temperatures reached in the metathesis reactions are responsible for the formation of the cubic phases, inert salts are added to lower the maximum reaction temperatures. The lower temperature reactions still result in cubic phosphides, although smaller crystallites form. Further experiments with phosphorus addition indicate that the phosphorus content is not responsible for cubic phase formation. Templating is ruled out using lattice mismatched KCl and hexagonal ZnS as additives. Therefore, the direct synthesis of the high-temperature cubic phase in metathesis reactions appears to be caused by nucleation of the metastable cubic form that is then trapped by rapid cooling. Heating the cubic phase of either ZrP or HfP to 1000 degrees C for 18 h, or carrying out metathesis reactions in sealed ampules at 1000 degrees C, results only in the hexagonal phase.
INTRAMOLECULAR PAUSON-KHAND REACTIONS OF AROMATIC ENYNES

The synthesis of a series of O-alkenylated ethynylphenol derivatives and their NMO promoted intramolecular Pauson-Khand reactions are reported. The effects of substitution on both the alkene and alkyne moiety have been investigated.
Synthesis of Methyl 3‐(N‐Bromoacetylamino)‐2‐Naphthoate

Methyl 3-(N-bromoacetylamino)-2-naphthoate (3) was obtained from 3-amino-2-naphthoic acid (1) as the starting material, with methyl 3-amino-2-naphthoate (2) as the intermediate.
A hypothesis-driven approach to assessing significance of differences in RNA expression levels among specific groups of genes

Abstract Genome-wide molecular gene expression studies generally compare expression values for each gene across multiple conditions followed by cluster and gene set enrichment analysis to determine whether differentially expressed genes are enriched in specific biochemical pathways, cellular components, biological processes, and/or molecular functions, etc. This approach to analyzing differences in gene expression enables discovery of gene function, but is not useful to determine whether pre-defined groups of genes share or diverge in their expression patterns in response to treatments nor to assess the correctness of pre-defined gene set groupings. Here we present a simple method that changes the dimension of comparison by treating genes as variable traits to directly assess significance of differences in expression levels among pre-defined gene groups. Because expression distributions are typically skewed (thus unfit for direct assessment using Gaussian statistical methods) our method involves transforming expression data to approximate a normal distribution followed by dividing the genes into groups, then applying Gaussian parametric methods to assess significance of observed differences. This method enables the assessment of differences in gene expression distributions within and across samples, enabling hypothesis-based comparison among groups of genes. We demonstrate this method by assessing the significance of specific gene groups’ differential response to heat stress conditions in maize.
Metalation of Carbaporphyrinoid Systems

Diverse carbaporphyrinoid systems have been synthesized using ‘3 + 1’ MacDonald condensations, LindseyRothemund reactions and other strategies. In common with the N-confused porphyrins (NCPs), these compounds have a CNNN core that can facilitate the generation of organometallic derivatives. Benzocarbaporphyrins and tropiporphyrins, with indene or cycloheptatriene units in place of a pyrrole ring, readily form silver(III) complexes and some gold(III) derivatives have also been prepared. On the other hand, benziporphyrins and azuliporphyrins, which have a benzene or azulene unit in place of a pyrrole moiety, are dianionic ligands that afford Ni, Pd and Pt complexes. Stable iridium and rhodium derivatives of azuliporphyrins can also be generated. 2-Methyl or 2-phenyl NCPs act as dianionic ligands forming Ni and Pd complexes but reactions with silver(I) acetate gave the aromatic 3-oxoNCP silver(III) derivatives. A related N-phenylpyrazole-containing porphyrinoid gave nickel(II) and palladium(II) complexes but these showed little or no aromatic character. Oxybenziporphyrins, which have a semiquinone subunit, can form Pd, Pt, Cu, Ag and Au derivatives and can therefore act as both dianionic and a trianionic ligands. Finally, a diazuliporphyrin has been used to prepare the first example of a palladium(II) dicarbaporphyrinoid complex. These investigations demonstrate that the unique characteristics of organometallic compounds derived from carbaporphyrins and related porphyrin analogues are starting to rival the significance of the better known metal complexes of N-confused porphyrins.
A short synthetic route to nordihydroguaiaretic acid (NDGA) and its stereoisomer using Ti-induced carbonyl-coupling reaction

Abstract A rapid synthetic approach to natural meso -nordihydroguaiaretic acid (NDGA) and its non- meso isomer is described from (3,4-dimethoxyphenyl)acetone using as a key step the low-valent Ti-induced carbonyl-coupling reaction of the ketone. The method involves a simple separation of the E - and Z -isomers that result from the dehydroxylation of the diol product of the coupling. The present approach allows the preparation of various analogs of NDGA.
Synthesis of novel heterocycles related to the dynemicin a ring skeleton

Studies directed towards the construction of the CDE ring framework of dynemycin A (1) are reported. A series of quinoline based dienophiles containing an activating group (e.g. 5, Scheme 1), reacted with acyclic dienes (e.g. 4, Scheme 1) in a Diels-Alder fashion under increased pressure to afford a variety of heterocyclic systems related to the CDE skeleton of dynemycin A. Reaction of dienophile 15 with cyclic diene 29 led to the novel hetereocycle 34 whereas attempted decarbonylation of 41 led to a novel rhodium-promoted intramolecular carbonylation of the terminal acetylene furnishing compound 43.
Rationally Engineered Mutants of Phosphotriesterase for Preparative Scale Isolation of Chiral Organophosphates

will catalyze the hydrolysis of the most acidic phenolic substituent from an organophosphate triester. The overall rate of hydrolysis is very much dependent on the pKa of the leaving group phenol. 4b To enhance the substrate stereoselectivity exhibited by the wildtype enzyme, we designed and characterized several site-directed mutants of PTE. Three regions within the active site of PTE (small, large, and leaVing group) have been identified that interact with the three substituents attached to the phosphorus center of typical substrates. 7 These subsites were graphically localized using the X-ray crystal structure of PTE in the presence of a bound substrate analogue. The relative sizes of these binding subsites appear to play the dominant roles in establishing the stereoselective properties of the wild-type PTE. 8 Thus, when the small subsite is reduced in size by mutating Gly60 to an alanine residue, the observed stereoselectivity of the mutant enzyme is dramatically enhanced toward the hydrolysis of the SP-isomer. For the racemic pairs of substrates I, II, and III, the kcat/Km values are 10- to 400-fold greater for the SP-isomers than for the corresponding RP-isomers and 10 000- to 15 000-fold greater for the
Do Increasing Markups Matter? Lessons from Empirical Industrial Organization

This article considers the recent literature on firm markups in light of both new and classic work in the field of industrial organization. We detail the shortcomings of papers that rely on discredited approaches from the "structure-conduct-performance" literature. In contrast, papers based on production function estimation have made useful progress in measuring broad trends in markups. However, industries are so heterogeneous that careful industry-specific studies are also required, and sorely needed. Examples of such studies illustrate differing explanations for rising markups, including endogenous increases in fixed costs associated with lower marginal costs. In some industries there is evidence of price increases driven by mergers. To fully understand markups, we must eventually recover the key economic primitives of demand, marginal cost, and fixed and sunk costs. We end by discussing the various aspects of antitrust enforcement that may be of increasing importance regardless of the cause of increased markups.
Differentiation of structurally similar phenethylamines via gas chromatography–vacuum ultraviolet spectroscopy (GC–VUV)

Abstract The vacuum ultraviolet region includes wavelengths shorter than 200 nm. Electronic transitions of sigma and pi bonds lie in this region, which have the potential to yield structural information. Thus, a VUV detector should be able to detect nearly any molecule analyzable by gas chromatography. This study sought to determine the extent to which structurally similar phenethylamines are differentiated using their VUV spectra. Phenethylamines are a common drug class including pseudoephedrine and illicit drugs such as methamphetamine. Several phenethylamines are difficult to analyze by electron impact mass spectrometry due to their fragmentation giving the same mass to charge ratio fragments at similar ratios. While phenethylamines are generally differentiable by retention time, an extra layer of specificity is preferred in forensic analyses. A vacuum ultraviolet (VUV) spectrophotometer coupled to a gas chromatograph was used to collect VUV spectra at high frequency between 125 and 430 nm. Eight phenethylamines were analyzed for this work using GC/VUV. A calibration curve and limit of detection study was performed that indicates a limit of detection around 10 μg mL−1 and an upper limit of linearity around 1000 μg mL−1. The spectra, analyzed by Principal Component Analysis and Discriminant Analysis, indicate the ability to reliably differentiate each of the drugs from one another including structural isomers and diastereomers. Lastly, five “street” samples containing amphetamines were analyzed to demonstrate “real world” performance.
A quantitative uncertainty metric controls error in neural network-driven chemical discovery

Machine learning (ML) models, such as artificial neural networks, have emerged as a complement to high-throughput screening, enabling characterization of new compounds in seconds instead of hours. The promise of ML models to enable large-scale chemical space exploration can only be realized if it is straightforward to identify when molecules and materials are outside the model's domain of applicability. Established uncertainty metrics for neural network models are either costly to obtain (e.g., ensemble models) or rely on feature engineering (e.g., feature space distances), and each has limitations in estimating prediction errors for chemical space exploration. We introduce the distance to available data in the latent space of a neural network ML model as a low-cost, quantitative uncertainty metric that works for both inorganic and organic chemistry. The calibrated performance of this approach exceeds widely used uncertainty metrics and is readily applied to models of increasing complexity at no additional cost. Tightening latent distance cutoffs systematically drives down predicted model errors below training errors, thus enabling predictive error control in chemical discovery or identification of useful data points for active learning.
Moment-based analysis of synchronization in small-world networks of oscillators

In this paper, we investigate synchronization in a small-world network of coupled nonlinear oscillators. This network is constructed by introducing random shortcuts in a nearest-neighbors ring. The local stability of the synchronous state is closely related with the support of the eigenvalue distribution of the Laplacian matrix of the network. We introduce, for the first time, analytical expressions for the first three moments of the eigenvalue distribution of the Laplacian matrix as a function of the probability of shortcuts and the connectivity of the underlying nearest-neighbor coupled ring. We apply these expressions to estimate the spectral support of the Laplacian matrix in order to predict synchronization in small-world networks. We verify the efficiency of our predictions with numerical simulations.
On self-avoiding polygons and walks: The snake method via pattern fluctuation

For $d \geq 2$ and $n \in \mathbb{N}$, let $\mathsf{W}_n$ denote the uniform law on self-avoiding walks of length $n$ beginning at the origin in the nearest-neighbour integer lattice $\mathbb{Z}^d$, and write $\Gamma$ for a $\mathsf{W}_n$-distributed walk. We show that the closing probability $\mathsf{W}_n \big( \vert\vert \Gamma_n \vert\vert = 1 \big)$ that $\Gamma$'s endpoint neighbours the origin is at most $n^{-1/2 + o(1)}$ in any dimension $d \geq 2$. The method of proof is a reworking of that in [4], which found a closing probability upper bound of $n^{-1/4 + o(1)}$. A key element of the proof is made explicit and called the snake method. It is applied to prove the $n^{-1/2 + o(1)}$ upper bound by means a technique of Gaussian pattern fluctuation.
Restrictions of rainbow supercharacters

Abstract The maximal subgroup of unipotent upper-triangular matrices of the finite general linear groups is a fundamental family of p-groups. Their representation theory is well known to be wild, but there is a standard supercharacter theory, replacing irreducible representations by super-representations, that gives us some control over its representation theory. While this theory has a beautiful underlying combinatorics built on set partitions, the structure constants of restricted super-representations remain mysterious. This paper proposes a new approach to solving the restriction problem by constructing natural intermediate modules that help “factor” the computation of the structure constants. We illustrate the technique by solving the problem completely in the case of rainbow supercharacters (and some generalizations). Along the way we introduce a new q-analogue of the binomial coefficients that depend on an underlying poset.
CM liftings of supersingular elliptic curves

Sous GRH, nous presentons un algorithme qui, etant donne un nombre premier p, calcule l'ensemble des discriminants fondamentaux D D p implique que l'application est necessairement surjective et nous calculons ensuite explicitement les cas |D| < Dp.
Multiphase segmentation for simultaneously homogeneous and textural images

Abstract Segmentation remains an important problem in image processing. For homogeneous images containing only piecewise smooth information, a number of important models have been developed and refined over the past several decades. However, these models often fail when applied to the substantially larger class of natural images that simultaneously contain regions of homogeneity and non-homogeneity such as texture. This work introduces a bi-level constrained minimization model for simultaneous multiphase segmentation of images containing both homogeneous and textural regions. We develop novel norms defined in different functional Banach spaces for the segmentation which results in a non-convex minimization. Finally, we develop a generalized notion of segmentation delving into approximation theory and demonstrating that a more refined decomposition of these images results in multiple meaningful components. Both theoretical results and demonstrations on natural images are provided.
Association schemes and Hypergroups

ABSTRACTIn this paper, we investigate hypergroups which arise from association schemes in a canonical way; this class of hypergroups is called realizable. We first study basic algebraic properties of realizable hypergroups. Then we prove that two interesting classes of hypergroups (partition hypergroups and linearly ordered hypergroups) are realizable. Along the way, we prove that a certain class of projective geometries is equipped with a canonical association scheme structure which allows us to link three objects; association schemes, hypergroups, and projective geometries (see, Section 1.2 for details).
Burgess bounds for multi-dimensional short mixed character sums

Abstract This paper proves Burgess bounds for short mixed character sums in multi-dimensional settings. The mixed character sums we consider involve both an exponential evaluated at a real-valued multivariate polynomial f, and a product of multiplicative Dirichlet characters. We combine a multi-dimensional Burgess method with recent results on multi-dimensional Vinogradov Mean Value Theorems for translation–dilation invariant systems in order to prove character sum bounds in k ≥ 1 dimensions that recapture the Burgess bound in dimension 1. Moreover, we show that by embedding any given polynomial f into an advantageously chosen translation–dilation invariant system constructed in terms of f, we may in many cases significantly improve the bound for the associated character sum, due to a novel phenomenon that occurs only in dimensions k ≥ 2 .
A Fast Noniterative Algorithm for Compressive Sensing Using Binary Measurement Matrices

In this paper, we present a new algorithm for compressive sensing that makes use of binary measurement matrices and achieves exact recovery of ultrasparse vectors in a single pass and without any iterations. Due to its noniterative nature, our algorithm is hundreds of times faster than $\ell _1$ -norm minimization and methods based on expander graphs, both of which require multiple iterations. Our algorithm can accommodate nearly sparse vectors, in which case, it recovers an index set of the largest components, and can also accommodate burst noise measurements. Compared to compressive sensing methods that are guaranteed to achieve exact recovery of all sparse vectors, our method requires fewer measurements. However, methods that achieve statistical recovery, that is, recovery of almost all but not all sparse vectors, can require fewer measurements than our method.
Inclusion of forbidden minors in random representable matroids

In 1984, Kelly and Oxley introduced the model of a random representable matroid M[An] corresponding to a random matrix AnFqm(n)n, whose entries are drawn independently and uniformly from Fq. Whereas properties such as rank, connectivity, and circuit size have been well-studied, forbidden minors have not yet been analyzed. Here, we investigate the asymptotic probability as n that a fixed Fq-representable matroid M is a minor of M[An]. (We always assume m(n)rank(M) for all sufficiently large n, otherwise M can never be a minor of the corresponding M[An].) When M is free, we show that M is asymptotically almost surely (a.a.s.) a minor of M[An]. When M is not free, we show a phase transition: M is a.a.s. a minor if nm(n), but is a.a.s. not if m(n)n. In the more general settings of mn and m>n, we give lower and upper bounds, respectively, on both the asymptotic and non-asymptotic probabilities that M is a minor of M[An]. The tools we develop to analyze matroid operations and minors of random matroids may be of independent interest.Our results directly imply that M[An] is a.a.s. not contained in any proper, minor-closed class M of Fq-representable matroids, provided: (i) nm(n), and (ii) m(n) is at least the minimum rank of any Fq-representable forbidden minor of M, for all sufficiently large n. As an application, this shows that graphic matroids are a vanishing subset of linear matroids, in a sense made precise in the paper. Our results provide an approach for applying the rich theory around matroid minors to the less-studied field of random matroids.
Model Reduction Near Periodic Orbits of Hybrid Dynamical Systems

We show that, near periodic orbits, a class of hybrid models can be reduced to or approximated by smooth continuous-time dynamical systems. Specifically, near an exponentially stable periodic orbit undergoing isolated transitions in a hybrid dynamical system, nearby executions generically contract superexponentially to a constant-dimensional subsystem. Under a non-degeneracy condition on the rank deficiency of the associated Poincare map, the contraction occurs in finite time regardless of the stability properties of the orbit. Hybrid transitions may be removed from the resulting subsystem via a topological quotient that admits a smooth structure to yield an equivalent smooth dynamical system. We demonstrate reduction of a high-dimensional underactuated mechanical model for terrestrial locomotion, assess structural stability of deadbeat controllers for rhythmic locomotion and manipulation, and derive a normal form for the stability basin of a hybrid oscillator. These applications illustrate the utility of our theoretical results for synthesis and analysis of feedback control laws for rhythmic hybrid behavior.
Modeling human ad hoc coordination

Whether in groups of humans or groups of computer agents, collaboration is most effective between individuals who have the ability to coordinate on a joint strategy for collective action. However, in general a rational actor will only intend to coordinate if that actor believes the other group members have the same intention. This circular dependence makes rational coordination difficult in uncertain environments if communication between actors is unreliable and no prior agreements have been made. An important normative question with regard to coordination in these ad hoc settings is therefore how one can come to believe that other actors will coordinate, and with regard to systems involving humans, an important empirical question is how humans arrive at these expectations. We introduce an exact algorithm for computing the infinitely recursive hierarchy of graded beliefs required for rational coordination in uncertain environments, and we introduce a novel mechanism for multiagent coordination that uses it. Our algorithm is valid in any environment with a finite state space, and extensions to certain countably infinite state spaces are likely possible. We test our mechanism for multiagent coordination as a model for human decisions in a simple coordination game using existing experimental data. We then explore via simulations whether modeling humans in this way may improve human-agent collaboration.
Entropy, stability, and Yang–Mills flow

Following [T. Colding and W. Minicozzi, II, Generic mean curvature flow I; generic singularities, Ann. of Math. 175(2) (2012) 755–833], we define a notion of entropy for connections over ℝn which has shrinking Yang–Mills solitons as critical points. As in [T. Colding and W. Minicozzi, II, Generic mean curvature flow I; generic singularities, Ann. of Math. 175(2) (2012) 755–833], this entropy is defined implicitly, making it difficult to work with analytically. We prove a theorem characterizing entropy stability in terms of the spectrum of a certain linear operator associated to the soliton. This leads furthermore to a gap theorem for solitons. These results point to a broader strategy of studying “generic singularities” of the Yang–Mills flow, and we discuss the differences in this strategy in dimension n = 4 versus n ≥ 5.
Proof Generation from Delta-Decisions

We show how to generate and validate logical proofs of unsatisfiability from delta-complete decision procedures that rely on error-prone numerical algorithms. Solving this problem is important for ensuring correctness of the decision procedures. At the same time, it is a new approach for automated theorem proving over real numbers. We design a first-order calculus, and transform the computational steps of constraint solving into logic proofs, which are then validated using proof-checking algorithms. As an application, we demonstrate how proofs generated from our solver can establish many nonlinear lemmas in the theormal proof of the Kepler Conjecture.
The lower semicontinuity of the Frobenius splitting numbers

We show that, under mild conditions, the (normalized) Frobenius splitting numbers of a local ring of prime characteristic are lower semicontinuous.
Superabundant Curves and the Artin Fan

We prove that every balanced 1-dimensional polyhedral complex arises as the tropicalization of a smooth curve over a non-Archimedean field mapping to a toric Artin fan, namely the quotient of a toric variety by its dense torus.
Persistently laminar branched surfaces

We define sink marks for branched complexes and find conditions for them to determine a branched surface structure. These will be used to construct branched surfaces in knot and tangle complements. We will extend Delman’s theorem and prove that a non 2-bridge Montesinos knot K has a persistently laminar branched surface unless it is equivalent to K(1/2q1, 1/q2, 1/q3, −1) for some positive integers qi. In most cases these branched surfaces are genuine, in which case K admits no atoroidal Seifert fibered surgery. It will also be shown that there are many persistently laminar tangles.
A Hard-core Stochastic Process with Simultaneous Births and Deaths

We introduce and examine a class of stochastic spatial point processes with births and deaths, related to spatial loss networks introduced in Ferrari et al. In these processes, a point stays in the...
A duality principle in spin glasses

We prove a duality principle that connects the thermodynamic limits of the free energies of the Hamiltonians and their squared interactions. Under the main assumption that the limiting free energy is concave in the squared temperature parameter, we show that this relation is valid in a large class of disordered systems. In particular, when applied to mean field spin glasses, this duality provides an interpretation of the Parisi formula as an inverted variational principle, establishing a prediction of Guerra.
Analysis of bi-material interface cracks with complex weighting functions and non-standard quadrature

Abstract A boundary element formulation is developed to determine the complex stress intensity factors associated with cracks on the interface between dissimilar materials. This represents an extension of the methodology developed previously by the authors for determination of free-edge generalized stress intensity factors on bi-material interfaces, which employs displacements and weighted tractions as primary variables. However, in the present work, the characteristic oscillating stress singularity is addressed through the introduction of complex weighting functions for both displacements and tractions, along with corresponding non-standard numerical quadrature formulas. As a result, this boundary-only approach provides extremely accurate mesh-insensitive solutions for a range of two-dimensional interface crack problems. A number of computational examples are considered to assess the performance of the method in comparison with analytical solutions and previous work on the subject. As a final application, the method is applied to study the scaling behavior of epoxy–metal butt joints.
Quick X-ray reflectivity using monochromatic synchrotron radiation for time-resolved applications.

A new technique for the parallel collection of X-ray reflectivity (XRR) data, compatible with monochromatic synchrotron radiation and flat substrates, is described and applied to the in situ observation of thin-film growth. The method employs a polycapillary X-ray optic to produce a converging fan of radiation, incident onto a sample surface, and an area detector to simultaneously collect the XRR signal over an angular range matching that of the incident fan. Factors determining the range and instrumental resolution of the technique in reciprocal space, in addition to the signal-to-background ratio, are described in detail. This particular implementation records ∼5° in 2θ and resolves Kiessig fringes from samples with layer thicknesses ranging from 3 to 76 nm. The value of this approach is illustrated by showing in situ XRR data obtained with 100 ms time resolution during the growth of epitaxial La0.7Sr0.3MnO3 on SrTiO3 by pulsed laser deposition at the Cornell High Energy Synchrotron Source (CHESS). Compared with prior methods for parallel XRR data collection, this is the first method that is both sample-independent and compatible with the highly collimated, monochromatic radiation typical of third-generation synchrotron sources. Further, this technique can be readily adapted for use with laboratory-based sources.
Turaev Torsion Invariants of 3-orbifolds

We construct a combinatorial invariant of 3-orbifolds with singular set a link that generalizes the Turaev torsion invariant of 3-manifolds. We give several gluing formulas from which we derive two consequences. The first is an understanding of how the components of the invariant change when we remove a curve from the singular set. The second is a formula relating the invariant of the 3-orbifold to the Turaev torsion invariant of the underlying 3-manifold in the case when the singular set is a nullhomologous knot.
Contractive multipliers from Hardy space to weighted Hardy space

It is shown how any contractive multiplier from the Hardy space to a weighted Hardy space $H^{2}_{\bbeta}$ can be factored as a fixed factor composed with the classical Schur multiplier (contractive multiplier between Hardy spaces). The result is applied to get results on interpolation for a Hardy-to-weighted-Hardy contractive multiplier class.
Bridging AIC and BIC: A New Criterion for Autoregression

To address order selection for an autoregressive model fitted to time series data, we propose a new information criterion. It has the benefits of the two well-known model selection techniques: the Akaike information criterion and the Bayesian information criterion. When the data are generated from a finite-order autoregression, the Bayesian information criterion is known to be consistent, and so is the new criterion. When the true order is infinity or suitably high with respect to the sample size, the Akaike information criterion is known to be efficient in the sense that its predictive performance is asymptotically equivalent to the best offered by the candidate models; in this case, the new criterion behaves in a similar manner. Different from the two classical criteria, the proposed criterion adaptively achieves either consistency or efficiency depending on the underlying true model. In practice, where the observed time series is given without any prior information about the model specification, the proposed order selection criterion is more flexible and reliable compared with classical approaches. Numerical results are presented, demonstrating the adaptivity of the proposed technique when applied to various data sets.
Distributed Linear Parameter Estimation: Asymptotically Efficient Adaptive Strategies

This paper considers the problem of distributed adaptive linear parameter estimation in multiagent inference networks. Local sensing model information is only partially available at the agents, and interagent communication is assumed to be unpredictable. The paper develops a generic mixed time-scale stochastic procedure consisting of simultaneous distributed learning and estimation, in which the agents adaptively assess their relative observation quality over time and fuse the innovations accordingly. Under rather weak assumptions on the statistical model and the interagent communication, it is shown that, by properly tuning the consensus potential with respect to the innovation potential, the asymptotic information rate loss incurred in the learning process may be made negligible. As such, it is shown that the agent estimates are asymptotically efficient, in that their asymptotic covariance coincides with that of a centralized estimator (the inverse of the centralized Fisher information rate for Gaussian...
Leader-follower based coalition formation in large-scale UAV networks, a quantum evolutionary approach

The problem of decentralized multiple Point of Interests (Pols) detection and associated task completion in an unknown environment with multiple resource-constrained and self-interested Unmanned Aerial Vehicles (UAVs) is studied. The UAVs form several coalitions to efficiently complete the compound tasks which are impossible to be performed individually. The objectives of such coalition formation are to firstly minimize resource consumption in completing the encountered tasks on time, secondly to enhance the reliability of the coalitions, and lastly in segregating the most trusted UAVs amid the self interested of them. As many previous publications have merely focused upon minimizing costs, this study considers a multi-objective optimization coalition formation problem that considers the three aforementioned objectives. In doing so, a leader-follower-inspired coalition formation algorithm amalgamating the three objectives to address the problem of the computational complexity of coalition formation in large-scale UAV networks is proposed. This algorithm attempts to form the coalitions with minimally exceeding the required resources for the encountered tasks while maximizing the number of completed tasks. The proposed algorithm is based on Quantum Evolutionary Algorithms (QEA) which are a combination of quantum computing and evolutionary algorithms. Results from simulations show that the proposed algorithm significantly outperforms the existing coalition formation algorithms such as merge-and-split and a famous multi-objective genetic algorithm called NSGA-II 1.
Density level set estimation on manifolds with DBSCAN

We show that DBSCAN can estimate the connected components of the λ-density level set {x : f(x) ≥ λ} given n i.i.d. samples from an unknown density f. We characterize the regularity of the level set boundaries using parameter β < 0 and analyze the estimation error under the Hausdorff metric. When the data lies in ℝD we obtain a rate of O(n-1/(2/β+D)), which matches known lower bounds up to logarithmic factors. When the data lies on an embedded unknown d-dimensional manifold in ℝD, then we obtain a rate of O(n-1/(2βd·max{1,β)). Finally, we provide adaptive parameter tuning in order to attain these rates with no a priori knowledge of the intrinsic dimension, density, or β.
MIT at SemEval-2017 Task 10: Relation Extraction with Convolutional Neural Networks

Over 50 million scholarly articles have been published: they constitute a unique repository of knowledge. In particular, one may infer from them relations between scientific concepts. Artificial neural networks have recently been explored for relation extraction. In this work, we continue this line of work and present a system based on a convolutional neural network to extract relations. Our model ranked first in the SemEval-2017 task 10 (ScienceIE) for relation extraction in scientific articles (subtask C).
Graphs, skeleta and reconstruction of polytopes

A renowned theorem of Blind and Mani, with a constructive proof by Kalai and an efficiency proof by Friedman, shows that the whole face lattice of a simple polytope can be determined from its graph. This is part of a broader story of reconstructing face lattices from partial information, first considered comprehensively in Grunbaum’s 1967 book. This survey paper includes varied results and open questions by many researchers on simplicial polytopes, nearly simple polytopes, cubical polytopes, zonotopes, crosspolytopes, and Eulerian posets.
The area of convex projective surfaces and Fock–Goncharov coordinates

The area of a convex projective surface of genus g ≥ 2 is at least (g − 1)π2/2 + ∥τ∥2/8 where τ = (log ti) is the vector of triangle invariants of Bonahon–Dreyer and ti are the Fock–Goncharov tripl...
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking

Model compression is essential for serving large deep neural nets on devices with limited resources or applications that require real-time responses. For advanced NLP problems, a neural language model usually consists of recurrent layers (e.g., using LSTM cells), an embedding matrix for representing input tokens, and a softmax layer for generating output tokens. For problems with a very large vocabulary size, the embedding and the softmax matrices can account for more than half of the model size. For instance, the bigLSTM model achieves state-of-the-art performance on the One-Billion-Word (OBW) dataset with around 800k vocabulary, and its word embedding and softmax matrices use more than 6GBytes space, and are responsible for over 90\% of the model parameters. In this paper, we propose GroupReduce, a novel compression method for neural language models, based on vocabulary-partition (block) based low-rank matrix approximation and the inherent frequency distribution of tokens (the power-law distribution of words). We start by grouping words into $c$ blocks based on their frequency, and then refine the clustering iteratively by constructing weighted low-rank approximation for each block, where the weights are based the frequencies of the words in the block. The experimental results show our method can significantly outperform traditional compression methods such as low-rank approximation and pruning. On the OBW dataset, our method achieved 6.6x compression rate for the embedding and softmax matrices, and when combined with quantization, our method can achieve 26x compression rate without losing prediction accuracy.