cssi/SciSciGPT-SciSciNet huggingface dataset:
Physiological Importance of Poly‐(R)‐3‐hydroxybutyrates

Poly-(R)-3-hydroxybutyrates (PHB), linear polymers of (R)-3-hydroxybutyrate, are components of all biological cells in which short polymers (<200 monomer residues) are covalently attached to certain proteins and/or noncovalently associated with polyphosphates - inorganic polyphosphate (polyP), RNA, and DNA. The low concentrations, lack of unusual atoms or functional groups, and flexible backbones of this complexed PHB, referred to as cPHB, make them invisible to many analytical procedures; whereas other physical properties - water-insolubility, high intrinsic viscosity, temperature sensitivity, multiple bonding interactions with other molecules - make them requisite participants in vital physiological processes as well as contributors to the development of certain diseases.
Supraicosahedral polyhedra in carboranes and metallacarboranes: The role of local vertex environments in determining polyhedral topology and the anomaly of 13-vertex closo polyhedra☆

Metal-free carboranes having 13 vertices are anomalous since their closo polyhedra having the expected 28 skeletal electrons are not the usual deltahedra with exclusively triangular faces but instead polyhedra with one or two trapezoidal faces obtained by removal of one or more edges from the corresponding 13-vertex deltahedron. Removal of such edges converts degree 6 boron vertices in the 13-vertex deltahedron into more favorable degree 5 boron vertices while lowering the degree of nearby carbon vertices. Thus the anomaly of the 13-vertex carborane closo polyhedron can be rationalized by the preference of boron for degree 5 vertices. The 12-vertex tetracarbon carborane (CH3)4C4B8H8 with a nido electron count of 28 skeletal electrons but with two quadrilateral faces has a solid state structure derived from a 13-vertex “closo” polyhedron with one quadrilateral face by removal of a degree 4 vertex to give the second quadrilateral face. However, the corresponding tetraethyl derivative (C2H5)4C4B8H8 has a different solid state structure derived from removal of a degree 6 vertex from an unusual 13-vertex deltahedron with three degree 6 vertices to give an open hexagonal face rather than two quadrilateral faces. In contrast to the 13-vertex closo polyhedra, the 14-vertex closo polyhedron is a true deltahedron, namely the D6d bicapped hexagonal antiprism, which is found in a carborane derivative as well as in several dimetallacarboranes with the metal atoms always at the degree 6 vertices. However, the 15-vertex closo polyhedron, so far found only in the metallaborane 1,2-μ-(CH2)3C2B12H12Ru(η6-p-cymene), is a non-deltahedron with one quadrilateral face.
Vanadium-51 MAS and Static NMR Studies of the Binary V2O5−WO3 System

Solid-state NMR spectra showing single-quantum excitation of the vanadium-51 (I = 7/2) central and six satellite transitions were obtained for polycrystalline V2O5 and x%V2O5−(100 − x%)WO3 (10 mol % ≤ x ≤ 40 mol %) solids by magic angle spinning (MAS) and static NMR spectroscopies. All MAS spectra show full spinning sideband manifolds resulting from incomplete averaging of the chemical shift and quadrupolar interaction anisotropies. Chemical shift parameters (δiso, δaniso, ηcs) and quadrupolar parameters (CQ, ηQ) were obtained by simulation of both MAS and static spectra. A single vanadium site was observed in the nominally 40 mol % V2O5−60 mol % WO3 and 30 mol % V2O5−70 mol % WO3 compositions. Interpretation of NMR spectral parameters suggests that the vanadium in this single site resides in a square pyramid-like oxygen coordination environment. Three sites were observed for the nominally 20 mol % V2O5−80 mol % WO3 and 10 mol % V2O5−90 mol % WO3 compositions. The spectral parameters for the three sites a...
K2SrIn7: An Electron-Deficient Indium Network Structure That Reflects Limitations of Cation Accommodation. Synthesis, Structure, and Bonding

A new phase in the K-Sr-In system was discovered following direct fusion of the neat elements in a niobium tube at 900 degrees C and equilibration at 700 degrees C for 5 days. Single-crystal X-ray diffraction analysis reveals that K(2)SrIn(7) crystallizes in an orthorhombic system, space group Cmcm, Z = 4, a = 5.0455(5) A, b = 11.960(2) A, c = 19.762(4) A. The structure contains a three-dimensional In network built of sheets of condensed pentagonal prismatic columns interbonded along. Two rather different types of channels are separately occupied by K and Sr atoms, the latter centered in 15-atom indium polyhedra. Band structure calculations and resistivity and susceptibility measurements indicate that the compound is metallic and diamagnetic. The one-electron deficiency in the valence band per formula unit brought on by the limited cation count is analyzed in terms of the character of the bonding, some of that from multicenter In bonding falling above E(F).
Lithosphere and shallow asthenosphere rheology from observations of post-earthquake relaxation

Abstract In tectonically active regions, post-earthquake motions are generally shaped by a combination of continued fault slippage (afterslip) on a timescale of days to months and viscoelastic relaxation of the lower crust and upper mantle on a timescale of days to years. Transient crustal motions have been observed following numerous magnitude >~7 earthquakes in various tectonic settings: continental rift zones (Basin and Range), continental plate boundary zones (San Andreas fault corridor; Alaska; Turkey), subduction zones (Japan, Chile, Sumatra), ongoing continental collision zones (Arabia; Tibet), and mid-ocean rifting zones (Iceland). When afterslip can be discriminated from viscoelastic relaxation and when temporal coverage of the postseismic measurements is broad (i.e., geodetic surveys of at least several years duration are available), a wide spectrum of relaxation timescales are usually identified. Current temporal resolution and modeling approaches (e.g., Burgers body analog) allow identification of transient (Kelvin) and steady-state (Maxwell) viscosities that are operable in the short-term and long-term, respectively. I compile results from 40 studies of post-earthquake motions, augmented by ten studies of contemporary surface loading or unloading, that illuminate current estimates of transient and steady-state viscosity of the lower crust and/or uppermost mantle. Lower crust viscosity estimates range from ~1018 to 1021 Pa s, with most estimates near the upper end except in areas of overthickened crust. Mantle lithosphere and asthenosphere viscosity estimates are particularly abundant and yield a picture of transient viscosity ranging from ~1016 to 1019 Pa s and steady-state viscosity ranging from ~1018 to 1021 Pa s. To first order, both transient and steady-state viscosities are well correlated with regional heat flow, and steady-state viscosities are comparable with temperature and strain-rate dependent rock viscosities from laboratory-based flow laws.
Design and synthesis of 3,5-dialkylamino substituted 8H,10H-3(R),5(R),15b(S)-2,3,6,7-tetrahydro-1,5,3-dioxazepino[3,2-c]indolo[3,2-g]pteridine-7-ones

Abstract 3,5-Dialkylamino substituted 8H,10H,15b(S)-2,3,6,7-tetrahydro-1,5,3-dioxazepino[3,2-c]indolo[3,2-g]pteridine-7-one derivatives 6a-6e were synthesized as potential anticancer agents. Preliminary results showed that they were active as inhibitors of the growth of murine leukemia L1210 cells in vitro with IC50 -values of 4 to 24 μM.
Asymmetric Total Synthesis of Callystatin A: Asymmetric Aldol Additions with Titanium Enolates of Acyloxazolidinethiones

A number of highly cytotoxic polyketides, including the anguinomycins,1 leptofuranins,2 leptomycin,3 and kazusamycin,4 having similar gross chemical structures have been isolated from Streptomyces strains. Recently, a structurally related polyketide, callystatin A 1, was isolated from the marine sponge, Callyspongia truncata, in the Nagasaki Prefecture.5 Callystatin A shows remarkable in vitro cytotoxicity (IC50 ) 0.01 ng/mL) against KB cells. The relative and absolute stereostructure of callystatin A was established by a combination of spectroscopic methods and chemical synthesis.5-7 The limited quantities of callystatin A available from natural sources, as well as the possibility for carrying out syntheses and structure elucidation of the related antitumor antibiotics, prompted us to pursue a total synthesis of callystatin A.8 Here we disclose the asymmetric total synthesis of (-)-callystatin A exploiting our recently developed asymmetric aldol protocol with chlorotitanium enolates of acyl oxazolidinethiones.9 Strategically, E-selective olefination10 of aldehyde 2 (Scheme 1) with the phosphorane derived from tributylphosphonium salt 3 appeared to offer the most convergent assembly of callystatin A. Aldehyde 2 representing C1 to C12 would be constructed from a similar olefination between the masked pyranone aldehyde 4 (Scheme 2) and phosphonium salt 5 (Scheme 3). The C13 to C22 propionate fragment 3 was to be constructed through consecutive asymmetric aldol additions9 employing acyl oxazolidinethione 6 (Scheme 4). The synthesis of aldehyde 4 began with S-glycidol 7 as illustrated in Scheme 2. Protection of S-glycidol as its TBDPS ether followed by copper-catalyzed epoxide opening with vinylmagnesium bromide provided the alcohol 8 in 85% overall yield. Conversion of the secondary alcohol to the isopropoxy propenyl ether provided a mixed acetal which was exposed to the Grubbs catalyst11 to effect ring-closing metathesis to dihydropyran 9 (71% overall). Removal of the TBPDS protecting group with n-Bu4-
A new method for the synthesis of fluoro-carbohydrates and glycosides using selectfluor

This paper describes a high-yield, one-step synthesis of 2-deoxy-2-fluoro sugars and their glycosides from glycals using the available electrophilic fluorination reagent 1-chloromethyl-4-fluoro-1,4-diazoniabicyclo[2.2.2]octane bis(tetrafluoroborate) (Selectfluor) in the presence of a nucleophile. The method was further expanded to the synthesis of glycosyl fluorides and glycosides from anomeric hydroxy or thioglycoside derivatives.
Scalable, Continuous Evolution of Genes at Mutation Rates above Genomic Error Thresholds.

Directed evolution is a powerful approach for engineering biomolecules and understanding adaptation. However, experimental strategies for directed evolution are notoriously labor intensive and low throughput, limiting access to demanding functions, multiple functions in parallel, and the study of molecular evolution in replicate. We report OrthoRep, an orthogonal DNA polymerase-plasmid pair in yeast that stably mutates ∼100,000-fold faster than the host genome in vivo, exceeding the error threshold of genomic replication that causes single-generation extinction. User-defined genes in OrthoRep continuously and rapidly evolve through serial passaging, a highly straightforward and scalable process. Using OrthoRep, we evolved drug-resistant malarial dihydrofolate reductases (DHFRs) in 90 independent replicates. We uncovered a more complex fitness landscape than previously realized, including common adaptive trajectories constrained by epistasis, rare outcomes that avoid a frequent early adaptive mutation, and a suboptimal fitness peak that occasionally traps evolving populations. OrthoRep enables a new paradigm of routine, high-throughput evolution of biomolecular and cellular function.
Large molecular hyperpolarizabilities. Quantitative analysis of aromaticity and auxiliary donor-acceptor effects

The linear and nonlinear optical properties of donor−acceptor π-electron chromophores having conjugated bridges varying in aromaticity and electron excessivity are investigated using the INDO/1 semiempirical Hamiltonian. NLO response properties of such chromophores are more sensitive to the electron excessivity of the bridges than to bridge aromaticity. Electron-excessive/deficient heterocyclic bridges have lesser/greater tendency to deplete the electron density from the donor/acceptor groups and thus increase their donor/acceptor ability. Thus, electron-excessive heterocyclic bridges act as auxiliary donors while electron-deficient heterocyclic bridges act as auxiliary acceptors, significantly enhancing NLO response. Interposing charged five-membered auxiliary donor and acceptor fragments between strong donor or acceptor groups results in large computed second-order NLO response.
MAJIQ-SPEL: web-tool to interrogate classical and complex splicing variations from RNA-Seq data

Summary Analysis of RNA sequencing (RNA-Seq) data have highlighted the fact that most genes undergo alternative splicing (AS) and that these patterns are tightly regulated. Many of these events are complex, resulting in numerous possible isoforms that quickly become difficult to visualize, interpret and experimentally validate. To address these challenges we developed MAJIQ-SPEL, a web-tool that takes as input local splicing variations (LSVs) quantified from RNA-Seq data and provides users with visualization and quantification of gene isoforms associated with those. Importantly, MAJIQ-SPEL is able to handle both classical (binary) and complex, non-binary, splicing variations. Using a matching primer design algorithm it also suggests to users possible primers for experimental validation by RT-PCR and displays those, along with the matching protein domains affected by the LSV, on UCSC Genome Browser for further downstream analysis. Availability and implementation Program and code will be available at http://majiq.biociphers.org/majiq-spel. Supplementary information Supplementary data are available at Bioinformatics online.
Recent Developments in II-VI Diluted Magnetic Semiconductors

Much of the work in diluted magnetic semiconductors (DMS) in past years has focused on the alloys such as Cd1−xMnxTe. Recently, there has been an increasing accent on DMS alloys containing the transition metal ions Fe2+ and Co2+. We review here the properties of these new materials and compare them with the alloys. We also examine the novel opportunities afforded by the molecular beam epitaxy of epilayers and heterostructures containing the “metastable” zinc-blende phase of Cd1−xMnxSe.
Aryl to Aryl Palladium Migration in the Heck and Suzuki Coupling of o-Halobiaryls

A novel 1,4-palladium migration between the o- and o'-positions of biaryls has been observed in organopalladium intermediates derived from o-halobiaryls. The organopalladium intermediates generated by this migration have been trapped either by a Heck reaction employing ethyl acrylate or by Suzuki cross-coupling using arylboronic acids. This palladium migration can be activated or deactivated by choosing the appropriate reaction conditions. Chemical and computational evidence supports the presence of an equilibrium that correlates with the C-H acidity of the available arene positions.
Resource-guided program synthesis

This article presents resource-guided synthesis, a technique for synthesizing recursive programs that satisfy both a functional specification and a symbolic resource bound. The technique is type-directed and rests upon a novel type system that combines polymorphic refinement types with potential annotations of automatic amortized resource analysis. The type system enables efficient constraint-based type checking and can express precise refinement-based resource bounds. The proof of type soundness shows that synthesized programs are correct by construction. By tightly integrating program exploration and type checking, the synthesizer can leverage the user-provided resource bound to guide the search, eagerly rejecting incomplete programs that consume too many resources. An implementation in the resource-guided synthesizer ReSyn is used to evaluate the technique on a range of recursive data structure manipulations. The experiments show that ReSyn synthesizes programs that are asymptotically more efficient than those generated by a resource-agnostic synthesizer. Moreover, synthesis with ReSyn is faster than a naive combination of synthesis and resource analysis. ReSyn is also able to generate implementations that have a constant resource consumption for fixed input sizes, which can be used to mitigate side-channel attacks.
Prediction of Treatment Outcome for Autism from Structure of the Brain Based On Sure Independence Screening

Autism spectrum disorder (ASD) is a complex neurodevelop-mental disorder, and behavioral treatment interventions have shown promise for young children with ASD. However, there is limited progress in understanding the effect of each type of treatment. In this project, we aim to detect structural changes in the brain after treatment and select structural features associated with treatment outcomes. The difficulty in building large databases of patients who have received specific treatments and the high dimensionality of medical image analysis problems are the challenges in this work. To select predictive features and build accurate models, we use the sure independence screening (SIS) method. SIS is a theoretically and empirically validated method for ultra-high dimensional general linear models, and it achieves both predictive accuracy and correct feature selection by iterative feature selection. Compared with step-wise feature selection methods, SIS removes multiple features in each iteration and is computationally efficient. Compared with other linear models such as elastic-net regression, support vector regression (SVR) and partial least squares regression (PSLR), SIS achieves higher accuracy. We validated the superior performance of SIS in various experiments: First, we extract brain structural features from FreeSurfer, including cortical thickness, surface area, mean curvature and cortical volume. Next, we predict different measures of treatment outcomes based on structural features. We show that SIS achieves the highest correlation between prediction and measurements in all tasks. Furthermore, we report regions selected by SIS as biomarkers for ASD.
High-quality lithium niobate photonic crystal nanocavities

Lithium niobate (LN) exhibits unique material characteristics that have found many important applications. Scaling LN devices down to a nanoscopic scale can dramatically enhance light–matter interaction that would enable nonlinear and quantum photonic functionalities beyond the reach of conventional means. However, developing LN-based nanophotonic devices turns out to be nontrivial. Although significant efforts have been devoted to this in recent years, the LN photonic crystal structures developed to date exhibit fairly low quality (Q). Here we demonstrate LN photonic crystal nanobeam resonators with optical Q as high as 105, more than two orders of magnitude higher than other LN photonic crystal nanocavities reported to date. The high optical Q, together with tight mode confinement, leads to an extremely strong nonlinear photorefractive effect, with a resonance tuning rate of ∼0.64 GHz/aJ, or equivalently ∼84 MHz/photon, three orders of magnitude greater than other LN resonators. In particular, we observed an intriguing quenching of photorefraction that has never been reported before. The devices also exhibit strong optomechanical coupling with a gigahertz nanomechanical mode with a significant f·Q product of 1.47×1012 Hz. The demonstration of high-Q LN photonic crystal nanoresonators paves a crucial step toward LN nanophotonics that could integrate the outstanding material properties with versatile nanoscale device engineering for diverse and intriguing functionalities.
Effective Inference for Generative Neural Parsing.

Generative neural models have recently achieved state-of-the-art results for constituency parsing. However, without a feasible search procedure, their use has so far been limited to reranking the output of external parsers in which decoding is more tractable. We describe an alternative to the conventional action-level beam search used for discriminative neural models that enables us to decode directly in these generative models. We then show that by improving our basic candidate selection strategy and using a coarse pruning function, we can improve accuracy while exploring significantly less of the search space. Applied to the model of Choe and Charniak (2016), our inference procedure obtains 92.56 F1 on section 23 of the Penn Treebank, surpassing prior state-of-the-art results for single-model systems.
Finite generation of some cohomology rings via twisted tensor product and Anick resolutions

Abstract Over a field of prime characteristic p > 2 , we prove that the cohomology rings of some pointed Hopf algebras of dimension p 3 are finitely generated. These are Hopf algebras arising in the ongoing classification of finite dimensional pointed Hopf algebras in positive characteristic. They include bosonizations of Nichols algebras of Jordan type in a general setting. When p = 3 , we also consider their Hopf algebra liftings, that is Hopf algebras whose associated graded algebra with respect to the coradical filtration is given by such a bosonization. Our proofs are based on an algebra filtration and a lemma of Friedlander and Suslin, drawing on both twisted tensor product resolutions and Anick resolutions to locate the needed permanent cocycles in May spectral sequences.
Modal-set estimation with an application to clustering.

We present a first procedure that can estimate -- with statistical consistency guarantees -- any local-maxima of a density, under benign distributional conditions. The procedure estimates all such local maxima, or $\textit{modal-sets}$, of any bounded shape or dimension, including usual point-modes. In practice, modal-sets can arise as dense low-dimensional structures in noisy data, and more generally serve to better model the rich variety of locally-high-density structures in data. The procedure is then shown to be competitive on clustering applications, and moreover is quite stable to a wide range of settings of its tuning parameter.
Global optimality conditions for deep neural networks

We study the error landscape of deep linear and nonlinear neural networks with the squared error loss. Minimizing the loss of a deep linear neural network is a nonconvex problem, and despite recent progress, our understanding of this loss surface is still incomplete. For deep linear networks, we present necessary and sufficient conditions for a critical point of the risk function to be a global minimum. Surprisingly, our conditions provide an efficiently checkable test for global optimality, while such tests are typically intractable in nonconvex optimization. We further extend these results to deep nonlinear neural networks and prove similar sufficient conditions for global optimality, albeit in a more limited function space setting.
Mixture models, robustness, and sum of squares proofs

We use the Sum of Squares method to develop new efficient algorithms for learning well-separated mixtures of Gaussians and robust mean estimation, both in high dimensions, that substantially improve upon the statistical guarantees achieved by previous efficient algorithms. Our contributions are: Mixture models with separated means: We study mixtures of poly(k)-many k-dimensional distributions where the means of every pair of distributions are separated by at least ke. In the special case of spherical Gaussian mixtures, we give a kO(1/e)-time algorithm that learns the means assuming separation at least ke, for any e> 0. This is the first algorithm to improve on greedy (“single-linkage”) and spectral clustering, breaking a long-standing barrier for efficient algorithms at separation k1/4. Robust estimation: When an unknown (1−e)-fraction of X1,…,Xn are chosen from a sub-Gaussian distribution with mean µ but the remaining points are chosen adversarially, we give an algorithm recovering µ to error e1−1/t in time kO(t), so long as sub-Gaussian-ness up to O(t) moments can be certified by a Sum of Squares proof. This is the first polynomial-time algorithm with guarantees approaching the information-theoretic limit for non-Gaussian distributions. Previous algorithms could not achieve error better than e1/2. As a corollary, we achieve similar results for robust covariance estimation. Both of these results are based on a unified technique. Inspired by recent algorithms of Diakonikolas et al. in robust statistics, we devise an SDP based on the Sum of Squares method for the following setting: given X1,…,Xn ∈ ℝk for large k and n = poly(k) with the promise that a subset of X1,…,Xn were sampled from a probability distribution with bounded moments, recover some information about that distribution.
Unified Acceleration Method for Packing and Covering Problems via Diameter Reduction

In a series of recent breakthroughs, Allen-Zhu and Orecchia [Allen-Zhu/Orecchia, STOC 2015; Allen-Zhu/Orecchia, SODA 2015] leveraged insights from the linear coupling method [Allen-Zhu/Oreccia, arXiv 2014], which is a first-order optimization scheme, to provide improved algorithms for packing and covering linear programs. The result in [Allen-Zhu/Orecchia, STOC 2015] is particularly interesting, as the algorithm for packing LP achieves both width-independence and Nesterov-like acceleration, which was not known to be possible before. Somewhat surprisingly, however, while the dependence of the convergence rate on the error parameter epsilon for packing problems was improved to O(1/epsilon), which corresponds to what accelerated gradient methods are designed to achieve, the dependence for covering problems was only improved to O(1/epsilon^{1.5}), and even that required a different more complicated algorithm, rather than from Nesterov-like acceleration. Given the primal-dual connection between packing and covering problems and since previous algorithms for these very related problems have led to the same epsilon dependence, this discrepancy is surprising, and it leaves open the question of the exact role that the linear coupling is playing in coordinating the complementary gradient and mirror descent step of the algorithm. In this paper, we clarify these issues, illustrating that the linear coupling method can lead to improved O(1/epsilon) dependence for both packing and covering problems in a unified manner, i.e., with the same algorithm and almost identical analysis. Our main technical result is a novel dimension lifting method that reduces the coordinate-wise diameters of the feasible region for covering LPs, which is the key structural property to enable the same Nesterov-like acceleration as in the case of packing LPs. The technique is of independent interest and that may be useful in applying the accelerated linear coupling method to other combinatorial problems.
A Thomason model structure on the category of small n–fold categories

We construct a cofibrantly generated Quillen model structure on the category of small n‐fold categories and prove that it is Quillen equivalent to the standard model structure on the category of simplicial sets. An n‐fold functor is a weak equivalence if and only if the diagonal of its n‐fold nerve is a weak equivalence of simplicial sets. This is an n‐fold analogue to Thomason’s Quillen model structure on Cat. We introduce an n‐fold Grothendieck construction for multisimplicial sets, and prove that it is a homotopy inverse to the n‐fold nerve. As a consequence, we completely prove that the unit and counit of the adjunction between simplicial sets and n‐fold categories are natural weak equivalences. 18D05, 18G55; 55U10, 55P99 An n‐fold category is a higher and wider categorical structure obtained by n applications of the internal category construction. In this paper we study the homotopy theory of n‐fold categories. Our main result is Theorem 9.28. Namely, we have constructed a cofibrantly generated model structure on the category of small n‐fold categories in which an n‐fold functor is a weak equivalence if and only if its nerve is a diagonal weak equivalence, this model structure is Quillen equivalent to the standard one on the category of simplicial sets, and the unit and counit of the Quillen equivalence are natural weak equivalences. As a consequence, topological spaces have combinatorial models in terms of n‐fold categories. Our main tools are model category theory, the n‐fold nerve and an n‐fold Grothendieck construction for multisimplicial sets. Notions of nerve and versions of the Grothendieck construction are very prominent in homotopy theory and higher category theory, as we now explain. The Thomason model structure on Cat is also often present, at least implicitly. The Grothendieck nerve of a category and the Grothendieck construction for functors are fundamental tools in homotopy theory. Theorems A and B of Quillen [75], and Thomason’s theorem [84] on Grothendieck constructions as models for certain
From quasirandom graphs to graph limits and graphlets

Abstract We generalize the notion of quasirandomness which concerns a class of equivalent properties that random graphs satisfy. We show that the convergence of a graph sequence under the spectral distance is equivalent to the convergence using the (normalized) cut distance. The resulting graph limit is called graphlet. We then consider several families of graphlets and, in particular, we characterize quasirandom graphlets with low ranks for both dense and sparse graphs. For example, we show that a graph sequence G n , for n = 1 , 2 , … , converges to a graphlet of rank 2 (i.e., all normalized eigenvalues G n converge to 0 except for two eigenvalues converging to 1 and ρ > 0 ) if and only if the graphlet is the union of 2 quasirandom graphlets.
Assessing the Impact of Representational and Contextual Problem Features on Student Use of Right-Hand Rules.

Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few studies have had the resolution to explore student use of right-hand rules in detail. This study reviews literature in several disciplines, including spatial cognition, to identify ten contextual and representational problem features that are most likely to influence performance on problems requiring a right-hand rule. Two quantitative measures of performance (correctness and response time) and two qualitative measures (methods used and type of errors made) were used to explore the impact of these problem features on student performance. Quantitative results are consistent with expectations from the literature, but reveal that some features (such as the type of reasoning required and the physical awkwardness of using a right-hand rule) have a greater impact than others (such as whether the vectors are placed together or separate). Additional insight is gained by the qualitative analysis, including identifying sources of difficulty not previously discussed in the literature and revealing that the use of supplemental methods, such as physically rotating the paper, can mitigate errors associated with certain features.
Abacus models for parabolic quotients of affine Weyl groups

We introduce abacus diagrams that describe the minimal length coset representatives of affine Weyl groups in types C˜/C, B˜/D, B˜/B and D˜/D. These abacus diagrams use a realization of the affine Weyl group C˜ due to Eriksson to generalize a construction of James for the symmetric group. We also describe several combinatorial models for these parabolic quotients that generalize classical results in type A˜ related to core partitions.
Complete minors, independent sets, and chordal graphs

The Hadwiger number h(G) of a graph G is the maximum size of a complete minor of G. Hadwiger’s Conjecture states that h(G) ≥ χ(G). Since χ(G)α(G) ≥ |V (G)|, Hadwiger’s Conjecture implies that α(G)h(G) ≥ |V (G)|. We show that (2α(G)− dlogτ (τα(G)/2)e)h(G) ≥ |V (G)| where τ ≈ 6.83. For graphs with α(G) ≥ 14, this improves on a recent result of Kawarabayashi and Song who showed (2α(G)− 2)h(G) ≥ |V (G)| when α(G) ≥ 3.
Free resolutions of some Schubert singularities in the Lagrangian Grassmannian

In this paper we construct free resolutions of certain class of closed subvarieties of affine space of symmetric matrices (of a given size). Our class covers the symmetric determinantal varieties (i.e., determinantal varieties in the space of symmetric matrices), whose resolutions were first constructed by Jozefiak-Pragacz-Weyman. Our approach follows the techniques developed in Free Resolutions of Some Schubert Singularities by Kummini-Lakshmibai-Sastry-Seshadri, and uses the geometry of Schubert varieties.
On an observation of Sibony

It is shown that if the boundary of a Reinhardt domain in $\mathbb{C}^n$ contains the origin, each holomorphic function on the domain which is infinitely many times differentiable up to the boundary extends holomorphically to a neighborhood of the origin.
Mode-Target Games: Reactive Synthesis for Control Applications

In this paper, we introduce a class of linear temporal logic (LTL) specifications for which the problem of synthesizing controllers can be solved in polynomial time. The new class of specifications is an LTL fragment that we term Mode Target (MT) and is inspired by numerous control applications where there are modes and corresponding (possibly multiple) targets for each mode. We formulate the problem of synthesizing a controller enforcing an MT specification as a game and provide an algorithm that requires $O(\sum _i t_i n^2)$ symbolic steps, where $n$ is the number of states in the game graph, and $t_i$ is the number of targets corresponding to mode $i$ .
The asymptotic trace norm of random circulants and the graph energy

We compute the expected normalized trace norm (matrix/graph energy) of random symmetric band circulant matrices and graphs in the limit of large sizes, and obtain explicit bounds on the rate of convergence to the limit, and on the probabilities of large deviations. We also show that random symmetric band Toeplitz matrices have the same limit norm assuming that their band widths remain small relative to their sizes. We compare the limit norms across a range of related random matrix and graph ensembles.
Low coherence unit norm tight frames

Equiangular tight frames (ETFs) have found significant applications in signal processing and coding theory due to their robustness to noise and transmission losses. ETFs are characterized by the fa...
The Orlik-Terao algebra and the cohomology of configuration space

ABSTRACTWe give a recursive algorithm for computing the Orlik-Terao algebra of the Coxeter arrangement of type An − 1 as a graded representation of Sn, and we give a conjectural description of this representation in terms of the cohomology of the configuration space of n points in SU(2) modulo translation. We also give a version of this conjecture for more general graphical arrangements.
Distributed resource allocation on dynamic networks in quadratic time

Abstract We consider the problem of allocating a fixed amount of resource among nodes in a network when each node suffers a cost which is a convex function of the amount of resource allocated to it. We propose a new deterministic and distributed protocol for this problem. Our main result is that the associated convergence time for the global objective scales quadratically in the number of nodes on any sequence of time-varying undirected graphs satisfying a long-term connectivity condition.
Semiconcavity of viscosity solutions for a class of degenerate elliptic integro-differential equations in $\\mathbb R^n$

This paper is concerned with semiconcavity of viscosity solutions for a class of degen- erate elliptic integro-differential equations in R n . This class of equations includes Bellman equations containing operators of Levy-Ito type. Holder and Lipschitz continuity of viscosity solutions for a more general class of degenerate elliptic integro-differential equations are also provided. (u(x + j(x,ξ)) − u(x) − B1(0)(ξ)Du(x) · j(x,ξ))µ(dξ), where B1(0) denotes the indicator function of the unit ball B1(0), j(x,ξ) is a function that determines the size of the jumps for the diffusion related to the operator I, and µ is a Levy measure. The Levy measure µ is a Borel measure on R n \ {0} satisfying
Adversarial Feature Learning

The ability of the Generative Adversarial Networks (GANs) framework to learn generative models mapping from simple latent distributions to arbitrarily complex data distributions has been demonstrated empirically, with compelling results showing that the latent space of such generators captures semantic variation in the data distribution. Intuitively, models trained to predict these semantic latent representations given data may serve as useful feature representations for auxiliary problems where semantics are relevant. However, in their existing form, GANs have no means of learning the inverse mapping -- projecting data back into the latent space. We propose Bidirectional Generative Adversarial Networks (BiGANs) as a means of learning this inverse mapping, and demonstrate that the resulting learned feature representation is useful for auxiliary supervised discrimination tasks, competitive with contemporary approaches to unsupervised and self-supervised feature learning.
Refined limit multiplicity for varying conductor

Recent results by Abert, Bergeron, Biringer et al., Finis, Lapid and Mueller, and Shin and Templier have extended the limit multiplicity property to quite general classes of groups and sequences of level subgroups. Automorphic representations in the limit multiplicity problem are traditionally counted with multiplicity according to the number of fixed vectors of a level subgroup; our goal is to perform a slightly more refined analysis and count only automorphic representations with a given conductor with multiplicity 1.
Discovering Conservation Laws from Data for Control

Conserved quantities, i.e. constants of motion, are critical for characterizing many dynamical systems in science and engineering. These quantities are related to underlying symmetries and they provide fundamental knowledge about physical laws, describe the evolution of the system, and enable system reduction. In this work, we formulate a data-driven architecture for discovering conserved quantities based on Koopman theory. The Koopman operator has emerged as a principled linear embedding of nonlinear dynamics, and its eigenfunctions establish intrinsic coordinates along which the dynamics behave linearly. Interestingly, eigenfunctions of the Koopman operator associated with vanishing eigenvalues correspond to conserved quantities of the underlying system. In this paper, we show that these invariants may be identified with data-driven regression and power series expansions, based on the infinitesimal generator of the Koopman operator. We further establish a connection between the Koopman framework, conserved quantities, and the Lie-Poisson bracket. This data-driven method for discovering conserved quantities is demonstrated on the three-dimensional rigid body equations, where we simultaneously discover the total energy and angular momentum and use these intrinsic coordinates to develop a model predictive controller to track a given reference value.
Steering Output Style and Topic in Neural Response Generation

We propose simple and flexible training and decoding methods for influencing output style and topic in neural encoder-decoder based language generation. This capability is desirable in a variety of applications, including conversational systems, where successful agents need to produce language in a specific style and generate responses steered by a human puppeteer or external knowledge. We decompose the neural generation process into empirically easier sub-problems: a faithfulness model and a decoding method based on selective-sampling. We also describe training and sampling algorithms that bias the generation process with a specific language style restriction, or a topic restriction. Human evaluation results show that our proposed methods are able to to restrict style and topic without degrading output quality in conversational tasks.
DeepCough: A deep convolutional neural network in a wearable cough detection system

In this paper, we present a system that employs a wearable acoustic sensor and a deep convolutional neural network for detecting coughs. We evaluate the performance of our system on 14 healthy volunteers and compare it to that of other cough detection systems that have been reported in the literature. Experimental results show that our system achieves a classification sensitivity of 95.1% and a specificity of 99.5%.
Perturbation of the eigenvectors of the graph Laplacian: Application to image denoising

Abstract Patch-based denoising algorithms currently provide the optimal techniques to restore an image. These algorithms denoise patches locally in “patch-space”. In contrast, we propose in this paper a simple method that uses the eigenvectors of the Laplacian of the patch-graph to denoise the image. Experiments demonstrate that our denoising algorithm outperforms the denoising gold-standards. We provide an analysis of the algorithm based on recent results on the perturbation of kernel matrices (El Karoui, 2010) [1,2] , and theoretical analyses of patch denoising algorithms (Levin et al., 2012) [3] , (Taylor and Meyer, 2012) [4] .
The Weil-étale fundamental group of a number field II

We define the fundamental group underlying the Weil-etale cohomology of number rings. To this aim, we define the Weil-etale topos as a refinement of the Weil-etale sites introduced by Lichtenbaum (Ann Math 170(2):657–683, 2009). We show that the (small) Weil-etale topos of a smooth projective curve defined in this paper is equivalent to the natural definition. Then we compute the Weil-etale fundamental group of an open subscheme of the spectrum of a number ring. Our fundamental group is a projective system of locally compact topological groups, which represents first degree cohomology with coefficients in locally compact abelian groups. We apply this result to compute the Weil-etale cohomology in low degrees and to prove that the Weil-etale topos of a number ring satisfies the expected properties of the conjectural Lichtenbaum topos.
A mass-decreasing flow in dimension three

In this article, we introduce a mass-decreasing flow for asymptotically flat three-manifolds with nonnegative scalar curvature. This flow is defined by iterating a suitable Ricci flow with surgery and conformal rescalings and has a number of nice properties. In particular, wormholes pinch off and nontrivial spherical space forms bubble off in finite time. Moreover, a noncompact variant of the Perelman-energy is monotone along the flow. Assuming a certain inequality between the mass and this Perelman-energy a priori, we can prove that the flow squeezes out all the initial mass.
On the birational geometry of schubert varieties

We classify all Q-factorializations of (co)minuscule Schubert varieties by using their Mori dream space structure. As a corollary we obtain a description of all IH-small resolutions of (co)minuscule Schubert varieties generalizing results of Perrin. We improve his results by including algebraically closed fields of positive characteristic and cominuscule Schubert varieties. Moreover, the use of Q-factorializations and Mori dream spaces simplifies the arguments substantially.
Shape Analysis of Framed Space Curves

In the elastic shape analysis approach to shape matching and object classification, plane curves are represented as points in an infinite-dimensional Riemannian manifold, wherein shape dissimilarity is measured by geodesic distance. A remarkable result of Younes, Michor, Shah and Mumford says that the space of closed planar shapes, endowed with a natural metric, is isometric to an infinite-dimensional Grassmann manifold via the so-called square root transform. This result facilitates efficient shape comparison by virtue of explicit descriptions of Grassmannian geodesics. In this paper, we extend this shape analysis framework to treat shapes of framed space curves. By considering framed curves, we are able to generalize the square root transform by using quaternionic arithmetic and properties of the Hopf fibration. Under our coordinate transformation, the space of closed framed curves corresponds to an infinite-dimensional complex Grassmannian. This allows us to describe geodesics in framed curve space explicitly. We are also able to produce explicit geodesics between closed, unframed space curves by studying the action of the loop group of the circle on the Grassmann manifold. We apply our results to compute means for collections of space curves and to perform statistical analysis of circular DNA molecule shapes.
Accelerated Wirtinger Flow for Multiplexed Fourier Ptychographic Microscopy

Fourier ptychographic microscopy enables gigapixel-scale imaging, with both large field-of-view and high resolution. Using a set of low-resolution images that are recorded under varying illumination angles, the goal is to computationally reconstruct high-resolution phase and amplitude images. To increase temporal resolution, one may use multiplexed measurements where the sample is illuminated simultaneously from a subset of the angles. In this paper, we develop an algorithm for Fourier ptychographic microscopy with such multiplexed illumination. Specifically, we consider gradient descent type updates and propose an analytical step size that ensures the convergence of the iterates to a stationary point. Furthermore, we propose an accelerated version of our algorithm (with the same step size) which significantly improves the convergence speed. We demonstrate that the practical performance of our algorithm is identical to the case where the step size is manually tuned. Finally, we apply our parameter-free approach to real data and validate its applicability.
Context Dependent Semantic Parsing over Temporally Structured Data

We describe a new semantic parsing setting that allows users to query the system using both natural language questions and actions within a graphical user interface. Multiple time series belonging to an entity of interest are stored in a database and the user interacts with the system to obtain a better understanding of the entity’s state and behavior, entailing sequences of actions and questions whose answers may depend on previous factual or navigational interactions. We design an LSTM-based encoder-decoder architecture that models context dependency through copying mechanisms and multiple levels of attention over inputs and previous outputs. When trained to predict tokens using supervised learning, the proposed architecture substantially outperforms standard sequence generation baselines. Training the architecture using policy gradient leads to further improvements in performance, reaching a sequence-level accuracy of 88.7% on artificial data and 74.8% on real data.
Characterization and Classification of Human Body Channel as a function of Excitation and Termination Modalities

Human Body Communication (HBC) has recently emerged as an alternative to radio frequency transmission for connecting devices on and in the human body with order(s) of magnitude lower energy. The communication between these devices can give rise to different scenarios, which can be classified as wearable-wearable, wearable-machine, machine-machine interactions. In this paper, for the first time, the human body channel characteristics is measured for a wide range of such possible scenarios (14 vs. a few in previous literature) and classified according to the form-factor of the transmitter and receiver. The effect of excitation/termination configurations on the channel loss is also explored, which helps explain the previously unexplained wide variation in HBC Channel measurements. Measurement results show that wearable-wearable interaction has the maximum loss (upto −50 dB) followed by wearable-machine and machinemachine interaction (min loss of 0.5 dB), primarily due to the small ground size of the wearable devices. Among the excitation configurations, differential excitation is suitable for small channel length whereas single ended is better for longer channel.