cssi/SciSciGPT-SciSciNet huggingface dataset:
Synthesis of the FR900482 Tetracyclic Ring System by Oxidation of A 2,3-Dihydro-1H-Pyrrolo[1, 2-a]Indole Derivative

Abstract The tetracyclic FR900482 ring skeleton has been synthesized from the 2,3-dihydro-1H-pyrrolo[1,2-a]indole derivative 5. Treatment of 5 with osmium tetraoxide, hydrogen sulfide, magnesium monoperoxyphthalic acid (MMPP), and triphenylphosphine resulted in the formation of 12.
Diethyl (N-Methoxy-N-methylcarbamoylmethyl)phosphonate - A Useful Emmons-Horner Wittig Reagent

Abstract Diethy (N-methoxy-N-methylcarbamoylmethyl)phosphonate ( 1 ) is easily prepared by heating 2-chloro-N-methoxy-N-methylethanamide and triethylphosphite. Reagent 1 is useful for converting aldehydes and ketones into compounds containing an α,β-unsaturated N-methoxy-N-methylamide group with high E selectivity.
Synthesis and characterization of K8-x(H2) ySi46

A hydrogen-containing inorganic clathrate with the nominal composition, K(7)(H(2))(3)Si(46), has been prepared in 98% yield by the reaction of K(4)Si(4) with NH(4)Br. Rietveld refinement of the powder X-ray diffraction data is consistent with the clathrate type I structure. Elemental analysis and (1)H MAS NMR confirmed the presence of hydrogen in this material. Type I clathrate structure is built up from a Si framework with two types of cages where the guest species, in this case K and H(2), can reside: a large cage composed of 24 Si, in which the guest resides in the 6d position, and a smaller one composed of 20 Si, in which the guest occupies the 2a position (cubic space group Pm3n). Potassium occupancy was examined using spherical aberration (Cs) corrected scanning transmission electron microscopy (STEM). The high-angle annular dark-field (HAADF) STEM experimental and simulated images indicated that the K is deficient in both the 2a and the 6d sites. (1)H and (29)Si MAS NMR are consistent with the presence of H(2) in a restricted environment and the clathrate I structure, respectively. FTIR and (29)Si{(1)H} CP MAS NMR results show no evidence for a Si-H bond, suggesting that hydrogen is present as H(2) in interstitial sites. Thermal gravimetry (TG) mass spectrometry (MS) provide additional confirmation of H(2) with hydrogen loss at approximately 400 degrees C.
Thermoresponsive Hydrogels in Catalysis

The tunable properties of thermoresponsive physical hydrogels recently found application in catalysis. The most relevant examples are described in this perspective article. Novel concepts are especially highlighted through the beneficial effects of thermoresponsive hydrogels on the catalytic performance. Their scope and future developments are also addressed.
Naturally Chiral Metal Surfaces as Enantiospecific Adsorbents

The creation of solid surfaces with intrinsic chirality is one promising route for developing novel enantiospecific processes. This paper focuses on high Miller index surfaces of pure metals such a...
An insight into the aromaticity of fullerene anions: Experimental evidence for diamagnetic ring currents in the five-membered rings of C606- and C706-

Reduction of the two "closed" (6,6) methanofullerenes, (6,6)C61H2 (1) and (6,6)C71H2 (5), to the corresponding hexaanions with lithium metal causes the bridgehead-bridgehead bonds to open, at least partially, and this change gives rise to diamagnetic ring currents in the resulting homoconjugated six- membered rings (6-MRs). These new ring currents shield the overlying hydrogen atoms on the methylene bridge and induce upfield shifts of 1.60 and 0.11 ppm in their 1 H NMR resonances, respectively. Analogous reduction of the already "open" (5,6)methanofullerenes, (5,6)C61H2 (2) and (5,6)C71H2 (3 and 4), only slightly enhances the shielding of the hydrogen atoms over the homoconjugated 6-MRs (upfield shifts of 0.13, 0.68, and 0.14 ppm, respectively) but leads to exceptionally strong diamagnetic ring currents in the homoconjugated five- membered rings (5-MRs), as evidenced by dramatic shielding of the hydrogen atoms situated over them (upfield shift of 5.01, 6.78, and 1.63 ppm, respectively). The strongest shielding is seen for the hydrogen atom sitting over the 5-MR at the pole of C71H2 6- (‰ )- 0.255 ppm) indicating that the excess charge density is concentrated at the poles.
β-selective C-glycosidations: lewis-acid mediated reactions of carbohydrates with silyl ketene acetals

Abstract Several examples of β-selective C-glycosidation reactions, involving TMSOTf-promoted addition of sterically hindered silyl ketene acetals to glucosyl and galactosyl acetates, are presented.
The structure of the yeast Ctf3 complex

Kinetochores are the chromosomal attachment points for spindle microtubules. They are also signaling hubs that control major cell cycle transitions and coordinate chromosome folding. Most well-studied eukaryotes rely on a conserved set of factors, which are divided among two loosely-defined groups, for these functions. Outer kinetochore proteins contact microtubules or regulate this contact directly. Inner kinetochore proteins designate the kinetochore assembly site by recognizing a specialized nucleosome containing the H3 variant Cse4/CENP-A. We previously determined the structure, resolved by cryo-electron microscopy (cryo-EM), of the yeast Ctf19 complex (Ctf19c, homologous to the vertebrate CCAN), providing a high-resolution view of inner kinetochore architecture (Hinshaw and Harrison, 2019). We now extend these observations by reporting a near-atomic model of the Ctf3 complex, the outermost Ctf19c sub-assembly seen in our original cryo-EM density. The model is sufficiently well-determined by the new data to enable molecular interpretation of Ctf3 recruitment and function.
Preparation of Fullerenes and Fullerene-Based Materials

Publisher Summary This chapter discusses the preparation, isolation, and characterization of fullerene clusters, and solids based on these clusters. Several techniques are used to prepare crude mixtures of fullerenes, and isolate and characterize pure C. Simple resistive vaporization of graphite rods could produce fullerenes in substantial yield. This procedure is often termed the Kratschmer–Huffman method and is a straightforward and low cost method for generating large quantities of fullerene-containing carbon soot. There are several experimental factors that can be varied to maximize the yield of fullerene clusters in the soot produced from the vaporization of graphite electrodes. These factors include the vaporization current density and helium partial pressure. A second, very useful and powerful technique for producing fullerene clusters involves laser ablation of graphite in a helium atmosphere. Several other techniques, including hydrocarbon combustion, low-pressure helium sputtering, electron beam evaporation, and inductively coupled RF evaporation of graphite targets have been used to prepare fullerene containing carbon products. The chapter also discusses several approaches for preparing isotopically substituted clusters. Finally, the chapter discusses the status and prospects of several new fullerene building blocks, including endohedral metal clusters and carbon nanotubes.
The Reflection-Informed Learning and Instruction to Improve Students' Academic Success in Undergraduate Classrooms.

This study addressed the role of the reflection-informed learning and instruction (RILI) model on students’ academic success by using CourseMIRROR mobile system. We hypothesized that prompting stud...
Synthesis of ‘inside–outside’ medium-sized rings via ring-closing metathesis

Abstract Functionalized and unfunctionalized dienes were synthesized from lactones 7 and 6 , respectively, which were subjected to ring-closing metathesis (RCM) using Grubbs’ catalysts. These dienes provide a systematic study of the stereochemical requirements for efficient cyclization. Moreover, it has been established that, within a uniquely defined oxabicyclo[3.3.0]octane template, medium sized rings bearing an ‘in–out’ intrabridgehead stereochemical relationship can been synthesized in good yield.
Stereoselective chloroacetate aldol reactions: syntheses of acetate aldol equivalents and darzens glycidic esters.

Aldol reaction of the Ti-enolate derived from cis-1-tosylamido-2-indanyl chloroacetate with representative aldehydes proceeded in excellent yield and high diastereoselectivities. Removal of chlorine provided alternative access to highly diastereoselective acetate aldol equivalents or the corresponding glycidic ester condensation products.
Enantioselective synthesis of acyclic allylic esters catalyzed by a palladium/BINAP(S) system

Abstract The synthesis of chiral nonracemic acyclic allylic pivalates via the Pd-catalyzed allylic substitution of racemic allylic carbonates is presented. Good to excellent enantioselectivities (up to 90%) were observed in several cases. An extraordinarily high preference for the production of the branched regioisomeric product is seen when starting from 3-buten-2-yl and crotyl substrates. A significant kinetic resolution (krel = 38) of the 1,3-dimethylallyl substrate was also observed, leading to the production of esters of both enantiomers of an allylic alcohol with a single enantiomer of catalyst.
Structural dynamics of carbon- and metal- containing carbon clusters

A summary of recent studies of the geometries and structural dynamics of pure carbon and metal containing carbon clusters is given. For pure carbon clusters the bicyclic and polycyclic rings can be converted into either monocyclic rings or fullerenes. Formation of the monocyclic rings is driven by a decrease in the strain energy, while fullerene formation is driven by formation of the stable fullerene cage. Mechanisms which explain the formation of bicyclic and polycyclic rings, as well as the conversion of these into monocyclic rings and fullerenes are discussed.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
On the nature of Ge-Pb bonding in the solid state. Synthesis, structural characterization, and electronic structures of two unprecedented germanide-plumbides.

Reported are the syntheses and the crystallographic characterization of two structurally related solid-state compounds: (Eu1–xCax)2Ge2Pb (space group Pbam) and (SrxEu1–x)2Ge2Pb (space group Cmmm). ...
Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex

Summary Human cognition requires the coordination of neural activity across widespread brain networks. Here, we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies within 2 to 15 Hz. These oscillatory clusters displayed spatial phase gradients, indicating that they formed traveling waves that propagated at ∼ 0.25–0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Human traveling theta and alpha waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. Our findings suggest that oscillations support brain connectivity by organizing neural processes across space and time.
A Convergent Synthesis of Hexahomotriazacalix[3]arene Macrocycles

A new, convergent synthesis of hexahomotriazacalix[3]arenes 1a−e is described. The key transformation in this synthesis involves the coupling of the triamines 4a−d with 2,6-bis(chloromethyl)-4-methylphenol 5 and results in the formation of the hexahomotriazacalix[3]arenes 1a−d in 90−95% yield. The triamines 4a−d were constructed by the one-pot reaction of monochloroaldehyde 3 and a primary amine followed by reduction to yield the triamines 4a−d in 50−55% yield. Deallylation of macrocycle 1d was accomplished by palladium catalysis to obtain the N-unsubstituted macrocycle 1e, which has the potential to be a precursor to a variety of N-substituted hexahomotriazacalix[3]arenes.
Intestinal Serum amyloid A suppresses systemic neutrophil activation and bactericidal activity in response to microbiota colonization.

The intestinal microbiota influences the development and function of myeloid lineages such as neutrophils, but the underlying molecular mechanisms are unresolved. Using gnotobiotic zebrafish, we identified the immune effector Serum amyloid A (Saa) as one of the most highly induced transcripts in digestive tissues following microbiota colonization. Saa is a conserved secreted protein produced in the intestine and liver with described effects on neutrophils in vitro, however its in vivo functions remain poorly defined. We engineered saa mutant zebrafish to test requirements for Saa on innate immunity in vivo. Zebrafish mutant for saa displayed impaired neutrophil responses to wounding but augmented clearance of pathogenic bacteria. At baseline, saa mutants exhibited moderate neutrophilia and altered neutrophil tissue distribution. Molecular and functional analyses of isolated neutrophils revealed that Saa suppresses expression of pro-inflammatory markers and bactericidal activity. Saa’s effects on neutrophils depended on microbiota colonization, suggesting this protein mediates the microbiota’s effects on host innate immunity. To test tissue-specific roles of Saa on neutrophil function, we over-expressed saa in the intestine or liver and found that sufficient to partially complement neutrophil phenotypes observed in saa mutants. These results indicate Saa produced by the intestine in response to microbiota serves as a systemic signal to neutrophils to restrict aberrant activation, decreasing inflammatory tone and bacterial killing potential while simultaneously enhancing their ability to migrate to wounds.
Enediynes from aza-enediynes: C,N-dialkynyl imines undergo both aza-Bergman rearrangement and conversion to enediynes and fumaronitriles.

Aza-enediynes (C,N-dialkynyl imines) undergo thermal aza-Bergman rearrangement to β-alkynyl acrylonitriles through 2,5-didehydropyridine (2,5-ddp) intermediates. Certain aza-enediynes also undergo an alternative process affording enediynes and fumaronitriles. Studies employing a specifically l3C-labeled aza-enediyne show that the conversion to enediyne is second order in aza-enediyne, proceeds by a “head-to-tail” coupling, and affords the (Z)-enediyne.
A new method for alkylation of aromatic aldehydes using alkylboron chloride derivatives in the presence of oxygen

Reactions of aromatic aldehydes with alkylboron chloride derivatives in the presence of oxygen have been investigated. Dialkylboron chlorides react with aryl aldehydes to produce arylalkylmethanols in good to excellent yields. Under the same reaction conditions, alkylboron dichlorides lead to the formation of arylalkyl chlorides.
The influence of fluorine on the asymmetric reduction of fluoromethyl ketones

Abstract A comparative study of the asymmetric reduction of representative aryl and alkyl α-fluoro- and α-chloromethyl ketones using (−)-diisopinocampheylchloroborane [(−)-DIP-Chloride™] and (−)-B-isopinocampheyl-9-borabicyclo[3.3.1]nonane [R-Alpine-Borane®] has been made. It was observed that DIP-Chloride™ is superior in terms of the rate and enantioselectivity for both classes of halo-ketones. While the reduction of monofluoroacetone and trifluoroacetone with DIP-Chloride™ provided the product alcohols in 61% ee and 96% ee, respectively, the reduction of difluoroacetone yielded only 5% ee. The influence of a lone halogen atom was not observed for monochloroacetone, all of which point towards a chelating effect of monofluoroacetone on the Lewis acidic chloroborane.
FORMATION OF PHENYLPIPERAZINES BY A NOVEL ALUMINA SUPPORTED BIS-ALKYLATION

Abstract The phenylpiperazine ring which could not be obtained by reacting aniline derivatives with bis(2-bromoethyl)-N-(ethoxycarbonyl)amine (1a) in a wide spectrum of solvents and temperatures was synthesized rapidly on solid support in high yield. By this approach the potent serotonin agonist TFMPP (2) was synthesized in 40 min, in 80% yield. The time scale of this reaction and the simplicity of the work-up match the requirements for short lived neurological radiopharmaceutical production.
MaGIC: a machine learning tool set and web application for monoallelic gene inference from chromatin.

A large fraction of human and mouse autosomal genes are subject to random monoallelic expression (MAE), an epigenetic mechanism characterized by allele-specific gene expression that varies between clonal cell lineages. MAE is highly cell-type specific and mapping it in a large number of cell and tissue types can provide insight into its biological function. Its detection, however, remains challenging. We previously reported that a sequence-independent chromatin signature identifies, with high sensitivity and specificity, genes subject to MAE in multiple tissue types using readily available ChIP-seq data. Here we present an implementation of this method as a user-friendly, open-source software pipeline for monoallelic gene inference from chromatin (MaGIC). The source code for the MaGIC pipeline and the Shiny app is available at https://github.com/gimelbrantlab/magic . The pipeline can be used by researchers to map monoallelic expression in a variety of cell types using existing models and to train new models with additional sets of chromatin marks.
Highly Regio- and Enantioselective Catalytic Hydrogenation of Enamides in Conjugated Diene Systems: Synthesis and Application of γ,δ-Unsaturated Amino Acids

An extremely efficient method has been found for the catalytic asymmetric hydrogenation of conjugated α,γ-dienamide esters using the Et-DuPHOS-Rh catalyst system. α,γ-Dienamide ester substrates were prepared via the Suzuki cross-coupling reaction and the Horner−Emmons olefination. Full conversion to the corresponding γ,δ-unsaturated amino acids with very high regio- and enantioselectivity was achieved after short reaction times. This new methodology was applied to the synthesis of the natural product bulgecinine from a prochiral dienamide ester.
What Is the Will Theory of Rights

This article helps to clear up some misunderstandings about the Will Theory of rights. Section II briefly outlines the Theories of Rights. Section III elucidates some salient differences among self-described anti-Interest Theory accounts. Section IV rebuts Carl Wellman and Arthur Ripstein’s respective arguments about the Will Theory differing from “Choice” or Kantian theories of a right. Section V then offers a candidate explanation of why people might subscribe to the Will Theory in the first place.
The reverse mathematics of non-decreasing subsequences

Every function over the natural numbers has an infinite subdomain on which the function is non-decreasing. Motivated by a question of Dzhafarov and Schweber, we study the reverse mathematics of variants of this statement. It turns out that this statement restricted to computably bounded functions is computationally weak and does not imply the existence of the halting set. On the other hand, we prove that it is not a consequence of Ramsey’s theorem for pairs. This statement can therefore be seen as an arguably natural principle between the arithmetic comprehension axiom and stable Ramsey’s theorem for pairs.
On the coherence conjecture of Pappas and Rapoport

We prove the (generalized) coherence conjecture proposed by Pappas and Rapoport. As a corollary, one of their theorems, which describes the geometry of the special bers of the local models for ramied unitary groups, holds unconditionally. Our proof is based on the study of the geometry (in particular, certain line bundles and ‘-adic sheaves) of the global Schubert varieties, which are the equal characteristic counterparts of the local models.
Abstract interpretation under speculative execution

Analyzing the behavior of a program running on a processor that supports speculative execution is crucial for applications such as execution time estimation and side channel detection. Unfortunately, existing static analysis techniques based on abstract interpretation do not model speculative execution since they focus on functional properties of a program while speculative execution does not change the functionality. To fill the gap, we propose a method to make abstract interpretation sound under speculative execution. There are two contributions. First, we introduce the notion of virtual control flow to augment instructions that may be speculatively executed and thus affect subsequent instructions. Second, to make the analysis efficient, we propose optimizations to handle merges and loops and to safely bound the speculative execution depth. We have implemented and evaluated the proposed method in a static cache analysis for execution time estimation and side channel detection. Our experiments show that the new method, while guaranteed to be sound under speculative execution, outperforms state-of-the-art abstract interpretation techniques that may be unsound.
Correlation structure of time-changed Pearson diffusions

Abstract The stochastic solution to diffusion equations with polynomial coefficients is called a Pearson diffusion. If the time derivative is replaced by a distributed order fractional derivative, the stochastic solution is called a distributed order fractional Pearson diffusion. This paper develops a formula for the covariance function of distributed order fractional Pearson diffusion in the steady state, in terms of generalized Mittag-Leffler functions. The correlation function decays like a power law. That formula shows that distributed order fractional Pearson diffusions exhibits long range dependence.
Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks.

On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly studied networks are friendship and interaction networks. The link prediction problem in friendship networks has been heavily studied. There has also been prior work on link prediction in interaction networks, independent of friendship networks. In this paper, we study the predictive power of combining friendship and interaction networks. We hypothesize that, by leveraging friendship networks, we can improve the accuracy of link prediction in interaction networks. We augment several interaction link prediction algorithms to incorporate friendships and predicted friendships. From experiments on Facebook data, we find that incorporating friendships into interaction link prediction algorithms results in higher accuracy, but incorporating predicted friendships does not when compared to incorporating current friendships.
Data-Driven Approximate Abstraction for Black-Box Piecewise Affine Systems

How to effectively and reliably guarantee the correct functioning of safety-critical cyber-physical systems in uncertain conditions is a challenging problem. This paper presents a data-driven algorithm to derive approximate abstractions for piecewise affine systems with unknown dynamics. It advocates a significant shift from the current paradigm of abstraction, which starts from a model with known dynamics. Given a black-box system with unknown dynamics and a linear temporal logic specification, the proposed algorithm is able to obtain an abstraction of the system with an arbitrarily small error and a bounded probability. The algorithm consists of three components, system identification, system abstraction, and active sampling. The effectiveness of the algorithm is demonstrated by a case study with a soft robot.
Digging Deep into the layers of CNNs: In Search of How CNNs Achieve View Invariance

Abstract: This paper is focused on studying the view-manifold structure in the feature spaces implied by the different layers of Convolutional Neural Networks (CNN). There are several questions that this paper aims to answer: Does the learned CNN representation achieve viewpoint invariance? How does it achieve viewpoint invariance? Is it achieved by collapsing the view manifolds, or separating them while preserving them? At which layer is view invariance achieved? How can the structure of the view manifold at each layer of a deep convolutional neural network be quantified experimentally? How does fine-tuning of a pre-trained CNN on a multi-view dataset affect the representation at each layer of the network? In order to answer these questions we propose a methodology to quantify the deformation and degeneracy of view manifolds in CNN layers. We apply this methodology and report interesting results in this paper that answer the aforementioned questions.
On the diffusion geometry of graph Laplacians and applications

Abstract We study directed, weighted graphs G = ( V , E ) and consider the (not necessarily symmetric) averaging operator ( L u ) ( i ) = − ∑ j ∼ i p i j ( u ( j ) − u ( i ) ) , where p i j are normalized edge weights. Given a vertex i ∈ V , we define the diffusion distance to a set B ⊂ V as the smallest number of steps d B ( i ) ∈ N required for half of all random walks started in i and moving randomly with respect to the weights p i j to visit B within d B ( i ) steps. Our main result is that the eigenfunctions interact nicely with this notion of distance. In particular, if u satisfies L u = λ u on V and e > 0 is so large that B = { i ∈ V : − e ≤ u ( i ) ≤ e } ≠ ∅ , then, for all i ∈ V , d B ( i ) log ⁡ ( 1 | 1 − λ | ) ≥ log ⁡ ( | u ( i ) | ‖ u ‖ L ∞ ) − log ⁡ ( 1 2 + e ) . d B ( i ) is a remarkably good approximation of | u | in the sense of having very high correlation. The result implies that the classical one-dimensional spectral embedding preserves particular aspects of geometry in the presence of clustered data. We also give a continuous variant of the result which has a connection to the hot spots conjecture.
An explicit solution to the chessboard pebbling problem

We consider the chessboard pebbling problem analysed by Chung et al. [Pebbling a chessboard, Am. Math. Mon. 102 (1995), pp. 113–123]. We study the number of reachable configurations and a related double sequence . The analysis involves solving a difference equation satisfied by . Exact expressions for these are derived, and we then consider various asymptotic limits.
Coded Energy-Efficient Beam-Alignment for Millimeter-Wave Networks

Millimeter-wave communications rely on narrow-beam transmissions to cope with the strong signal attenuation at these frequencies, thus demanding precise alignment between transmitter and receiver. However, the beam-alignment procedure may entail a huge overhead and its performance may be degraded by detection errors. This paper proposes a coded energy-efficient beam-alignment scheme, robust against detection errors. Specifically, the beam-alignment sequence is designed such that the error-free feedback sequences are generated from a codebook with the desired error correction capabilities. Therefore, in the presence of detection errors, the error-free feedback sequences can be recovered with high probability. The assignment of beams to codewords is designed to optimize energy efficiency, and a water-filling solution is proved. The numerical results with analog beams depict up to 4dB and 8dB gains over exhaustive and uncoded beam-alignment schemes, respectively.
Learning Scale-Free Networks by Dynamic Node Specific Degree Prior

Learning network structure underlying data is an important problem in machine learning. This paper presents a novel degree prior to study the inference of scale-free networks, which are widely used to model social and biological networks. In particular, this paper formulates scale-free network inference using Gaussian Graphical model (GGM) regularized by a node degree prior. Our degree prior not only promotes a desirable global degree distribution, but also exploits the estimated degree of an individual node and the relative strength of all the edges of a single node. To fulfill this, this paper proposes a ranking-based method to dynamically estimate the degree of a node, which makes the resultant optimization problem challenging to solve. To deal with this, this paper presents a novel ADMM (alternating direction method of multipliers) procedure. Our experimental results on both synthetic and real data show that our prior not only yields a scalefree network, but also produces many more correctly predicted edges than existing scale-free inducing prior, hub-inducing prior and the l1 norm.
HOMFLY polynomials, stable pairs and motivic Donaldson–Thomas invariants

Hilbert scheme topological invariants of plane curve singularities are identified to framed threefold stable pair invariants. As a result, the conjecture of Oblomkov and Shende on HOMFLY polynomials of links of plane curve singularities is given a Calabi-Yau threefold interpretation. The motivic Donaldson-Thomas theory developed by M. Kontsevich and the third author then yields natural motivic invariants for algebraic knots. This construction is motivated by previous work of V. Shende, C. Vafa and the first author on the large $N$-duality derivation of the above conjecture.
Semiparametric Contextual Bandits

This paper studies semiparametric contextual bandits, a generalization of the linear stochastic bandit problem where the reward for an action is modeled as a linear function of known action features confounded by an non-linear action-independent term. We design new algorithms that achieve $O(d\sqrt{T})$ regret over $T$ rounds, when the linear function is $d$-dimensional, which matches the best known bounds for the simpler unconfounded case and improves on a recent result of Greenewald et al. (2017). Via an empirical evaluation, we show that our algorithms outperform prior approaches when there are non-linear confounding effects on the rewards. Technically, our algorithms use a new reward estimator inspired by doubly-robust approaches and our proofs require new concentration inequalities for self-normalized martingales.
On the prediction of >100 MeV solar energetic particle events using GOES satellite data

Solar energetic particles are a result of intense solar events such as solar flares and Coronal Mass Ejections (CMEs). These latter events all together can cause major disruptions to spacecraft that are in Earth's orbit and outside of the magnetosphere. In this work we are interested in establishing the necessary conditions for a major geo-effective solar particle storm immediately after a major flare, namely the existence of a direct magnetic connection. To our knowledge, this is the first work that explores not only the correlations of GOES X-ray and proton channels, but also the correlations that happen across all the proton channels. We found that proton channels autocorrelations and cross-correlations may also be precursors to the occurrence of an SEP event. In this paper, we tackle the problem of predicting >100 MeV SEP events from a multivariate time series perspective using easily interpretable decision tree models.
An Information Theoretic Converse for the “Consecutive Complete–S” PICOD Problem

Pliable Index CODing (PICOD) is a variant of the Index Coding (IC) problem in which a user is satisfied whenever it can successfully decode any one message that is not in its side information set, as opposed to a fixed pre-determined message. The complete-S PICOD with m messages, for $S\subseteq [0:m-1]$, has $n = \sum_{s\in S}\left({l}m\\s\right)$ users with distinct side information sets. Past work on PICOD provided tight converse results when either the sender is constrained to use linear codes, or for some special classes of complete$-S$ PICOD. This paper provides a tight information theoretic converse result (i.e., no restriction to linear codes) for the so-called “consecutive complete–S” PICOD, where the set S satisfies $S = [s_{\min}\:\ s_{\max}]$ for some $0\leq s_{\min} \leq s_{\max} \leq m-1$. This result extends existing converse results and shows that linear codes have the smallest possible code length given by $ \min(m-s_{\min},\ 1+s_{\max})$. The central contribution is a novel proof technique rooted in combinatorics. The main idea is to consider all the messages a user can eventually successfully decode, in addition to its own desired message. This allows us to circumvent the necessity of essentially considering all possible assignments of desired messages for the users. The keystone of the proof is to show that, for the case of $S= \{s\}$ and $m=2s+1,$ there exists at least one user who can decode $s+1$ messages. From this, the extension to the “consecutive complete–S” PICOD follows.
Stability and Generalization of Learning Algorithms that Converge to Global Optima

We establish novel generalization bounds for learning algorithms that converge to global minima. We do so by deriving black-box stability results that only depend on the convergence of a learning algorithm and the geometry around the minimizers of the loss function. The results are shown for nonconvex loss functions satisfying the Polyak-Łojasiewicz (PL) and the quadratic growth (QG) conditions. We further show that these conditions arise for some neural networks with linear activations. We use our black-box results to establish the stability of optimization algorithms such as stochastic gradient descent (SGD), gradient descent (GD), randomized coordinate descent (RCD), and the stochastic variance reduced gradient method (SVRG), in both the PL and the strongly convex setting. Our results match or improve state-of-the-art generalization bounds and can easily be extended to similar optimization algorithms. Finally, we show that although our results imply comparable stability for SGD and GD in the PL setting, there exist simple neural networks with multiple local minima where SGD is stable but GD is not.
Egocentric Height Estimation

Egocentric, or first-person vision which became popular in recent years with an emerge in wearable technology, is different than exocentric (third-person) vision in some distinguishable ways, one of which being that the camera wearer is generally not visible in the video frames. Recent work has been done on action and object recognition in egocentric videos, as well as work on biometric extraction from first-person videos. Height estimation can be a useful feature for both soft-biometrics and object tracking. Here, we propose a method of estimating the height of an egocentric camera without any calibration or reference points. We used both traditional computer vision approaches and deep learning in order to determine the visual cues that results in best height estimation. Here, we introduce a framework inspired by two stream networks comprising of two Convolutional Neural Networks, one based on spatial information, and one based on information given by optical flow in a frame. Given an egocentric video as an input to the framework, our model yields a height estimate as an output. We also incorporate late fusion to learn a combination of temporal and spatial cues. Comparing our model with other methods we used as baselines, we achieve height estimates for videos with a Mean Average Error of 14.04 cm over a range of 103 cm of data, and classification accuracy for relative height (tall, medium or short) up to 93.75% where chance level is 33%.
Path count asymptotics and Stirling numbers

We obtain formulas for the growth rate of the numbers of certain paths in infinite graphs built on the two-dimensional Eulerian graph. Corollaries are identities relating Stirling numbers of the first and second kinds.
Entity-aware Image Caption Generation

Current image captioning approaches generate descriptions which lack specific information, such as named entities that are involved in the images. In this paper we propose a new task which aims to generate informative image captions, given images and hashtags as input. We propose a simple but effective approach to tackle this problem. We first train a convolutional neural networks - long short term memory networks (CNN-LSTM) model to generate a template caption based on the input image. Then we use a knowledge graph based collective inference algorithm to fill in the template with specific named entities retrieved via the hashtags. Experiments on a new benchmark dataset collected from Flickr show that our model generates news-style image descriptions with much richer information. Our model outperforms unimodal baselines significantly with various evaluation metrics.
Learning from sparse data by exploiting monotonicity constraints

When training data is sparse, more domain knowledge must be incorporated into the learning algorithm in order to reduce the effective size of the hypothesis space. This paper builds on previous work in which knowledge about qualitative monotonicities was formally represented and incorporated into learning algorithms (e.g., Clark & Matwin's work with the CN2 rule learning algorithm). We show how to interpret knowledge of qualitative influences, and in particular of monotonicities, as constraints on probability distributions, and to incorporate this knowledge into Bayesian network learning algorithms. We show that this yields improved accuracy, particularly with very small training sets (e.g. less than 10 examples).
Geometric flows and Strominger systems

A geometric flow on (2, 2)-forms is introduced which preserves the balanced condition of metrics, and whose stationary points satisfy the anomaly equation in Strominger systems. The existence of solutions for a short time is established, using Hamilton’s version of the Nash–Moser implicit function theorem.
Completeness results for metrized rings and lattices

The Boolean ring $B$ of measurable subsets of the unit interval, modulo sets of measure zero, has proper radical ideals (for example, ${0})$ that are closed under the natural metric, but has no prime ideal closed under that metric; hence closed radical ideals are not, in general, intersections of closed prime ideals. Moreover, $B$ is known to be complete in its metric. Together, these facts answer a question posed by J. Gleason. From this example, rings of arbitrary characteristic with the same properties are obtained. The result that $B$ is complete in its metric is generalized to show that if $L$ is a lattice given with a metric satisfying identically either the inequality $d(xvee y,,xvee z)leq d(y,z)$ or the inequality $d(xwedge y,xwedge z)leq d(y,z),$ and if in $L$ every increasing Cauchy sequence converges and every decreasing Cauchy sequence converges, then every Cauchy sequence in $L$ converges; that is, $L$ is complete as a metric space. We show by example that if the above inequalities are replaced by the weaker conditions $d(x,,xvee y)leq d(x,y),$ respectively $d(x,,xwedge y)leq d(x,y),$ the completeness conclusion can fail. We end with two open questions.
Numerical Study of Mechanism of U-shaped Vortex Formation

This paper illustrates the mechanism of U-shaped vortex formation which is found both by experiment and DNS. The main goal of this paper is to explain how the U-shaped vortex is formed and further develops. According to the results obtained by our direct numerical simulation with high order accuracy, the U-shaped vortex is part of the coherent vortex structure and is actually the tertiary streamwise vortices induced by the secondary vortices. The new finding is quite different from existing theories which describe that the U-shaped vortex is newly formed as the head of young turbulence spot and finally break down to small pieces. In addition, we find that the U-shaped vortex has the same vorticity sign as the original λ-shaped vortex tube legs and serves as a second neck to supply vorticity to the ringlike vortex when the original vortex tube is stretched and multiple rings are generated.
Energy efficient distributed coding for data collection in a noisy sparse network

We consider the problem of data collection in a two-layer network consisting of (1) noisy links between N distributed agents and a remote sink node; (2) a noisy sparse network formed by these distributed agents. We jointly consider the design of the optimal graph topology for the inter-agent network and the in-network computing scheme under the sparsity constraint and the energy constraint, and study the effect of inter-agent communications on the overall energy consumption. Despite the sparse connections between agents, we provide an in-network coding scheme that reduces the overall energy consumption by a factor of Θ(logN) compared to a naive scheme based on direct agent-to-sink communications only. By providing lower bounds on both the energy consumption and the sparseness (number of links) of the network, we show that the proposed scheme is energy-optimal except for a factor of Θ(log logN). The proposed scheme extends a previous work of Gallager [2] on noisy broadcasting from a complete graph to a sparse graph, while bringing in new techniques from error control coding and noisy circuits.
Cloud-based topological interference management: A case with no cooperative transmission gain

We study the problem of managing interference in linear networks, with backhaul constraints that admit centralized allocation of messages to transmitters through the cloud. Our setting is that of a generic channel, where no channel state information is available at the transmitters. Knowing only the network topology, we characterize the optimal decisions for assigning messages to transmitters, given that each receiver is interested in one message that can be available at N transmitters. We show that using linear cooperation schemes, the per user degrees of freedom does not increase as we increase N beyond unity. Hence, we conclude for the considered problem that cooperative transmission does not increase the degrees of freedom.
Systematic enumeration of configuration classes for entropic sampling of Ising models

We describe a systematic method for complete enumeration of configuration classes (CCs) of the spin-1/2 Ising model in the energy-magnetization plane. This technique is applied to the antiferromagnetic (AF) Ising model in an external magnetic field on the square lattice, which is simulated using the tomographic entropic sampling (TES) algorithm. We estimate the number of configurations, Ω(E,m,L), and related microcanonical averages, for all allowed energies E and magnetizations m for L = 10 to 30, with ΔL = 2. With prior knowledge of the CCs, we can be sure that all allowed classes are sampled during the simulation. Complete enumeration of CCs also enables us to use the final estimate of Ω(E,m,L) to obtain good initial estimates, Ω0(E,m,L′), for successive system sizes (L′ > L) through a two-dimensional interpolation. Using these results we calculate canonical averages of the thermodynamic quantities of interest as continuous functions of temperature T and external field h. In addition, we determine the critical line in the h-T plane using finite-size scaling analysis, and compare these results with several approximate theoretical expressions.
Tunable wave propagation by varying prestrain in tensegrity-based periodic media

Abstract This paper investigates the dynamic properties of one, two and three-dimensional tensegrity-based periodic structures introduced in Rimoli and Pal (2017), which are here termed as tensegrity beams, plates and solids, respectively. We study their linear wave propagation properties and show that in each case, these properties can be significantly altered by the prestrain in the cables. As the prestrain is varied, we observe jumps in the wave velocities at two critical prestrain values, which define transitions between the three distinct phases of these structural assemblies. At low cable prestrains, the wave speeds are zero as the lattices have zero effective stiffness. At moderate prestrains, the wave speed is nonzero and finally, at prestrain levels where the bars buckle, the wave speeds change to a near constant value. Dispersion analysis on these beams, plates and solids reveal unique properties such as very low wave velocities compared to their constituent material and the existence of flat bands at low frequencies. Furthermore, we find that shear waves travel faster than longitudinal waves in tensegrity solids in a range of cable prestrains. Finally, we verify the key observations through detailed numerical simulations on finite tensegrity solids.
Linear Stability of Compressible Vortex Sheets in 2D Elastodynamics: Variable Coefficients

The linear stability with variable coefficients of the vortex sheets for the two-dimensional compressible elastic flows is studied. As in our earlier work (Chen et al. in Adv Math 311:18–60, 2017b) on the linear stability with constant coefficients, the problem has a free boundary which is characteristic, and also the Kreiss–Lopatinskii condition is not uniformly satisfied. In addition, the roots of the Lopatinskii determinant of the para-linearized system may coincide with the poles of the system. Such a new collapsing phenomenon causes serious difficulties when applying the bicharacteristic extension method of Coulombel (SIAM J Math Anal 34(1):142–172, 2002; Ann Inst H Poincare Anal Non Lineaire 21(4):401–443, 2004) and Coulombel and Secchi (Indiana Univ Math J 53(4):941–1012, 2004). Motivated by our method introduced in the constant-coefficient case (Adv Math 311:18–60, 2017b), we perform an upper triangularization to the para-linearized system to separate the outgoing mode into a closed form where the outgoing mode only appears at the leading order. This procedure results in a gain of regularity for the outgoing mode, which allows us to overcome the loss of regularity of the characteristic components at the poles and hence to close all the energy estimates. We find that, analogous to the constant-coefficient case, elasticity generates notable stabilization effects, and there are additional stable subsonic regions compared with the isentropic Euler flows. Moreover, since our method does not rely on the construction of the characterisic curves, it can also be applied to other fluid models such as the non-isentropic Euler equations and the MHD equations.
Local and Global Existence of Strong Solutions to Large Cross Diffusion Systems

We study the solvability of a general class of cross diffusion systems and establish the local and global existence of their strong solutions under the weakest assumption that they are VMO. This work simplifies the setting in our previous work [16] and provides new extensions which are more verifiable in applications.
Dual Polynomials for Collision and Element Distinctness

The approximate degree of a Boolean function f : {−1, 1} → {−1, 1} is the minimum degree of a real polynomial that approximates f to within error 1/3 in the `∞ norm. In an influential result, Aaronson and Shi (J. ACM 2004) proved tight Ω(n) and Ω(n) lower bounds on the approximate degree of the Collision and Element Distinctness functions, respectively. Their proof was non-constructive, using a sophisticated symmetrization argument and tools from approximation theory. More recently, several open problems in the study of approximate degree have been resolved via the construction of dual polynomials. These are explicit dual solutions to an appropriate linear program that captures the approximate degree of any function. We reprove Aaronson and Shi’s results by constructing explicit dual polynomials for the Collision and Element Distinctness functions. ∗Harvard University, School of Engineering and Applied Sciences. Supported by an NDSEG Fellowship and NSF grant CNS1237235. †Yahoo Labs. Parts of this work were performed while the author was a Research Fellow at the Simons Institute for the Theory of Computing. Supported in part by a Research Fellowship from the Simons Institute for the Theory of Computing. ISSN 1433-8092 Electronic Colloquium on Computational Complexity, Report No. 41 (2015)