cssi/SciSciGPT-SciSciNet huggingface dataset:
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have much better quality than template-based models especially for membrane proteins. The 3D models built from our contact prediction have TMscore>0.5 for 208 of the 398 membrane proteins, while those from homology modeling have TMscore>0.5 for only 10 of them. Further, even if trained mostly by soluble proteins, our deep learning method works very well on membrane proteins. In the recent blind CAMEO benchmark, our fully-automated web server implementing this method successfully folded 6 targets with a new fold and only 0.3L-2.3L effective sequence homologs, including one β protein of 182 residues, one α+β protein of 125 residues, one α protein of 140 residues, one α protein of 217 residues, one α/β of 260 residues and one α protein of 462 residues. Our method also achieved the highest F1 score on free-modeling targets in the latest CASP (Critical Assessment of Structure Prediction), although it was not fully implemented back then. Availability http://raptorx.uchicago.edu/ContactMap/
Improved full-length killer cell immunoglobulin-like receptor transcript discovery in Mauritian cynomolgus macaques

Killer cell immunoglobulin-like receptors (KIRs) modulate disease progression of pathogens including HIV, malaria, and hepatitis C. Cynomolgus and rhesus macaques are widely used as nonhuman primate models to study human pathogens, and so, considerable effort has been put into characterizing their KIR genetics. However, previous studies have relied on cDNA cloning and Sanger sequencing that lack the throughput of current sequencing platforms. In this study, we present a high throughput, full-length allele discovery method utilizing Pacific Biosciences circular consensus sequencing (CCS). We also describe a new approach to Macaque Exome Sequencing (MES) and the development of the Rhexome1.0, an adapted target capture reagent that includes macaque-specific capture probe sets. By using sequence reads generated by whole genome sequencing (WGS) and MES to inform primer design, we were able to increase the sensitivity of KIR allele discovery. We demonstrate this increased sensitivity by defining nine novel alleles within a cohort of Mauritian cynomolgus macaques (MCM), a geographically isolated population with restricted KIR genetics that was thought to be completely characterized. Finally, we describe an approach to genotyping KIRs directly from sequence reads generated using WGS/MES reads. The findings presented here expand our understanding of KIR genetics in MCM by associating new genes with all eight KIR haplotypes and demonstrating the existence of at least one KIR3DS gene associated with every haplotype.
Effect of carbenoid structure on the reactions of rhodium-stabilized carbenoids with cycloheptatriene

Rhodium prolinate catalyzed reactions of diazocarbonyls with cycloheptatriene are very dependent on the carbenoid structure and can result in either cyclopropanation, C–H insertion or a combined C–H insertion Cope rearrangement.
Temporal Genetic Dynamics of an Experimental, Biparental Field Population of Phytophthora capsici

Defining the contributions of dispersal, reproductive mode, and mating system to the population structure of a pathogenic organism is essential to estimating its evolutionary potential. After introduction of the devastating plant pathogen, Phytophthora capsici, into a grower's field, a lack of aerial spore dispersal restricts migration. Once established, coexistence of both mating types results in formation of overwintering recombinant oospores, engendering persistent pathogen populations. To mimic these conditions, in 2008, we inoculated a field with two P. capsici isolates of opposite mating type. We analyzed pathogenic isolates collected in 2009-13 from this experimental population, using genome-wide single-nucleotide polymorphism markers. By tracking heterozygosity across years, we show that the population underwent a generational shift; transitioning from exclusively F1 in 2009-10; multi-generational in 2011; and ultimately all inbred in 2012-13. Survival of F1 oospores, characterized by heterozygosity excess, coupled with a low rate of selfing, delayed declines in heterozygosity due to inbreeding and attainment of equilibrium genotypic frequencies. Large allele and haplotype frequency changes in specific genomic regions accompanied the generational shift, representing putative signatures of selection. Finally, we identified an approximately 1.6 Mb region associated with mating type determination, constituting the first detailed genomic analysis of a mating type region (MTR) in Phytophthora. Segregation patterns in the MTR exhibited tropes of sex-linkage, where maintenance of allele frequency differences between isolates of opposite mating type was associated with elevated heterozygosity despite inbreeding. Characterizing the trajectory of this experimental system provides key insights into the processes driving persistent, sexual pathogen populations.
The Preparation Of 2-[4,5-Dihydro-3-Aryl-5-Isoxazolyl]-Phenols From C(α),O-Dilithiooximes and Lithiated Hydroxyaryl Aldehydes

Abstract C(a), O-Oximes were dilithiated in excess lithium diisopropylamide, and the resulting intermediates were condensed with lithiated hydroxyphenyl aldehydes and related materials and cyclized with acid to afford 2-[4,5-dihydro-3-aryl-5-isoxazolyl]phenols, substituted 4,5-dihydroisoxazoles (2-isoxazolines).
CaYGaO4; a fully ordered novel olivine type gallate

Abstract CaYGaO 4 was synthesized by conventional solid-state method. Its crystal structure was determined by single-crystal X-ray diffraction technique to be olivine structure type. CaYGaO 4 comprises an orthorhombic space group Pnma , with lattice constants of a = 11.3484(1) A, b = 6.5712(6) A and c = 5.2818(8) A. All three cations occupy their specific atomic positions and the structure is fully ordered. The crystallographic ordering scheme in the new gallate system, is different from those reported for the previously studied silicate and germanate olivines. The partial replacement of the Ga 3+ by Fe 3+ ions could be achieved, resulting in a series of solid solutions with the chemical composition of CaYGa 1− x Fe x O 4 (0 x ⩽ 0.50). The unit cell volumes of the doped variants are consistent with Vegard’s law.
Platinum-catalyzed asymmetric alkylation of secondary phosphines: enantioselective synthesis of p-stereogenic phosphines.

The chiral Pt catalyst precursor Pt((R,R)-Me-Duphos)(Ph)(Cl) mediated alkylation of racemic secondary phosphines PHR(R‘) with benzyl halides in the presence of base to give enantioenriched tertiary...
A New Total Synthesis of the Zinc Matrixmetalloproteinase Inhibitor Ageladine A Featuring a Biogenetically Patterned 6π-2-Azatriene Electrocyclization

[reaction: see text] A convergent second generation total synthesis of the heterocyclic marine sponge metabolite ageladine A has been achieved by using a biomimetically inspired 6pi-2-azatriene electrocyclization as the key step for formation of the imidazolopyridine moiety.
Charge-Conjugation Invariance of the Spectator Equations

In response to recent criticism, the authors show how to define the spectator equations for negative energies so that charge conjugation invariance is preserved. The result, which emerges naturally from the application of spectator principles to systems of particles with negative energies, is to replace all factors of the external energies W {sub iota} by {radical} W{sup 2} {sub iota}, insuring that the amplitudes are independent of the sign of the energies W {sub iota}.
The First Total Synthesis of (−)-Tamandarin A

[formula: see text] Tamandarin A (1), a newly isolated natural product similar in structure to didemnin B (2), was shown to be somewhat more active in vitro than 2 against pancreatic carcinoma with an ED50 value 1.5 to 2 ng/mL. We report here the first total synthesis of 1. The key steps include a practical stereoselective synthesis of the Hiv-isostatine unit, high-yielding linear precursor formation, a successful macrocyclization, and coupling of the macrocycle with the side chain to afford tamandarin A (1).
Hi-C 2.0: An optimized Hi-C procedure for high-resolution genome-wide mapping of chromosome conformation

Chromosome conformation capture-based methods such as Hi-C have become mainstream techniques for the study of the 3D organization of genomes. These methods convert chromatin interactions reflecting topological chromatin structures into digital information (counts of pair-wise interactions). Here, we describe an updated protocol for Hi-C (Hi-C 2.0) that integrates recent improvements into a single protocol for efficient and high-resolution capture of chromatin interactions. This protocol combines chromatin digestion and frequently cutting enzymes to obtain kilobase (kb) resolution. It also includes steps to reduce random ligation and the generation of uninformative molecules, such as unligated ends, to improve the amount of valid intra-chromosomal read pairs. This protocol allows for obtaining information on conformational structures such as compartment and topologically associating domains, as well as high-resolution conformational features such as DNA loops.
A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastoma.

We have identified molecules that exhibit synthetic lethality in cells with loss of the neurofibromin 1 (NF1) tumor suppressor gene. However, recognizing tumors that have inactivation of the NF1 tumor suppressor function is challenging because the loss may occur via mechanisms that do not involve mutation of the genomic locus. Degradation of the NF1 protein, independent of NF1 mutation status, phenocopies inactivating mutations to drive tumors in human glioma cell lines. NF1 inactivation may alter the transcriptional landscape of a tumor and allow a machine learning classifier to detect which tumors will benefit from synthetic lethal molecules. We developed a strategy to predict tumors with low NF1 activity and hence tumors that may respond to treatments that target cells lacking NF1. Using RNAseq data from The Cancer Genome Atlas (TCGA), we trained an ensemble of 500 logistic regression classifiers that integrates mutation status with whole transcriptomes to predict NF1 inactivation in glioblastoma (GBM). On TCGA data, the classifier detected NF1 mutated tumors (test set area under the receiver operating characteristic curve (AUROC) mean = 0.77, 95% quantile = 0.53 – 0.95) over 50 random initializations. On RNA-Seq data transformed into the space of gene expression microarrays, this method produced a classifier with similar performance (test set AUROC mean = 0.77, 95% quantile = 0.53 – 0.96). We applied our ensemble classifier trained on the transformed TCGA data to a microarray validation set of 12 samples with matched RNA and NF1 protein-level measurements. The classifier’s NF1 score was associated with NF1 protein concentration in these samples. We demonstrate that TCGA can be used to train accurate predictors of NF1 inactivation in GBM. The ensemble classifier performed well for samples with very high or very low NF1 protein concentrations but had mixed performance in samples with intermediate NF1 concentrations. Nevertheless, high-performing and validated predictors have the potential to be paired with targeted therapies and personalized medicine.
Cyclopropanones derived from saturated fulvene endoperoxides: Synthesis of highly oxygenated organic compounds☆

Abstract Saturated fulvene endoperoxides give highly oxygenated compounds upon thermolysis in the presence of acetic acid. Depending on whether the fulvene precursor is 6-mono or 6,6-disubstituted, one obtains either lactol acetates or 1,5-carbonyl compounds, respectively.
Bipolar switching by HCN voltage sensor underlies hyperpolarization activation.

Despite sharing a common architecture with archetypal voltage-gated ion channels (VGICs), hyperpolarization- and cAMP-activated ion (HCN) channels open upon hyperpolarization rather than depolarization. The basic motions of the voltage sensor and pore gates are conserved, implying that these domains are inversely coupled in HCN channels. Using structure-guided protein engineering, we systematically assembled an array of mosaic channels that display the full complement of voltage-activation phenotypes observed in the VGIC superfamily. Our studies reveal that the voltage sensor of the HCN channel has an intrinsic ability to drive pore opening in either direction and that the extra length of the HCN S4 is not the primary determinant for hyperpolarization activation. Tight interactions at the HCN voltage sensor–pore interface drive the channel into an hERG-like inactivated state, thereby obscuring its opening upon depolarization. This structural element in synergy with the HCN cyclic nucleotide-binding domain and specific interactions near the pore gate biases the channel toward hyperpolarization-dependent opening. Our findings reveal an unexpected common principle underpinning voltage gating in the VGIC superfamily and identify the essential determinants of gating polarity.
Extremely Regioselective Intramolecular Silylformylation of Bis(silylamino)alkynes

Intramolecular silylformylation of ω-bis(dimethylsilylamino)-i-alkynes is investigated. This process affords exo-(1-formylalkenylidene)azasilacycloalkane as the initial product, which is converted to the more stable exo-(1-hydroxymethylalkenylidene)azasilacycloalkane through NaBH4 reduction in methanol in high overall yield. Both exo-alkenylidene azasilacycloalkanes are literature unknown compounds and would be versatile polyfunctionalized intermediates in organic syntheses. It should be noted that only the exo-SiMe2H group is removed in this reduction, and the resulting cyclic silylamine is stable against methanolysis and hydrolysis, which is unexpected and unprecedented. The observed stability of the Si−N bond in the cyclic silylamine is found to be ascribed to the existence of the exo-alkylene group at the C-5 position. Thus, the hydrogenation of this double bond leads to a facile Si−N bond cleavage by methanol. In a similar manner, the reactions of 1-bis(dimethylsilyl)amino-2-(1-hexynyl)cycloalkane, f...
PRECISION SUPERSYMMETRY MEASUREMENTS AT THE e-e- COLLIDER

Measurements of supersymmetric particle couplings provide important verification of supersymmetry. If some of the superpartners are at the multi-TeV scale, they will escape direct detection at planned future colliders. However, such particles induce nondecoupling corrections in processes involving the accessible superparticles through violations of the supersymmetric equivalence between gauge boson and gaugino couplings. These violations are analogous to the oblique corrections in the electroweak sector of the Standard Model, and can be parametrized in terms of super-oblique parameters. The e-e- collision mode of a future linear collider is shown to be an excellent environment for such high precision measurements of these SUSY parameters, which will provide an important probe of superparticles beyond reachable energies.
Highly functionalized trans-2,5-disubstituted tetrahydrofurans from ribofuranoside templates: precursors to linked polycyclic ethers☆

Abstract Iodoetherification of C5 allylated ribo-furanosides leads to trans-2,5-disubstituted tetrahydrofurans with high selectivity. The application of this reaction to the synthesis of complex polycyclic ethers is illustrated in the preparation of a truncated, tricyclic analog of monensin A.
Titanocene-catalyzed metallation of propargylic acetates in homopropargyl alcohol synthesis

Abstract The titanium-catalyzed metallation and subsequent carbonyl addition of propargylic acetates enable the direct formation of homopropargylic alcohols in good yields. The corresponding products were obtained as single regioisomers without the corresponding allene adducts observed.
Oracle separation of BQP and PH

We present a distribution D over inputs in {−1,1}2N, such that: (1) There exists a quantum algorithm that makes one (quantum) query to the input, and runs in time O(logN), that distinguishes between D and the uniform distribution with advantage Ω(1/logN). (2) No Boolean circuit of quasi-polynomial size and constant depth distinguishes between D and the uniform distribution with advantage better than polylog(N)/√N. By well known reductions, this gives a separation of the classes Promise-BQP and Promise-PH in the black-box model and implies an oracle O relative to which BQPO ⊈PHO.
Direct conversion of amidoximes to amidines via transfer hydrogenation

Amidoximes, O-alkylamidoximes, and O-acylamidoximes are directly converted to amidines by reaction with ammonium formate and Pd/C in acetic acid.
Vitamin B12 catalyzed radical cyclizations of arylalkenes

The use of vitamin B 1 2 for synthetic organic transformations has been extensively studied. Herein, we report the intramolecular cyclization reaction of a series of arylalkene substrates catalyzed by vitamin B 1 2 . Thesereactions proceed in good yields in environmentally benign solvents and do not require the use of a toxic heavy metal catalyst. Variation of the reaction pH can predictably alter the product distribution.
General preparative route to benzo[g]quinolines (1-azaanthracenes)

A convenient synthetic pathway to benzo[g]quinolines (1-azaanthracenes) has been developed. The nickel catalyzed coupling of methyl 2-chloronicotinate (3a) with benzylic organo zinc reagents 2a-e led to the methyl 2-benzylic substituted nicotinates 4a-e. Treatment of methyl 2-chloro-6-methylnicotinate (3b)with 2a in a similar manner led to methyl 2-benzyl-6-methyInicotinate (4f). The coupling of 2-chloro-3-acetylpyridine (5) with benzyl zinc bromide (2a) led to 2-benzyl-3-acetylpyridine (4g). The coupling of the 2,5-dichlorobenzylic organic zinc reagent (2f) with methyl 2-choronicotinate (3a) was unselective but readily coupled with methyl 2-bromonicotinate (6) to yield methyl 2-(2,5-dichlorobenzyl)nicotinate (4h). The esters 4a-f,h on reduction with lithium aluminum hydride led to the corresponding alcohols 7a-f,h which were subsequently oxidized with manganese dioxide to the respective 2-benzylic substituted pyridine-3-carboxaldehydes 8a-f,h. In one case the coupling of benzy] zinc bromide (2a) with 2-chloropyridine-3-carboxaldehyde (9) led directly to 2-benzylpyridine-3-carboxaldehyde (8a), but in poor yield. Cyclizations of the aldehydes 8a-d,f,h or the ketone 4g with polyphosphoric acid afforded the benzo[g]quinolines 10a-d,f-h in high yields. Aldehyde 8e was cyclized to 10e using a solution of sulfuric acid in methanol. Several of the benzo[g]quinolines 10c,d could be readly converted into the benzo[q]quinoline-5,10-diones 11c,d on treatment with ammonium ceric nitrate.
Synthesis and structural studies of aza analogues of functionalized amino acids: New anticonvulsant agents

We have reported that functionalized amino acids 1 display potent anticonvulsant activities in mice and rats, and that the activity resides primarily in the d-isomer. In this study we investigated ...
High-affinity low-capacity and low-affinity high-capacity N-acetyl-2-aminofluorene (AAF) macromolecular binding sites are revealed during the growth cycle of adult rat hepatocytes in primary culture

Long-term cultures of primary adult rat hepatocytes were used to study the effects of N-acetyl-2-aminofluorene (AAF) on hepatocyte proliferation during the growth cycle; on the initiation of hepatocyte DNA synthesis in quiescent cultures; and, on hepatocyte DNA replication following the initiation of DNA synthesis. Scatchard analyses were used to identify the pharmacologic properties of radiolabeled AAF metabolite binding to hepatocyte macromolecules. Two classes of growth cycle-dependent AAF metabolite binding sites-a high-affinity low-capacity site (designated Site I) and a low-affinity high-capacity site (designated Site II)-associated with two spatially distinct classes of macromolecular targets, were revealed. Based upon radiolabeled AAF metabolite binding to purified hepatocyte genomic DNA or to DNA, RNA, proteins, and lipids from isolated nuclei, Site IDAY 4 targets (KD[APPARENT] ≈ 2-4×10-6 M and BMAX[APPARENT] ≈ 6 pmol/106 cells/24 h) were consistent with genomic DNA; and with AAF metabolized by a nuclear cytochrome P450. Based upon radiolabeled AAF binding to total cellular lysates, Site IIDAY 4 targets (KD[APPARENT] ≈ 1.5×10-3 M and BMAX[APPARENT] ≈ 350 pmol/106 cells/24 h) were consistent with cytoplasmic proteins; and with AAF metabolized by cytoplasmic cytochrome P450s. DNA synthesis was not inhibited by concentrations of AAF that saturated DNA binding in the neighborhood of the Site I KD. Instead, hepatocyte DNA synthesis inhibition required higher concentrations of AAF approaching the Site II KD. These observations raise the possibility that carcinogenic DNA adducts derived from AAF metabolites form below concentrations of AAF that inhibit replicative and repair DNA synthesis.
Synthesis of conjugated enediynes via palladium catalyzed cross-coupling reactions of potassium alkynyltrifluoroborates

An efficient synthesis of cross-conjugated enediynes has been developed utilizing the palladium catalyzed cross-coupling reactions of 1,1-dibromo-1-alkenes with potassium alkynyltrifluoroborates under mild conditions.
Amide-directed hydrocarbonylation of N-alkenylamides and α-alkenyllactams

Abstract The amide-directed Rh-catalyzed hydroformylation and Pd-catalyzed hydroesterification of N-allylamides give the iso-aldehyde and ester, respectively, with good regioselectivity. The Rh- and Co2Rh2(CO)12-catalyzed reactions of N-methallylamide give an 1-acyl-2-formylpyrrolidine through a novel double carbonylation and an 1-acylpyrrolidine through reductive annulation, respectively, with excellent selectivity. A cyclic hemiamidal, N-benzoyl-2-hydroxy-4-methylpyrrolidine, the key intermediate for the double carbonylation and the reductive annulation, is obtained selectivity in a Rh4(CO)12-catalyzed reaction of N-methallylamide. The hydrocarbonylations of this cyclic hemiamidal catalyzed by RhCl(PPh3)3, Co2Rh2(CO)12, and Co2(CO)8 give the corresponding double carbonylation product (2-formylpyrrolidine), reductive annulation product (pyrrolidine), and amidocarbonylation product (proline), respectively, in excellent yield and selectivity. The mechanisms of the novel double carbonylation and the reductive annulation is studied on the basis of deuterium-labeling experiments, and it is found that these reactions proceed via enamide intermediate followed by extremely regioselective metal hydride addition to the enamide. The Rh-catalyzed hydrocarbonylations of the α-methally-γ- and δ-lactams in triethyl orthoformate followed by treatment with TFA give the corresponding 1-azabicyclo[4.n0]alketones via bicyclic hemiamidals through annulation in excellent overall yields. The Co2Rh2(CO)12-catalyzed reactions of these α-methallyl lactams give the corresponding 1-azabicyclo[4.n.0]alkanones as the sole isolable products in high yields. The RhCl(PPh3)3-catalyzed hydrocarbonylation of 6-allylpiperidin-2-one gives a mixture of 1-azabicyclo[4.4.0] and 1-azabicyclo[4.3.0] products. However, the addition of phosphines to the Rh catalyst remarkably improves the normal selectivity (n/iso = 9) to give 1-azabicyclo[4.4.0]dec-2-en-10-one as the predominant product.
Data Clustering with Actuarial Applications

Data clustering refers to the process of dividing a set of objects into homogeneous groups or clusters such that the objects in each cluster are more similar to each other than to those of other cl...
Photochemistry of trans-Stilbene Adsorbed on Al2O3(0001)

Temperature-programmed desorption (TPD) was used to study the desorption and photochemistry of trans-stilbene on Al2O3(0001) in ultrahigh vacuum. At low coverages, the TPD traces of cis-stilbene and trans-stilbene both show only one peak, attributed to monolayer desorption, at 275 and 315 K, respectively. As the coverage is increased, a second, multilayer peak is seen at 230 K for cis-stilbene and at 260 K for trans-stilbene. The relative intensities of the monolayer and multilayer peaks were observed to fit a statistical adlayer sticking model similar to those of other hydrocarbons and described in previous work. When trans-stilbene is exposed to light at 313 nm, TPD traces show a new peak at 380 K which is attributed to the formation of the stilbene dimer, 1,2,3,4-tetraphenylcyclobutane (or isodistilbene). The photodimerization is coverage and temperature dependent with little or no photochemistry occurring at coverages below 0.10 ML or temperatures below 100 K. The data are consistent with the dimeriza...
Online Distributed Estimation of Principal Eigenspaces

Principal components analysis (PCA) is a widely used dimension reduction technique with an extensive range of applications. In this paper, an online distributed algorithm is proposed for recovering the principal eigenspaces. We further establish its rate of convergence and show how it relates to the number of nodes employed in the distributed computation, the effective rank of the data matrix under consideration, and the gap in the spectrum of the underlying population covariance matrix. The proposed algorithm is illustrated on low-rank approximation and k-means clustering tasks. The numerical results show a substantial computational speed-up vis-a-vis standard distributed PCA algorithms, without compromising learning accuracy.
Homomorphism complexes and maximal chains in graded posets

Abstract We apply the homomorphism complex construction to partially ordered sets, introducing a new topological construction based on the set of maximal chains in a graded poset. Our primary objects of study are distributive lattices, with special emphasis on finite products of chains. For the special case of a Boolean algebra, we observe that the corresponding homomorphism complex is isomorphic to the subcomplex of cubical cells in a permutahedron. Thus, this work can be interpreted as a generalization of the study of these complexes. We provide a detailed investigation when our poset is a product of chains, in which case we find an optimal discrete Morse matching and prove that the corresponding complex is torsion-free.
Cooperation in stochastic games: a prisoner’s dilemma experiment

This experiment investigates a stochastic version of the infinitely repeated prisoner’s dilemma. The stochastic element introduces the importance of beliefs about the future for supporting cooperation as well as cooperation and defection on the equilibrium path. There is more cooperation in treatments where beliefs predict cooperation after subjects gain sufficient experience. There is some evidence for cooperation and defection as predicted by equilibrium, but there is stronger evidence for behavior conditioning on past actions that is not consistent with equilibrium play. In particular, subjects continue cooperating even when it is no longer possible in equilibrium for the realized game.
mmWave massive MIMO with simple RF and appropriate DSP

There is considerable interest in the combined use of millimeter-wave (mmwave) frequencies and arrays of massive numbers of antennas (massive MIMO) for next-generation wireless communications systems. A symbiotic relationship exists between these two factors: mmwave frequencies allow for densely packed antenna arrays, and hence massive MIMO can be achieved with a small form factor; low per-antenna SNR and shadowing can be overcome with a large array gain; steering narrow beams or nulls with a large array is a good match for the line-of-sight (LOS) or near-LOS mmwave propagation environments, etc. However, the cost and power consumption for standard implementations of massive MIMO arrays at mmwave frequencies is a significant drawback to rapid adoption and deployment. In this paper, we examine a number of possible approaches to reduce cost and power at both the basestation and user terminal, making up for it with signal processing and additional (cheap) antennas. These approaches include low-resolution Analog-to-Digital Converters (ADCs), wireless local oscillator distribution networks, spatial multiplexing and multi-streaming instead of higher-order modulation etc. We will examine the potential of these approaches in making mmwave massive MIMO a reality and discuss the requirements in terms of digital signal processing (DSP).
Algebraic Approach to Colombeau Theory

We present a differential algebra of generalized functions over a field of generalized scalars by means of several axioms in terms of general algebra and topology. Our differential algebra is of Colombeau type in the sense that it contains a copy of the space of Schwartz distributions, and the set of regular distributions with C ∞-kernels forms a differential subalgebra. We discuss the uniqueness of the field of scalars as well as the consistency and independence of our axioms. This article is written mostly to satisfy the interest of mathematicians and scientists who do not necessarily belong to the Colombeau community; that is to say, those who do not necessarily work in the non-linear theory of generalized functions.
Preserving Entanglement during Weak Measurement Demonstrated with a Violation of the Bell-Leggett-Garg Inequality

Weak measurement has provided new insight into the nature of quantum measurement, by demonstrating the ability to extract average state information without fully projecting the system. For single-qubit measurements, this partial projection has been demonstrated with violations of the Leggett–Garg inequality. Here we investigate the effects of weak measurement on a maximally entangled Bell state through application of the Hybrid Bell–Leggett–Garg inequality (BLGI) on a linear chain of four transmon qubits. By correlating the results of weak ancilla measurements with subsequent projective readout, we achieve a violation of the BLGI with 27 s.d.s. of certainty. Scientists in the US have developed a method to evaluate the properties of complex quantum states without causing their destruction. A team at the University of California Santa Barbara led by John Martinis verified that the properties of entangled quantum states can be probed using weak measurements. By extracting only small parts of quantum information in a single measurement, weak measurements avoid the problem whereby quantum states are destroyed when the information contained in them is measured. Although this has been successfully demonstrated for single quantum states, it remained unclear if weak measurements were compatible with more complicated entangled systems. By implementing an experimental test that verifies with high accuracy the preservation of those entangled states in measurements, the researchers have made it possible to probe the properties of qubits in complex quantum computing schemes.
On the Insufficiency of Existing Momentum Schemes for Stochastic Optimization

Momentum based stochastic gradient methods such as heavy ball (HB) and Nesterov's accelerated gradient descent (NAG) method are widely used in practice for training deep networks and other supervised learning models, as they often provide significant improvements over stochastic gradient descent (SGD). In general, “fast gradient” methods have provable improvements over gradient descent only for the deterministic case, where the gradients are exact. In the stochastic case, the popular explanations for their wide applicability is that when these fast gradient methods are applied in the stochastic case, they partially mimic their exact gradient counterparts, resulting in some practical gain. This work provides a counterpoint to this belief by proving that there are simple problem instances where these methods cannot outperform SGD despite the best setting of its parameters. These negative problem instances are, in an informal sense, generic; they do not look like carefully constructed pathological instances. These results suggest (along with empirical evidence) that HB or NAG's practical performance gains are a by-product of minibatching. Furthermore, this work provides a viable (and provable) alternative, which, on the same set of problem instances, significantly improves over HB, NAG, and SGD's performance. This algorithm, denoted as ASGD, is a simple to implement stochastic algorithm, based on a relatively less popular version of Nesterov's AGD. Extensive empirical results in this paper show that ASGD has performance gains over HB, NAG, and SGD.
Generalized Tschebyscheff of the Second Kind and Bernstein Polynomials Change of Bases

We construct multiple representations relative to different bases of the generalized Tschebyscheff polynomials of second kind. Also, we provide an explicit closed from of The generalized Polynomials of degree r less than or equal n in terms of the Bernstein basis of fixed degree n. In addition, we create the change-of-basis matrices between the generalized Tschebyscheff of the second kind polynomial basis and Bernstein polynomial basis.
Distributed majorization-minimization for Laplacian regularized problems

We consider the problem of minimizing a block separable convex function &#x0028 possibly nondifferentiable, and including constraints &#x0029 plus Laplacian regularization, a problem that arises in applications including model fitting, regularizing stratified models, and multi-period portfolio optimization. We develop a distributed majorization-minimization method for this general problem, and derive a complete, self-contained, general, and simple proof of convergence. Our method is able to scale to very large problems, and we illustrate our approach on two applications, demonstrating its scalability and accuracy.
Randomized interior point methods for sampling and optimization

We present a Markov chain (Dikin walk) for sampling from a convex body equipped with a self-concordant barrier, whose mixing time from a \central point" is strongly polynomial in the description of the convex set. The mixing time of this chain is invariant under ane transformations of the convex set, thus eliminating the need for rst placing the body in an isotropic position. This strengthens and previous results of [11] for polytopes and generalizes these results to arbitrary convex sets. In the case of a convex set K dened by a semidenite constraint of rank at most and at most m additional linear constraints, our results specialize to the following statement. Let s jpj jqj for any chord pq of K passing through a point x2 K. Then, after t = O n(m +n ) n ln((m +n )s) + ln 1 steps are taken by a Dikin walk starting at x, the total variation distance and theL2 distance of the density (xt) of the point to the uniform density are less than . On every convex set of dimensionn, there exists a self-concordant barrier whose \complexity" is polynomially bounded. Consequently, a rapidly mixing Markov chain of the kind we describe can be dened on any convex set. We use these results to design an algorithm consisting of a single random walk for optimizing a linear function on a convex set. We show that this random walk reaches an approximately optimal point in polynomial time with high probability and that the corresponding objective values converge with probability 1 to the optimal objective value as the number of steps tends to innity. One technical contribution is a family of lower
A note on weak convergence of singular integrals in metric spaces

We prove that in any metric space $(X,d)$ the singular integral operators {equation*} T^k_{\mu,\ve}(f)(x)=\int_{X\setminus B(x,\varepsilon)}k(x,y)f(y)d\mu (y).{equation*} converge weakly in some dense subspaces of $L^2(\mu)$ under minimal regularity assumptions for the measures and the kernels.
A Parametric MPC Approach to Balancing the Cost of Abstraction for Differential-Drive Mobile Robots

When designing control strategies for differential-drive mobile robots, one standard tool is the consideration of a point at a fixed distance along a line orthogonal to the wheel axis instead of the full pose of the vehicle. This abstraction supports replacing the non-holonomic, three-state unicycle model with a much simpler two-state single-integrator model (i.e., a velocity-controlled point). Yet this transformation comes at a performance cost, through the robot's precision and maneuverability. This work contains derivations for expressions of these precision and maneuverability costs in terms of the transformation's parameters. Furthermore, these costs show that only selecting the parameter once over the course of an application may cause an undue loss of precision. Model Predictive Control (MPC) represents one such method to ameliorate this condition. However, MPC typically realizes a control signal, rather than a parameter, so this work also proposes a Parametric Model Predictive Control (PMPC) method for parameter and sampling horizon optimization. Experimental results are presented that demonstrate the effects of the parameterization on the deployment of algorithms developed for the single-integrator model on actual differential-drive mobile robots.
Peer to Peer Hate: Hate Speech Instigators and Their Targets

While social media has become an empowering agent to individual voices and freedom of expression, it also facilitates anti-social behaviors including online harassment, cyberbullying, and hate speech. In this paper, we present the first comparative study of hate speech instigators and target users on Twitter. Through a multi-step classification process, we curate a comprehensive hate speech dataset capturing various types of hate. We study the distinctive characteristics of hate instigators and targets in terms of their profile self-presentation, activities, and online visibility. We find that hate instigators target more popular and high profile Twitter users, and that participating in hate speech can result in greater online visibility. We conduct a personality analysis of hate instigators and targets and show that both groups have eccentric personality facets that differ from the general Twitter population. Our results advance the state of the art of understanding online hate speech engagement.
Structured Neural Summarization

Summarization of long sequences into a concise statement is a core problem in natural language processing, requiring non-trivial understanding of the input. Based on the promising results of graph neural networks on highly structured data, we develop a framework to extend existing sequence encoders with a graph component that can reason about long-distance relationships in weakly structured data such as text. In an extensive evaluation, we show that the resulting hybrid sequence-graph models outperform both pure sequence models as well as pure graph models on a range of summarization tasks.
Cross-Sentence N-ary Relation Extraction with Graph LSTMs

Past work in relation extraction focuses on binary relations in single sentences. Recent NLP inroads in high-valued domains have kindled strong interest in the more general setting of extracting n-ary relations that span multiple sentences. In this paper, we explore a general relation extraction framework based on graph long short-term memory (graph LSTM), which can be easily extended to cross-sentence n-ary relation extraction. The graph formulation provides a unifying way to explore different LSTM approaches and incorporate various intra-sentential and inter-sentential dependencies, such as sequential, syntactic, and discourse relations. A robust contextual representation is learned for the entities, which serves as input to the relation classifier, making it easy for scaling to arbitrary relation arity n, as well as for multi-task learning with related relations. We evaluated this framework in two important domains in precision medicine and demonstrated its effectiveness with both supervised learning and distant supervision. Cross-sentence extraction produced far more knowledge, and multi-task learning significantly improved extraction accuracy. A thorough analysis comparing various LSTM approaches yielded interesting insight on how linguistic analysis impacts the performance.
LOJASIEWICZ INEQUALITIES AND APPLICATIONS

In real algebraic geometry, Lojasiewicz's theorem asserts that any integral curve of the gradient flow of an analytic function that has an accumulation point has a unique limit. Lojasiewicz proved this result in the early 1960s as a consequence of his gradient inequality. Many problems in calculus of variations are questions about critical points or gradient flow lines of an infinite dimensional functional. Perhaps surprisingly, even blowups at sin- gularities of many nonlinear PDE's can, in a certain sense, be thought of as limits of infinite dimensional gradient flows of analytic functionals. The question of uniqueness of blowups is perhaps the most fundamental question about singularities. This approach to uniqueness was pioneered by Leon Simon thirty years ago for the area functional and many related functionals using an elaborate reduction to a finite dimensional setting where Lojasiewicz's arguments applied. Recently, the authors proved two new infinite dimensional Lojasiewicz inequalities at non- compact singularities where it was well-known that a reduction to Lojasiewicz's arguments is not possible, but instead entirely new techniques are required. As a consequence, the authors settled a major long-standing open question about uniqueness of blowups for mean curvature flow at all generic singularities and for mean convex mean curvature flow at all singularities.
A comprehensive lattice-stability limit surface for graphene

Abstract The limits of reversible deformation in graphene under various loadings are examined using lattice-dynamical stability analysis. This information is then used to construct a comprehensive lattice-stability limit surface for graphene, which provides an analytical description of incipient lattice instabilities of all kinds, for arbitrary deformations, parametrized in terms of symmetry-invariants of strain/stress. Symmetry-invariants allow obtaining an accurate parametrization with a minimal number of coefficients. Based on this limit surface, we deduce a general continuum criterion for the onset of all kinds of lattice-stabilities in graphene: an instability appears when the magnitude of the deviatoric strain γ reaches a critical value γc which depends upon the mean normal strain E ¯ and the directionality θ of the principal deviatoric stretch with respect to reference lattice orientation. We also distinguish between the distinct regions of the limit surface that correspond to fundamentally different mechanisms of lattice instabilities in graphene, such as structural versus material instabilities, and long-wave (elastic) versus short-wave instabilities. Utility of this limit surface is demonstrated in assessment of incipient failures in defect-free graphene via its implementation in a continuum finite elements analysis (FEA). The resulting scheme enables on-the-fly assessments of not only the macroscopic conditions (e.g., load and deflection) but also the microscopic conditions (e.g., local stress/strain, spatial location, temporal proximity, and nature of incipient lattice instability) at which an instability occurs in a defect-free graphene sheet subjected to an arbitrary loading condition.
On the topology of valuation-theoretic representations of integrally closed domains

Abstract Let F be a field. For each nonempty subset X of the Zariski–Riemann space of valuation rings of F, let A ( X ) = ⋂ V ∈ X V and J ( X ) = ⋂ V ∈ X M V , where M V denotes the maximal ideal of V. We examine connections between topological features of X and the algebraic structure of the ring A ( X ) . We show that if J ( X ) ≠ 0 and A ( X ) is a completely integrally closed local ring that is not a valuation ring of F, then there is a space Y of valuation rings of F that is perfect in the patch topology such that A ( X ) = A ( Y ) . If any countable subset of points is removed from Y, then the resulting set remains a representation of A ( X ) . Additionally, if F is a countable field, the set Y can be chosen homeomorphic to the Cantor set . We apply these results to study properties of the ring A ( X ) with specific focus on topological conditions that guarantee A ( X ) is a Prufer domain, a feature that is reflected in the Zariski–Riemann space when viewed as a locally ringed space. We also classify the rings A ( X ) where X has finitely many patch limit points, thus giving a topological generalization of the class of Krull domains, one that includes interesting Prufer domains. To illustrate the latter, we show how an intersection of valuation rings arising naturally in the study of local quadratic transformations of a regular local ring can be described using these techniques.
Rademacher Complexity for Adversarially Robust Generalization

Many machine learning models are vulnerable to adversarial attacks; for example, adding adversarial perturbations that are imperceptible to humans can often make machine learning models produce wrong predictions with high confidence. Moreover, although we may obtain robust models on the training dataset via adversarial training, in some problems the learned models cannot generalize well to the test data. In this paper, we focus on $\ell_\infty$ attacks, and study the adversarially robust generalization problem through the lens of Rademacher complexity. For binary linear classifiers, we prove tight bounds for the adversarial Rademacher complexity, and show that the adversarial Rademacher complexity is never smaller than its natural counterpart, and it has an unavoidable dimension dependence, unless the weight vector has bounded $\ell_1$ norm. The results also extend to multi-class linear classifiers. For (nonlinear) neural networks, we show that the dimension dependence in the adversarial Rademacher complexity also exists. We further consider a surrogate adversarial loss for one-hidden layer ReLU network and prove margin bounds for this setting. Our results indicate that having $\ell_1$ norm constraints on the weight matrices might be a potential way to improve generalization in the adversarial setting. We demonstrate experimental results that validate our theoretical findings.