cssi/SciSciGPT-SciSciNet huggingface dataset:
Acceleration of SVRG and Katyusha X by Inexact Preconditioning.

Empirical risk minimization is an important class of optimization problems with many popular machine learning applications, and stochastic variance reduction methods are popular choices for solving them. Among these methods, SVRG and Katyusha X (a Nesterov accelerated SVRG) achieve fast convergence without substantial memory requirement. In this paper, we propose to accelerate these two algorithms by \textit{inexact preconditioning}, the proposed methods employ \textit{fixed} preconditioners, although the subproblem in each epoch becomes harder, it suffices to apply \textit{fixed} number of simple subroutines to solve it inexactly, without losing the overall convergence. As a result, this inexact preconditioning strategy gives provably better iteration complexity and gradient complexity over SVRG and Katyusha X. We also allow each function in the finite sum to be nonconvex while the sum is strongly convex. In our numerical experiments, we observe an on average $8\times$ speedup on the number of iterations and $7\times$ speedup on runtime.
Facile fluorination of deoxy-4′-thiopyrimidine nucleosides with “down” hydroxyl groups. Retention of configuration after fluoride opening of the quaternized N3-MEM anhydronucleosides

Abstract Attempted fluorination of 1-(5- O -trityl-3-deoxy-4-thio-β-D- erythro -pentofuranosyl)-3-(2- methoxyethoxymethyl)uracil ( 12 ) and 1-(5- O -trityl-2-deoxy-4-thio-β-D- erythro -pentofuranosyl)-3-(2- methoxyethoxymethyl)uracil ( 14 ) with diethylaminosulfur trifluoride (DAST) produced very reactive N 3 - MEM- O 2 ,2- and N 3 -MEM- O 2 ,3-anhydronucleoside intermediates ( 16 ) that reacted with KF to give the desired fluorinated nucleosides with retention of configuration.
Probing the Mechanism of Fluoride-Ion Conduction in LaF3 and Strontium-Doped LaF3 with High-Resolution 19F MAS NMR

19F MAS NMR of fluoride-ion conductors is shown to be an effective method for probing the mechanisms of anion motion at a local level. The three fluoride-ion sites in the superionic conductor LaF3 and its anion-deficient solid solution La1.99Sr0.01F2.99 all have different dynamic behavior. The three sites are resolved in the 19F spectra, allowing motion between and in each of the sublattices to be observed directly.
First regiospecific, enantiospecific total synthesis of gardnerine and gardnutine

Abstract The first enantiospecific total synthesis of gardnerine and gardnutine has been achieved from 6-methoxy- d -tryptophan via the asymmetric Pictet–Spengler reaction, a stereocontrolled intramolecular enolate driven palladium-mediated cross-coupling reaction and a chemospecific, regiospecific hydroboration/oxidation sequence as key steps.
Photochemistry of Atropisomers: Non-biaryl Atropisomers for Stereospecific Phototransformations

This review highlights the use of atropisomeric (axially chiral) chromophores for stereospecific photoreactions. The presence of axial chirality in the substrate imparts excellent stereo (enantio- ...
Diels-Alder reactivity of a ketovinylphosphonate with cyclopentadiene and furan

Abstract The Diels-Alder reactions between diethyl ketovinylphosphonate 5 and cyclopentadiene or furan were performed with and without Lewis acid assistance. The acetyl group directed endo in all cases, with ratios varying from 1.4:1 –6.7:1 (acetyl endo).
HALIDE-TERMINATED N-ACYLIMINIUM ION-ALKYNE CYCLIZATIONS: A NEW CONSTRUCTION OF CARBACEPHEM ANTIBIOTICS

A series of 4-(3-alkynyl)azetidinones 13 was prepared from 4-(phenylsulfonyl)azetidine-2-one (9) and isopropyl glyoxylate hydrate. The 3-pentynyl (13a) and 4-phenyl-3-butynyl (13b) azetidinone acetates underwent 6-exo cyclization when treated with 3 equiv of SnCl4 at 0 °C to provide 3-(1-chloroalkylidene)carbacephems 15a (65%) and 15b (33%) respectively. In contrast, the 3-butynyl (13d) and 4-(trimethylsilyl)-3-butynyl (13c) azetidinone acetates underwent 7-endo cyclization under similar conditions to give 1-azabicyclo[5.2.0]nonenes 14a (11%) and 14b (71%), respectively. Beginning with penicillin degradation product 18, the more elaborate 3-pentynyl azetidinone cyclization substrate 27 was prepared in seven steps. Exposure to 27 to 3 equiv of SnCl4 in CH2Cl2 at 0 °C for 6 h, followed by allowing the reaction mixture to warm to rt, provided the desired 3-(1-chloroethylidene)carbacephem 28 in 60% yield and high (>99%) enantiometric purity. Cleavage of the chloroethylidene group of 28 with ozone gave 3-hydro...
Dissecting differential signals in high-throughput data from complex tissues.

MOTIVATION Samples from clinical practices are often mixtures of different cell types. The high-throughput data obtained from these samples are thus mixed signals. The cell mixture brings complications to data analysis, and will lead to biased results if not properly accounted for. RESULTS We develop a method to model the high-throughput data from mixed, heterogeneous samples, and to detect differential signals. Our method allows flexible statistical inference for detecting a variety of cell-type specific changes. Extensive simulation studies and analyses of two real datasets demonstrate the favorable performance of our proposed method compared with existing ones serving similar purpose. AVAILABILITY AND IMPLEMENTATION The proposed method is implemented as an R package and is freely available on GitHub (https://github.com/ziyili20/TOAST). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Synthesis and characterization of new 19-vertex macropolyhedral boron hydrides.

The new boron hydride anions 10-R-B19H19- (R = H, Thx) were synthesized by the reaction of M2[B18H20] (M = Na, K) with HBRCl.SMe2 (R = H, Thx) or HBCl2.SMe2 in diethyl ether. The anions are comprised of edge-sharing, nido 10- and 11-vertex cluster fragments, and are characterized by their 11B, 11B[1H], and 11B-11B COSY NMR spectra. The salt [(Ph3P)2N][B19H20].0.5THF crystallized in the triclinic space group P1 (a = 12.6344-(2) A, b = 13.5978(2) A, c = 14.1401(2) A; alpha = 77.402(2) degrees, beta = 81.351(2) degrees, gamma = 73.253(2) degrees). Possible synthetic pathways are discussed. The dianion B19H19(2-) is formed by deprotonation of B19H20- with Proton Sponge (1,8-bis(dimethylamino)naphthalene) in THF, and is identified on the basis of its 11B, 11B[1H], and 11B-11B COSY NMR spectra.
PQS-2: ring-closing- and cross-metathesis reactions on lipophilic substrates; in water only at room temperature, with in-flask catalyst recycling

A ubiquinol side-chain hydrogenated version (PQS-2) of the recently introduced PQS is described. It forms catalytic nanomicellar reactors in water that provide the medium for highly reactive Ru carbene catalysts to effect both ring closing metathesis to trisubstituted olefins and cross-metathesis reactions at room temperature. The catalyst can be recycled without removal from the reaction vessel.
Measuring intolerance to mutation in human genetics

In numerous applications, from working with animal models to mapping the genetic basis of human disease susceptibility, knowing whether a single disrupting mutation in a gene is likely to be deleterious is useful. With this goal in mind, a number of measures have been developed to identify genes in which protein-truncating variants (PTVs), or other types of mutations, are absent or kept at very low frequency in large population samples-genes that appear 'intolerant' to mutation. One measure in particular, the probability of being loss-of-function intolerant (pLI), has been widely adopted. This measure was designed to classify genes into three categories, null, recessive and haploinsufficient, on the basis of the contrast between observed and expected numbers of PTVs. Such population-genetic approaches can be useful in many applications. As we clarify, however, they reflect the strength of selection acting on heterozygotes and not dominance or haploinsufficiency.
Asymmetric Syn-Selective Aldol Reactions of γ-Oxygenated Vinylogous Urethane with a Second Generation Chiral Auxiliary: Application in Construction of (+)-3-Deoxy-d-manno-2-octulosonic Acid

Various examples of highly diastereoselective aldol reactions are presented where the nonracemic lithium enolate 6 derived from a C4-oxygenated vinylogous urethane reacts in syn fashion to provide upon intramolecular lactonization useful γ-alkoxy-δ-lactone synthons 12a−f. In one particular example, the result of reaction with an acrolein surrogate, the lactone product 12e is applied in an efficient asymmetric synthesis of (+)-KDO (10 steps, 34% overall yield). Notable transformations include (1) hydrolysis of the vinylogous urethane functionality, (2) stereoselective reduction of the resulting β-keto-lactone 2, (3) stereoselective dihydroxylation of the vinyl side chain of δ-lactone 17, and (4) addition of α-ethoxy-vinyllithium to the lactone carbonyl of 19 to procure the aldulosonic acid residue in 1 upon ozonolysis.
Predicting serious rare adverse reactions of novel chemicals.

Motivation Adverse drug reactions (ADRs) are one of the main causes of death and a major financial burden on the world's economy. Due to the limitations of the animal model, computational prediction of serious and rare ADRs is invaluable. However, current state-of-the-art computational methods do not yield significantly better predictions of rare ADRs than random guessing. Results We present a novel method, based on the theory of 'compressed sensing' (CS), which can accurately predict serious side-effects of candidate and market drugs. Not only is our method able to infer new chemical-ADR associations using existing noisy, biased and incomplete databases, but our data also demonstrate that the accuracy of CS in predicting a serious ADR for a candidate drug increases with increasing knowledge of other ADRs associated with the drug. In practice, this means that as the candidate drug moves up the different stages of clinical trials, the prediction accuracy of our method will increase accordingly. Availability and implementation The program is available at https://github.com/poleksic/side-effects. Supplementary information Supplementary data are available at Bioinformatics online.
Efficacy Study of a Social Communication and Self-Regulation Intervention for School-Age Children With Autism Spectrum Disorder: A Randomized Controlled Trial.

Purpose This study aimed to examine the initial efficacy of a parent-assisted blended intervention combining components of Structured TEACCHing and Social Thinking, designed to increase social comm...
Strict Bott–Samelson Resolutions of Schubert Varieties

ABSTRACTWe explore the relationship between two desingularization techniques for Schubert varieties. The Bott–Samelson resolution is the more common of the two, but it fails to encompass many prope...
Winning Strategies in Multimove Chess ( i , j )

We propose a class of chess variants, Multimove Chess (i,j), in which White gets i moves per turn and Black gets j moves per turn. One side is said to win when it takes the opponent's king. All other rules of chess apply. We prove that if (i,j) is not (1,1) or (2,2), and if $i \geq \min(j,4)$, then White always has a winning strategy, and otherwise Black always has a winning strategy.
An Extension of the Order Bound for AG Codes

The most successful method to obtain lower bounds for the minimum distance of an algebraic geometric code is the order bound, which generalizes the Feng-Rao bound. By using a finer partition of the set of all codewords of a code we improve the order bounds by Beelen and by Duursma and Park. We show that the new bound can be efficiently optimized and we include a numerical comparison of different bounds for all two-point codes with Goppa distance between 0 and 2g *** 1 for the Suzuki curve of genus g = 124 over the field of 32 elements.
COMBINATORIAL YAMABE FLOW ON HYPERBOLIC SURFACES WITH BOUNDARY

This paper studies the combinatorial Yamabe flow on hyperbolic surfaces with boundary. It is proved by applying a variational principle that the length of boundary components is uniquely determined by the combinatorial conformal factor. The combinatorial Yamabe flow is a gradient flow of a concave function. The long-time behavior of the flow and the geometric meaning is investigated.
P versus NP and geometry

In this primarily expository article, I describe geometric approaches to variants of P versus NP, present several results that illustrate the role of group actions in complexity theory, and make a first step towards geometric definitions of complexity classes. My goal is to help bring geometry and complexity theory closer together.
The "Hot Spots" Conjecture on the Vicsek Set

We prove the Hot Spot conjecture on the Vicsek set. Specifically, we show that every eigenfunction of the second smallest eigenvalue of the Neumann Laplacian on the Vicsek set attains its maximum and minimum on the boundary.
Raman cooling of solids through photonic density of states engineering

The laser cooling of vibrational states of solids has been achieved through photoluminescence in rare-earth elements, optical forces in optomechanics, and Brillouin scattering light–sound interaction. The net cooling of solids through spontaneous Raman scattering and the laser refrigeration of indirect band gap semiconductors both remain unsolved challenges. Here, we show analytically that photonic density of states (DoS) engineering can address the two fundamental requirements for achieving spontaneous Raman cooling: suppressing the dominance of Stokes (heating) transitions and the enhancement of anti-Stokes (cooling) efficiency beyond the natural optical absorption of the material. We develop a general model for the DoS modification to spontaneous Raman scattering probabilities, and elucidate the necessary and minimum condition required for achieving net Raman cooling. With a suitably engineered DoS, we establish the enticing possibility of the refrigeration of intrinsic silicon by annihilating phonons from all its Raman-active modes simultaneously, through a single telecom wavelength pump. This result points to a highly flexible approach for the laser cooling of any transparent semiconductor, including indirect band gap semiconductors, far away from significant optical absorption, band-edge states, excitons, or atomic resonances.
An infinite cardinal version of Gallai’s Theorem for colorings of the plane

We generalize a result of Tibor Gallai as follows: for any finite set of points $\mathcal{S}$ in the plane, if the plane is colored in finitely many colors, then there exist $2^{\aleph_0}$ monochromatic subsets of the plane homothetic to $\mathcal{S}$. Furthermore, we prove an even stronger result for $n$-dimensional Euclidean space.
Action-conditional video prediction using deep networks in Atari games

Motivated by vision-based reinforcement learning (RL) problems, in particular Atari games from the recent benchmark Aracade Learning Environment (ALE), we consider spatio-temporal prediction problems where future image-frames depend on control variables or actions as well as previous frames. While not composed of natural scenes, frames in Atari games are high-dimensional in size, can involve tens of objects with one or more objects being controlled by the actions directly and many other objects being influenced indirectly, can involve entry and departure of objects, and can involve deep partial observability. We propose and evaluate two deep neural network architectures that consist of encoding, action-conditional transformation, and decoding layers based on convolutional neural networks and recurrent neural networks. Experimental results show that the proposed architectures are able to generate visually-realistic frames that are also useful for control over approximately 100-step action-conditional futures in some games. To the best of our knowledge, this paper is the first to make and evaluate long-term predictions on high-dimensional video conditioned by control inputs.
Homology representations arising from the half cube, II

In a previous work, we defined a family of subcomplexes of the n-dimensional half cube by removing the interiors of all half cube shaped faces of dimension at least k, and we proved that the reduced homology of such a subcomplex is concentrated in degree k-1. This homology module supports a natural action of the Coxeter group W(D"n) of type D. In this paper, we explicitly determine the characters (over C) of these homology representations, which turn out to be multiplicity free. Regarded as representations of the symmetric group S"n by restriction, the homology representations turn out to be direct sums of certain representations induced from parabolic subgroups. The latter representations of S"n agree (over C) with the representations of S"n on the (k-2)-nd homology of the complement of the k-equal real hyperplane arrangement.
The pulsating variable star population in DDO210

We have probed the pulsating variable star content of the isolated Local Group dwarf galaxy, DDO210 (Aquarius), using archival Advanced Camera for Surveys/$Hubble$ $Space$ $Telescope$ imaging in the F475W and F814W passbands. We find a total of 32 RR Lyrae stars (24 ab-type, 8 c-type) and 75 Cepheid variables. The mean periods of the ab-type and c-type RR Lyrae stars are calculated to be $\langle$P$_{\mathrm{ab}}\rangle = 0.609\pm0.011$ and $\langle$P$_{\mathrm{c}}\rangle = 0.359\pm0.025$ days, respectively. The light curve properties of the fundamental mode RR Lyrae stars yield a mean metallicity of $\langle$[Fe/H]$\rangle$ = -1.63$\pm$0.11 dex for this ancient population, consistent with a recent synthetic colour-magnitude diagram analysis. We find this galaxy to be Oosterhoff-intermediate and lacking in high-amplitude, short-period ab-type RR Lyrae, consistent with behavior recently observed for many dwarf spheroidals and ultra-faint dwarfs in the Local Group. We find a distance modulus of $\mu = 25.07\pm 0.12$ as determined by the RR Lyrae stars, slightly larger but agreeing with recent distance estimates from the red giant branch tip. We also find a sizable population of Cepheid variables in this galaxy. We provide evidence in favor of most if not all of these stars being short-period classical Cepheids. Assuming all of these stars to be classical Cepheids, we find that most of these Cepheids are $\sim$300 Myr old, with the youngest Cepheids being offset from the older Cepheids and the centre of the galaxy. We conclude that this may have resulted from a migration of star formation in DDO210.
Nonbacktracking Bounds on the Influence in Independent Cascade Models

This paper develops upper and lower bounds on the influence measure in a network, more precisely, the expected number of nodes that a seed set can influence in the independent cascade model. In particular, our bounds exploit nonbacktracking walks, Fortuin-Kasteleyn-Ginibre type inequalities, and are computed by message passing algorithms. Nonbacktracking walks have recently allowed for headways in community detection, and this paper shows that their use can also impact the influence computation. Further, we provide parameterized versions of the bounds that control the trade-off between the efficiency and the accuracy. Finally, the tightness of the bounds is illustrated with simulations on various network models.
DNA Base Pair Mismatches Induce Structural Changes and Alter the Free-Energy Landscape of Base Flip.

Double-stranded DNA may contain mismatched base pairs beyond the Watson–Crick pairs, guanine–cytosine and adenine–thymine. Such mismatches bear adverse consequences for human health. We utilize molecular dynamics and metadynamics computer simulations to study the structure and dynamics of both matched and mismatched base pairs. We discover significant differences between the matched and mismatched pairs in structure and base flip work profiles. Mismatched pairs shift more in the plane normal to the DNA strand and exhibit more noncanonical structures, including the e-motif. We discuss the potential implications on the mismatch repair enzymes’ detection of DNA mismatches.
Overlapping Clustering Models, and One (class) SVM to Bind Them All

People belong to multiple communities, words belong to multiple topics, and books cover multiple genres; overlapping clusters are commonplace. Many existing overlapping clustering methods model each person (or word, or book) as a non-negative weighted combination of "exemplars" who belong solely to one community, with some small noise. Geometrically, each person is a point on a cone whose corners are these exemplars. This basic form encompasses the widely used Mixed Membership Stochastic Blockmodel of networks and its degree-corrected variants, as well as topic models such as LDA. We show that a simple one-class SVM yields provably consistent parameter inference for all such models, and scales to large datasets. Experimental results on several simulated and real datasets show our algorithm (called SVM-cone) is both accurate and scalable.
AMOS: An automated model order selection algorithm for spectral graph clustering

One of the longstanding problems in spectral graph clustering (SGC) is the so-called model order selection problem: automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. In this paper, we propose AMOS, an automated model order selection algorithm for SGC. Based on a recent analysis of clustering reliability for SGC under the random interconnection model, AMOS works by incrementally increasing the number of clusters, estimating the quality of identified clusters, and providing a series of clustering reliability tests. Consequently, AMOS outputs clusters of minimal model order with statistical clustering reliability guarantees. Comparing to three other automated graph clustering methods on real-world datasets, AMOS shows superior performance in terms of multiple external and internal clustering metrics.
Bayesian propensity scores for high-dimensional causal inference: A comparison of drug-eluting to bare-metal coronary stents.

High-dimensional data provides many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model. We discuss methods for Bayesian propensity score analysis of binary treatments, focusing on modern methods for high-dimensional Bayesian regression and the propagation of uncertainty. We introduce a novel and simple estimator for the average treatment effect that capitalizes on conjugacy of the beta and binomial distributions. Through simulations, we show the utility of horseshoe priors and Bayesian additive regression trees paired with our new estimator, while demonstrating the importance of including variance from the treatment regression model. An application to cardiac stent data with almost 500 confounders and 9000 patients illustrates approaches and facilitates comparison with existing alternatives. As measured by a falsifiability endpoint, we improved confounder adjustment compared with past observational research of the same problem.
Minimum cycle and homology bases of surface-embedded graphs

We study the problems of finding a minimum cycle basis (a minimum-weight set of cycles that form a basis for the cycle space) and a minimum homology basis (a minimum-weight set of cycles that generates the 1-dimensional $(\mathbb{ Z}_ 2 )$-homology classes) of an undirected graph cellularly embedded on a surface. The problems are closely related, because the minimum cycle basis of a graph contains its minimum homology basis, and the minimum homology basis of the 1-skeleton of any graph is exactly its minimum cycle basis. For the minimum cycle basis problem, we give a deterministic $ O ( n^ ω + 2^{ 2 g} n^ 2 + m )$-time algorithm for graphs cellularly embedded on an orientable surface of genus $ g$ . Prior to this work, the best known algorithms for surface-embedded graphs were those for general graphs: an $ O ( m^ ω )$-time Monte Carlo algorithm and a deterministic $ O ( nm^ 2 /\ log n + n^ 2 m )$-time algorithm . For the minimum homology basis problem, we give a deterministic $ O (( g + b )^ 3 n\ log n + m )$-time algorithm for graphs cellularly embedded on an orientable or non-orientable surface of genus $ g$ with $ b$ boundary components, improving on existing algorithms for many values of $ g$ and $ n$ . The algorithm assumes that shortest paths are unique; this assumption can be avoided by either using random perturbations of the edge weights guaranteeing a high probability of success or by deterministic means at a cost of an $ O (\log n )$ factor increase in running time.
Learning the Probability of Activation in the Presence of Latent Spreaders

When an infection spreads in a community, an individual's probability of becoming infected depends on both her susceptibility and exposure to the contagion through contact with others. While one often has knowledge regarding an individual's susceptibility, in many cases, whether or not an individual's contacts are contagious is unknown.We study the problem of predicting if an individual will adopt a contagion in the presence of multiple modes of infection (exposure/susceptibility) and latent neighbor influence. We present a generative probabilistic model and a variational inference method to learn the parameters of our model. Through a series of experiments on synthetic data, we measure the ability of the proposed model to identify latent spreaders, and predict the risk of infection. Applied to a real dataset of 20,000 hospital patients, we demonstrate the utility of our model in predicting the onset of a healthcare associated infection using patient room-sharing and nurse-sharing networks. Our model outperforms existing benchmarks and provides actionable insights for the design and implementation of targeted interventions to curb the spread of infection.
The Lifespan of Small Data Solutions to the KP-I

Author(s): Harrop-Griffiths, Benjamin; Ifrim, Mihaela; Tataru, Daniel | Abstract: We show that for small, localized initial data there exists a global solution to the KP-I equation in a Galilean-invariant space using the method of testing by wave packets.
25 Tweets to Know You: A New Model to Predict Personality with Social Media.

Predicting personality is essential for social applications supporting human-centered activities, yet prior modeling methods with users’ written text require too much input data to be realistically used in the context of social media. In this work, we aim to drastically reduce the data requirement for personality modeling and develop a model that is applicable to most users on Twitter. Our model integrates Word Embedding features with Gaussian Processes regression. Based on the evaluation of over 1.3K users on Twitter, we find that our model achieves comparable or better accuracy than state-of-the-art techniques with 8 times fewer data.
Geodesic cusp excursions and metric diophantine approximation

We derive several results that describe the rate at which a generic geodesic makes excursions into and out of a cusp on a finite area hyperbolic surface and relate them to approximation with respect to the orbit of infinity for an associated Fuchsian group. This provides proofs of some well known theorems from metric diophantine approximation in the context of Fuchsian groups. It also gives new results in the classical setting.
Mr. Jones - Towards a Proactive Smart Room Orchestrator.

In this paper, we report work in progress on the development of Mr. Jones -- a proactive orchestrator and decision support agent for a collaborative decision making setting embodied by a smart room. The duties of such an agent may range across interactive problem solving with other agents in the environment, developing automated summaries of meetings, visualization of the internal decision making process, proactive data and resource management, and so on. Specifically, we highlight the importance of integrating higher level symbolic reasoning and intent recognition in the design of such an agent, and outline pathways towards the realization of these capabilities. We will demonstrate some of these functionalities here in the context of automated orchestration of a meeting in the CEL -- the Cognitive Environments Laboratory at IBM's T.J. Watson Research Center.
Systematic target function annotation of human transcription factors.

Transcription factors (TFs), the key players in transcriptional regulation, have attracted great experimental attention, yet the functions of most human TFs remain poorly understood. Recent capabilities in genome-wide protein binding profiling have stimulated systematic studies of the hierarchical organization of human gene regulatory network and DNA-binding specificity of TFs, shedding light on combinatorial gene regulation. We show here that these data also enable a systematic annotation of the biological functions and functional diversity of TFs. We compiled a human gene regulatory network for 384 TFs covering the 146,096 TF–target gene (TF–TG) relationships, extracted from over 850 ChIP-seq experiments as well as the literature. By integrating this network of TF–TF and TF–TG relationships with 3715 functional concepts from six sources of gene function annotations, we obtained over 9000 confident functional annotations for 279 TFs. We observe extensive connectivity between TFs and Mendelian diseases, GWAS phenotypes, and pharmacogenetic pathways. Further, we show that TFs link apparently unrelated functions, even when the two functions do not share common genes. Finally, we analyze the pleiotropic functions of TFs and suggest that the increased number of upstream regulators contributes to the functional pleiotropy of TFs. Our computational approach is complementary to focused experimental studies on TF functions, and the resulting knowledge can guide experimental design for the discovery of unknown roles of TFs in human disease and drug response.
Masking line foregrounds in intensity-mapping surveys

We address the problem of line confusion in intensity mapping surveys and explore the possibility to mitigate line foreground contamination by progressively masking the brightest pixels in the observed map. We consider experiments targeting CO(1-0) at $z=3$, Ly$\alpha$ at $z=7$, and CII at $z=7$, and use simulated intensity maps, which include both clustering and shot noise components of the signal and possible foregrounds, in order to test the efficiency of our method. We find that for CO and Ly$\alpha$ it is quite possible to remove most of the foreground contribution from the maps via only 1%-3% pixel masking. The CII maps will be more difficult to clean, however, due to instrumental constraints and the high-intensity foreground contamination involved. While the masking procedure sacrifices much of the astrophysical information present in our maps, we demonstrate that useful cosmological information in the targeted lines can be successfully retrieved.
Sets of rich lines in general position

Given a set of $n$ points in $R^2$, the Szemer\'edi-Trotter theorem establishes that the number of lines which can be incident to at least $k > 1$ of these points is $O(n^2/k^3 + n/k)$. J.\ Solymosi conjectured that if one requires the points to be in a grid formation and the lines to be in general position---no two parallel, no three meeting at a point---then one can get a much tighter bound. We prove: for every $\epsilon > 0$ there exists some $\delta > 0$ such that for sufficiently large values of $n$, every set of lines in general position, each intersecting an $n \times n$ grid of points in at least $n^{1-\delta}$ places, has size at most $n^\epsilon$.
Inversion polynomials for permutations avoiding consecutive patterns

Abstract In 2012, Sagan and Savage introduced the notion of st-Wilf equivalence for a statistic st and for sets of permutations that avoid particular permutation patterns. In this paper we consider inv-Wilf equivalence on sets of permutations that avoid two or more consecutive permutation patterns. We say that two sets of generalized permutation patterns Π and Π ′ are inv-Wilf equivalent if the generating function for the inversion statistic on the permutations that simultaneously avoid all elements of Π is equal to the generating function for the inversion statistic on the permutations that simultaneously avoid all elements of Π ′ . In 2013, Cameron and Killpatrick gave the inversion generating function for Fibonacci tableaux which are in one-to-one correspondence with the set of permutations that simultaneously avoid the consecutive patterns 321 and 312. In this paper, we use the language of Fibonacci tableaux to study the inversion generating functions for permutations that avoid Π where Π is a set of three or more consecutive permutation patterns. In addition, we introduce the more general notion of strip tableaux which are a useful combinatorial object for studying consecutive pattern avoidance. We give the inversion generating functions for Π a subset of 4 or 5 consecutive permutation patterns and for all but one of the cases where Π is a subset of three consecutive permutation patterns.
Unsupervised POS Induction with Word Embeddings

Unsupervised word embeddings have been shown to be valuable as features in supervised learning problems; however, their role in unsupervised problems has been less thoroughly explored. In this paper, we show that embeddings can likewise add value to the problem of unsupervised POS induction. In two representative models of POS induction, we replace multinomial distributions over the vocabulary with multivariate Gaussian distributions over word embeddings and observe consistent improvements in eight languages. We also analyze the e ect of various choices while inducing word embeddings on “downstream” POS induction results.
Smoothing spline growth curves with covariates

We adapt the interactive spline model of Wahba. to growth curves o with covariates. The smoothing spline formulation permits a nonpara-metric representation of the growth curves. In the limit when the discretization error is small relative to the estimation error, the resulting growth curve estimates often depend only weakly on the number and locations of the knots. The smoothness parameter is determined from the data by minimizing an empirical estimate of the expected error. We show that the risk estimate of Craven and Wahba is a weighted goodness of fit estimate, A modified loss estimate is given, where a2 is replaced by its unbiased estimate.
The Distribution of the Variance of Primes in Arithmetic Progressions

Hooley conjectured that the variance V(x;q) of the distribution of primes up to x in the arithmetic progressions modulo q is asymptotically x log q, in some unspecified range of q\leq x. On average over 1\leq q \leq Q, this conjecture is known unconditionally in the range x/(log x)^A \leq Q \leq x; this last range can be improved to x^{\frac 12+\epsilon} \leq Q \leq x under the Generalized Riemann Hypothesis (GRH). We argue that Hooley's conjecture should hold down to (loglog x)^{1+o(1)} \leq q \leq x for all values of q, and that this range is best possible. We show under GRH and a linear independence hypothesis on the zeros of Dirichlet L-functions that for moderate values of q, \phi(q)e^{-y}V(e^y;q) has the same distribution as that of a certain random variable of mean asymptotically \phi(q) log q and of variance asymptotically 2\phi(q)(log q)^2. Our estimates on the large deviations of this random variable allow us to predict the range of validity of Hooley's Conjecture.
A note on the random greedy triangle-packing algorithm

The random greedy algorithm for constructing a large partial Steiner-Triple-System is defined as follows. Begin with a complete graph on n vertices and proceed to remove the edges of triangles one at a time, where each triangle removed is chosen uniformly at random out of all remaining triangles. This stochastic process terminates once it arrives at a triangle-free graph, and a longstanding open problem is to estimate the final number of edges, or equivalently the time it takes the process to conclude. The intuition that the edge distribution is roughly uniform at all times led to a folklore conjecture that the final number of edges is n 3/2+o(1) with high probability, whereas the best known upper bound is n 7/4+o(1) . It is no coincidence that various methods break precisely at the exponent 7/4 as it corresponds to the inherent barrier where co-degrees become comparable to the variations in their values that arose earlier in the process. In this work we significantly improve upon the previous bounds by establishing that w.h.p. the number of edges in the final graph is at most n 5/3+o(1) . Our approach relies on a system of martingales used to control key graph parameters, where the crucial new idea is to harness the self-correcting nature of the process in order to control these parameters well beyond the point where their early variation matches the order of their expectation.
Ensemble Control of Time-Invariant Linear Systems with Linear Parameter Variation

In this paper, we study the control of a class of time-invariant linear ensemble systems whose natural dynamics are linear in the system parameter. This class of ensemble control systems arises from practical engineering and physical applications, such as transport of quantum particles and control of uncertain harmonic systems. We establish explicit algebraic criteria to examine controllability of such ensemble systems. Our derivation is based on the notion of polynomial approximation, where the elements of the reachable set of the ensemble system are represented in polynomials of the system parameter and used to approximate the desired state of interest. In addition, we highlight the role of the spectra of the system matrices play in the determination of ensemble controllability. Finally, illustrative examples and numerical simulations for optimal control of this class of linear ensemble systems are presented to demonstrate the theoretical results.
Equivalence for Networks With Adversarial State

We address the problem of finding the capacity of noisy networks with either independent point-to-point compound channels (CC) or arbitrarily varying channels (AVC). These channels model the presence of a Byzantine adversary, which controls a subset of links or nodes in the network. We derive equivalence results showing that these point-to-point channels with state can be replaced by noiseless bit-pipes without changing the network capacity region. Exact equivalence results are found for the CC model, and for some instances of the AVC, including all nonsymmetrizable AVCs. These results show that a feedback path between the output and input of a CC can increase the equivalent capacity, and that if common randomness can be established between the terminals of an AVC (either by a feedback, a forward path, or via a third-party node), then again the equivalent capacity can increase. This leads to an observation that deleting an edge of arbitrarily small capacity can cause a significant change in network capacity. We also analyze an example involving an AVC for which no fixed-capacity bit-pipe is equivalent.
Toric symplectic ball packing

Abstract We define and solve the toric version of the symplectic ball packing problem, in the sense of listing all 2 n -dimensional symplectic–toric manifolds which admit a perfect packing by balls embedded in a symplectic and torus equivariant fashion. In order to do this we first describe a problem in geometric–combinatorics which is equivalent to the toric symplectic ball packing problem. Then we solve this problem using arguments from Convex Geometry and Delzant theory. Applications to symplectic blowing-up are also presented, and some further questions are raised in the last section.
An O(N) Direct Solver for Integral Equations on the Plane

Abstract An efficient direct solver for volume integral equations with O ( N ) complexity for a broad range of problems is presented. The solver relies on hierarchical compression of the discretized integral operator, and exploits that off-diagonal blocks of certain dense matrices have numerically low rank. Technically, the solver is inspired by previously developed direct solvers for integral equations based on “recursive skeletonization” and “Hierarchically Semi-Separable” (HSS) matrices, but it improves on the asymptotic complexity of existing solvers by incorporating an additional level of compression. The resulting solver has optimal O ( N ) complexity for all stages of the computation, as demonstrated by both theoretical analysis and numerical examples. The computational examples further display good practical performance in terms of both speed and memory usage. In particular, it is demonstrated that even problems involving 107 unknowns can be solved to precision 10 − 10 using a simple Matlab implementation of the algorithm executed on a single core.
Chain integral solutions to tautological systems

We give a new geometrical interpretation of the local analytic solutions to a differential system, which we call a tautological system τ, arising from the universal family of Calabi–Yau hypersurfaces Y_a in a G-variety X of dimension n. First, we construct a natural topological correspondence between relative cycles in H_n (X−Y_a, ∪ D−Y_a) bounded by the union of G-invariant divisors ∪D in X to the solution sheaf of τ, in the form of chain integrals. Applying this to a toric variety with torus action, we show that in addition to the period integrals over cycles in Y_a, the new chain integrals generate the full solution sheaf of a GKZ system. This extends an earlier result for hypersurfaces in a projective homogeneous variety, whereby the chains are cycles [3, 7]. In light of this result, the mixed Hodge structure of the solution sheaf is now seen as the MHS of H_n (X−Y_a,∪ D−Y_a). In addition, we generalize the result on chain integral solutions to the case of general type hypersurfaces. This chain integral correspondence can also be seen as the Riemann–Hilbert correspondence in one homological degree. Finally, we consider interesting cases in which the chain integral correspondence possibly fails to be bijective.
Disfluency Detection Using a Bidirectional LSTM.

We introduce a new approach for disfluency detection using a Bidirectional Long-Short Term Memory neural network (BLSTM). In addition to the word sequence, the model takes as input pattern match features that were developed to reduce sensitivity to vocabulary size in training, which lead to improved performance over the word sequence alone. The BLSTM takes advantage of explicit repair states in addition to the standard reparandum states. The final output leverages integer linear programming to incorporate constraints of disfluency structure. In experiments on the Switchboard corpus, the model achieves state-of-the-art performance for both the standard disfluency detection task and the correction detection task. Analysis shows that the model has better detection of non-repetition disfluencies, which tend to be much harder to detect.
Towards Three-Dimensional Conformal Probability

In this outline of a program, based on rigorous renormalization group theory, we introduce new definitions which allow one to formulate precise mathematical conjectures related to conformal invariance as studied by physicists in the area known as higher-dimensional conformal bootstrap which has developed at a breathtaking pace over the last few years. We also explore a second theme, intimately tied to conformal invariance for random distributions, which can be construed as a search for very general first and second-quantized Kolmogorov-Chentsov Theorems. First-quantized refers to regularity of sample paths. Second-quantized refers to regularity of generalized functionals or Hida distributions and relates to the operator product expansion.We formulate this program in both the Archimedean and p-adic situations. Indeed, the study of conformal field theory and its connections with probability provides a golden opportunity where p-adic analysis can lead the way towards a better understanding of open problems in the Archimedean setting. Finally, we present a summary of progress made on a p-adic hierarchical model and point out possible connections to number theory. Parts of this article were presented in author’s talk at the 6th International Conference on p-adicMathematical Physics and its Applications,Mexico 2017.
Multi-degree Bounds on the Betti Numbers of Real Varieties and Semi-algebraic Sets and Applications

We prove new bounds on the Betti numbers of real varieties and semi-algebraic sets that have a more refined dependence on the degrees of the polynomials defining them than results known before. Our method also unifies several different types of results under a single framework, such as bounds depending on the total degrees, on multi-degrees, as well as in the case of quadratic and partially quadratic polynomials. The bounds we present in the case of partially quadratic polynomials offer a significant improvement over what was previously known. Finally, we extend a result of Barone and Basu on bounding the number of connected components of real varieties defined by two polynomials of differing degrees to the sum of all Betti numbers, thus making progress on an open problem posed in that paper.
Strong convergence of integrators for nonequilibrium Langevin dynamics

Several numerical schemes are proposed for the solution of Nonequilibrium Langevin Dynamics (NELD), and the strong rate of convergence for each scheme is analyzed. The schemes considered here emplo...
Stein Variational Gradient Descent as Moment Matching

Stein variational gradient descent (SVGD) is a non-parametric inference algorithm that evolves a set of particles to fit a given distribution of interest. We analyze the non-asymptotic properties of SVGD, showing that there exists a set of functions, which we call the Stein matching set, whose expectations are exactly estimated by any set of particles that satisfies the fixed point equation of SVGD. This set is the image of Stein operator applied on the feature maps of the positive definite kernel used in SVGD. Our results provide a theoretical framework for analyzing the properties of SVGD with different kernels, shedding insight into optimal kernel choice. In particular, we show that SVGD with linear kernels yields exact estimation of means and variances on Gaussian distributions, while random Fourier features enable probabilistic bounds for distributional approximation. Our results offer a refreshing view of the classical inference problem as fitting Stein’s identity or solving the Stein equation, which may motivate more efficient algorithms.
A Digital Predistortion Scheme Exploiting Degrees-of-Freedom for Massive MIMO Systems

The primary source of nonlinear distortion in wireless transmitters is the power amplifier (PA). Conventional digital predistortion (DPD) schemes use high- order polynomials to accurately approximate and compensate for the nonlinearity of the PA. This is not practical for scaling to tens or hundreds of PAs in massive multiple-input multiple-output (MIMO) systems. There is more than one candidate precoding matrix in a massive MIMO system because of the excess degrees-of- freedom (DoFs), and each precoding matrix requires a different DPD polynomial order to compensate for the PA nonlinearity. This paper proposes a low-order DPD method achieved by exploiting massive DoFs of next-generation front ends. We propose a novel indirect learning structure which adapts the channel and PA distortion iteratively by cascading adaptive zero forcing precoding and DPD. Our solution uses a 3rd order polynomial to achieve the same performance as the conventional DPD using an 11th order polynomial for a 100×10 massive MIMO configuration. Experimental results show a 70% reduction in computational complexity, enabling ultra-low latency communications.