cssi/SciSciGPT-SciSciNet huggingface dataset:
Evaluation of correlates of protection against influenza A(H3N2) and A(H1N1)pdm09 infection: Applications to the hospitalized patient population

BACKGROUND Influenza vaccines are important for prevention of influenza-associated hospitalization. However, the effectiveness of influenza vaccines can vary by year and influenza type and subtype and mechanisms underlying this variation are incompletely understood. Assessments of serologic correlates of protection can support interpretation of influenza vaccine effectiveness in hospitalized populations. METHODS We enrolled adults hospitalized for treatment of acute respiratory illnesses during the 2014-2015 and 2015-2016 influenza seasons whose symptoms began <10 days prior to enrollment. Influenza infection status was determined by RT-PCR. Influenza vaccination status was defined by self-report and medical record/registry documentation. Serum specimens collected at hospital admission were tested in hemagglutination-inhibition (HAI) and neuraminidase-inhibition (NAI) assays. We evaluated how well antibody measured in these specimens represented pre-infection immune status, and measured associations between antibody and influenza vaccination and infection. RESULTS Serum specimens were retrieved for 315 participants enrolled during the 2014-2015 season and 339 participants during the 2015-2016 season. Specimens were collected within 3 days of illness onset from 65% of participants. Geometric mean titers (GMTs) did not vary by the number of days from illness onset to specimen collection among influenza positive participants suggesting that measured antibody was representative of pre-infection immune status rather than a de novo response to infection. In both seasons, vaccinated participants had higher HAI and NAI GMTs than unvaccinated. HAI titers against the 2014-2015 A(H3N2) vaccine strain did not correlate with protection from infection with antigenically-drifted A(H3N2) viruses that circulated that season. In contrast, higher HAI titers against the A(H1N1)pdm09 vaccine strain were associated with reduced odds of A(H1N1)pdm09 infection in 2015-2016. CONCLUSIONS Serum collected shortly after illness onset at hospital admission can be used to assess correlates of protection against influenza infection. Broader implementation of similar studies would provide an opportunity to understand the successes and shortcomings of current influenza vaccines.
Preparation, X-ray crystal structures, and reactivity of alkynylcyclopropenylium salts

Several 1,2-diphenyl-3-alkynylcyclopropenes were prepared by the reaction of acetylenic nucleophiles with diphenylcyclopropenylium perchlorate. The cyclopropenes were converted into alkynylcyclopropenylium salts via hydride abstraction with triphenylmethyl cation. Attempts to prepare a dication from either ethyne-bridged or butadiyne-bridged biscyclopropenes produced only the corresponding monocations. A dication was prepared when an ethylene spacer was inserted between the acetylene groups of the butadiyne-bridged biscyclopropene. Single-crystal X-ray structures of three of the cyclopropenylium ions were obtained. pKR+ titrations were carried out on two of the salts, which showed that acetylene substituents provide about the same degree of stability to the cyclopropenylium core as a phenyl group. Nucleophilic addition to the alkynylcyclopropenylium ions under kinetic conditions gave a statistical mixture of products; however, under thermodynamic reaction conditions, nucleophilic addition followed by ring...
An enantiospecific synthesis of L(−)- and D(+)-6-Chloro-5-hydroxytryptophan: an unusual amino acid residue from the cyclic hexapeptide keramamide a

Abstract An enantiospecific synthesis of both L(−)- and D(+)-6-chloro-5-hydroxytryptophan 1a and important derivatives 1b and 1c was achieved in five steps from 6-chloro-5-methoxy-3-methylindole 2.
Cross-linking BioThings APIs through JSON-LD to facilitate knowledge exploration.

Application Programming Interfaces (APIs) are now widely used to distribute biological data. And many popular biological APIs developed by many different research teams have adopted Javascript Object Notation (JSON) as their primary data format. While usage of a common data format offers significant advantages, that alone is not sufficient for rich integrative queries across APIs. Here, we have implemented JSON for Linking Data (JSON-LD) technology on the BioThings APIs that we have developed, MyGene.info , MyVariant.info and MyChem.info . JSON-LD provides a standard way to add semantic context to the existing JSON data structure, for the purpose of enhancing the interoperability between APIs. We demonstrated several use cases that were facilitated by semantic annotations using JSON-LD, including simpler and more precise query capabilities as well as API cross-linking. We believe that this pattern offers a generalizable solution for interoperability of APIs in the life sciences.
Stepwise C-Terminal Truncation of Cardiac Troponin T Alters Function at Low and Saturating Ca2+

Activation of striated muscle contraction occurs in response to Ca2+ binding to troponin C. The resulting reorganization of troponin repositions tropomyosin on actin and permits activation of myosin-catalyzed ATP hydrolysis. It now appears that the C-terminal 14 amino acids of cardiac troponin T (TnT) control the level of activity at both low and high Ca2+. We made a series of C-terminal truncation mutants of human cardiac troponin T, isoform 2, to determine if the same residues of TnT are involved in the low and high Ca2+ effects. We measured the effect of these mutations on the normalized ATPase activity at saturating Ca2+. Changes in acrylodan tropomyosin fluorescence and the degree of Ca2+ stimulation of the rate of binding of rigor myosin subfragment 1 to pyrene-labeled actin-tropomyosin-troponin were measured at low Ca2+. These measurements define the distribution of actin-tropomyosin-troponin among the three regulatory states. Residues SKTR and GRWK of TnT were required for the functioning of TnT at both low and high Ca2+. Thus, the effects on forming the inactive B-state and in retarding formation of the active M-state require the same regions of TnT. We also observed that the rate of binding of rigor subfragment 1 to pyrene-labeled regulated actin at saturating Ca2+ was higher for the truncation mutants than for wild-type TnT. This violated an assumption necessary for determining the B-state population by this kinetic method.
New Condensed Cluster Structure with Triple Metal Layers: La2INi2 and La2ICu2. Synthesis, Structure, and Bonding

Syntheses of the title compounds result from appropriate reactions of the elements and LaI{sub 3} in sealed Nb or Ta containers at 800 C. These exhibit a new structural type with an unusual metal-rich layered structure, detailed for La{sub 2}INi{sub 2} by single-crystal X-ray diffraction. This is related to the Gd{sub 2}IFe{sub 2}-type structure known for La{sub 2}IZ{sub 2} for Z = Fe, Co, and others. Both structures contain AlB{sub 2}-like slabs, namely, graphite-like Z{sub 2} (Z = Ni, Fe) layers between eclipsed pairs of La layers, but these are instead separated by single iodine layers. The La{sub 2}INi{sub 2} structure differs in that the iodine positions along {rvec c} project onto only one Z position instead of both and the cell is half as large. An additional set of very weak reflections and streaks revealed in widely varying amounts by precession photographs suggests a superstructure in c or intergrowths by small amounts of disordered components, but a reasonable model could not be derived beyond some possible short-range disordering in the iodine layers. Comparisons of La{sub 2}INi{sub 2} with La{sub 2}IFe{sub 2} in terms of electronic band structures show that filling of antibonding states occurs in the Ni layers. Integratedmore » overlap populations in the Fe vs Ni compounds show corresponding decreases for Z-Z and La-Z bonding and a smaller strengthening of La-La bonding in the layers, while the a lattice parameter increases and the trigonal prismatic La{sub 6}Z units decrease in height. These conflicts are reflected in the Z-layer puckering and the doubled c dimension found in La{sub 2}IFe{sub 2} and other phases with the Gd{sub 2}IFe{sub 2}-type structure.« less
Wolf-Hirschhorn Syndrome-Associated Genes Are Enriched in Motile Neural Crest Cells and Affect Craniofacial Development in Xenopus laevis

Wolf-Hirschhorn Syndrome (WHS) is a human developmental disorder arising from a hemizygous perturbation, typically a microdeletion, on the short arm of chromosome four. In addition to pronounced intellectual disability, seizures, and delayed growth, WHS presents with a characteristic facial dysmorphism and varying prevalence of microcephaly, micrognathia, cartilage malformation in the ear and nose, and facial asymmetries. These affected craniofacial tissues all derive from a shared embryonic precursor, the cranial neural crest (CNC), inviting the hypothesis that one or more WHS-affected genes may be critical regulators of neural crest development or migration. To explore this, we characterized expression of multiple genes within or immediately proximal to defined WHS critical regions, across the span of craniofacial development in the vertebrate model system Xenopus laevis. This subset of genes, whsc1, whsc2, letm1, and tacc3, are diverse in their currently-elucidated cellular functions; yet we find that their expression demonstrates shared tissue-specific enrichment within the anterior neural tube, migratory neural crest, and later craniofacial structures. We examine the ramifications of this by characterizing craniofacial development and neural crest migration following individual gene depletion. We observe that several WHS-associated genes significantly impact facial patterning, cartilage formation, neural crest motility in vivo and in vitro, and can separately contribute to forebrain scaling. Thus, we have determined that numerous genes within and surrounding the defined WHS critical regions potently impact craniofacial patterning, suggesting their role in WHS presentation may stem from essential functions during neural crest-derived tissue formation.
Cyanocuprate-mediated intramolecular biaryl couplings applied to an ellagitannin. Synthesis of (+)-O-permethyltellimagrandin II

Abstract Generation of an intramolecularly tethered, nonracemic diaryl cuprate followed by its oxidation with ground state oxygen at −78° leads to a biaryl precursor to an ellagitannin. Subsequent attachment of the appropriate glucose unit completes the synthesis of the title compound.
Functionalized 4-carboxy- and 4-keto-2,3-dihydropyrroles via Ni(II)-catalyzed nucleophilic amine ring-opening cyclizations of cyclopropanes.

A general synthetic approach to vinylogous 4-carboxy- and 4-keto-2,3-dihydropyrroles is reported using Ni(ClO4)2·6H2O as a Lewis acid catalyst for nucleophilic amine ring-opening cyclizations of donor–acceptor (D–A) cyclopropanes. This methodology provided good to excellent yields of functionalized 2,3-dihydropyrroles under milder reaction conditions than previously reported and is amenable to a variety of D–A cyclopropanes and primary amines.
A General Framework for Counterfactual Learning-to-Rank

Implicit feedback (e.g., click, dwell time) is an attractive source of training data for Learning-to-Rank, but its naive use leads to learning results that are distorted by presentation bias. For the special case of optimizing average rank for linear ranking functions, however, the recently developed SVM-PropRank method has shown that counterfactual inference techniques can be used to provably overcome the distorting effect of presentation bias. Going beyond this special case, this paper provides a general and theoretically rigorous framework for counterfactual learning-to-rank that enables unbiased training for a broad class of additive ranking metrics (e.g., Discounted Cumulative Gain (DCG)) as well as a broad class of models (e.g., deep networks). Specifically, we derive a relaxation for propensity-weighted rank-based metrics which is subdifferentiable and thus suitable for gradient-based optimization. We demonstrate the effectiveness of this general approach by instantiating two new learning methods. One is a new type of unbiased SVM that optimizes DCG - called SVM PropDCG - and we show how the resulting optimization problem can be solved via the Convex Concave Procedure (CCP). The other is Deep PropDCG, where the ranking function can be an arbitrary deep network. In addition to the theoretical support, we empirically find that SVM PropDCG significantly outperforms existing linear rankers in terms of DCG. Moreover, the ability to train non-linear ranking functions via Deep PropDCG further improves performance.
Mirror symmetry and the Strominger-Yau-Zaslow conjecture

This survey was written for the Current Developments in Mathematics conference, 2012, and is an updating of my article "The Strominger-Yau-Zaslow conjecture: From torus fibrations to degenerations," in the Seattle 2005 proceedings. We trace progress and thinking about the SYZ conjecture since its introduction in 1996. We begin with the original differential geometric conjecture and its refinements, and explain how it led to the algebro-geometric program developed by myself and Siebert. After explaining the overall philosophy, I explain how recent results fit into this program.
A contractive approach to separable Lyapunov functions for monotone systems

Monotone systems preserve a partial ordering of states along system trajectories and are often amenable to separable Lyapunov functions that are either the sum or the maximum of a collection of functions of a scalar argument. In this paper, we consider constructing separable Lyapunov functions for monotone systems that are also contractive, that is, the distance between any pair of trajectories exponentially decreases. We assume the system evolves in a forward invariant rectangular domain, and the distance between trajectories is defined in terms of a Finsler type metric characterized by a possibly state-dependent norm. When this norm is a weighted one-norm, we obtain conditions which lead to sum-separable Lyapunov functions, and when this norm is a weighted infinity-norm, symmetric conditions lead to max-separable Lyapunov functions. In addition, we consider two classes of Lyapunov functions: the first class is separable along the system’s state, and the second class is separable along components of the system’s vector field. The latter case is advantageous for many practically motivated systems for which it is difficult to measure the system’s state but easier to measure the system’s velocity or rate of change.
The Consequences of Friendships: Evidence on the Effect of Social Relationships in School on Academic Achievement

Abstract This paper examines the impact of youth friendship links on student's own academic performance (grade point average) using the Add Health. We estimate a reduced form, high dimensional fixed effects model of within cohort or grade friendship links and use this model to predict each student's number of friends whose mothers completed four years of college. The effects of friendship links are identified using across-cohort, within school variation in demographic composition of the student's cohort or grade. We find that increases in the number of friendship links with students whose mothers are college educated raises grade point average among girls, but not among boys. Additional analyses suggest a positive view of the school environment and a perception of one's self as functioning well in that environment as possible mechanisms. The effects are relatively broad based across students over maternal education, racial and ethnic composition, and across schools that vary in demographic composition.
Talakat: bullet hell generation through constrained map-elites

We describe a search-based approach to generating new levels for bullet hell games, which are action games characterized by and requiring avoidance of a very large amount of projectiles. Levels are represented using a domain-specific description language, and search in the space defined by this language is performed by a novel variant of the Map-Elites algorithm which incorporates a feasible-infeasible approach to constraint satisfaction. Simulation-based evaluation is used to gauge the fitness of levels, using an agent based on best-first search. The performance of the agent can be tuned according to the two dimensions of strategy and dexterity, making it possible to search for level configurations that require a specific combination of both. As far as we know, this paper describes the first generator for this game genre, and includes several algorithmic innovations.
Analysis of Fast Alternating Minimization for Structured Dictionary Learning

Methods exploiting sparsity have been popular in imaging and signal processing applications including compression, denoising, and imaging inverse problems. Data-driven approaches such as dictionary learning enable one to discover complex image features from datasets and provide promising performance over analytical models. Alternating minimization algorithms have been particularly popular in dictionary and transform learning. In this work, we study the properties of alternating minimization for structured (unitary) sparsifying operator learning. While the algorithm converges to the stationary points of the non-convex problem in general, we prove local linear convergence to the underlying generative model under mild assumptions. Our experiments show that the unitary operator learning algorithm is robust to initialization.
A data-driven approach to pre-operative evaluation of lung cancer patients

Many early stage lung cancer patients have resectable tumors, however, their cardiopulmonary function needs to be properly evaluated before they are deemed operative candidates. Such patients are typically asked to undergo standard pulmonary function tests, including cardiopulmonary exercise tests (CPET) or stair climbs. The standard tests are conducted only at selected healthcare provider locations, and are labor intensive. In addition, they are sometimes ineffective due to patient co-morbidities, such as limited mobility, which limits patient participation. To address these shortcomings, we envision that cardiopulmonary function can be evaluated in the patient's environment using an inexpensive wearable device during routine physical activities. We present a cloud-connected mask that is fitted with CO 2 , O 2 , flow volume, and accelerometer sensors. The data collected from the device is transmitted to a cloud service, which facilitates utilization of various data mining algorithms for extraction of insights from the data. As a necessary first step toward cardiopulmonary function evaluation, we study automatic recognition of the user's physical activity from mask sensors data via an empirical analysis of several data representation and classification algorithms. The results demonstrate accurate activity recognition using mask sensors, and underscore the potential of our approach for cardiopulmonary function evaluation.
Population Stability: Regulating Size in the Presence of an Adversary

We introduce a new coordination problem in distributed computing that we call the population stability problem. A system of agents each with limited memory and communication, as well as the ability to replicate and self-destruct, is subjected to attacks by a worst-case adversary that can at a bounded rate (1) delete agents chosen arbitrarily and (2) insert additional agents with arbitrary initial state into the system. The goal is perpetually to maintain a population whose size is within a constant factor of the target size N. The problem is inspired by the ability of complex biological systems composed of a multitude of memory-limited individual cells to maintain a stable population size in an adverse environment. Such biological mechanisms allow organisms to heal after trauma or to recover from excessive cell proliferation caused by inflammation, disease, or normal development. We present a population stability protocol in a communication model that is a synchronous variant of the population model of Angluin et al. In each round, pairs of agents selected at random meet and exchange messages, where at least a constant fraction of agents is matched in each round. Our protocol uses three-bit messages and ω(log^2 N) states per agent. We emphasize that our protocol can handle an adversary that can both insert and delete agents, a setting in which existing approximate counting techniques do not seem to apply. The protocol relies on a novel coloring strategy in which the population size is encoded in the variance of the distribution of colors. Individual agents can locally obtain a weak estimate of the population size by sampling from the distribution, and make individual decisions that robustly maintain a stable global population size.
Combinatorics of Tableau Inversions

A tableau inversion is a pair of entries in row-standard tableau $T$ that lie in the same column of $T$ yet lack the appropriate relative ordering to make $T$ column-standard. An $i$-inverted Young tableau is a row-standard tableau along with precisely $i$ inversion pairs. Tableau inversions were originally introduced by Fresse to calculate the Betti numbers of Springer fibers in Type A, with the number of $i$-inverted tableaux that standardize to a fixed standard Young tableau corresponding to a specific Betti number of the associated fiber. In this paper we approach the topic of tableau inversions from a completely combinatorial perspective. We develop formulas enumerating the number of $i$-inverted Young tableaux for a variety of tableaux shapes, not restricting ourselves to inverted tableau that standardize a specific standard Young tableau, and construct bijections between $i$-inverted Young tableaux of a certain shape with $j$-inverted Young tableaux of different shapes. Finally, we share some the results of a computer program developed to calculate tableaux inversions.
Generalized Boundary Strata Classes

We describe a generalization of the usual boundary strata classes in the Chow ring of \(\overline {M}_{g,n}\). The generalized boundary strata classes additively span a subring of the tautological ring. We describe a multiplication law satisfied by these classes and check that every double ramification cycle lies in this subring.
Non)Uniqueness of critical points in variational data assimilation

Abstract In this paper we apply the 4D-Var data assimilation scheme to the initialization problem for a family of quasilinear evolution equations. The resulting variational problem is non-convex, so it need not have a unique minimizer. We comment on the implications of non-uniqueness for numerical applications, then prove uniqueness results in the following situations: (1) the observational times are sufficiently small; (2) the prior covariance is sufficiently small. We also give an example of a data set where the cost functional has a critical point of arbitrarily large Morse index, thus demonstrating that the geometry can be highly nonconvex even for a relatively mild nonlinearity.
Learning Feature Representations for Keyphrase Extraction

In supervised approaches for keyphrase extraction, a candidate phrase is encoded with a set of hand-crafted features and machine learning algorithms are trained to discriminate keyphrases from non-keyphrases. Although the manually-designed features have shown to work well in practice, feature engineering is a difficult process that requires expert knowledge and normally does not generalize well. In this paper, we present SurfKE, a feature learning framework that exploits the text itself to automatically discover patterns that keyphrases exhibit. Our model represents the document as a graph and automatically learns feature representation of phrases. The proposed model obtains remarkable improvements in performance over strong baselines.
A generalized mean field algorithm for variational inference in exponential families

We present a ciass of generalized mean field (GMF) algorithms for approximate inference in exponential family graphical models which is analogous to the generalized belief propagation (GBP) or cluster variational methods. While those methods are based on overlapping clusters, our approach is based on nonoverlapping clusters. Unlike the cluster variational methods, the approach is proved to converge to a globally consistent set of marginals and a lower bound on the likelihood, while providing much of the flexibility associated with cluster variational methods. We present experiments that analyze the effect of different choices of clustering on inference quality, and compare GMF with belief propagation on several canonical models.
A new variable step-size zero-point attracting projection algorithm

This paper proposes a new variable step-size (VSS) scheme for the recently introduced zero-point attracting projection (ZAP) algorithm. The proposed variable step-size ZAPs are based on the gradient of the estimated filter coefficients' sparseness that is approximated by the difference between the sparseness measure of current filter coefficients and an averaged sparseness measure. Simulation results demonstrate that the proposed approach provides both faster convergence rate and better tracking ability than previous ones.
Fisher Exact Scanning for Dependency

We introduce a method—called Fisher exact scanning (FES)—for testing and identifying variable dependency that generalizes Fisher’s exact test on 2 × 2 contingency tables to R × C contingency tables...
Average-Case Reconstruction for the Deletion Channel: Subpolynomially Many Traces Suffice

The deletion channel takes as input a bit string x &#x220A; {0,1}^n, and deletes each bit independently with probability q, yielding a shorter string. The trace reconstruction problem is to recover an unknown string x &#x220A; from many independent outputs (called traces) of the deletion channel applied to x.We show that if x is drawn uniformly at random and q
Bayesian latent pattern mixture models for handling attrition in panel studies with refreshment samples

Many panel studies collect refreshment samples—new, randomly sampled respondents who complete the questionnaire at the same time as a subsequent wave of the panel. With appropriate modeling, these samples can be leveraged to correct inferences for biases caused by nonignorable attrition. We present such a model when the panel includes many categorical survey variables. The model relies on a Bayesian latent pattern mixture model, in which an indicator for attrition and the survey variables are modeled jointly via a latent class model. We allow the multinomial probabilities within classes to depend on the attrition indicator, which offers additional flexibility over standard applications of latent class models. We present results of simulation studies that illustrate the benefits of this flexibility. We apply the model to correct attrition bias in an analysis of data from the 2007–2008 Associated Press/Yahoo News election panel study.
Strict doubly ergodic infinite transformations

ABSTRACTWe give examples of rank-one transformations that are (weak) doubly ergodic and rigid (so all their Cartesian products are conservative), but with non-ergodic two-fold Cartesian product. We give conditions for rank-one infinite measure-preserving transformations to be (weak) doubly ergodic and for their k-fold Cartesian product to be conservative. We also show that a (weak) doubly ergodic nonsingular group action is ergodic with isometric coefficients, and that the latter strictly implies W-measurable sensitivity.
Last but not least: Additional positional effects on citation and readership in arXiv

We continue investigation of the effect of position in announcements of newly received articles, a single day artifact, with citations received over the course of ensuing years. Earlier work focused on the “visibility” effect for positions near the beginnings of announcements, and on the “self-promotion” effect associated with authors intentionally aiming for these positions, with both found correlated to a later enhanced citation rate. Here we consider a “reverse-visibility” effect for positions near the ends of announcements, and on a “procrastination” effect associated with submissions made within the 20 minute period just before the daily deadline. For two large subcommunities of theoretical high-energy physics, we find a clear “reverse-visibility” effect, in which articles near the ends of the lists receive a boost in both short-term readership and long-term citations, almost comparable in size to the “visibility” effect documented earlier. For one of those subcommunities, we find an additional “procrastination” effect, in which last position articles submitted shortly before the deadline have an even higher citation rate than those that land more accidentally in that position. We consider and eliminate geographic effects as responsible for the above, and speculate on other possible causes, including “oblivious” and “nightowl” effects. © 2010 Wiley Periodicals, Inc.
The set of forces that ideal trusses, or wire webs, under tension can support

Abstract The problem of determining those multiplets of forces, or sets of force multiplets, acting at a set of points, such that there exists a truss structure, or wire web, that can support these force multiplets with all the elements of the truss or wire web being under tension, is considered. The two-dimensional problem where the points are at the vertices of a convex polygon is essentially solved: each multiplet of forces must be such that the net anticlockwise torque around any vertex of the forces summed over any number of consecutive points clockwise past the vertex must be non-negative; and one can find a truss structure that supports under tension, and only supports, those force multiplets in a convex polyhedron of force multiplets that is generated by a finite number of force multiplets each satisfying the torque condition. Progress is also made on the problem where only a subset of the points are at the vertices of a convex polygon, and the other points are inside. In particular, in the case where only one point is inside, an explicit procedure is described for constructing a suitable truss, if one exists. An alternative recipe to that provided by Guevara Vasquez et al. (2011), based on earlier work of Camar-Eddine and Seppecher (2003), is given for constructing a truss structure, with elements under either compression or tension, that supports an arbitrary collection of balanced forces at the vertices of a convex polygon. Finally some constraints are given on the forces that a three-dimension truss, or wire web, under tension must satisfy.
A Micro-Foundation of Social Capital in Evolving Social Networks

A social network confers benefits and advantages on individuals (and on groups); the literature refers to these benefits and advantages as social capital . An individual’s social capital depends on its position in the network and on the shape of the network—but positions in the network and the shape of the network are determined endogenously and change as the network forms and evolves. This paper presents a micro-founded mathematical model of the evolution of a social network and of the social capital of individuals within the network. The evolution of the network and of social capital are driven by exogenous and endogenous processes—entry, meeting, linking—that have both random and deterministic components. These processes are influenced by the extent to which individuals are homophilic (prefer others of their own type), structurally opportunistic (prefer neighbors of neighbors to strangers), socially gregarious (desire more or fewer connections) and by the distribution of types in the society. In the analysis, we identify different kinds of social capital: bonding capital refers to links to others; popularity capital refers to links from others; bridging capital refers to connections between others. We show that each form of capital plays a different role and is affected differently by the characteristics of the society. Bonding capital is created by forming a circle of connections; homophily increases bonding capital because it makes this circle of connections more homogeneous. Popularity capital leads to preferential attachment : individuals who become popular tend to become more and more popular because others are more likely to link to them. Homophily creates inequality in the popularity capital attained by different social categories; more gregarious types of agents are more likely to become popular. However, in homophilic societies, individuals who belong to less gregarious, less opportunistic, or major types are likely to be more central in the network and thus acquire a bridging capital. And, while extreme homophily maximizes an individual’s bonding capital, it also creates structural holes in the network, which hinder the exchange of ideas and information across social categories. Such structural holes represent a potential source of bridging capital: non-homophilic (tolerant or open-minded) individuals can fill these holes and broker interactions at the interface between different social categories.
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization

The problem of minimizing sum-of-nonconvex functions (i.e., convex functions that are average of non-convex ones) is becoming increasingly important in machine learning, and is the core machinery for PCA, SVD, regularized Newton's method, accelerated non-convex optimization, and more. We show how to provably obtain an accelerated stochastic algorithm for minimizing sum-of-nonconvex functions, by $\textit{adding one additional line}$ to the well-known SVRG method. This line corresponds to momentum, and shows how to directly apply momentum to the finite-sum stochastic minimization of sum-of-nonconvex functions. As a side result, our method enjoys linear parallel speed-up using mini-batch.
Voltage Regulation Algorithms for Multiphase Power Distribution Grids

Time-varying renewable energy generation can result in serious under-/over-voltage conditions in future distribution grids. Augmenting conventional utility-owned voltage regulating equipment with the reactive power capabilities of distributed generation units is a viable solution. Local control options attaining global voltage regulation optimality at fast convergence rates is the goal here. In this context, novel reactive power control rules are analyzed under a unifying linearized grid model. For single-phase grids, our proximal gradient scheme has computational complexity comparable to that of the rule suggested by the IEEE 1547.8 standard, but it enjoys well-characterized convergence guarantees. Furthermore, adding memory to the scheme results in accelerated convergence. For three-phase grids, it is shown that reactive power injections have a counter-intuitive effect on bus voltage magnitudes across phases. Nevertheless, when our control scheme is applied to unbalanced conditions, it is shown to reach an equilibrium point. Numerical tests using the IEEE 13-bus, the IEEE 123-bus, and a Southern California Edison 47-bus feeder with increased renewable penetration verify the properties of the schemes and their resiliency to grid topology reconfigurations.
The mass shell of the Nelson model without cut-offs

Abstract The massless Nelson model describes non-relativistic, spinless quantum particles interacting with a relativistic, massless, scalar quantum field. The interaction is linear in the field. We analyze its one particle sector. First, we construct the renormalized mass shell of the non-relativistic particle for an arbitrarily small infrared cut-off that turns off the interaction with the low energy modes of the field. No ultraviolet cut-off is imposed. Second, we implement a suitable Bogolyubov transformation of the Hamiltonian in the infrared regime. This transformation depends on the total momentum of the system and is non-unitary as the infrared cut-off is removed. For the transformed Hamiltonian we construct the mass shell in the limit where both the ultraviolet and the infrared cut-off are removed. The limiting fibre Hamiltonians are obtained by convergence in the norm resolvent sense. Our approach is constructive and leads to explicit expansion formulae which are amenable to rigorously control the S-matrix elements.
Fast Monte Carlo Markov chains for Bayesian shrinkage models with random effects

Abstract When performing Bayesian data analysis using a general linear mixed model, the resulting posterior density is almost always analytically intractable. However, if proper conditionally conjugate priors are used, there is a simple two-block Gibbs sampler that is geometrically ergodic in nearly all practical settings, including situations where p > n (Abrahamsen and Hobert, 2017). Unfortunately, the (conditionally conjugate) multivariate Gaussian prior on β does not perform well in the high-dimensional setting where p ≫ n . In this paper, we consider an alternative model in which the multivariate Gaussian prior is replaced by the normal-gamma shrinkage prior developed by Griffin and Brown (2010). This change leads to a much more complex posterior density, and we develop a simple MCMC algorithm for exploring it. This algorithm, which has both deterministic and random scan components, is easier to analyze than the more obvious three-step Gibbs sampler. Indeed, we prove that the new algorithm is geometrically ergodic in most practical settings.
MRI Reconstruction Via Cascaded Channel-Wise Attention Network

We consider an MRI reconstruction problem with input of k-space data at a very low undersampled rate. This can practically benefit patient due to reduced time of MRI scan, but it is also challenging since quality of reconstruction may be compromised. Currently, deep learning based methods dominate MRI reconstruction over traditional approaches such as Compressed Sensing, but they rarely show satisfactory performance in the case of low undersampled k-space data. One explanation is that these methods treat channel-wise features equally, which results in degraded representation ability of the neural network. To solve this problem, we propose a new model called MRI Cascaded Channel-wise Attention Network (MICCAN), highlighted by three components: (i) a variant of U-net with Channel-wise Attention (UCA) module, (ii) a long skip connection and (iii) a combined loss. Our model is able to attend to salient information by filtering irrelevant features and also concentrate on high-frequency information by enforcing low-frequency information bypassed to the final output. We conduct both quantitative evaluation and qualitative analysis of our method on a cardiac dataset. The experiment shows that our method achieves very promising results in terms of three common metrics on the MRI reconstruction with low undersampled k-space data. Code is public availablel1.1https://github.com/charwing10/isbi2019miccan
Exploiting evidence in probabilistic inference

We define the notion of compiling a Bayesian network with evidence and provide a specific approach for evidence–based compilation, which makes use of logical processing. The approach is practical and advantageous in a number of application areas—including maximum likelihood estimation, sensitivity analysis, and MAP computations—and we provide specific empirical results in the domain of genetic linkage analysis. We also show that the approach is applicable for networks that do not contain determinism, and show that it empirically subsumes the performance of the quickscore algorithm when applied to noisy–or networks.
Finitely Suslinian models for planar compacta with applications to Julia sets

A compactum XC is unshielded if it coincides with the boundary of the unbounded component of C\X. Call a compactum X finitely Suslinian if every collection of pairwise disjoint subcontinua of X whose diam- eters are bounded away from zero isnite. We show that any unshielded planar compactum X admits a topologically unique monotone map mX : X ! XFS onto anitely Suslinian quotient such that any monotone map of X onto a �nitely Suslinian quotient factors through mX. We call the pair (XFS,mX) (or, more loosely, XFS) the finest finitely Suslinian model of X. If f : C ! C is a branched covering map and XC is a fully invariant compactum, then the appropriate extension MX of mX monotonically semi- conjugates f to a branched covering map g : C ! C which serves as a model for f. If f is a polynomial and Jf is its Julia set, we show that mX (or MX) can be dened on each component Z of Jf individually as thenest monotone map of Z onto a locally connected continuum.
Identifying Dogmatism in Social Media: Signals and Models.

We explore linguistic and behavioral features of dogmatism in social media and construct statistical models that can identify dogmatic comments. Our model is based on a corpus of Reddit posts, collected across a diverse set of conversational topics and annotated via paid crowdsourcing. We operationalize key aspects of dogmatism described by existing psychology theories (such as over-confidence), finding they have predictive power. We also find evidence for new signals of dogmatism, such as the tendency of dogmatic posts to refrain from signaling cognitive processes. When we use our predictive model to analyze millions of other Reddit posts, we find evidence that suggests dogmatism is a deeper personality trait, present for dogmatic users across many different domains, and that users who engage on dogmatic comments tend to show increases in dogmatic posts themselves.
Binary Cumulant Varieties

Algebraic statistics for binary random variables is concerned with highly structured algebraic varieties in the space of 2×2×···×2-tensors. We demonstrate the advantages of representing such varieties in the coordinate system of binary cumulants. Our primary focus lies on hidden subset models. Parametrizations and implicit equations in cumulants are derived for hyperdeterminants, for secant and tangential varieties of Segre varieties, and for certain context-specific independence models. Extending work of Rota and collaborators, we explore the polynomial inequalities satisfied by cumulants.
Sharp Moderate Maximal Inequalities for Upward Skip-Free Markov Chains

The $$L^p$$ maximal inequalities for martingales are one of the classical results in probability theory. Here we establish the sharp moderate maximal inequalities for upward skip-free Markov chains, which include the $$L^p$$ maximal inequalities as special cases. Furthermore, we apply our theory to two specific examples and obtain their moderate maximal inequalities: the first one is the M/M/1 queue and the second one is an upward skip-free Markov chain with large death jumps. These two examples have the same total birth and death rates. However, the former exhibits a phase transition phenomenon while the latter does not.
Seeking Open-Ended Evolution in Swarm Chemistry II: Analyzing Long-Term Dynamics via Automated Object Harvesting

We studied the long-term dynamics of evolutionary Swarm Chemistry by extending the simulation length ten-fold compared to earlier work and by developing and using a new automated object harvesting ...
Semantic 3D occupancy mapping through efficient high order CRFs

Semantic 3D mapping can be used for many applications such as robot navigation and virtual interaction. In recent years, there has been great progress in semantic segmentation and geometric 3D mapping. However, it is still challenging to combine these two tasks for accurate and large-scale semantic mapping from images. In the paper, we propose an incremental and (near) real-time semantic mapping system. A 3D scrolling occupancy grid map is built to represent the world, which is memory and computationally efficient and bounded for large scale environments. We utilize the CNN segmentation as prior prediction and further optimize 3D grid labels through a novel CRF model. Superpixels are utilized to enforce smoothness and form robust PN high order potential. An efficient mean field inference is developed for the graph optimization. We evaluate our system on the KITTI dataset and improve the segmentation accuracy by 10% over existing systems.
A distributed, dynamical system view of finite, static games

This paper contains a reformulation of any n-player finite, static game into a framework of distributed, dynamical system based on agents' payoff-based deviations. The reformulation generalizes the method employed in the second part of the study of countries' relation formation problem in [1] to the case of any finite, static game. In the paper two deviation rules are provided and possible applications of this framework are discussed.
Entity-Centric Contextual Affective Analysis

While contextualized word representations have improved state-of-the-art benchmarks in many NLP tasks, their potential usefulness for social-oriented tasks remains largely unexplored. We show how contextualized word embeddings can be used to capture affect dimensions in portrayals of people. We evaluate our methodology quantitatively, on held-out affect lexicons, and qualitatively, through case examples. We find that contextualized word representations do encode meaningful affect information, but they are heavily biased towards their training data, which limits their usefulness to in-domain analyses. We ultimately use our method to examine differences in portrayals of men and women.
On logarithmically Benford Sequences

Let $\mathcal{I} \subset \mathbb{N}$ be an infinite subset, and let $\{a_i\}_{i \in \mathcal{I}}$ be a sequence of nonzero real numbers indexed by $\mathcal{I}$ such that there exist positive constants $m, C_1$ for which $|a_i| \leq C_1 \cdot i^m$ for all $i \in \mathcal{I}$. Furthermore, let $c_i \in [-1,1]$ be defined by $c_i = \frac{a_i}{C_1 \cdot i^m}$ for each $i \in \mathcal{I}$, and suppose the $c_i$'s are equidistributed in $[-1,1]$ with respect to a continuous, symmetric probability measure $\mu$. In this paper, we show that if $\mathcal{I} \subset \mathbb{N}$ is not too sparse, then the sequence $\{a_i\}_{i \in \mathcal{I}}$ fails to obey Benford's Law with respect to arithmetic density in any sufficiently large base, and in fact in any base when $\mu([0,t])$ is a strictly convex function of $t \in (0,1)$. Nonetheless, we also provide conditions on the density of $\mathcal{I} \subset \mathbb{N}$ under which the sequence $\{a_i\}_{i \in \mathcal{I}}$ satisfies Benford's Law with respect to logarithmic density in every base. As an application, we apply our general result to study Benford's Law-type behavior in the leading digits of Frobenius traces of newforms of positive, even weight. Our methods of proof build on the work of Jameson, Thorner, and Ye, who studied the particular case of newforms without complex multiplication.
Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization

Bayesian optimization offers the possibility of optimizing black-box operations not accessible through traditional techniques. The success of Bayesian optimization methods, such as Expected Improvement (EI) are significantly affected by the degree of trade-off between exploration and exploitation. Too much exploration can lead to inefficient optimization protocols, whilst too much exploitation leaves the protocol open to strong initial biases, and a high chance of getting stuck in a local minimum. Typically, a constant margin is used to control this trade-off, which results in yet another hyper-parameter to be optimized. We propose contextual improvement as a simple, yet effective heuristic to counter this - achieving a one-shot optimization strategy. Our proposed heuristic can be swiftly calculated and improves both the speed and robustness of discovery of optimal solutions. We demonstrate its effectiveness on both synthetic and real world problems and explore the unaccounted for uncertainty in the pre-determination of search hyperparameters controlling explore-exploit trade-off.