cssi/SciSciGPT-SciSciNet huggingface dataset:
In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment.

Angiogenesis is a crucial step in tumour progression, as this process allows tumours to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenes...
Synthesis of dihydrofuroflavonoids via palladium-catalyzed annulation of 1,3-dienes

The palladium-catalyzed annulation of 1,3-dienes by o-iodoacetoxyflavonoids provides an efficient approach to biologically interesting dihydrofuroflavonoids. This reaction is very general, regioselective, and a wide variety of terminal, cyclic, and internal 1,3-dienes can be utilized.
Influences of simulated gastrointestinal environment on physicochemical properties of gold nanoparticles and their implications on intestinal epithelial permeability.

Gold nanoparticles (Au NPs) hold great promise in food, industrial and biomedical applications due to their unique physicochemical properties. However, influences of the gastrointestinal tract (GIT...
The BD2 domain of BRD4 is a determinant in EndoMT and vein graft neointima formation.

Abstract Background Vein-graft bypass is commonly performed to overcome atherosclerosis but is limited by high failure rates, principally due to neointimal wall thickening. Recent studies reveal that endothelial-mesenchymal transition (EndoMT) is critical for vein-graft neointima formation. BETs are a family of Bromo/ExtraTerminal domains-containing epigenetic reader proteins (BRD2, BRD3, BRD4). They bind acetylated histones through their unique tandem bromodomains (BD1, BD2), facilitating transcriptional complex formation and cell-state transitions. The role for BETs, including individual BRDs and their unique BDs, is not well understood in EndoMT and neointimal formation. Methods and results Repression of BRD4 expression abrogated TGFβ1-induced EndoMT, with greater effects than BRD2 or BRD3 knockdown. An inhibitor selective for BD2 in all BETs, but not that for BD1, blocked EndoMT. Moreover, expression of a dominant-negative BRD4-specific BD2 fully abolished EndoMT. Concordantly, BRD4 knockdown repressed TGFβ1-stimulated increase of ZEB1 protein – a transcription factor integral in EndoMT. In vivo, lentiviral gene transfer of either BRD4 shRNA or dominant negative BRD4-specific BD2 mitigated neointimal development in rat jugular veins grafted to carotid arteries. Conclusions Our data reveal the BD2 domain of BRD4 as a determinant driving EndoMT in vitro and neointimal formation in vivo. These findings provide new insight into BET biology, while offering prospects of specific BET domain targeting as an approach to limiting neointima and extending vein graft patency.
Expression reflects population structure.

Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naive principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal components of genotype to the principal components of gene expression via canonical correlation analysis. Our method is able to determine the significance of the variance in the canonical correlation projection explained by each gene. We identify 3,571 significant genes, only 837 of which had been previously reported to have an associated eQTL in the GEUVADIS results. We show that our projections are not primarily driven by differences in allele frequency at known cis-eQTLs and that similar projections can be recovered using only several hundred randomly selected genes and SNPs. Finally, we present preliminary work on the consequences for eQTL analysis. We observe that using our projection co-ordinates as covariates results in the discovery of slightly fewer genes with eQTLs, but that these genes replicate in GTEx matched tissue at a slightly higher rate.
Highly Regio- and Enantioselective Monoepoxidation of Conjugated Dienes

This paper describes a highly effective and mild asymmetric monoepoxidation method for conjugated dienes using a fructose-derived chiral ketone 1 as catalyst and Oxone as oxidant. The regioselectivies and enantioslectivies are very high in most cases. For unsymmetrical dienes, the regioselectivity can be regulated by using steric and electronic control. The olefin substrates include trans-disubstituted and trisubstituted olefins that can bear a wide range of functional groups such as hydroxyl groups, TBS ethers, or esters. The enantiomeric excesses for the major monoepoxides range from 89% to 97%. The epoxidation is believed to proceed via a spiro mode.
Pnictide Oxides: A Unique Class of Compounds

Abstract Layered pnictide oxides are an unusual class of compounds which have received little attention. The characteristic feature of these materials is the presence of pnictogen and oxygen atoms which are not bonded to each other and are considered to be anions. This class of compounds is made up of ternary pnictide oxides of alkaline or rare earth metals, and quaternary pnictide oxides of alkali or alkaline earth metal along with transition metals. This Comment discusses structure and bonding in this small group of compounds. Additionally, magnetic and electronic properties of many of the transition metal pnictide oxide compounds are presented.
Functional regulatory evolution outside of the minimal even-skipped stripe 2 enhancer.

Transcriptional enhancers are regions of DNA that drive precise patterns of gene expression. Although many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called ‘minimal’ enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here, we explore how the Drosophila erecta even-skipped ( eve ) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the D. erecta eve stripe 2 enhancer ( eveS2 ) fails to drive appreciable expression in D. melanogaster . However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor-binding sites that drive patterning.
Progress toward the Total Synthesis of Bafilomycin A1: Stereoselective Synthesis of the C15−C25 Subunit by Additions of Nonracemic Allenylzinc Reagents to Aldehydes

A highly stereoselective synthesis of the C15−C25 subunit (2) of bafilomycin A1 (1) has been accomplished by a route utilizing additions of chiral nonracemic allenylzinc reagents to aldehydes.
Surface science aspects of etching reactions

Abstract Basic studies of the surface science aspects of plasma-assisted etching were initiated over 10 years ago in laboratories throughout the world. Several approaches to this experimentally challenging problem have been taken: (1) simulate the reactive gas glow discharge environment with directed beams of energetic positive ions and thermal energy reactive molecules/radicals in a UHV environment; (2) simulate the reactive gas glow discharge by using a beam of reactive ions (reactive ion beam etching); and (3) carry out careful ex-situ analyses of surfaces etched in reactive gas glow discharges without air exposure. This report will be limited to a review of the work reported using the first of these approaches only and summarizes the status of this virtually unexplored field of surface chemistry. The report includes a discussion of the experimental aspects of this field and then focuses on the gas-solid system which has been studied most thoroughly; i.e., silicon-fluorine. A considerable quantity of new unpublished data is presented and a framework is proposed to explain the many observations associated with the spontaneous reaction of fluorine with silicon. The role of energetic ions in this reaction is then discussed in detail. Other materials combinations which are discussed are silicon-chlorine, silicon-bromine, silicon-hydrogen and SiO2-fluorine. The report concludes with a tabulation of the many other gas-solid systems which have been studied and also a discussion of the extent to which these basic studies relate to actual reactive gas processing environments.
A convenient synthesis of 2-nitroindoles

The reaction of 2-iodo- and 2-bromoindoles with silver nitrite in aqueous acetone affords the corresponding 2-nitroindoles in modest to good yields.
Catalytic C−F Bond Activation of Nonactivated Monofluoroarenes

Catalytic hydrogenolysis of the C−F bond in most unreactive monofluoroarenes readily occurs under mild conditions, in the presence of homogeneous and/or heterogeneous Rh catalysts generated from [(Cy3P)2Rh(H)Cl2], H2, and aqueous alkali.
Preparation of 3-(10′-halo-9′-anthracenyl) isoxazolecarboxylic esters

The 10-halo (Cl or Br) anthracene-9-nitrile oxides (1a,b) were obtained directly from the treatment of 9-anthracenylaldoxime with N-halosuccinimide (NCS or NBS) in DMF. The 3-(10′-halo-9′-anthracenyl)-5-isoxazolecarboxylic esters (5a,b and 6a,b) were prepared via 1,3-dipolar cycloaddition between the obtained nitrile oxides 1a (or 1b) and two different dipolarophiles: ethyl β-pyrrolidinocrotonate (an enamine of ethyl acetoacetate) or dimethyl acetylenedicarbox-ylate (DMAD) respectively. The 10 (or 10′)- position of the anthracene in either anthracene-9-nitrile oxide or 3-(9′-anthracenyl) isoxazole molecules (3,4) is readily halogenated by N-halosuc-cinimide in DMF. X-ray studies showed that 5a possesses two aromatic ring systems that lie at 74.4° from coplanarity. The bond linking the two ring systems is 1.4893(18) A, indicating only partial conjugation between the two ring systems. The crystal lattice showed unique head-to-tail intermolecular stacking of anthracene rings.
Second-sphere coordination revisited

Since the concept of second-sphere coordination of transition metal complexes was introduced by Alfred Werner in 1913, the investigation of the phenomenon has emerged as a major thrust area - a significant part of which is based on the use of transition metal complexes as first coordination spheres as well as macrocycles as second-sphere ligands in promoting the assembly and dictating the main structural features of the second-sphere adducts. In this review, we first of all summarize the work carried out in our laboratory on the second-sphere coordination chemistry of transition metal complexes in the past three decades. Significant advances of relevance to the second-sphere coordination chemistry of square-planar gold complex anions with cyclodextrins are presented as the second part of this review.
Diverse communities behave like typical random ecosystems

In 1972, Robert May triggered a worldwide research program studying ecological communities using random matrix theory. Yet, it remains unclear if and when we can treat real communities as random ecosystems. Here, we draw on recent progress in random matrix theory and statistical physics to extend May's approach to generalized consumer-resource models. We show that in diverse ecosystems adding even modest amounts of noise to consumer preferences results in a transition to ``typicality,'' where macroscopic ecological properties of communities are indistinguishable from those of random ecosystems, even when resource preferences have prominent designed structures. We test these ideas using numerical simulations on a wide variety of ecological models. Our work offers an explanation for the success of random consumer resource models in reproducing experimentally observed ecological patterns in microbial communities and highlights the difficulty of scaling up bottom-up approaches in synthetic ecology to diverse communities.
Novel photocycloadditions of electron-deficient nitrones to 2-methyl-2-butene

In Order to decrease the ground state reactivity and increase their potential for [3+2] cycloadditions, cyano- and methoxy-carbonyl-substituted nitrones 1a and 1b, respectively, were prepared and irradiated in the presence of electron-rich alkenes such as 2 to afford the corresponding oxazolidines in which th oxygen atom becomes attached to the least substituted terminus of the olefin and nitrogen attaches to the more highly substituted counterpart. While the oxazolidines 12a and 12b obtained from 1b, via the intermediacy of oxaziridine(s) 15 and subsequent NO bond scission, are isolated and characterized, the oxazolidin(s) 18 formed bny cyclization of 1a are more labile and may undergo ionization to the stabilized oxazolinium ion 19 followed by nucleophilic attack by cyanide ion with accompanying ring opening to afford 6. A sequential diradical mechanism is proposed to rationalize the formation of the observed photoproducts 5 and 6.
2,4-DINITROPHENYLHYDROXYLAMINE: AN EFFICIENT AND MORE GENERAL REAGENT FOR IRON-CATALYZED ALLYLIC AMINATION

2,4-Dinitrophenylhydroxylamine (1) is an efficient reagent for the iron-catalyzed regioselective allylic amination of olefins. Moderate to excellent yields of N-DNP-N-allyl amines (2) are obtained ...
Intramolecular Aza-[4+3] Cycloaddition Reactions of α-Halohydroxamates

Polyheterocyclic scaffolds were prepared by intramolecular aza-[4+3] cycloaddition reactions of aza-oxyallylic cations with cyclic dienes. The aza-oxyallylic cation was generated in situ by the dehydrohalogenation of α-halohydroxamates. The highly functionalized heterocyclic products undergo a variety of reactions that provide useful scaffolds for target-directed synthesis, including macrocyclic furans and polyhydroxylated azepanes.
Binding Thermodynamics and Kinetics Calculations Using Chemical Host and Guest: A Comprehensive Picture of Molecular Recognition

Understanding the fine balance between changes of entropy and enthalpy and the competition between a guest and water molecules in molecular binding is crucial in fundamental studies and practical applications. Experiments provide measurements. However, illustrating the binding/unbinding processes gives a complete picture of molecular recognition not directly available from experiments, and computational methods bridge the gaps. Here, we investigated guest association/dissociation with β-cyclodextrin (β-CD) by using microsecond-time-scale molecular dynamics (MD) simulations, postanalysis and numerical calculations. We computed association and dissociation rate constants, enthalpy, and solvent and solute entropy of binding. All the computed values of kon, koff, ΔH, ΔS, and ΔG using GAFF-CD and q4MD-CD force fields for β-CD could be compared with experimental data directly and agreed reasonably with experiment findings. In addition, our study further interprets experiments. Both force fields resulted in simi...
A novel route to 2-(dialkylaminomethyl)benzo[b]furans via a microwave-enhanced, solventless Mannich condensation–cyclization on cuprous iodide doped alumina

Abstract A microwave-enhanced, solventless Mannich condensation–cyclization sequence involving the reaction of o-ethynylphenol with secondary amines and para-formaldehyde on cuprous iodide doped alumina in the absence of solvents has been developed. The procedure generates 2-(dialkylaminomethyl)benzo[b]furans in good yields.
Enantioselective reduction of aryl ketones using LiBH4 and TarB-X: a chiral Lewis acid

Abstract High enantioselectivities are obtained using a tartaric acid-derived boronate ester in combination with lithium borohydride for asymmetric reduction of aryl ketones. The chiral Lewis acid, TarB-X, is easily prepared in 1 h, and the resulting alcohols are obtained in enantiomeric excesses of 88–99%.
Diene Condensation of Cyclopentadiene with Dienophiles of Allylacetylene Series

Diene condensation of cyclopentadiene with 2-substituted allylacetylenes occurs nonselectively at a double and triple bonds; therewith the dienophile activity grows in parallel with the electron-withdrawing properties of the substituent. Depending on electronic character of functional groups the reaction proceeds as “neutral” diene synthesis. The relative activity of cyclopentadiene and 1,3-cyclohexadiene in reactions with allylacetylenes is essentially governed by the different distance between the 1,4-reactive sites in these systems.
Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory.

Background Unplanned readmission of a hospitalized patient is an indicator of patients' exposure to risk and an avoidable waste of medical resources. In addition to hospital readmission, intensive care unit (ICU) readmission brings further financial risk, along with morbidity and mortality risks. Identification of high-risk patients who are likely to be readmitted can provide significant benefits for both patients and medical providers. The emergence of machine learning solutions to detect hidden patterns in complex, multi-dimensional datasets provides unparalleled opportunities for developing an efficient discharge decision-making support system for physicians and ICU specialists. Methods and findings We used supervised machine learning approaches for ICU readmission prediction. We used machine learning methods on comprehensive, longitudinal clinical data from the MIMIC-III to predict the ICU readmission of patients within 30 days of their discharge. We incorporate multiple types of features including chart events, demographic, and ICD-9 embeddings. We have utilized recent machine learning techniques such as Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM), by this we have been able to incorporate the multivariate features of EHRs and capture sudden fluctuations in chart event features (e.g. glucose and heart rate). We show that our LSTM-based solution can better capture high volatility and unstable status in ICU patients, an important factor in ICU readmission. Our machine learning models identify ICU readmissions at a higher sensitivity rate of 0.742 (95% CI, 0.718-0.766) and an improved Area Under the Curve of 0.791 (95% CI, 0.782-0.800) compared with traditional methods. We perform in-depth deep learning performance analysis, as well as the analysis of each feature contribution to the predictive model. Conclusion Our manuscript highlights the ability of machine learning models to improve our ICU decision-making accuracy and is a real-world example of precision medicine in hospitals. These data-driven solutions hold the potential for substantial clinical impact by augmenting clinical decision-making for physicians and ICU specialists. We anticipate that machine learning models will improve patient counseling, hospital administration, allocation of healthcare resources and ultimately individualized clinical care.
Immunization Laws and Policies Among U.S. Institutes of Higher Education

Recent outbreaks of vaccine-preventable diseases (e.g., mumps and meningitis) among young adults at higher education institutions (e.g., university, college, and junior college campuses) have proliferated nationally. Collectively, they illustrate a pressing public health concern regarding low vaccination rates among higher education populations contributing to outbreaks of communicable diseases. A primary cause of these outbreaks are lax requirements for student vaccinations among higher education institutions as a requirement for matriculation. A series of inconsistences and failures concerning vaccination law or policy requirements among select higher education institutions lends to profound public health and ethical repercussions for students and community members. Against the backdrop of rising rates or outbreaks of vaccine-preventable conditions among institutional populations, addressing these findings is vital to alleviate future outbreaks on campuses and surrounding locales.
A remark on our paper “Negative holomorphic curvature and positive canonical bundle”

This is a continuation of our first paper in [WY16]. There are two purposes of this paper: One is to give a proof of the main result in [WY16] without going through the argument depending on numerical effectiveness. The other one is to provide a proof of our conjecture, mentioned in [TY], where the assumption of negative holomorphic sectional curvature is dropped to quasi-negative. We should note that a solution to our conjecture is also provided by Diverio-Trapani [DT]. Both proofs depend on our argument in [WY16]. But our argument here makes use of the argument given by the second author and Cheng in [CY75].
Almost perfect restriction semigroups

Abstract We call a restriction semigroup almost perfect if it is proper and the least congruence that identifies all its projections is perfect. We show that any such semigroup is isomorphic to a ‘W-product’ W ( T , Y ) , where T is a monoid, Y is a semilattice and there is a homomorphism from T into the inverse semigroup TI Y of isomorphisms between ideals of Y. Conversely, all such W-products are almost perfect. Since we also show that every restriction semigroup has an easily computed cover of this type, the combination yields a ‘McAlister-type’ theorem for all restriction semigroups. It is one of the theses of this work that almost perfection and perfection, the analogue of this definition for restriction monoids, are the appropriate settings for such a theorem. That these theorems do not reduce to a general theorem for inverse semigroups illustrates a second thesis of this work: that restriction (and, by extension, Ehresmann) semigroups have a rich theory that does not consist merely of generalizations of inverse semigroup theory. It is then with some ambivalence that we show that all the main results of this work easily generalize to encompass all proper restriction semigroups. The notation W ( T , Y ) recognizes that it is a far-reaching generalization of a long-known similarly titled construction. As a result, our work generalizes Szendrei's description of almost factorizable semigroups while at the same time including certain classes of free restriction semigroups in its realm.
Mission: Ultra large-scale feature selection using count-sketches

Feature selection is an important challenge in machine learning. It plays a crucial role in the explainability of machine-driven decisions that are rapidly permeating throughout modern society. Unfortunately, the explosion in the size and dimensionality of real-world datasets poses a severe challenge to standard feature selection algorithms. Today, it is not uncommon for datasets to have billions of dimensions. At such scale, even storing the feature vector is impossible, causing most existing feature selection methods to fail. Workarounds like feature hashing, a standard approach to large-scale machine learning, helps with the computational feasibility, but at the cost of losing the interpretability of features. In this paper, we present MISSION, a novel framework for ultra large-scale feature selection that performs stochastic gradient descent while maintaining an efficient representation of the features in memory using a Count-Sketch data structure. MISSION retains the simplicity of feature hashing without sacrificing the interpretability of the features while using only O(log^2(p)) working memory. We demonstrate that MISSION accurately and efficiently performs feature selection on real-world, large-scale datasets with billions of dimensions.
Asymptotically Efficient Distributed Estimation With Exponential Family Statistics

This paper studies the problem of distributed parameter estimation in multiagent networks with exponential family observation statistics. A certainty-equivalence type distributed estimator of the consensus-plus-innovations form is proposed in which, at each observation sampling epoch, agents update their local parameter estimates by appropriately combining the data received from their neighbors and the locally sensed new information (innovation). Under global observability of the networked sensing model, i.e., the ability to distinguish between different instances of the parameter value based on the joint observation statistics, and mean connectivity of the inter-agent communication network, the proposed estimator is shown to yield consistent parameter estimates at each network agent. Further, it is shown that the distributed estimator is asymptotically efficient, in that, the asymptotic covariances of the agent estimates coincide with that of the optimal centralized estimator, i.e., the inverse of the centralized Fisher information rate. From a technical viewpoint, the proposed distributed estimator leads to non-Markovian mixed time-scale stochastic recursions and the analytical methods developed in this paper contribute to the general theory of distributed stochastic approximation.
Convex Total Least Squares

We study the total least squares (TLS) problem that generalizes least squares regression by allowing measurement errors in both dependent and independent variables. TLS is widely used in applied fields including computer vision, system identification and econometrics. The special case when all dependent and independent variables have the same level of uncorrelated Gaussian noise, known as ordinary TLS, can be solved by singular value decomposition (SVD). However, SVD cannot solve many important practical TLS problems with realistic noise structure, such as having varying measurement noise, known structure on the errors, or large outliers requiring robust error-norms. To solve such problems, we develop convex relaxation approaches for a general class of structured TLS (STLS). We show both theoretically and experimentally, that while the plain nuclear norm relaxation incurs large approximation errors for STLS, the re-weighted nuclear norm approach is very effective, and achieves better accuracy on challenging STLS problems than popular nonconvex solvers. We describe a fast solution based on augmented Lagrangian formulation, and apply our approach to an important class of biological problems that use population average measurements to infer cell-type and physiological-state specific expression levels that are very hard to measure directly.
The HOMFLY polynomial of links in closed braid form

Abstract We provide a new proof of Jaeger’s formula expressing the HOMFLY polynomial of a link presented in closed braid form, replacing the original representation theoretic proof with an easy combinatorial and geometric argument. Using new variants of Jaeger’s result we provide a direct and elementary proof of the fact that the braid index of a link that has an n -string closed braid diagram that is also reduced and alternating, is exactly n . Until now this fact was only known as a consequence of a result due to Murasugi on fibered links that are star products of elementary torus links and of the fact that alternating braids are fibered.
Efficient Numerical Algorithms Based on Difference Potentials for Chemotaxis Systems in 3D

In this work, we propose efficient and accurate numerical algorithms based on difference potentials method for numerical solution of chemotaxis systems and related models in 3D. The developed algorithms handle 3D irregular geometry with the use of only Cartesian meshes and employ Fast Poisson Solvers. In addition, to further enhance computational efficiency of the methods, we design a difference-potentials-based domain decomposition approach which allows mesh adaptivity and easy parallelization of the algorithm in space. Extensive numerical experiments are presented to illustrate the accuracy, efficiency and robustness of the developed numerical algorithms.
Depth-Zero Representations of Nonlinear Covers of p-Adic Groups

We generalize the methods of Moy-Prasad in order to define and study the genuine depth-zero representations of some nonlinear covers of reductive groups over p-adic local fields. In particular, we construct all depth-zero supercuspidal representations of the metaplectic group Mp 2n over a p-adic field of odd residue characteristic.
A Software-defined SoC Memory Bus Bridge Architecture for Disaggregated Computing

Disaggregation and rack-scale systems have the potential of drastically decreasing TCO and increasing utilization of cloud datacenters, while maintaining performance. While the concept of organising resources in separate pools and interconnecting them together on demand is straightforward, its materialisation can be radically different in terms of performance and scale potential. In this paper, we presenta memory bus bridge architecture which enables communication between 100s of masters and slaves in todays complex multiprocessor SoCs, that are physically intregrated in different chips and even different mainboards. The bridge tightly couples serial transceivers and a circuit network for chip-to-chip transfers. A key property of the proposed bridge architecture is that it is software-defined and thus can be configured at runtime, via a software control plane, to prepare and steer memory access transactions to remote slaves. This is particularly important because it enables datacenter orchestration tools to manage the disaggregated resource allocation. Moreover, we evaluate a bridge prototype we have build for ARM AXI4 memory bus interconnect and we discuss application-level observed performance.
VALUES AT s = -1 OF L-FUNCTIONS FOR MULTI-QUADRATIC EXTENSIONS OF NUMBER FIELDS, AND THE FITTING IDEAL OF THE TAME KERNEL

Fix a Galois extension of totally real number fields such that the Galois group G has exponent 2. Let S be a finite set of primes of F containing the infinite primes and all those which ramify in , let denote the primes of lying above those in S, and let denote the ring of -integers of . We then compare the Fitting ideal of as a ℤ[G]-module with a higher Stickelberger ideal. The two extend to the same ideal in the maximal order of ℚ[G], and hence in ℤ[1/2][G]. Results in ℤ[G] are obtained under the assumption of the Birch–Tate conjecture, especially for biquadratic extensions, where we compute the index of the higher Stickelberger ideal. We find a sufficient condition for the Fitting ideal to contain the higher Stickelberger ideal in the case where is a biquadratic extension of F containing the first layer of the cyclotomic ℤ2-extension of F, and describe a class of biquadratic extensions of F = ℚ that satisfy this condition.
Hall–Littlewood RSK field

We introduce a randomized Hall–Littlewood RSK algorithm and study its combinatorial and probabilistic properties. On the probabilistic side, a new model—the Hall–Littlewood RSK field—is introduced. Its various degenerations contain known objects (the stochastic six vertex model, the asymmetric simple exclusion process) as well as a variety of new ones. We provide formulas for a rich class of observables of these models, extending existing results about Macdonald processes. On the combinatorial side, we establish analogs of properties of the classical RSK algorithm: invertibility, symmetry, and a “bijectivization” of the skew-Cauchy identity.
Generic construction of scale-invariantly coarse grained memory

Encoding temporal information from the recent past as spatially distributed activations is essential in order for the entire recent past to be simultaneously accessible. Any biological or synthetic agent that relies on the past to predict/plan the future, would be endowed with such a spatially distributed temporal memory. Simplistically, we would expect that resource limitations would demand the memory system to store only the most useful information for future prediction. For natural signals in real world which show scale free temporal fluctuations, the predictive information encoded in memory is maximal if the past information is scale invariantly coarse grained. Here we examine the general mechanism to construct a scale invariantly coarse grained memory system. Remarkably, the generic construction is equivalent to encoding the linear combinations of Laplace transform of the past information and their approximated inverses. This reveals a fundamental construction constraint on memory networks that attempt to maximize predictive information storage relevant to the natural world.
Multi-objective Weighted Sampling

Key value data sets of the form {(x, wx)} where wx > 0 are prevalent. Common queries over such data are segment f-statistics Q(f, H) = Sx?H f(wx), specified for a segment H of the keys and a function f. Different choices of f correspond to count, sum, moments, capping, and threshold statistics. When the data set is large, we can compute a smaller sample from which we can quickly estimate statistics. A weighted sample of keys taken with respect to f(wx) provides estimates with statistically guaranteed quality for f-statistics. Such a sample S(f) can be used to estimate g-statistics for g&#x2260f, but quality degrades with the disparity between g and f. In this paper we address applications that require quality estimates for a set F of different functions. A naive solution is to compute and work with a different sample S(f) for each f?F. Instead, this can be achieved more effectively and seamlessly using a single multi-objective sample S(F) of a much smaller size. We review multi-objective sampling schemes and place them in our context of estimating f-statistics. We show that a multi-objective sample for F provides quality estimates for any f that is a positive linear combination of functions from F. We then establish a surprising and powerful result when the target set M is all monotone non-decreasing functions, noting that M includes most natural statistics. We provide efficient multi-objective sampling algorithms for M and show that a sample size of k ln n (where n is the number of active keys) provides the same estimation quality, for any f?M, as a dedicated weighted sample of size k for f.
Regular cross sections of Borel flows

A Borel flow is an action of the Euclidean space on a standard Borel space. A cross-section of a Borel flow is a Borel set that intersects every orbit in a countable non empty set. We shall start with one-dimensional flows and shall be interested in constructing cross-sections with a prescribed set of possible distances between adjacent points within orbits. The main result here is that given any two rationally independent positive reals and a free Borel flow one can always find a cross-section with distances between adjacent points being only these two real numbers. If time permits, we shall then discuss partial generalizations of this result to higher dimensions. Regular cross sections is a powerful tool in the theory of Borel flows and as a concrete application of the above constructions we shall give a classification of Borel flows up to Lebesgue orbit equivalence, by which we understand an orbit equivalence which preserves the Lebesgue measure when restricted onto any orbit. SNACKS IN FACULTY LOUNGE AT 3:30 PM. EVERYONE WELCOME (EVEN IF YOU ARE UNABLE TO ATTEND THE TALK)
Bethe projections for non-local inference

Many inference problems in structured prediction are naturally solved by augmenting a tractable dependency structure with complex, non-local auxiliary objectives. This includes the mean field family of variational inference algorithms, soft- or hard-constrained inference using Lagrangian relaxation or linear programming, collective graphical models, and forms of semi-supervised learning such as posterior regularization. We present a method to discriminatively learn broad families of inference objectives, capturing powerful non-local statistics of the latent variables, while maintaining tractable and provably fast inference using non-Euclidean projected gradient descent with a distance-generating function given by the Bethe entropy. We demonstrate the performance and flexibility of our method by (1) extracting structured citations from research papers by learning soft global constraints, (2) achieving state-of-the-art results on a widely-used handwriting recognition task using a novel learned non-convex inference procedure, and (3) providing a fast and highly scalable algorithm for the challenging problem of inference in a collective graphical model applied to bird migration.
A new invariant metric and applications

We study a new construction of an invariant metric for compact subgroups of the automorphism group of a domain in complex space. Applications are provided.
Unbounded disjointness preserving linear functionals and operators

Let E and F be Banach lattices. We show first that the disjointness preserving linear functionals separate the points of any infinite dimensional Banach lattice E, which shows that in this case the unbounded disjointness preserving operators from \({E\to F}\) separate the points of E. Then we show that every disjointness preserving operator \({T:E\to F}\) is norm bounded on an order dense ideal. In case E has order continuous norm, this implies that every unbounded disjointness preserving map \({T:E\to F}\) has a unique decomposition T = R + S, where R is a bounded disjointness preserving operator and S is an unbounded disjointness preserving operator, which is zero on a norm dense ideal. For the case that E = C(X), with X a compact Hausdorff space, we show that every disjointness preserving operator \({T:C(X)\to F}\) is norm bounded on a norm dense sublattice algebra of C(X), which leads then to a decomposition of T into a bounded disjointness preserving operator and a finite sum of unbounded disjointness preserving operators, which are zero on order dense ideals.
Efficient Learning of Simplices

We show an ecient algorithm for the following problem: Given uniformly random points from an arbitrary n-dimensional simplex, estimate the simplex. The size of the sample and the number of arithmetic operations of our algorithm are polynomial in n. This answers a question of Frieze, Jerrum and Kannan Frieze et al. (1996). Our result can also be interpreted as eciently learning the intersection of n + 1 half-spaces in R n in the model where the intersection is bounded and we are given polynomially many uniform samples from it. Our proof uses the local search technique from Independent Component Analysis (ICA), also used by Frieze et al. (1996). Unlike these previous algorithms, which were based on analyzing the fourth moment, ours is based on the third moment. We also show a direct connection between the problem of learning a simplex and ICA: a simple randomized reduction to ICA from the problem of learning a simplex. The connection is based on a known representation of the uniform measure on a simplex. Similar representations lead to a reduction from the problem of learning an ane transformation
FearNet: Brain-Inspired Model for Incremental Learning

Incremental class learning involves sequentially learning classes in bursts of examples from the same class. This violates the assumptions that underlie methods for training standard deep neural networks, and will cause them to suffer from catastrophic forgetting. Arguably, the best method for incremental class learning is iCaRL, but it requires storing training examples for each class, making it challenging to scale. Here, we propose FearNet for incremental class learning. FearNet is a generative model that does not store previous examples, making it memory efficient. FearNet uses a brain-inspired dual-memory system in which new memories are consolidated from a network for recent memories inspired by the mammalian hippocampal complex to a network for long-term storage inspired by medial prefrontal cortex. Memory consolidation is inspired by mechanisms that occur during sleep. FearNet also uses a module inspired by the basolateral amygdala for determining which memory system to use for recall. FearNet achieves state-of-the-art performance at incremental class learning on image (CIFAR-100, CUB-200) and audio classification (AudioSet) benchmarks.
Implementing a Bayesian scheme for revising belief commitments

Our previous work on classifying complex ship images [1,2] has evolved into an effort to develop software tools for building and solving generic classification problems. Managing the uncertainty associated with feature data and other evidence is an important issue in this endeavor. Pearl [7-11] has developed a Bayesian framework for managing uncertainty that has proven to be applicable to several of the belief maintenance functions that are necessary for classification problem solving. One such function is to determine a belief commitment which designates in categorical terms the most probable instantiation of all hypothesis variables given the evidence available. Before these belief commitments can be computed, the straightforward implementation of Pearl's procedure involves finding an analytical solution to some often very difficult optimization problems. We describe an implementation of this procedure using tensor products that solves these problems enumeratively and avoids the need for case by case analysis. The procedure is thereby made more practical to use in the general case.
Definability aspects of the Denjoy integral

Author(s): Walsh, Sean | Abstract: The Denjoy integral is an integral that extends the Lebesgue integral and can integrate any derivative. In this paper, it is shown that the graph of the indefinite Denjoy integral $f\mapsto \int_a^x f$ is a coanalytic non-Borel relation on the product space $M[a,b]\times C[a,b]$, where $M[a,b]$ is the Polish space of real-valued measurable functions on $[a,b]$ and where $C[a,b]$ is the Polish space of real-valued continuous functions on $[a,b]$. Using the same methods, it is also shown that the class of indefinite Denjoy integrals, called $ACG_{\ast}[a,b]$, is a coanalytic but not Borel subclass of the space $C[a,b]$, thus answering a question posed by Dougherty and Kechris. Some basic model theory of the associated spaces of integrable functions is also studied. Here the main result is that, when viewed as an $\mathbb{R}[X]$-module with the indeterminate $X$ being interpreted as the indefinite integral, the space of continuous functions on the interval $[a,b]$ is elementarily equivalent to the Lebesgue-integrable and Denjoy-integrable functions on this interval, and each is stable but not superstable, and that they all have a common decidable theory when viewed as $\mathbb{Q}[X]$-modules.
A dynamical systems approach to the Kadison–Singer problem

Abstract In these notes we develop a link between the Kadison–Singer problem and questions about certain dynamical systems. We conjecture that whether or not a given state has a unique extension is related to certain dynamical properties of the state. We prove that if any state corresponding to a minimal idempotent point extends uniquely to the von Neumann algebra of the group, then every state extends uniquely to the von Neumann algebra of the group. We prove that if any state arising in the Kadison–Singer problem has a unique extension, then the injective envelope of a C*-crossed product algebra associated with the state necessarily contains the full von Neumann algebra of the group. We prove that this latter property holds for states arising from rare ultrafilters and δ -stable ultrafilters, independent, of the group action and also for states corresponding to non-recurrent points in the corona of the group.
On discrete fractional integral operators and related Diophantine equations

We study discrete versions of fractional integral operators along curves and surfaces. $l^p \to l^q$ estimates are obtained from upper bounds of the number of solutions of associated Diophantine systems. In particular, this relates the discrete fractional integral along the curve $\gamma(m) = (m,m^2,...,m^k)$ to Vinogradov's mean value theorem. Sharp $l^p \to l^q$ estimates of the discrete fractional integral along the hyperbolic paraboloid in $\mathbf{Z}^3$ are also obtained except for endpoints.
Kloosterman sums and Maass cusp forms of half integral weight for the modular group

We estimate the sums \[ \sum_{c\leq x} \frac{S(m,n,c,\chi)}{c}, \] where the $S(m,n,c,\chi)$ are Kloosterman sums of half-integral weight on the modular group. Our estimates are uniform in $m$, $n$, and $x$ in analogy with Sarnak and Tsimerman's improvement of Kuznetsov's bound for the ordinary Kloosterman sums. Among other things this requires us to develop mean value estimates for coefficients of Maass cusp forms of weight $1/2$ and uniform estimates for $K$-Bessel integral transforms. As an application, we obtain an improved estimate for the classical problem of estimating the size of the error term in Rademacher's formula for the partition function $p(n)$.
An information-theoretic framework for fast and robust unsupervised learning via neural population infomax

A framework is presented for unsupervised learning of representations based on infomax principle for large-scale neural populations. We use an asymptotic approximation to the Shannon's mutual information for a large neural population to demonstrate that a good initial approximation to the global information-theoretic optimum can be obtained by a hierarchical infomax method. Starting from the initial solution, an efficient algorithm based on gradient descent of the final objective function is proposed to learn representations from the input datasets, and the method works for complete, overcomplete, and undercomplete bases. As confirmed by numerical experiments, our method is robust and highly efficient for extracting salient features from input datasets. Compared with the main existing methods, our algorithm has a distinct advantage in both the training speed and the robustness of unsupervised representation learning. Furthermore, the proposed method is easily extended to the supervised or unsupervised model for training deep structure networks.
On nilpotent Lie algebras of small breadth

Abstract A Lie algebra L is said to be of breadth k if the maximal dimension of the images of left multiplication by elements of the algebra is k . In this paper we give characterization of finite dimensional nilpotent Lie algebras of breadth less than or equal to two. Furthermore, using these characterizations we determined the isomorphism classes of these algebras.
The poset of the nilpotent commutator of a nilpotent matrix

Abstract Let B be an n × n nilpotent matrix with entries in an infinite field k . The nilpotent commutator N B of B is known to be an irreducible algebraic variety. Assume that B is in Jordan canonical form with the associated Jordan block partition P and let Q ( P ) be the Jordan partition of a generic element of N B . P. Oblak associated to a given partition P another partition resulting from a recursive process. She conjectured that this partition is the same as Q ( P ) . R. Basili, A. Iarrobino and the author later generalized the process introduced by Oblak. The main result of this paper states that all such processes give rise to the same partition – a partition that is defined in terms of the lengths of unions of special symmetric chains in a poset associated to N B . This poset was defined by P. Oblak as the digraph determined by the non-zero entries of a generic matrix in a maximal nilpotent subalgebra of N B .
On Fairness and Calibration

The machine learning community has become increasingly concerned with the potential for bias and discrimination in predictive models. This has motivated a growing line of work on what it means for a classification procedure to be "fair." In this paper, we investigate the tension between minimizing error disparity across different population groups while maintaining calibrated probability estimates. We show that calibration is compatible only with a single error constraint (i.e. equal false-negatives rates across groups), and show that any algorithm that satisfies this relaxation is no better than randomizing a percentage of predictions for an existing classifier. These unsettling findings, which extend and generalize existing results, are empirically confirmed on several datasets.