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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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20395978 · Jun 202019922001200920172026
48 results for binding sums

The study shows examples of contact 3-manifold binding sums that fail to preserve certain properties.

problem Examples of contact 3-manifold binding sums that fail to preserve properties like tightness or symplectic fillability.
method Examples and proofs of vanishing Heegaard Floer contact invariant for Stein fillable manifolds.
result Binding sums of contact 3-manifolds do not preserve properties such as tightness or symplectic fillability.

We introduce the notion of a nested open book, a submanifold equipped with an open book structure compatible with an ambient open book, and describe in detail the special case of a push-off of the binding of an open book. This enables us to explicitly describe a natural open book decomposition of a fibre connected sum …

2016-10-24abs ↗pdf ↗

In the present paper we describe compatible open books for the fibre connected sum along binding components of open books, as well as for the fibre connected sum along multi-sections of open books. As an application the first description provides simple ways of constructing open books supporting all tight contact struc…

2012-07-17abs ↗pdf ↗

We use contact fiber sums of open book decompositions to define an infinite hierarchy of filling obstructions for contact 3-manifolds, called planar k-torsion for nonnegative integers k, all of which cause the contact invariant in Embedded Contact Homology to vanish. Planar 0-torsion is equivalent to overtwistedness, w…

2010-01-23abs ↗pdf ↗

This abstract reviews recent methods for predicting protein-ligand binding affinity.

problem Predicting protein-ligand binding affinity for various applications in life sciences.
method Traditional and deep learning models for binding affinity prediction.
result Improved predictive performance of AI-driven models.

Study on binding numbers of tight contact structures on lens spaces L(n,1)L(n,1).

problem Determining the minimum number of binding components for tight contact structures on lens spaces.
method Using the d3d_3-invariant, restrictions on planar monodromy factorizations, and the Durst-Kegel algorithm.
result The binding number of universally tight contact structures on L(n,1)L(n,1) is equal to nn.

Given two open books with equal pages we show the existence of an exact symplectic cobordism whose negative end equals the disjoint union of the contact manifolds associated to the given open books, and whose positive end induces the contact manifold associated to the open book with the same page and concatenated monod…

2012-07-24abs ↗pdf ↗

PANDA predicts protein binding affinity changes from sequences, outperforming existing methods.

problem Accurately predicting changes in protein binding affinity due to mutations.
method Sequence-based machine learning approach using protein sequence information.
result PANDA achieves higher Pearson correlation coefficients than existing methods.

The identification of novel drug-target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification, where the goal is to determine whether a DT pair interacts or not. However, protein-l…

2018-01-30abs ↗pdf ↗

We study an explicit construction of planar open books with four binding components on any three-manifold which is given by integral surgery on three component pure braid closures. This construction is general, indeed any planar open book with four binding components is given this way. Using this construction and resul…

2010-08-20abs ↗pdf ↗

Let TT denote a binding component of an open book (Σ,φ)(Σ, φ) compatible with a closed contact 3-manifold (M,ξ)(M, ξ). We describe an explicit open book (Σ,φ)(Σ', φ') compatible with (M,ζ)(M, ζ), where ζζ is the contact structure obtained from ξξ by performing a full Lutz twist along TT. Here, (Σ,φ)(Σ', φ') is obtained from $(Σ, …

2009-05-07abs ↗pdf ↗

Motivation: Prediction of the interaction affinity between proteins and compounds is a major challenge in the drug discovery process. WideDTA is a deep-learning based prediction model that employs chemical and biological textual sequence information to predict binding affinity. Results: WideDTA uses four text-based inf…

2019-02-04abs ↗pdf ↗

NeuralMD accelerates protein-ligand binding simulations 1Kx faster.

problem Accurate and efficient simulation of protein-ligand binding dynamics.
method Physics-informed multi-grained group symmetric framework with BindingNet and augmented neural differential equation solver.
result Achieves over 1Kx speedup and up to 15x reduction in reconstruction error compared to standard methods.

This paper studies a subgroup of the Goeritz group related to Heegaard splittings induced by openbook decompositions.

problem Understanding the subgroup of the Goeritz group associated with Heegaard splittings from openbook decompositions.
method Analyzes the mapping class group of a 3-manifold, focusing on elements that preserve the binding and commute with the monodromy.
result Characterizes the Goeritz group subgroup as a quotient of specific mapping class groups and provides a criterion for certain elements.

Computational approaches to drug discovery can reduce the time and cost associated with experimental assays and enable the screening of novel chemotypes. Structure-based drug design methods rely on scoring functions to rank and predict binding affinities and poses. The ever-expanding amount of protein-ligand binding an…

2016-12-08abs ↗pdf ↗

Consider a transverse knot which is the binding of an open book for the ambient contact manifold. In this paper, we show that the transverse invariants defined by Lisca, Ozsvath, Stipsicz, and Szabo (LOSS) are nonvanishing for such transverse knots. This is true regardless of whether or not the ambient contact structur…

2008-06-10abs ↗pdf ↗

Let SS be a compact, connected, oriented surface, possibly with boundary, of negative Euler characteristic. In this article we extend Lindenstrauss-Mirzakhani's and Hamenstädt's classification of locally finite mapping class group invariant ergodic measures on the space of measured laminations $\mathcal{M}\mathcal{L}(…

2018-07-05abs ↗pdf ↗

We show that if (B,π) is an open book decomposition of a contact 3-manifold (Y,ξ), then the complement of the binding B has no Giroux torsion. We also prove the sutured Heegaard-Floer c-bar invariant of the binding of an open book is non-zero.

2009-09-18abs ↗pdf ↗

Major histocompatibility complex class two (MHC-II) molecules are trans-membrane proteins and key components of the cellular immune system. Upon recognition of foreign peptides expressed on the MHC-II binding groove, helper T cells mount an immune response against invading pathogens. Therefore, mechanistic identificati…

2017-12-01abs ↗pdf ↗

When analyzing the genome, researchers have discovered that proteins bind to DNA based on certain patterns of the DNA sequence known as "motifs". However, it is difficult to manually construct motifs due to their complexity. Recently, externally learned memory models have proven to be effective methods for reasoning ov…

2017-02-22abs ↗pdf ↗

NucleusDiff models atomic nuclei interactions to prevent separation violations in drug design.

problem Maintaining minimum pairwise distance between atoms to avoid separation violations in drug design.
method Enforces distance constraint between atomic nuclei and manifolds in a diffusion model.
result Reduces separation violations by up to 100.00% and enhances binding affinity by up to 22.16%.

Parametric insurance offers better risk-sharing in high-risk settings than traditional indemnity insurance.

problem High-risk environments where traditional indemnity insurance is unaffordable or ineffective.
method Comparison of excess-of-loss indemnity insurance and parametric insurance within a mean-variance framework, considering fixed costs and binding budget constraints.
result Parametric insurance yields higher welfare for risk-averse individuals, especially when indemnity insurance is impractical.

Computational approaches to transcription factor binding site identification have been actively researched for the past decade. Negative examples have long been utilized in de novo motif discovery and have been shown useful in transcription factor binding site search as well. However, understanding of the roles of nega…

2011-04-07abs ↗pdf ↗

BIND removes background noise from binary matrices, improving detection accuracy and fairness.

problem Real data often violates the i.i.d assumption for binary matrix entries, leading to inaccurate detection.
method BIND optimizes detection by estimating row- and column-wise mixture distributions and eliminating background noise.
result BIND effectively removes background noise and increases detection accuracy and fairness.

Language models fail to execute simple steps, showing gating and binding errors.

problem Procedural hallucinations in language models, failing to execute simple steps.
method Analyzed long-context binding tasks, identifying gating and binding errors.
result Procedural errors are due to gating and binding failures, with recency bias contributing to the latter.

A new model explains protein interactions via electron delocalization.

problem Understanding how protein interactions affect each other.
method Quantized discrete differential geometry of n-simplices.
result Allosteric regulation follows from the model of interactions.

Adaptive anchor methods improve multi-modal learning by balancing intra-modal and inter-modal information.

problem Fixed anchor methods limit multi-modal learning by over-reliance on a single modality and inadequate cross-modal correlation.
method Adaptive anchor methods using centroid-based anchors from all modalities.
result Adaptive anchor methods like CentroBind consistently outperform fixed anchor methods across various datasets.

We unify recent neural approaches to one-shot learning with older ideas of associative memory in a model for metalearning. Our model learns jointly to represent data and to bind class labels to representations in a single shot. It builds representations via slow weights, learned across tasks through SGD, while fast wei…

2018-07-12abs ↗pdf ↗

In this note we define three invariants of contact structures in terms of open books supporting the contact structures. These invariants are the support genus (which is the minimal genus of a page of a supporting open book for the contact structure), the binding number (which is the minimal number of binding components…

2006-05-16abs ↗pdf ↗

Given a closed binding curve γγ of a surface ΣΣ, any equivalence class of marked complete hyperbolic structure can be decomposed into polygons(possibly with a puncture) with sides being hyperbolic geodesic segments. When ΣΣ is a one-holed torus and γ=A3B2γ= A^3 B^2, we show that any equivalence class of marked complete …

2011-10-16abs ↗pdf ↗

This paper classifies fibered links in 3-sphere using open book decompositions.

problem Classifying fibered links in the 3-sphere.
method Constructing links and their pair-of-pants fiber surfaces from a Hopf link, then verifying monodromies using Heegaard diagrams.
result Monodromies of the links in the family are the only ones corresponding to pair-of-pants open book decompositions of the 3-sphere.

By recent results of Baker--Etnyre--Van Horn-Morris, a rational open book decomposition defines a compatible contact structure. We show that the Heegaard Floer contact invariant of such a contact structure can be computed in terms of the knot Floer homology of its (rationally null-homologous) binding. We then use this …

2011-05-04abs ↗pdf ↗

Developed accurate empirical potentials for Si:H nanowires using multi-fidelity Gaussian process.

problem Accurate modeling of Si:H nanowires using fast but inaccurate empirical potentials and slow but accurate first-principle calculations.
method Employed multi-fidelity Gaussian process regression to integrate low-fidelity empirical potential data with high-fidelity first-principle calculations.
result Demonstrated the accuracy of developed empirical potentials for Si:H nanowires.