Paper List
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Nyxus: A Next Generation Image Feature Extraction Library for the Big Data and AI Era
This paper addresses the core pain point of efficiently extracting standardized, comparable features from massive (terabyte to petabyte-scale) biomedi...
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Topological Enhancement of Protein Kinetic Stability
This work addresses the long-standing puzzle of why knotted proteins exist by demonstrating that deep knots provide a functional advantage through enh...
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A Multi-Label Temporal Convolutional Framework for Transcription Factor Binding Characterization
This paper addresses the critical limitation of existing TF binding prediction methods that treat transcription factors as independent entities, faili...
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Social Distancing Equilibria in Games under Conventional SI Dynamics
This paper solves the core problem of proving the existence and uniqueness of Nash equilibria in finite-duration SI epidemic games, showing they are a...
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Binding Free Energies without Alchemy
This paper addresses the core bottleneck of computational expense in Absolute Binding Free Energy calculations by eliminating the need for numerous al...
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SHREC: A Spectral Embedding-Based Approach for Ab-Initio Reconstruction of Helical Molecules
This paper addresses the core bottleneck in cryo-EM helical reconstruction: eliminating the dependency on accurate initial symmetry parameter estimati...
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Budget-Sensitive Discovery Scoring: A Formally Verified Framework for Evaluating AI-Guided Scientific Selection
This paper addresses the critical gap in evaluating AI-guided scientific selection strategies under realistic budget constraints, where existing metri...
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Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration
This paper addresses the core challenge of accurately decomposing shared (joint) and dataset-specific (individual) sources of variation in multi-modal...
Scalable DNA Ternary Full Adder Enabled by a Competitive Blocking Circuit
Institute of Computational Science and Technology, Guangzhou University, China | School of Computer Science and Technology, Wuhan University of Science and Technology, China | School of Computer Science and Technology, Dalian University of Technology, China | School of Computing Science, Peking University, China
30秒速读
IN SHORT: This paper addresses the core bottleneck of carry information attenuation and limited computational scale in DNA binary adders by introducing a scalable ternary architecture.
核心创新
- Methodology Proposes a novel Competitive Blocking (CB) circuit that leverages differential reaction kinetics (k2 ≫ k1, k3) to dynamically select and block reaction pathways for precise carry information management.
- Methodology Introduces a ternary (base-3) adder architecture, moving beyond binary systems, which inherently reduces the frequency of carry propagation and increases single-bit information density.
- Methodology Implements a Dynamic Concentration Adjustment (CA) strategy, applying chemical equilibrium principles to optimize reactant ratios and signal transmission, enabling significant bit-width extension.
主要结论
- The CB circuit reliably performs ternary full-adder logic, with experimental validation showing successful 10-bit addition operations.
- The integrated CA strategy enables the adder to scale to 17-bit addition, representing a massive increase in computational scale.
- The architecture achieves a 'scale/strand' metric improvement of 2,405,552x compared to a recent state-of-the-art binary DNA adder capable of only 4 consecutive carries.
摘要: DNA adder circuits are programmable reaction networks that process DNA molecular inputs to compute a sum and serve as essential components for digital computation. Currently, DNA adders primarily focus on binary addition. While efforts extend the operational bit-width by minimizing the number of DNA strands and developing carry-transmission mechanisms, challenges such as the susceptibility of carrying information to attenuation and the limited expressive capacity of the binary system impose significant constraints on computational scale. This paper proposes a scalable ternary adder architecture by introducing an innovative competitive blocking (CB) circuit. The architecture employs a dual cooperative optimization strategy that significantly enhances single-bit computational capacity and incorporates a dynamic concentration adjustment (CA) to effectively broaden the computational bit-width. Consequently, a significant increase in molecular computing scale is achieved compared to previous binary adders. Biochemical experimental results indicate that the CB circuit effectively outputs the ternary full-adder bit and successfully performs 10-bit addition. Furthermore, by implementing the CA strategy, this adder can be further extended to support 17-bit addition. This research provides a novel methodological foundation for advancing DNA computing technologies and offers promising potential for scalable digital computing applications.