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Ling Xin

Publications and source records attributed to Ling Xin.

6 recordsLinked to original sources

Geometric Structural Knowledge Graph Foundation Model

Structural knowledge graph foundation models aim to generalize reasoning to completely new graphs with unseen entities and relations. A key limitation of existing approaches like Ultra is their reliance on a single relational transformation (e.g., element-wise multiplication) in message passing, which can constrain expressiveness and fail to capture diverse relational and structural patterns exhibited on diverse graphs. In this paper, we propose Gamma, a novel foundation model that introduces multi-head geometric attention to knowledge graph reasoning. Gamma replaces the single relational transformation with multiple parallel ones, including real, complex, split-complex, and dual number based transformations, each designed to model different relational structures. A relational conditioned attention fusion mechanism then adaptively fuses them at link level via a lightweight gating with entropy regularization, allowing the model to robustly emphasize the most appropriate relational bias for each triple pattern. We present a full formalization of these algebraic message functions and discuss how their combination increases expressiveness beyond any single space. Comprehensive experiments on 56 diverse knowledge graphs demonstrate that Gamma consistently outperforms Ultra in zero-shot inductive link prediction, with a 5.5% improvement in mean reciprocal rank on the inductive benchmarks and a 4.4% improvement across all benchmarks, highlighting benefits from complementary geometric representations.

cs.AI

Modulating lipid membrane morphology by dynamic DNA origami networks

Membrane morphology and its dynamic adaptation regulate many cellular functions, which are often mediated by membrane proteins. Advances in DNA nanotechnology have enabled the realization of various protein-inspired structures and functions with precise control at the nanometer level, suggesting a viable tool to artificially engineer the membrane morphology. In this work, we demonstrate a DNA origami cross (DOC) structure that can be anchored onto giant unilamellar vesicles (GUVs) and subsequently polymerized into micron-scale reconfigurable one-dimensional (1D) chains or two-dimensional (2D) lattices. Such DNA origami-based networks can be switched between left-handed (LH) and right-handed (RH) conformations by DNA fuels and exhibit potent efficacy in remodeling the membrane curvatures of GUVs. This work sheds light on designing hierarchically-assembled dynamic DNA systems for the programmable modulation of synthetic cells for useful applications.

physics.bio-ph

Choosing the number of factors in factor analysis with incomplete data via a hierarchical Bayesian information criterion

The Bayesian information criterion (BIC), defined as the observed data log likelihood minus a penalty term based on the sample size $N$, is a popular model selection criterion for factor analysis with complete data. This definition has also been suggested for incomplete data. However, the penalty term based on the `complete' sample size $N$ is the same no matter whether in a complete or incomplete data case. For incomplete data, there are often only $N_i<N$ observations for variable $i$, which means that using the `complete' sample size $N$ implausibly ignores the amounts of missing information inherent in incomplete data. Given this observation, a novel criterion called hierarchical BIC (HBIC) for factor analysis with incomplete data is proposed. The novelty is that it only uses the actual amounts of observed information, namely $N_i$'s, in the penalty term. Theoretically, it is shown that HBIC is a large sample approximation of variational Bayesian (VB) lower bound, and BIC is a further approximation of HBIC, which means that HBIC shares the theoretical consistency of BIC. Experiments on synthetic and real data sets are conducted to access the finite sample performance of HBIC, BIC, and related criteria with various missing rates. The results show that HBIC and BIC perform similarly when the missing rate is small, but HBIC is more accurate when the missing rate is not small.

stat.ML

A rotary plasmonic nanoclock

One of the fundamental challenges in nanophotonics is to gain full control over nanoscale optical elements. The precise spatiotemporal arrangement determines their interactions and collective behavior. To this end, DNA nanotechnology is employed as an unprecedented tool to create nanophotonic devices with excellent spatial addressability and temporal programmability. However, most of the current DNA-assembled nanophotonic devices can only reconfigure among random or very few defined states. Here, we demonstrate a DNA-assembled rotary plasmonic nanoclock. In this system, a rotor gold nanorod can carry out directional and reversible 360 degree rotation with respect to a stator gold nanorod, transitioning among 16 well-defined configurations powered by DNA fuels. The full-turn rotation process is monitored by optical spectroscopy in real time. We further demonstrate autonomous rotation of the plasmonic nanoclock powered by DNAzyme-RNA interactions. Such assembly approaches pave a viable route towards advanced nanophotonic systems entirely from the bottom-up.

physics.app-ph

Dynamic Plasmonic System That Responds to Thermal and Aptamer-Target Regulations

The DNA origami technique has empowered a new paradigm in plasmonics for manipulating light and matter at the nanoscale. This interdisciplinary field has witnessed vigorous growth, outlining a viable route to construct advanced plasmonic architectures with tailored optical properties. However, so far plasmonic systems templated by DNA origami have been restricted to respond to only single stimuli. Despite broad interest and scientific importance, thermal and aptamer-target regulations have not yet been widely utilized to reconfigure three-dimensional plasmonic architectures. In this Letter, we demonstrate a chiral plasmonic nanosystem integrated with split aptamers, which can respond to both thermal and aptamer-target regulations. We show that our dual-responsive system can be noninvasively tuned in a wide range of temperatures, readily correlating thermal control with optical signal changes. Meanwhile, our system can detect specific targets including adenosine triphosphate and cocaine molecules, which further enhance the optical response modulations and in turn influence the thermal tunability.

physics.app-ph

Watching a Single Fluorophore Molecule Walk into a Plasmonic Hotspot

Plasmonic nanoantennas allow for enhancing the spontaneous emission, altering the emission polarization, and shaping the radiation pattern of quantum emitters. A critical challenge for the experimental realizations is positioning a single emitter into the hotspot of a plasmonic antenna with nanoscale accuracy. We demonstrate a dynamic light-matter interaction nanosystem enabled by the DNA origami technique. A single fluorophore molecule can autonomously and unidirectionally walk into the hotspot of a plasmonic nanoantenna along a designated origami track. Successive fluorescence intensity increase and lifetime reduction are in situ monitored using single-molecule fluorescence spectroscopy, while the fluorophore walker gradually approaches and eventually enters the plasmonic hotspot. Our scheme offers a dynamic platform, which can be used to develop functional materials, investigate intriguing light-matter interaction phenomena, and serve as prototype system for examining theoretical models.

physics.optics