Polymer property prediction is a critical task in polymer science.Conventional approaches typically rely on a single data modality or a limited set of modalities,which constrains both predictive accuracy and practical...Polymer property prediction is a critical task in polymer science.Conventional approaches typically rely on a single data modality or a limited set of modalities,which constrains both predictive accuracy and practical applicability.In this paper,we present Uni-Poly,a novel framework that integrates diverse data modalities to achieve a comprehensive and unified representation of polymers.Uni-Poly encompasses all commonly used structural formats,including SMILES,2D graphs,3D geometries,and fingerprints.In addition,it incorporates domain-specific textual descriptions to enrich the representation.Experimental results demonstrate that Uni-Poly outperforms all single-modality and multi-modality baselines across various property prediction tasks.The integration of textual descriptions provides complementary information that structural representations alone cannot capture.These findings underscore the value of leveraging multimodal and domain-specific information to enhance polymer property prediction,thereby advancing high-throughput screening and the discovery of novel polymer materials.展开更多
This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems.It calls for more research attention...This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems.It calls for more research attention on three aspects:(i)application of control and detection uni ed framework to enhancing the diagnosis capability of feedback control systems,(ii)projection-based fault detection,and complementary and explainable applications of projection-and machine learning-based techniques,and(iii)system performance degradation detection that is of elemental importance for today's automatic control systems.Some ideas and conceptual schemes are presented and illustrated by means of examples,serving as convincing arguments for research e orts in these aspects.They would contribute to the future development of capable diagnosis systems for functionality safe and cyber secure automatic control systems.展开更多
基金funded by the National Natural Science Foundation of China,No.62474183,The funder played no role in study design,data collection,analysis and interpretation of data,or the writing of this manuscript.
文摘Polymer property prediction is a critical task in polymer science.Conventional approaches typically rely on a single data modality or a limited set of modalities,which constrains both predictive accuracy and practical applicability.In this paper,we present Uni-Poly,a novel framework that integrates diverse data modalities to achieve a comprehensive and unified representation of polymers.Uni-Poly encompasses all commonly used structural formats,including SMILES,2D graphs,3D geometries,and fingerprints.In addition,it incorporates domain-specific textual descriptions to enrich the representation.Experimental results demonstrate that Uni-Poly outperforms all single-modality and multi-modality baselines across various property prediction tasks.The integration of textual descriptions provides complementary information that structural representations alone cannot capture.These findings underscore the value of leveraging multimodal and domain-specific information to enhance polymer property prediction,thereby advancing high-throughput screening and the discovery of novel polymer materials.
文摘This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems.It calls for more research attention on three aspects:(i)application of control and detection uni ed framework to enhancing the diagnosis capability of feedback control systems,(ii)projection-based fault detection,and complementary and explainable applications of projection-and machine learning-based techniques,and(iii)system performance degradation detection that is of elemental importance for today's automatic control systems.Some ideas and conceptual schemes are presented and illustrated by means of examples,serving as convincing arguments for research e orts in these aspects.They would contribute to the future development of capable diagnosis systems for functionality safe and cyber secure automatic control systems.
