Object-oriented Neural Programming (OONP) for Document Understanding

We propose Object-oriented Neural Programming (OONP), a framework for semantically parsing documents in specific domains. Basically, OONP reads a document and parses it into a predesigned object-oriented data structure (referred to as ontology in this paper) that reflects the domain-specific semantics of the document. An OONP parser models semantic parsing as a decision process: a neural net-based Reader sequentially goes through the document, and during the process it builds and updates an intermediate ontology to summarize its partial understanding of the text it covers. OONP supports a rich family of operations (both symbolic and differentiable) for composing the ontology, and a big variety of forms (both symbolic and differentiable) for representing the state and the document. An OONP parser can be trained with supervision of different forms and strength, including supervised learning (SL) , reinforcement learning (RL) and hybrid of the two. Our experiments on both synthetic and real-world document parsing tasks have shown that OONP can learn to handle fairly complicated ontology with training data of modest sizes.Comment: accepted by ACL 201

Event-driven continuous STDP learning with deep structure for visual pattern recognition

Human beings can achieve reliable and fast visual pattern recognition with limited time and learning samples. Underlying this capability, ventral stream plays an important role in object representation and form recognition. Modeling the ventral steam may shed light on further understanding the visual brain in humans and building artificial vision systems for pattern recognition. The current methods to model the mechanism of ventral stream are far from exhibiting fast, continuous and event-driven learning like the human brain. To create a visual system similar to ventral stream in human with fast learning capability, in this study, we propose a new spiking neural system with an event-driven continuous spike timing dependent plasticity (STDP) learning method using specific spiking timing sequences. Two novel continuous input mechanisms have been used to obtain the continuous input spiking pattern sequence. With the event-driven STDP learning rule, the proposed learning procedure will be activated if the neuron receive one pre- or post-synaptic spike event. The experimental results on MNIST database show that the proposed method outperforms all other methods in fast learning scenarios and most of the current models in exhaustive learning experiments

Near-Infrared and Visible Photoactivation to Uncage Carbon Monoxide from an Aqueous-Soluble PhotoCORM.

Multiphoton excitation allows one to access high energy excited states and perform valuable tasks in biological systems using tissue penetrating near-infrared (NIR) light. Here, we describe new photoactive manganese tricarbonyl complexes incorporating the ligand 4'-p-N,N-bis(2-hydroxyethyl)amino-benzyl-2,2':6',2″-terpyridine (TPYOH), which can serve as an antenna for two photon NIR excitation. Solutions of Mn(CO)3(TPYOH)X (X = Br- or CF3SO3-) complexes are very photoactive toward CO release under visible light excitation (405 nm, 451 nm). The same responses were also triggered by multiphoton excitation at 750 and 800 nm. In this context, we discuss the potential applications of these complexes as visible/NIR light photoactivated carbon monoxide releasing moieties (photoCORMs). We also report the isolation and crystal structures of the TPYOH complexes Mn(TPYOH)Cl2 and [Mn(TPYOH)2](CF3SO3)2, to illustrate a possible photolysis product(s)

Orientational behaviors of silk fibroin hydrogels

In this study, a novel shear-induced silk fibroin hydrogel with three-dimensional (3D) anisotropic and oriented gel skeleton/network morphology is presented. Amphipathic anionic and nontoxic sodium surfactin is blended with the silk fibroin to decrease its gelation time during the mechanical shearing process. The fibroin/surfactin blended solutions undergo a facial shearing process to accomplish a solâ gel transition within one hour. The dynamic solâ gel transition kinetic analysis, gel skeleton/network morphology, and mechanical property measurements are determined in order to visualize the fibroin/surfactin solâ gel transition during the shearing process and its resulting hydrogel. The results demonstrate that there is significant b-sheet assembly from random coil conformations in the fibroin/surfactin blended system during the facile shearing process. The silk fibroin b-sheets further transform into a fibrous large-scale aggregation with orientational and parallel arrangements to the shearing direction. The shear-induced fibroin/ surfactin hydrogel exhibits notable anisotropic and oriented 3D skeleton/network morphology and a significant mechanical compressive strength in proportion to the shearing stress, compared with the control fibroin/surfactin hydrogel undergoing no shearing process. Due to its oriented gel skeleton/network structure and significantly enhanced mechanical properties, the shear-induced fibroin/ surfactin gel may be suitable as a biomaterial in 3D oriented tissue regeneration, including for nerves, the cultivation of bone cells, and the repair of defects in muscle and ligament tissues.The work is supported by National Natural Science Foundation of China (Grant No. 51373114), PAPD and College Nature Science Research Project of Jiangsu Province, China (Grant No. 15KJA540001). S. C. Kundu holds ERA Chair Full Professor of European Commission Programme (RoReCaST) at 3Bs Research Group, University of Minho, Portugal.info:eu-repo/semantics/publishedVersio

Evolutionary transition between invertebrates and vertebrates via methylation reprogramming in embryogenesis

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Xu, X., Li, G., Li, C., Zhang, J., Wang, Q., Simmons, D. K., Chen, X., Wijesena, N., Zhu, W., Wang, Z., Wang, Z., Ju, B., Ci, W., Lu, X., Yu, D., Wang, Q., Aluru, N., Oliveri, P., Zhang, Y. E., Martindale, M. Q., & Liu, J. Evolutionary transition between invertebrates and vertebrates via methylation reprogramming in embryogenesis. National Science Review, 6(5), (2019):993-1003, doi:10.1093/nsr/nwz064.Major evolutionary transitions are enigmas, and the most notable enigma is between invertebrates and vertebrates, with numerous spectacular innovations. To search for the molecular connections involved, we asked whether global epigenetic changes may offer a clue by surveying the inheritance and reprogramming of parental DNA methylation across metazoans. We focused on gametes and early embryos, where the methylomes are known to evolve divergently between fish and mammals. Here, we find that methylome reprogramming during embryogenesis occurs neither in pre-bilaterians such as cnidarians nor in protostomes such as insects, but clearly presents in deuterostomes such as echinoderms and invertebrate chordates, and then becomes more evident in vertebrates. Functional association analysis suggests that DNA methylation reprogramming is associated with development, reproduction and adaptive immunity for vertebrates, but not for invertebrates. Interestingly, the single HOX cluster of invertebrates maintains unmethylated status in all stages examined. In contrast, the multiple HOX clusters show dramatic dynamics of DNA methylation during vertebrate embryogenesis. Notably, the methylation dynamics of HOX clusters are associated with their spatiotemporal expression in mammals. Our study reveals that DNA methylation reprogramming has evolved dramatically during animal evolution, especially after the evolutionary transitions from invertebrates to vertebrates, and then to mammals.This work was supported by the National Key Research and Development Program of China (2018YFC1003303), the Strategic Priority Research Program of the CAS (XDB13040200), the National Natural Science Foundation of China (91519306, 31425015), the Youth Innovation Promotion Association of the CAS and the Key Research Program of Frontier Sciences, CAS (QYZDY-SSW-SMC016)