Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER

As the categories of named entities rapidly increase in real-world applications, class-incremental learning for NER is in demand, which continually learns new entity classes while maintaining the old knowledge. Due to privacy concerns and storage constraints, the model is required to update without any annotations of the old entity classes. However, in each step on streaming data, the "O" class in each step might contain unlabeled entities from the old classes, or potential entities from the incoming classes. In this work, we first carry out an empirical study to investigate the concealed entity problem in class-incremental NER. We find that training with "O" leads to severe confusion of "O" and concealed entity classes, and harms the separability of potential classes. Based on this discovery, we design a rehearsal-based representation learning approach for appropriately learning the "O" class for both old and potential entity classes. Additionally, we provide a more realistic and challenging benchmark for class-incremental NER which introduces multiple categories in each step. Experimental results verify our findings and show the effectiveness of the proposed method on the new benchmark

Outbred genome sequencing and CRISPR/Cas9 gene editing in butterflies

Butterflies are exceptionally diverse but their potential as an experimental system has been limited by the difficulty of deciphering heterozygous genomes and a lack of genetic manipulation technology. Here we use a hybrid assembly approach to construct high-quality reference genomes for Papilio xuthus (contig and scaffold N50: 492 kb, 3.4 Mb) and Papilio machaon (contig and scaffold N50: 81 kb, 1.15 Mb), highly heterozygous species that differ in host plant affiliations, and adult and larval colour patterns. Integrating comparative genomics and analyses of gene expression yields multiple insights into butterfly evolution, including potential roles of specific genes in recent diversification. To functionally test gene function, we develop an efficient (up to 92.5%) CRISPR/Cas9 gene editing method that yields obvious phenotypes with three genes, Abdominal-B, ebony and frizzled. Our results provide valuable genomic and technological resources for butterflies and unlock their potential as a genetic model system

Mudskipper genomes provide insights into the terrestrial adaptation of amphibious fishes

Mudskippers are amphibious fishes that have developed morphological and physiological adaptations to match their unique lifestyles. Here we perform whole-genome sequencing of four representative mudskippers to elucidate the molecular mechanisms underlying these adaptations. We discover an expansion of innate immune system genes in the mudskippers that may provide defence against terrestrial pathogens. Several genes of the ammonia excretion pathway in the gills have experienced positive selection, suggesting their important roles in mudskippers’ tolerance to environmental ammonia. Some vision-related genes are differentially lost or mutated, illustrating genomic changes associated with aerial vision. Transcriptomic analyses of mudskippers exposed to air highlight regulatory pathways that are up- or down-regulated in response to hypoxia. The present study provides a valuable resource for understanding the molecular mechanisms underlying water-to-land transition of vertebrates

The oyster genome reveals stress adaptation and complexity of shell formation

The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved

Research on Personal Data Privacy Security in the Era of Big Data

Big data privacy security has become a hot research topic in contemporary society. Based on the data relevance and life-cycle in the era of big data, this paper analyzes the causes of security problems in China’s data privacy. It puts forward suggestions from three aspects to provide references for subsequent research. Based on the current research progress, this paper first sorts out the definitions of data privacy and data privacy protection, then summarizes the causes of privacy security from the perspectives of technology and management and reveals the consequences of data privacy security issues. The demonstrated results trigger an insight into the solution strategy of data privacy problems and offer suggestions for solving problems from the perspective of management based on the data life-cycle model. Finally, starting from other stages of the data life-cycle and the application scenarios of big data, this paper looks forward to the future research direction. This study found that the present study needs to focus on the combination of system and technology, the improvement of laws and regulations, and the data life-cycle model in both technical and institutional management

Robust Graph Structure Learning under Heterophily

Graph is a fundamental mathematical structure in characterizing relations between different objects and has been widely used on various learning tasks. Most methods implicitly assume a given graph to be accurate and complete. However, real data is inevitably noisy and sparse, which will lead to inferior results. Despite the remarkable success of recent graph representation learning methods, they inherently presume that the graph is homophilic, and largely overlook heterophily, where most connected nodes are from different classes. In this regard, we propose a novel robust graph structure learning method to achieve a high-quality graph from heterophilic data for downstream tasks. We first apply a high-pass filter to make each node more distinctive from its neighbors by encoding structure information into the node features. Then, we learn a robust graph with an adaptive norm characterizing different levels of noise. Afterwards, we propose a novel regularizer to further refine the graph structure. Clustering and semi-supervised classification experiments on heterophilic graphs verify the effectiveness of our method.Comment: 26 pages, 5 figure

Investigation of the Deformation Failure Occurring When Extracting Minerals via Underground Mining: A Case Study

Metal mines mined using the sublevel caving method often exhibit various environmental problems on the ground surface. This can affect the safety of the production process in the mining area. A numerical model using Universal Distinct Element Code has been established to investigate deformation failure giving rise to this underground mining. The calculations are combined with in-situ monitoring data collected over a period of 10 years. The results indicate that the strata movement in the footwall can be divided into two stages: an arch caving development stage and post arch caving development stage. Mining disturbance is the main cause of caving in the arch caving development stage. The overlying strata experience ‘caving–stability–caving’, leading to the formation of an ‘arch-shaped’ caving pattern. In the post arch caving development stage, flexural-toppling deformation occurs in the strata in the direction of the collapse pit due to the tectonic stress present and high dip angles of the discontinuities. Through-going failure surface has been analyzed by studying the plastic state and displacement of elements. The formation of through-going failure surface is related to the flexural-toppling deformation and stress concentration caused by mining activities. Based on the different failure mechanisms, an efficient partition has been proposed such that the footwall can be divided into a stable zone, flexural-toppling failure zone, compression and slipping-toppling failure zone, and shear-slipping failure zone. The results are a useful reference when applied to the Chengchao Iron Mine and other similar metal mines

Investigation of the Deformation Failure Occurring When Extracting Minerals via Underground Mining: A Case Study

Metal mines mined using the sublevel caving method often exhibit various environmental problems on the ground surface. This can affect the safety of the production process in the mining area. A numerical model using Universal Distinct Element Code has been established to investigate deformation failure giving rise to this underground mining. The calculations are combined with in-situ monitoring data collected over a period of 10 years. The results indicate that the strata movement in the footwall can be divided into two stages: an arch caving development stage and post arch caving development stage. Mining disturbance is the main cause of caving in the arch caving development stage. The overlying strata experience ‘caving–stability–caving’, leading to the formation of an ‘arch-shaped’ caving pattern. In the post arch caving development stage, flexural-toppling deformation occurs in the strata in the direction of the collapse pit due to the tectonic stress present and high dip angles of the discontinuities. Through-going failure surface has been analyzed by studying the plastic state and displacement of elements. The formation of through-going failure surface is related to the flexural-toppling deformation and stress concentration caused by mining activities. Based on the different failure mechanisms, an efficient partition has been proposed such that the footwall can be divided into a stable zone, flexural-toppling failure zone, compression and slipping-toppling failure zone, and shear-slipping failure zone. The results are a useful reference when applied to the Chengchao Iron Mine and other similar metal mines

Provable Filter for Real-world Graph Clustering

Graph clustering, an important unsupervised problem, has been shown to be more resistant to advances in Graph Neural Networks (GNNs). In addition, almost all clustering methods focus on homophilic graphs and ignore heterophily. This significantly limits their applicability in practice, since real-world graphs exhibit a structural disparity and cannot simply be classified as homophily and heterophily. Thus, a principled way to handle practical graphs is urgently needed. To fill this gap, we provide a novel solution with theoretical support. Interestingly, we find that most homophilic and heterophilic edges can be correctly identified on the basis of neighbor information. Motivated by this finding, we construct two graphs that are highly homophilic and heterophilic, respectively. They are used to build low-pass and high-pass filters to capture holistic information. Important features are further enhanced by the squeeze-and-excitation block. We validate our approach through extensive experiments on both homophilic and heterophilic graphs. Empirical results demonstrate the superiority of our method compared to state-of-the-art clustering methods.Comment: 12 pages, 5 figure

In Situ Fabrication of a Superhydrophobic ORMOSIL Coating on Wood by an Ammonia–HMDS Vapor Treatment

A superhydrophobic ORMOSIL (organically modified silicate) coating was in situ fabricated on a wood surface by ammonia–hexamethylisilazane (HMDS) vapor treatment. The wood was immerged in tetraethoxysilane (TEOS), and then the TEOS absorbed on the wood surface was hydrolyzed and condensed to hydrophobic SiO2 nanoparticles with ammonia and HDMS vapor treatment. The effect of the treatment temperature and time on the hydrophobicity of wood was investigated. At a treatment temperature of 50 °C, a superhydrophobic surface was achieved on the wood with a treatment time longer than 2 h. SEM images indicated that there were SiO2 nanoparticles fabricated on the wood surface, and FTIR revealed that the hydrophobic –Si(CH3)3 groups were incorporated on the wood surface. The ORMOSIL-modified wood possessed improved liquid repellency. The water absorption decreased significantly from 72.3% to 31.9% after modification