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At present, the query and acquisition of the fragmented knowledge in Chinese court verdicts mainly adopt the class case retrieval method based on the search engine and the rough extraction method for a part of the data in court verdicts. These traditional methods cannot structurally extract fragmented knowledge in Chinese court verdicts and meet the needs of people for the follow-up analysis of court verdicts. Thus, in this paper, we present a structured subject event extraction method (SEE) for Chinese court verdict cases combining with techniques of event extraction (EE) and attribute-value pair extraction (AVPE). Specifically, we provide a subject event representation frame for organizing fragmented knowledge in Chinese court verdict cases. Then, we extract subject events from the unstructured cases based on the trained sequence labeling models and constructed heuristic rules, and fill them into the subject event representation frame in the form of attribute-value pairs (AVPs). The experimental results show that SEE can efficiently and automatically extract subject events from Chinese court verdict cases and visually display them via frame-filling, which promotes the efficiency of people in searching for legal materials and facilitates further research and analysis.

The multivariate time series (MTS) classification is an important classification problem in which data has the temporal attribute. Because relationships between many variables of the MTS are complex and time-varying, existing methods perform not well in MTS classification with many attribute variables. Thus, in this paper, we propose a novel model-based classification method, called Kullback-Leibler Divergence-based Gaussian Model Classification (KLD-GMC), which converts the original MTS data into two important parameters of the multivariate Gaussian model: the mean vector and the inverse covariance matrix. The inverse covariance is the most important parameter, which can obtain the information between the variables. So that the more variables, the more information could be obtained by the inverse covariance, KLD-GMC can deal with the relationship between variables well in the MTS. Then the sparse inverse covariance of each subsequence is solved by Graphical Lasso. Furthermore, the Kullback-Leibler divergence is used as the similarity measurement to implement the classification of unlabeled subsequences, because it can effectively measure the similarity between different distributions. Experimental results on classical MTS datasets demonstrate that our method can improve the performance of multivariate time series classification and outperform the state-of-the-art methods.

Invertebrate immune priming has attracted wide attention of biologists in recent years because it challenges core notions about the disparate nature of acquired and innate immunity. However, the metabolic switch and energetic cost during eliciting immune priming are poorly investigated issues, which could widen and deepen our understanding of the physiological mechanism of immune priming. In this study, using sublethal dose of Bacillus thuringiensis (Bt) as an elicitor, we detected typical immune priming responses in Galleria mellonella. We found that the intensity of immune priming is positively correlated with the levels of antimicrobial peptides and phagocytosis ability of hemocytes. Subsequently, we employed LC-MS/MS-based untargeted metabolomics techniques to analyze the metabolic changes in the fat body of G. mellonella larvae during immune priming. The results showed that there were 74 and 56 significantly altered metabolites in positive and negative ion mode, respectively, after Bt priming. Most of the differential metabolites were enriched in the following metabolic pathways: amino acid biosynthesis, carbon metabolism, aminoacyl-tRNA biosynthesis and ABC transporters. The energetic cost of immune priming was depicted mainly in the slow growth of body mass and decreased levels of sucrose, lactose, D-ribulose 1,5-bisphosphate, Glycerate-3P and isocitric acid, which are enriched in carbon metabolism and involved in energy production. Meanwhile, correlation and interaction network analysis showed negative correlations between carbohydrates and metabolites involved in amino acid biosynthesis, suggesting that amino acids acted as the main energy source and helped the organisms synthesize immune effectors to participate in the immune priming response. Our results pave the way for uncovering the physiological mechanism of insect immune priming and discovering novel targets for Bt insecticide.

Entity linking is a task to extract query mentions in documents, and then link them to their corresponding entities in a knowledge base. It can improve the performances of knowledge network construction, knowledge fusion, information retrieval, natural language processing, and knowledge base population. In this paper, we introduce the difficulties and applications of entity linking and focus on the main methods to address this issue. At last, we list the knowledge bases, data sets, and the evaluation criterion and some challenges of entity linking.

The present study explored the ability of a novel spent chrysanthemum adsorbent prepared from acid acetaldehyde for the removal of Cu 2+ from an aqueous solution. The effect of various parameters, including solution pH, adsorbent dosage, contact time and temperature on adsorption of Cu 2+ were studied by batch experiments. According to the experimental results, the optimal pH range and optimum dosage were found to be 3.0–5.0 and 6.0 g/L, respectively. The adsorption amount at equilibrium decreased with the increase of temperature. Freudlich model provided better correlation for the adsorption of Cu 2+ by modified spent Chrysanthemum (MSC) (R = 0.99)and spent Chrysanthemum (SC)(R = 0.98). Adsorption capacity of MSC was 692 mg/g at 293 K, but it was 400 mg/g at 293 K for SC. The adsorption process on Cu 2+ proceeded rapidly and almost reached adsorption equilibrium within 20 min. The kinetics data of MSC were analyzed using the pseudo-first-order equations and pseudo-second-order equations. The pseudo-second-order equation fitted the experimental data very well (R = 0.99). The adsorption amount at equilibrium decreased with the increase of temperature. The thermodynamic parameters showed that the biosorption was exothermic and spontaneous. Experimental results showed that MSC could be used as an effective biosorbent for Cu 2+ removal from aqueous solutions.

With the advent of the era of big data, the information from multi-sources often conflicts due to that errors and fake information are inevitable. Therefore, how to obtain the most trustworthy or true information (i.e. truth) people need gradually becomes a troublesome problem. In order to meet this challenge, a novel hot technology named truth discovery that can infer the truth and estimate the reliability of the source without supervision has attracted more and more attention. However, most existing truth discovery methods only consider that the information is either same or different rather than the fine-grained relation between them, such as inclusion, support, mutual exclusion, etc. Actually, this situation frequently exists in real-world applications. To tackle the aforementioned issue, we propose a novel truth discovery method named OTDCR in this paper, which can handle the fine-grained relation between the information and infer the truth more effectively through modeling the relation. In addition, a novel method of processing abnormal values is applied to the preprocessing of truth discovery, which is specially designed for categorical data with the relation. Experiments in real dataset show our method is more effective than several outstanding methods.

Classification is a hot topic in such fields as machine learning and data mining. The traditional approach of machine learning is to find a classifier closest to the real classification function, while ensemble classification is to integrate the results of base classifiers, then make an overall prediction. Compared to using a single classifier, ensemble classification can significantly improve the generalization of the learning system in most cases. However, the existing ensemble classification methods rarely consider the weight of the classifier, and there are few methods to consider updating the weights dynamically. In this paper, we are inspired by the idea of truth discovery and propose a new ensemble classification method based on the truth discovery (named ECTD). As far as we know, we are the first to apply the idea of truth discovery in the field of ensemble learning. Experimental results demonstrate that the proposed method performs well in ensemble classification.

Background The immune system of many invertebrates, including insects, has been shown to comprise memory, or specific immune priming. However, knowledge of the molecular mechanisms especially the candidate immune-related genes mediated the specificity of the immune priming are still very scarce and fragmentary. We therefore used two closely related Gram-negative pathogenic bacteria (Photorhabdus luminescens TT01 and P. luminescens H06) as the priming agents and employed Illumina/Solexa platform to investigate the transcriptional changes of the haemocytes of Bombyx mori larvae after priming. Results In total, 23.0 Gbp of sequence data and 153,331,564 reads were generated, representing 10,496 genes. Approximately 89% of the genes or sequenced reads could be aligned to the silkworm reference genome. The differentially expressed genes (DEGs) of PBS-vs-TT01 (up-regulated expression of TT01 relative to PBS), PBS-vs-H06 (up-regulated expression of H06 relative to PBS) and TT01-vs-H06 (up-regulated expression of H06 relative to TT01) were 707, 159 and 461 respectively. In addition, expression patterns of 25 selected DEGs derived from quantitative real-time polymerase chain reaction (qRT-PCR) were consistent with their transcript abundance changes obtained by transcriptomic analyses. The DEGs are mainly related to pattern recognition receptors (PRRs), antimicrobial peptides (AMPs), signaling molecular, effector molecules, phagosome and spliceosome, indicating that they have participated in the regulation of the specific immune priming in the B. mori larvae. Conclusions The transcriptome profiling data sets from this study will provide valuable resources to better understand the molecular and biological mechanisms regulating the specificity of invertebrates' immune priming. All these will shed light on controlling insect pests or preventing epidemic of infectious diseases in economic invertebrates.

Starting in July 2016, the Ministry of Science and Technology of China, along with several other national agencies, sponsors a 54-month 45-million RMB (Chinese Yuan) project on knowledge engineering with Big Data ( www.bigke.org ) for 15 top research and development institutions to study the fundamental theory and the applications of BigKE, a big-data knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation. The project seeks to provide petabyte-scale data and knowledge services in identified application domains. In this paper, we discuss our BigKE framework, and present a novel application scenario for BigKE services.

In this study, the removal of Cr(VI) from aqueous solutions by modified Litchi peel (MLP) has been investigated. Fourier-transform infrared spectrophotometer (FTIR) and scanning electron microscopic analysis (SEM) were used to characterize the biosorbents. The main results are as follow: 1) the optimal pH condition and optimum dosage for the adsorption of Cr(VI) were found to be 1–4 and 8.0 g L − 1 , respectively; 2) the adsorption process on Cr(VI) increased rapidly in 80 min and almost reached adsorption equilibrium in 100 min; 3) the adsorption of Cr(VI) increased with the increase of temperature. Furthermore, the Langmuir and Freudlich models were used to study the equilibrium process. It was found that the Langmuir model provided better correlation for the adsorption of Cr(VI) on MLP and Litchi peel (LP). The maximum adsorption at equilibrium for MLP is 9.55 mg g − 1 at 303 K, while for LP it is only 7.05 mg g − 1 at 303 K. Different kinetic models were used to analyze the kinetics of the adsorption. The pseudo-second-order model could better reflect the MLP adsorption kinetic process of Cr(VI). The thermodynamic parameters showed that the biosorption was endothermic, and there was an energy barrier for the adsorption of Cr(VI) on MLP. The present study demonstrated that MLP is an effective adsorbent for removing Cr(VI) from aqueous solutions.

Contents, layout styles, and parse structures of web news pages differ greatly from one page to another. In addition, the layout style and the parse structure of a web news page may change from time to time. For these reasons, how to design features with excellent extraction performances for massive and heterogeneous web news pages is a challenging issue. Our extensive case studies indicate that there is potential relevancy between web content layouts and their tag paths. Inspired by the observation, we design a series of tag path extraction features to extract web news. Because each feature has its own strength, we fuse all those features with the DS (Dempster-Shafer) evidence theory, and then design a content extraction method CEDS. Experimental results on both CleanEval datasets and web news pages selected randomly from well-known websites show that the F1-score with CEDS is 8.08% and 3.08% higher than existing popular content extraction methods CETR and CEPR-TPR respectively.

Larvae of Galleria mellonella are useful models for studying the innate immunity of invertebrates or for evaluating the virulence of microbial pathogens. In this work, we demonstrated that prior exposure of G. mellonella larvae to high doses (1×10(4), 1×10(5) or 1×10(6) cells/larva) of heat-killed Photorhabdus luminescens TT01 increases the resistance of larvae to a lethal dose (50 cells/larva) of viable P. luminescens TT01 infection administered 48h later. We also found that the changes in immune protection level were highly correlated to the changes in levels of cellular and humoral immune parameters when priming the larvae with different doses of heat-killed P. luminescens TT01. Priming the larvae with high doses of heat-killed P. luminescens TT01 resulted in significant increases in the hemocytes activities of phagocytosis and encapsulation. High doses of heat-killed P. luminescens TT01 also induced an increase in total hemocyte count and a reduction in bacterial density within the larval hemocoel. Quantitative real-time PCR analysis showed that genes coding for cecropin and gallerimycin and galiomycin increased in expression after priming G. mellonella with heat-killed P. luminescens TT01. All the immune parameters changed in a dose-dependent manner. These results indicate that the insect immune system is capable of sensing the extent of priming agent and mounting a proportionate immune response.

In this study, we describe RNA-seq expression profiling of larval Bombyx mori response to hemocoel injection of Bacillus thuringiensis (Bt). Two transcriptomes were generated from the hemocytes of the PBS- and Bt-injected B. mori larvae. More than 49 million 100-bp paired-end reads, encompassing over 7.3 Gb of sequence data, were generated for each library. After filtering the raw reads and removing the rRNA mapped reads, more than 89% of the reads in each library could be mapped to the silkworm genome reference sequence. Comparison of gene expression levels revealed that a total of 133 unigenes were upregulated while 84 unigenes were downregulated in PBS vs Bt. To further investigate the biological functions of different expression genes (DEGs), gene ontology (GO) and functional enrichment analysis were performed to map all the DEGs to terms in the GO, euKaryotic Ortholog Groups of proteins (KOG) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) database. Among these DEGs, many genes involved in immunity against Bt challenge were identified. These included genes participated in pattern recognition, antimicrobial peptides, insecticide resistance or detoxification, immune melanization, cytoskeleton reorganization and many other immune effectors. To confirm the gene expression patterns identified by the RNA-seq data, the transcript levels of 10 immune related DEGs were examined by quantitative real-time PCR (qRT-PCR). The results showed that the DEGs obtained from the deep sequencing data were accurate and gene expression profiles from RNA-Seq data were reliable. Our studies provide insights into the to immune response of B. mori underling the stress of Bt, which is valuable to understand how Bt affects the innate immune system of silkworm and provide new approaches to control insect pests by using Bt as a biological insecticide.