A hybrid representation based simile component extraction

Simile, a special type of metaphor, can help people to express their ideas more clearly. Simile component extraction is to extract tenors and vehicles from sentences. This task has a realistic significance since it is useful for building cognitive knowledge base. With the development of deep neural networks, researchers begin to apply neural models to component extraction. Simile components should be in cross-domain. According to our observations, words in cross-domain always have different concepts. Thus, concept is important when identifying whether two words are simile components or not. However, existing models do not integrate concept into their models. It is difficult for these models to identify the concept of a word. What’s more, corpus about simile component extraction is limited. There are a number of rare words or unseen words, and the representations of these words are always not proper enough. Exiting models can hardly extract simile components accurately when there are low-frequency words in sentences. To solve these problems, we propose a hybrid representation-based component extraction (HRCE) model. Each word in HRCE is represented in three different levels: word level, concept level and character level. Concept representations (representations in concept level) can help HRCE to identify the words in cross-domain more accurately. Moreover, with the help of character representations (representations in character levels), HRCE can represent the meaning of a word more properly since words are consisted of characters and these characters can partly represent the meaning of words. We conduct experiments to compare the performance between HRCE and existing models. The experiment results show that HRCE significantly outperforms current models

Identification and characterization of microRNAs and endogenous siRNAs in Schistosoma japonicum

<p>Abstract</p> <p>Background</p> <p>Small endogenous non-coding RNAs (sncRNAs) such as small interfering RNA (siRNA), microRNA and other small RNA transcripts are derived from distinct loci in the genome and play critical roles in RNA-mediated gene silencing mechanisms in plants and metazoa. They are approximately 22 nucleotides long; regulate mRNA stability through perfect or imperfect match to the targets. The biological activities of sncRNAs have been related to many biological events, from resistance to microbe infections to cellular differentiation. The development of the zoonotic parasite <it>Schistosoma japonicum </it>parasite includes multiple steps of morphological alterations and biological differentiations, which provide a unique model for studies on the functions of small RNAs. Characterization of the genome-wide transcription of the sncRNAs will be a major step in understanding of the parasite biology. The objective of this study is to investigate the transcriptional profile and potential function of the small non-coding RNAs in the development of <it>S. japanicum</it>.</p> <p>Results</p> <p>The endogenous siRNAs were found mainly derived from transposable elements (TE) or transposons and the natural antisense transcripts (NAT). In contrast to other organisms, the TE-derived siRNAs in <it>S. japonicum </it>were more predominant than other sncRNAs including microRNAs (miRNAs). Further, there were distinct length and 3'end variations in the sncRNAs, which were associated with the developmental differentiation of the parasite. Among the identified miRNA transcripts, there were 38 unique to <it>S. japonicum </it>and 16 that belonged to 13 miRNA families are common to other metazoan lineages. These miRNAs were either ubiquitously expressed, or they exhibited specific expression patterns related to the developmental stages or sex. Genes that encoded miRNAs are mainly located in clusters within the genome of <it>S. japonicum</it>. However, genes within one cluster could be differentially transcribed, which suggested that individual genes might be regulated by distinct mechanisms during parasite development.</p> <p>Conclusions</p> <p>Many miRNA and endogenous siRNA transcripts were identified in <it>S. japonicum </it>and the amount of siRNA was at least 4.4 and 1.6 times more than that of miRNA in both schistosomulum and adult worm stages respectively. SiRNAs are mainly derived from transposable elements (or transposons); while natural antisense transcripts (NAT)-derived siRNAs were much less. A majority of miRNA transcripts identified in the parasite were species-specific and the expression of certain miRNAs was found developmentally regulated. Both miRNA and siRNAs are potentially important regulators in the development of schistosomal parasites.</p

Ramp facies in an intracratonic basin: A case study from the Upper Devonian and Lower Carboniferous in central Hunan, southern China

AbstractDetailed studies on Late Devonian to Early Carboniferous carbonate rocks in central Hunan, southern China have led to the recognition of 25 lithofacies which can be grouped into: (1) inner ramp peritidal platform, (2) inner ramp organic bank and mound, (3) mid ramp, (4) outer ramp, and (5) shelf basin facies associations. The peritidal platform facies association dominates the Zimenqiao Formation (Namurian A or late Datangian) and is characterized by gypsum and dolostone-containing sequences, indicating a peritidal platform environment. The other four facies associations dominate the Menggongao Formation (late Famennian), Liujiatang Formation (Tournaisian or Yangruanian), Shidengzi Formations (early Visean or early Datangian). Five upward-shallowing cycles were distinguished in these three Formations. The predominant facies associations developed in each Formation demonstrate an overall transgression–regression cycle in the Late Devonian to Early Carboniferous in central Hunan. The overall transgressive sequence was preserved in the Shaodong, Menggongao, and Liujiatang Formations, and the overall regressive sequence was preserved in the Liujiatang, Shidengzi, Ceshui and Zimenqiao Formations

Learning Disentangled Semantic Representation for Domain Adaptation

Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space with entangling domain information and semantic information. Different from previous efforts on the entangled feature space, we aim to extract the domain invariant semantic information in the latent disentangled semantic representation (DSR) of the data. In DSR, we assume the data generation process is controlled by two independent sets of variables, i.e., the semantic latent variables and the domain latent variables. Under the above assumption, we employ a variational auto-encoder to reconstruct the semantic latent variables and domain latent variables behind the data. We further devise a dual adversarial network to disentangle these two sets of reconstructed latent variables. The disentangled semantic latent variables are finally adapted across the domains. Experimental studies testify that our model yields state-of-the-art performance on several domain adaptation benchmark datasets

Model Reference Control for an Economic Growth Cycle Model

A useful method in intelligent engineering, called model reference control MRC , is applied in an economic control problem. The authors review the main framework of MRC and Goodwin growth cycle GGC model between two countries and drive the employment rate to be approximate stable in a high level by controlling the workers&apos; share in the national income automatically. It is very helpful to constitute economic policies for a country or an economic union

Strength and size of phosphorus-rich patches determine the foraging strategy of Neyraudia reynaudiana

BackgroundUnder natural conditions, soil nutrients are heterogeneously distributed, and plants have developed adaptation strategies to efficiently forage patchily distributed nutrient. Most previous studies examined either patch strength or patch size separately and focused mainly on root morphological plasticity (increased root proliferation in nutrient-rich patch), thus the effects of both patch strength and size on morphological and physiological plasticity are not well understood. In this study, we examined the foraging strategy of Neyraudia reynaudiana (Kunth) Keng ex Hithc, a pioneer grass colonizing degraded sites, with respect to patch strength and size in heterogeneously distributed phosphorus (P), and how foraging patchily distributed P affects total plant biomass production. Plants were grown in sand-culture pots divided into 1/2, 1/4, 1/6 compartments and full size and supplied with 0+0/30, 0+7.5/30 and 7.5+0/30mg P/kg dry soil as KH2PO4 or 0+15/15, 0+18.5/ 18.5, 7.5+15/15mgkg-1 in the homogenous treatment. The first amount was the P concentration in the central region, and that the second amount was the P concentration in the outer parts of the pot.ResultsAfter 3months of growth under experimental conditions, significantly (p&lt;0.05) high root elongation, root surface area, root volume and average root diameter was observed in large patches with high patch strength. Roots absorbed significantly more P in P-replete than P-deficient patches. Whole plant biomass production was significantly higher in larger patches with high patch strength than small patches and homogeneous P distribution.ConclusionThe result demonstrates that root morphological and physiological plasticity are important adaptive strategies for foraging patchily distributed P and the former is largely determined by patch strength and size. The results also establish that foraging patchily distributed P resulted in increased total plant biomass production compared to homogeneous P distribution

Pedagogical practices of good nursing, medicine and dentistry professors from the student's perception

The aim of this qualitative study was to analyze, in the light of Shuman's concept of pedagogical content knowledge, the pedagogical practices of good nursing, medicine and dentistry professors from the perception of students of a public university in southern Brazil. The study comprised 16 students who were approached through interviews focused by vignettes and qualitative indicators. Pedagogical content knowledge is observed when good professors share the learning objectives while associating theory and practice, fostering student reasoning using a wide range of strategies responsive to contents and the public; carefully prepare and organize their lessons; and allow to be evaluated. Pedagogical content knowledge is presented as a differential in teaching practice; however, students perceive these practices in few professors, leading to the need for recommending rooms and strategies for training health teaching staff