A BERT-Based Approach for Extracting Prerequisite Relations among Wikipedia Concepts

Concept prerequisite relation prediction is a common task in the field of knowledge discovery. Concept prerequisite relations can be used to rank learning resources and help learners plan their learning paths. As the largest Internet encyclopedia, Wikipedia is composed of many articles edited in multiple languages. Basic knowledge concepts in a variety of subjects can be found on Wikipedia. Although there are many knowledge concepts in each field, the prerequisite relations between them are not clear. When we browse pages in an area on Wikipedia, we do not know which page to start. In this paper, we propose a BERT-based Wikipedia concept prerequisite relation prediction model. First, we created two types of concept pair features, one is based on BERT sentence embedding and the other is based on the attributes of Wikipedia articles. Then, we use these two types of concept pair features to predict the prerequisite relations between two concepts. Experimental results show that our proposed method performs better than state-of-the-art methods for English and Chinese datasets.

Download Full-text

Distant Supervision for Relation Extraction with Sentence Selection and Interaction Representation

Wireless Communications and Mobile Computing ◽

10.1155/2021/8889075 ◽

2021 ◽

Vol 2021 ◽

pp. 1-16

Author(s):

Tiantian Chen ◽

Nianbin Wang ◽

Hongbin Wang ◽

Haomin Zhan

Keyword(s):

Large Scale ◽

Semantic Information ◽

State Of The Art ◽

Relation Extraction ◽

Semantic Features ◽

Distant Supervision ◽

Word Level ◽

Proposed Model ◽

Relation Prediction ◽

Better Than

Distant supervision (DS) has been widely used for relation extraction (RE), which automatically generates large-scale labeled data. However, there is a wrong labeling problem, which affects the performance of RE. Besides, the existing method suffers from the lack of useful semantic features for some positive training instances. To address the above problems, we propose a novel RE model with sentence selection and interaction representation for distantly supervised RE. First, we propose a pattern method based on the relation trigger words as a sentence selector to filter out noisy sentences to alleviate the wrong labeling problem. After clean instances are obtained, we propose the interaction representation using the word-level attention mechanism-based entity pairs to dynamically increase the weights of the words related to entity pairs, which can provide more useful semantic information for relation prediction. The proposed model outperforms the strongest baseline by 2.61 in F1-score on a widely used dataset, which proves that our model performs significantly better than the state-of-the-art RE systems.

Download Full-text

Polymorphism, what it is and how to identify it

Acta Crystallographica Section A Foundations and Advances ◽

10.1107/s2053273314086136 ◽

2014 ◽

Vol 70 (a1) ◽

pp. C1386-C1386

Author(s):

Jean-Pierre Brog ◽

Claire-Lise Chanez ◽

Aurelien Crochet ◽

Katharina Fromm

Keyword(s):

Pharmaceutical Industry ◽

Materials Science ◽

State Of The Art ◽

Basic Research ◽

The Other ◽

Basic Knowledge ◽

Mechanical Resistance ◽

Current State ◽

Number Of Publications ◽

Identification And Characterization

Polymorphism is a very important phenomenon not only in basic research, but certainly in pharmaceutical industry and materials science. Polymorphs possess different properties, for instance the solubility or the mechanical resistance can differ dramatically from one polymorph to the other – properties which can be crucial for their application. Hence, it is important to be able to control the formation of polymorphs and to understand their formation. We here gave some insights into the basic knowledge of polymorph formation and their identification and characterization in order to give an overview on the current state of the art. In order to give interested peoples a tool in hand to test their compounds for polymorphism, we established a series of flow sheets to follow, depending on the class of compounds, hoping that they are useful for many scientists who are not so well acquainted with polymorphism. The presented schemes resume thus the identification steps for polymorphs. It should also help to use the term polymorph correctly in order to reduce the number of publications in which this term is not used in a correct way.

Download Full-text

Um agrupamento de modelos conexonistas por meio de sinapses artificiais e suas aplicações no mercado de criptomoedas

10.31414/ee.2020.t.131152 ◽

2020 ◽

Author(s):

◽

C. O. Vilão Júnior

Keyword(s):

Neural Networks ◽

Reinforcement Learning ◽

State Of The Art ◽

A Priori ◽

The Other ◽

Biological Inspiration ◽

Deep Networks ◽

Ensemble Algorithms ◽

The Brain ◽

Better Than

This work proposes an algorithm, named CMEAS, has biological inspiration focused on the way that the growth of neuronal axons reaches their synaptic destination in other neural networks. This growth follows specific pathways in the brain of animals defined by certain proteins. CMEAS was developed to group two convolutional neural networks, trained a priori on two topics that simultaneously influence the cryptocurrency market, such as news and prices. The means by which networks are grouped occurs using connections external to the original networks to connect to the internal neurons of each network. Two strands were proposed in order to train CMEAS, being one with supervised learning and the other with reinforcement learning. The results confirmed by the Wilcoxon tests demonstrate that the CMEAS had a better profit factor and a higher sharpe index in the experiments in relation to the classic ensemble algorithms through voting and stand-alone deep networks, the algorithm was also superior in all the metrics of the buy and hold strategy, in addition, the algorithm obtained similar results, however, better than those of CNN-LSTM considered state of the art, given the metrics used

Download Full-text

Im2Mesh GAN: Accurate 3D Hand Mesh Recovery from a Single RGB Image

10.21203/rs.3.rs-955086/v1 ◽

2021 ◽

Author(s):

Akila Pemasiri ◽

Kien Nguyen ◽

Sridha Sridha ◽

Clinton Fookes

Keyword(s):

State Of The Art ◽

Input Image ◽

Data Availability ◽

The Other ◽

Challenging Problem ◽

Topological Relationship ◽

New Type ◽

Adversarial Training ◽

Rgb Image ◽

Better Than

Abstract This work addresses hand mesh recovery from a single RGB image. In contrast to most of the existing approaches where parametric hand models are employed as the prior, we show that the hand mesh can be learned directly from the input image. We propose a new type of GAN called Im2Mesh GAN to learn the mesh through end-to-end adversarial training. By interpreting the mesh as a graph, our model is able to capture the topological relationship among the mesh vertices. We also introduce a 3D surface descriptor into the GAN architecture to further capture the associated 3D features. We conduct experiments with the proposed Im2Mesh GAN architecture in two settings: one where we can reap the benefits of coupled groundtruth data availability of the images and the corresponding meshes; and the other which combats the more challenging problem of mesh estimation without the corresponding groundtruth. Through extensive evaluations we demonstrate that even without using any hand priors the proposed method performs on par or better than the state-of-the-art.

Download Full-text

Closing the GAP—A 5Å Scanning Microscope

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100061938 ◽

1969 ◽

Vol 27 ◽

pp. 6-7

Author(s):

A. V. Crewe

Keyword(s):

Normal Form ◽

The Other ◽

Resolving Power ◽

Scanning Microscope ◽

Conventional Microscope ◽

Other Hand ◽

Closing The Gap ◽

Thermal Sources ◽

Better Than ◽

Transmission Microscope

We have become accustomed to differentiating between the scanning microscope and the conventional transmission microscope according to the resolving power which the two instruments offer. The conventional microscope is capable of a point resolution of a few angstroms and line resolutions of periodic objects of about 1Å. On the other hand, the scanning microscope, in its normal form, is not ordinarily capable of a point resolution better than 100Å. Upon examining reasons for the 100Å limitation, it becomes clear that this is based more on tradition than reason, and in particular, it is a condition imposed upon the microscope by adherence to thermal sources of electrons.

Download Full-text

MUNDANE MIRACLES IN AWADH. ENCOUNTERS WITH THE REVEALED AND THE HIDDEN

Studia Religiosa Rossica: Russian Journal of Religion ◽

10.28995/2658-4158-2020-3-130-140 ◽

2020 ◽

pp. 130-140

Author(s):

Maxim B. Demchenko ◽

Keyword(s):

The Other ◽

Local People ◽

Natural Phenomena ◽

Mughal Empire ◽

The Public ◽

British Raj ◽

The Subject ◽

Other World ◽

Better Than

The sphere of the unknown, supernatural and miraculous is one of the most popular subjects for everyday discussions in Ayodhya – the last of the provinces of the Mughal Empire, which entered the British Raj in 1859, and in the distant past – the space of many legendary and mythological events. Mostly they concern encounters with inhabitants of the “other world” – spirits, ghosts, jinns as well as miraculous healings following magic rituals or meetings with the so-called saints of different religions (Hindu sadhus, Sufi dervishes),with incomprehensible and frightening natural phenomena. According to the author’s observations ideas of the unknown in Avadh are codified and structured in Avadh better than in other parts of India. Local people can clearly define if they witness a bhut or a jinn and whether the disease is caused by some witchcraft or other reasons. Perhaps that is due to the presence in the holy town of a persistent tradition of katha, the public presentation of plots from the Ramayana epic in both the narrative and poetic as well as performative forms. But are the events and phenomena in question a miracle for the Avadhvasis, residents of Ayodhya and its environs, or are they so commonplace that they do not surprise or fascinate? That exactly is the subject of the essay, written on the basis of materials collected by the author in Ayodhya during the period of 2010 – 2019. The author would like to express his appreciation to Mr. Alok Sharma (Faizabad) for his advice and cooperation.

Download Full-text

Temperature Effects during Endodormancy Induction on Subsequent Anthesis and Growth of Peach Trees

HortScience ◽

10.21273/hortsci.33.3.452c ◽

1998 ◽

Vol 33 (3) ◽

pp. 452c-452 ◽

Cited By ~ 1

Author(s):

Schuyler D. Seeley ◽

Raymundo Rojas-Martinez ◽

James Frisby

Keyword(s):

Temperature Effects ◽

Shoot Length ◽

The Other ◽

Nighttime Temperatures ◽

Peach Trees ◽

Better Than

Mature peach trees in pots were treated with nighttime temperatures of –3, 6, 12, and 18 °C for 16 h and a daytime temperature of 20 °C for 8 h until the leaves abscised in the colder treatments. The trees were then chilled at 6 °C for 40 to 70 days. Trees were removed from chilling at 40, 50, 60, and 70 days and placed in a 20 °C greenhouse under increasing daylength, spring conditions. Anthesis was faster and shoot length increased with longer chilling treatments. Trees exposed to –3 °C pretreatment flowered and grew best with 40 days of chilling. However, they did not flower faster or grow better than the other treatments with longer chilling times. There was no difference in flowering or growth between the 6 and 12 °C pretreatments. The 18 °C pretreatment resulted in slower flowering and very little growth after 40 and 50 days of chilling, but growth was comparable to other treatments after 70 days of chilling.

Download Full-text

Nglyc: A Random Forest Method for Prediction of N-Glycosylation Sites in Eukaryotic Protein Sequence

Protein and Peptide Letters ◽

10.2174/0929866526666191002111404 ◽

2020 ◽

Vol 27 (3) ◽

pp. 178-186 ◽

Cited By ~ 2

Author(s):

Ganesan Pugalenthi ◽

Varadharaju Nithya ◽

Kuo-Chen Chou ◽

Govindaraju Archunan

Keyword(s):

Random Forest ◽

Protein Sequence ◽

Glycosylation Site ◽

Computational Method ◽

The Other ◽

Eukaryotic Protein ◽

Random Forest Method ◽

Glycosylation Sites ◽

Human And Mouse ◽

Better Than

Background: N-Glycosylation is one of the most important post-translational mechanisms in eukaryotes. N-glycosylation predominantly occurs in N-X-[S/T] sequon where X is any amino acid other than proline. However, not all N-X-[S/T] sequons in proteins are glycosylated. Therefore, accurate prediction of N-glycosylation sites is essential to understand Nglycosylation mechanism. Objective: In this article, our motivation is to develop a computational method to predict Nglycosylation sites in eukaryotic protein sequences. Methods: In this article, we report a random forest method, Nglyc, to predict N-glycosylation site from protein sequence, using 315 sequence features. The method was trained using a dataset of 600 N-glycosylation sites and 600 non-glycosylation sites and tested on the dataset containing 295 Nglycosylation sites and 253 non-glycosylation sites. Nglyc prediction was compared with NetNGlyc, EnsembleGly and GPP methods. Further, the performance of Nglyc was evaluated using human and mouse N-glycosylation sites. Results: Nglyc method achieved an overall training accuracy of 0.8033 with all 315 features. Performance comparison with NetNGlyc, EnsembleGly and GPP methods shows that Nglyc performs better than the other methods with high sensitivity and specificity rate. Conclusion: Our method achieved an overall accuracy of 0.8248 with 0.8305 sensitivity and 0.8182 specificity. Comparison study shows that our method performs better than the other methods. Applicability and success of our method was further evaluated using human and mouse N-glycosylation sites. Nglyc method is freely available at https://github.com/bioinformaticsML/ Ngly.

Download Full-text

pLoc_bal-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by General PseAAC and Quasi-balancing Training Dataset

Medicinal Chemistry ◽

10.2174/1573406415666181218102517 ◽

2019 ◽

Vol 15 (5) ◽

pp. 472-485 ◽

Cited By ~ 21

Author(s):

Kuo-Chen Chou ◽

Xiang Cheng ◽

Xuan Xiao

Keyword(s):

Drug Development ◽

Subcellular Localization ◽

Basic Research ◽

The Other ◽

Training Dataset ◽

Sequence Information ◽

Eukaryotic Proteins ◽

Validation Tests ◽

User Friendly ◽

Better Than

Background/Objective: Information of protein subcellular localization is crucially important for both basic research and drug development. With the explosive growth of protein sequences discovered in the post-genomic age, it is highly demanded to develop powerful bioinformatics tools for timely and effectively identifying their subcellular localization purely based on the sequence information alone. Recently, a predictor called “pLoc-mEuk” was developed for identifying the subcellular localization of eukaryotic proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems where many proteins, called “multiplex proteins”, may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mEuk was trained by an extremely skewed dataset where some subset was about 200 times the size of the other subsets. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset. Methods: To alleviate such bias, we have developed a new predictor called pLoc_bal-mEuk by quasi-balancing the training dataset. Cross-validation tests on exactly the same experimentconfirmed dataset have indicated that the proposed new predictor is remarkably superior to pLocmEuk, the existing state-of-the-art predictor in identifying the subcellular localization of eukaryotic proteins. It has not escaped our notice that the quasi-balancing treatment can also be used to deal with many other biological systems. Results: To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mEuk/. Conclusion: It is anticipated that the pLoc_bal-Euk predictor holds very high potential to become a useful high throughput tool in identifying the subcellular localization of eukaryotic proteins, particularly for finding multi-target drugs that is currently a very hot trend trend in drug development.

Download Full-text

Computer Vision and robotics in postal automation

Human Systems Management ◽

10.3233/hsm-1999-183-411 ◽

1999 ◽

Vol 18 (3-4) ◽

pp. 265-273

Author(s):

Giovanni B. Garibotto

Keyword(s):

Image Processing ◽

Computer Vision ◽

Pattern Recognition ◽

Material Handling ◽

State Of The Art ◽

Short Description ◽

The Other ◽

Functional Requirements ◽

Postal Automation ◽

And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

Download Full-text