Automated Learning of Hungarian Morphology for Inflection Generation and Morphological Analysis

The automated learning of morphological features of highly agglutinative languages is an important research area for both machine learning and computational linguistics. In this paper we present a novel morphology model that can solve the inflection generation and morphological analysis problems, managing all the affix types of the target language. The proposed model can be taught using (word, lemma, morphosyntactic tags) triples. From this training data, it can deduce word pairs for each affix type of the target language, and learn the transformation rules of these affix types using our previously published, lower-level morphology model called ASTRA. Since ASTRA can only handle a single affix type, a separate model instance is built for every affix type of the target language. Besides learning the transformation rules of all the necessary affix types, the proposed model also calculates the conditional probabilities of the affix type chains using relative frequencies, and stores the valid lemmas and their parts of speech. With these pieces of information, it can generate the inflected form of input lemmas based on a set of affix types, and analyze input inflected word forms. For evaluation, we use Hungarian data sets and compare the accuracy of the proposed model with that of state of the art morphology models published by SIGMORPHON, including the Helsinki (2016), UF and UTNII (2017), Hamburg, IITBHU and MSU (2018) models. The test results show that using a training data set consisting of up to 100 thousand random training items, our proposed model outperforms all the other examined models, reaching an accuracy of 98% in case of random input words that were not part of the training data. Using the high-resource data sets for the Hungarian language published by SIGMORPHON, the proposed model achieves an accuracy of about 95-98%

Dirac eigenmodes at the QCD Anderson transition

Recently we found an Anderson-type localization-delocalization transition in the QCD Dirac spectrum at high temperature. Using spectral statistics we obtained a critical exponent compatible with that of the corresponding Anderson model. Here we study the spatial structure of the eigenmodes both in the localized and the transition region. Based on previous studies in the Anderson model, at the critical point, the eigenmodes are expected to have a scale invariant multifractal structure. We verify the scale invariance of Dirac eigenmodes at the critical point.Comment: to appear in Proceedings of The 32nd International Symposium on Lattice Field Theory, 23-28 June, 2014, Columbia University New York, N

Measures on the square as sparse graph limits

We study a metric on the set of finite graphs in which two graphs are considered to be similar if they have similar bounded dimensional "factors". We show that limits of convergent graph sequences in this metric can be represented by symmetric Borel measures on [0, 1](2). This leads to a generalization of dense graph limit theory to sparse graph sequences. (C) 2019 Elsevier Inc. All rights reserved

Rectus sheath haematoma following exercise testing: a case report

<p>Abstract</p> <p>Introduction</p> <p>Exercise testing is a safe diagnostic procedure which is widely used in the evaluation of patients suspected of having coronary heart disease or for the assessment of the prognosis in patients with established disease. Its complications are mainly cardiac disorders. Here, we report a rectus sheath haematoma as a complication of this procedure in a patient with acute coronary syndrome. To our knowledge, this is the first case report of rectus sheath haematoma in association with exercise testing.</p> <p>Case presentation</p> <p>A 72-year-old Caucasian woman was admitted for acute coronary syndrome. She received conservative treatment including low molecular weight heparin and anti-platelet agents. On the fifth day of her hospital stay, she underwent an exercise test, where no ischaemic response occurred. Several hours later, she experienced pain in the left side of her abdomen. Subsequent investigations revealed a rectus sheath haematoma. The patient underwent surgical haematoma evacuation. A few days later, re-operation was performed for recurrent bleeding in the abdominal wall. The patient had several characteristics known to increase the risk of bleeding during treatment for acute coronary syndrome.</p> <p>Conclusion</p> <p>Awareness of this possible consequence of exercise testing is important for preventing and treating it correctly. For prevention, an assessment of the bleeding risk of the individual patient is necessary before the test, and excessive anticoagulation must be avoided.</p

Orthotropic Strength and Elasticity of Hardwoods in Relation to Composite Manufacture. Part I. Orthotropy of Shear Strength

The orthotropy of apparent shear strength of three Appalachian (aspen, red oak, and yellow-poplar) and two East European (true poplar and turkey oak) hardwood species was investigated. The experimental approach included shear force applications in planes parallel to the grain so that the annual ring orientation and the orientation of the grain relative to the applied force direction were systematically rotated. Statistical analyses of results demonstrated significant effects of grain and ring orientation on the shear strength for all species. Furthermore, interaction between these two factors was detected. Three models, developed to appraise the orthotropic nature of shear strength, were fitted to experimental data demonstrating acceptable to good agreement between predicted and experimental values. A combined model based on tensor theory and a modified version of Hankinson's formula provided the best fit by r2 analysis. The information obtained and the models developed might be used to explore the shear strength of structural composites in which the constituents are systematically or randomly aligned

Identification of influence of digital twin technologies on production systems: a return on investment-based approach

The object of this study is the impact of different digital twin solutions on the performance of job-shop manufacturing systems, while economic aspects are also taken into consideration. This paper proposes an approach to analyze the impact of different identification systems on the efficiency and ROI of digital twin deployment in production systems. In order to achieve this aim, let’s analyze the investment and operation cost of different Internet of Things technologies. The next phase of the research work was the definition of performance parameters, which makes it possible to analyze the impact of different digital twin solutions on the productivity of the job-shop manufacturing system. It is possible to choose four financial indicators to analyze the economic impact of digital twin solution on job-shop manufacturing: return on investment, compound annual growth rate, internal rate of return and net present value. Our approach is based on a novel agent-based simulation model using AnyLogic simulation tool. From the results of this productivity analyses, the model computes the financial indicators, which describe the expected financial impact of the investment and operation cost. It is compared the impact of barcodes and radiofrequency identification technologies on the financial and technological impact of the job-shop manufacturing environment. The numerical analysis of a job-shop manufacturing system shows, that the radiofrequency identification-based digital twin solution has 9.2 % higher return on investment, 53 % higher net present value and 1.6 % higher compound annual growth rate. The model can be easily converted to analyze other types of manufacturing systems, which can lead to increased efficiency of digital twin solution

RNA-seq-based genome annotation and identification of long-noncoding RNAs in the grapevine cultivar ‘Riesling’

Background: The technological advances of RNA-seq and de novo transcriptome assembly have enabled genome annotation and transcriptome profiling in highly heterozygous species such as grapevine (Vitis vinifera L.). This work is an attempt to utilize a de novo-assembled transcriptome of the V. vinifera cultivar ‘Riesling’ to improve annotation of the grapevine reference genome sequence. Results: Here we show that the transcriptome assembly of a single V. vinifera cultivar is insufficient for a complete genome annotation of the grapevine reference genome constructed from V. vinifera PN40024. Further, we provide evidence that the gene models we identified cannot be completely anchored to the previously published V. vinifera PN40024 gene models. In addition to these findings, we present a computational pipeline for the de novo identification of lncRNAs. Our results demonstrate that, in grapevine, lncRNAs are significantly different from protein coding transcripts in such metrics as length, GC-content, minimum free energy, and length-corrected minimum free energy. Conclusions: In grapevine, high-level heterozygosity necessitates that transcriptome characterization be based on cultivar-specific reference genome sequences. Our results strengthen the hypothesis that lncRNAs have thermodynamically different properties than protein-coding RNAs. The analyses of both coding and non-coding RNAs will be instrumental in uncovering inter-cultivar variation in wild and cultivated grapevine species