New Religious Teachings and Narrative Baojuan in the Late 19th Century: The Example of the Complete Recension of the Scroll of Mulian

Most baojuan (precious scrolls), predominantly religious-oriented prosimetric texts in the vernacular language, in the late period of their development (late 19th–early 20th centuries) lost connection with heterodox religious teachings. Notwithstanding this several newly emerged religious traditions in the 19th century continuedto use the baojuan form to propagate their teachings. This paper analyses specific religious ideas in the Complete Recension of the Scroll of Mulian, first printed in Hangzhou in 1877. This text still has not been translated into any foreign language and is rarely discussed in research work, although it is considerably different from the more widespread recensions of this baojuan. The Complete Recension includes many additional entertaining episodes from the voluminous Mulian dramas of southern China. We can also find ideas of syncretic religious teachings, including references to the inner alchemy technique, which is especially characteristic of the Former Heaven Religion (Xiantiandao) groups. I also compare this text with other recensions of the Mulian Baojuan still recited in China in order to demonstrate the interplay of various beliefs and practices in the late baojuan texts

Wilt L. Idema and Allard M. Olof, The Legend of Prince Golden Calf in China and Korea

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An integrated simulation tool proposed for modeling and optimization of CHP units

Master's thesis in Petroleum engineeringIn this project, a novel framework for CHP optimization is proposed. The objective of the study was to develop an automatic optimization tool based on the integration of IPSEpro simulation software and MATLAB programming environment. The data exchange between these components was organized via COM interface. An experimentally validated model of the commercial AET100 CHP unit was utilized. The CHP was considered as a part of a grid. Therefore electricity trading possibility was taken into account. The system was extended to polygeneration by implementing a solar panel as an additional power source. The objective was to minimize the cost function, which consists of operational and capital investments costs, under a set of constraints. For solving the problem, the Genetic Algorithm was applied. As an addition to the study, two other algorithms (Particle Swarm Optimization and Differential Evolution) were also tested. The applying a tool to real data was not considered in the project. However, an optimization was done for test data to show the performance of a developed framework. The test optimization was done for the 24-hours period in July and December, with different electricity and gas price profiles and various ambient conditions. The obtained results were analyzed in details. It was shown that the proposed optimization tool provides appropriate results. It is flexible and has a good potential to be further extended and developed

Phase behavior and orientational ordering in block copolymers doped with anisotropic nanoparticles

A molecular field theory and coarse-grained computer simulations with dissipative particle dynamics have been used to study the spontaneous orientational ordering of anisotropic nanoparticles in the lamellar and hexagonal phases of diblock copolymers and the effect of nanoparticles on the phase behavior of these systems. Both the molecular theory and computer simulations indicate that strongly anisotropic nanoparticles are ordered orientationally mainly in the boundary region between the domains and the nematic order parameter possesses opposite signs in adjacent domains. The orientational order is induced by the boundary and by the interaction between nanoparticles and the monomer units in different domains. In simulations, sufficiently long and strongly selective nanoparticles are ordered also inside the domains. The nematic order parameter and local concentration profiles of nanoparticles have been calculated numerically using the model of a nanoparticle with two interaction centers and also determined using the results of computer simulations. A number of phase diagrams have been obtained which illustrate the effect of nanoparticle selectivity and molar fraction of the stability ranges of various phases. Different morphologies have been identified by analyzing the static structure factor and a phase diagram has been constructed in coordinates' nanoparticle concentration-copolymer composition. Orientational ordering of even a small fraction of nanoparticles may result in a significant increase of the dielectric anisotropy of a polymer nanocomposite, which is important for various applications

Screening for Primordial RNA–Peptide Interactions Using High-Density Peptide Arrays

RNA–peptide interactions are an important factor in the origin of the modern mechanism of translation and the genetic code. Despite great progress in the bioinformatics of RNA–peptide interactions due to the rapid growth in the number of known RNA–protein complexes, there is no comprehensive experimental method to take into account the influence of individual amino acids on non-covalent RNA–peptide bonds. First, we designed the combinatorial libraries of primordial peptides according to the combinatorial fusion rules based on Watson–Crick mutations. Next, we used high-density peptide arrays to investigate the interaction of primordial peptides with their cognate homo-oligonucleotides. We calculated the interaction scores of individual peptide fragments and evaluated the influence of the peptide length and its composition on the strength of RNA binding. The analysis shows that the amino acids phenylalanine, tyrosine, and proline contribute significantly to the strong binding between peptides and homo-oligonucleotides, while the sum charge of the peptide does not have a significant effect. We discuss the physicochemical implications of the combinatorial fusion cascade, a hypothesis that follows from the amino acid partition used in the work

A Method for Creating Structural Models of Text Documents Using Neural Networks.

The article describes modern neural network BERT-based models and considers their application for Natural Language Processing tasks such as question answering and named entity recognition. The article presents a method for solving the problem of automatically creating structural models of text documents. The proposed method is hybrid and is based on jointly utilizing several NLP models. The method builds a structural model of a document by extracting sentences that correspond to various aspects of the document. Information extraction is performed by using the BERT Question Answering model with questions that are prepared separately for each aspect. The answers are filtered via the BERT Named Entity Recognition model and used to generate the contents of each field of the structural model. The article proposes two algorithms for field content generation: Exclusive answer choosing algorithm and Generalizing answer forming algorithm, that are used for short and voluminous fields respectively. The article also describes the software implementation of the proposed method and discusses the results of experiments conducted to evaluate the quality of the method.The article describes modern neural network BERT-based models and considers their application for Natural Language Processing tasks such as question answering and named entity recognition. The article presents a method for solving the problem of automatically creating structural models of text documents. The proposed method is hybrid and is based on jointly utilizing several NLP models. The method builds a structural model of a document by extracting sentences that correspond to various aspects of the document. Information extraction is performed by using the BERT Question Answering model with questions that are prepared separately for each aspect. The answers are filtered via the BERT Named Entity Recognition model and used to generate the contents of each field of the structural model. The article proposes two algorithms for field content generation: Exclusive answer choosing algorithm and Generalizing answer forming algorithm, that are used for short and voluminous fields respectively. The article also describes the software implementation of the proposed method and discusses the results of experiments conducted to evaluate the quality of the method