Regenerative Medicine in Orthopaedics: Microsurgery Achievements for Translational Animal Model

Purpose: Despite many scientific advances, Regenerative Medicine is still in the preclinical stages in many areas. In this article, we intend to discuss the role of microsurgery in the bench-to-bedside transition of such primary findings. Method: By searching the papers related to the history of Regenerative Medicine (RM) and the news of Tissue Engineering (TE) in orthopedics in Pubmed, Scopus, and Google Scholar databases, we accessed a complete archive of various topics related to this field. Result: We first assessed the history and achievements of regenerative medicine, then we realized the importance of translational medical sciences and the role of animal models in this incipient phenomenon. Finally, after mastering the capabilities of microsurgery and the useful contribution of this technique to the advancement of clinical applications of regenerative medicine in various branches such as skin, skeletal system, nerves, and blood vessels, we decided to express the gist of our studies through this article. Conclusion: Considering the widespread use of small animals in regenerative medicine projects and the inevitable role of microsurgery in performing the best intervention on these animal models, the significant progress of regenerative medicine clinical application requires special attention to microsurgery in associated research.

Binding Energy, Root Mean Square Radius and Magnetic Dipole Moment of the Triton Nucleus

The basis functions of the translation invariant shell model are used to construct the ground state nuclear wave functions of 3H. The used residual two-body interactions consist of central, tensor, spin orbit and quadratic spin orbit terms with Gaussian radial dependence. The parameters of these interactions are so chosen in such a way that they represent the long-range attraction and the short-range repulsion of the nucleon-nucleon interactions. These parameters are so chosen to reproduce good agreement between the calculated values of the binding energy, the root mean-square radius, the D-state probability, the magnetic dipole moment and the electric quadrupole moment of the deuteron nucleus. The variation method is then used to calculate the binding energy of triton by varying the oscillator parameter which exists in the nuclear wave function. The obtained nuclear wave functions are then used to calculate the root mean-square radius and the magnetic dipole moment of the triton.

Improving Phrase-Based Statistical Machine Translation Models by Incorporating Syntax-Based Language Models

This paper proposed a method to incorporate syntax-based language models in phrase-based statistical machine translation (SMT) systems. The syntax-based language model used in this paper is based on link grammar,which is a high lexical formalism. In order to apply language models based on link grammar in phrase-based models,the concept of linked phrases,an extension of the concept of traditional phrases in phrase-based models was brought out. Experiments were conducted and the results showed that the use of syntax-based language models could improve the performance of the phrase-based models greatly.

Novel translational rat models of dopamine transporter deficiency

Dopamine （DA） is one of the brain＇s fundamental neurotransmitters. Despite the fact that the dopaminergic synapses constitute less than 1% of all brain synapses, DA is implicated in a number of critical physiological functions and in the pathogenesis of important psychiatric diseases such as schizophrenia, attention-deficit/hyperactivity disorder （ADHD）, Parkinson＇s disease （PD） and others.

Graph-based Lexicalized Reordering Models for Statistical Machine Translation

Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.

Ethical Problems in MTI Students’Escort Interpreting from the Perspective of Chesterman’s Models on Translation Ethics

The professionalization of translation has been discussed by many scholars in recent years,which has inspired the intense discussion of translation ethics.Drawing upon Chesterman’s models on translation ethics,this paper intends to examine the ethical problems in MTI students’escort interpreting for Vanuatu Sport Technical Assistance Project for the Pacific Mini Games in 2017 and China-ASEAN International Capacity Cooperation Forum in 2016.The data was collected by the methods of participant observation and informal interviews in the process of the two interpreting projects,especially the six-month assistance project.The ethical problems in the escort interpreting and the reasons that caused the problems were analyzed through case study.It is found that the major ethical problems that occurred are related to the ethics of communication,the norm-based ethics,and the ethics of commitment.These ethical problems were mainly related to the student escort interpreters’language proficiency,professional qualities,and intercultural/interpersonal communication competence.Some solutions are suggested based on Chesterman’s models on translation ethics.It is hoped that the research findings can provide some references to the implementation of the similar interpreting programs in the future,and enhance interpreting teaching and training programs.

Natural Frequency of Planetary Transmission with Thin-Walled Ring Gear on Elastic Supports

A lumped parameter-rigid elastic coupled dynamic model of two-stage planetary gears for a hybrid car is established through the inter-stage coupled method,in which the supports of the ring gear of planet set Ⅱ are represented as an elastic foundation with radial and tangential uniform distributed stiffness,and the ring gear of planet set Ⅱ is modeled as an elastic continuum body. The natural frequencies based on the eigenvalue problem of dynamic model of planetary transmission are solved and the associated vibration modes are discussed. The rules are revealed which are the influences of the ring gear elastic supports stiffness and rim thickness on natural frequencies of planetary transmission. The theoretical analysis indicates that the vibration modes of planetary transmission with thin-walled ring gear on elastic supports are classified into seven types: Ⅰ/Ⅱ stage coupled rotational mode,Ⅰ stage translational mode,Ⅰ stage planet mode,Ⅱ stage translational mode,Ⅱ stage degenerate planet mode,Ⅱ stage distinct planet mode and purely ring gear mode. For each vibration mode, its properties are summarized. The numerical solutions show that the elastic supports stiffness and rim thickness of the ring gear of planet set Ⅱ have different influences on natural frequencies.

Korean Morphological Analysis for Korean-Vietnamese Statistical Machine Translation

This paper describes the experiments with Korean-to-Vietnamese statistical machine translation(SMT). The fact that Korean is a morphologically complex language that does not have clear optimal word boundaries causes a major problem of translating into or from Korean. To solve this problem, we present a method to conduct a Korean morphological analysis by using a pre-analyzed partial word-phrase dictionary(PWD).Besides, we build a Korean-Vietnamese parallel corpus for training SMT models by collecting text from multilingual magazines. Then, we apply such a morphology analysis to Korean sentences that are included in the collected parallel corpus as a preprocessing step. The experiment results demonstrate a remarkable improvement of Korean-to-Vietnamese translation quality in term of bi-lingual evaluation understudy(BLEU).

Raising International Discourse Rights in Translation and Interpreting Pedagogy

This research project aims at consolidating and revitalizing translation and interpreting pedagogy with dual emphasis on the cultural soft power and international discourse rights of China via emphasizing international competitiveness.In order to realize the significant needs of the current market requirements and the new era of China,this project proposes the“ICC”interpreting training model.It refers to the combination of intercultural communication competency with international competitiveness as the teaching and learning outcomes by means of integrating the following five components in the course content and the whole curriculum design:(1)interpreting competency-bilingual competence and interpreting skill-based training;e.g.,short-term memory and note-taking;(2)national value-strengthening translation and the crucial roles and responsibilities of interpreter trainers and trainees in disseminating national culture;(3)expertise of subject matters-equipping students with expertise for work field and meeting the market requirements;e.g.,specific professional knowledge and jargons demanded by the tasks;(4)professional ethics and image-extra-linguistic knowledge emphasizing a translator’s and an interpreter’s professional code of conduct and ethics in a way that can establish the“iconic”image of a professional interpreter;e.g.,confidentiality,posture,and appearance;(5)practical assessment-evaluation of students’performance in practical translation and interpreting opportunities and/or internship in organizations of various natures according to international standards.This research proposes a new training model to incorporate intercultural communication competency with international competitiveness.The significant role of interpreting pedagogy in contributing to a sound national name is investigated.The new“ICC”model that this research is proposing answers such a call for the significant role of raising cultural soft power and international discourse rights in China.

English-Chinese Neural Machine Translation Based on Self-organizing Mapping Neural Network and Deep Feature Matching

The traditional Chinese-English translation model tends to translate some source words repeatedly,while mistakenly ignoring some words.Therefore,we propose a novel English-Chinese neural machine translation based on self-organizing mapping neural network and deep feature matching.In this model,word vector,two-way LSTM,2D neural network and other deep learning models are used to extract the semantic matching features of question-answer pairs.Self-organizing mapping(SOM)is used to classify and identify the sentence feature.The attention mechanism-based neural machine translation model is taken as the baseline system.The experimental results show that this framework significantly improves the adequacy of English-Chinese machine translation and achieves better results than the traditional attention mechanism-based English-Chinese machine translation model.

DYNAMIC MODEL OF TRANSLATION PHASE

In order to elucidate the origin of biological ordering structure, which is far from equi-librum and continuously exchanges substances with its environment, I. Prigogine advancedthe theory of dissipative structure and discussed the formation of this structure in a dynamicsystem. Xu Jinghua and Ding Dafu also presented a model of dissipative structure of DNAtemplate replication and obtained an interesting result of helix structure. In this paper we pre-sent a dynamic model. of protein synthesis and consider possible influences of position-controlfactors in oosperm, attempting to obtain some ideas about the primary cause of morphodif-ferentiation.

Deep transfer network of heterogeneous domain feature in machine translation

In order to address the shortcoming of feature representation limitation in machine translation(MT)system,this paper presents a feature transfer method in MT.Meta feature transfer of the decoding process considered not only their own translation system,but also transferred knowledge of another translation system.The domain meta feature and the objective function of domain adaptation are used to better model the domain transfer task.In this paper,extensive experiments and comparisons are made.The experiment results show that the proposed model has a significant improvement in domain transfer task.The first model has better performance than baseline system,which improves 3.06 BLEU score on the news test set,improves 3.27 BLEU score on the education test set,and improves 3.93 BLEU score on the law test set;The second model improves 3.16 BLEU score on the news test set,improves 3.54 BLEU score on the education test set,and improves 4.2 BLEU score on the law test set.