Foregrounding Theory in Novel Translation: A Case Study of the Translation of The Journey to the West

Foregrounding is a symbolic feature of the language forms of literature. It is interconnected with the theme and aesthetic value of literary works. With the case study of The Journey to the West translated by Anthony C. Yu, the thesis makes an analysis of its foregrounding language from five major aspects of foregrounding phenomena, namely, lexical deviation, phonological deviation, grammatical deviation, graphological deviation and semantic deviation. It is hoped that this study could demonstrate the implication and significance of foregrounding theory to novel translation.

Comparative Analysis of the Two English Versions of Qiangjinjiu Based on Translation Aesthetics

Poetry is the creation of beauty and thus aesthetics is an important translation criterion for poetry. By fully understanding the two English translated versions of Qiangjinjiu respectively by Xu Yuanchong and Burton Watson, the thesis will make a comparative analysis of the two versions from the perspective of translation aesthetics. In order to better illustrate the connotation of poetry translation and translation aesthetics, the essay will mainly compare the poetic representation of the two English versions from the aspects of rhythm, form, image, culture and content, targeting to present the differences between the two English versions and offer some suggestions on poetry translation.

Translation of Classics by JX Native Literati of Song Dynasty under Foregrounding Theory

As a symbolic feature of the language forms of literature, foregrounding is closely connected with the theme and aesthetic value of literary works. Through an analysis of some classics by Jiangxi native literati in Song Dynasty, the thesis focuses on the significance of foregrounding theory to literary translation or even to general translation. With a case study of the classics from four aspects of foregrounding theory, namely, phonological deviation, lexical deviation, semantic deviation and graphological deviation, the research would illustrate foregrounding language in literature and its applicability to classics translation in detail

Using multitask classification methods to investigate the kinase-specific phosphorylation sites

<p>Abstract</p> <p>Background</p> <p>Identification of phosphorylation sites by computational methods is becoming increasingly important because it reduces labor-intensive and costly experiments and can improve our understanding of the common properties and underlying mechanisms of protein phosphorylation.</p> <p>Methods</p> <p>A multitask learning framework for learning four kinase families simultaneously, instead of studying each kinase family of phosphorylation sites separately, is presented in the study. The framework includes two multitask classification methods: the Multi-Task Least Squares Support Vector Machines (MTLS-SVMs) and the Multi-Task Feature Selection (MT-Feat3).</p> <p>Results</p> <p>Using the multitask learning framework, we successfully identify 18 common features shared by four kinase families of phosphorylation sites. The reliability of selected features is demonstrated by the consistent performance in two multi-task learning methods.</p> <p>Conclusions</p> <p>The selected features can be used to build efficient multitask classifiers with good performance, suggesting they are important to protein phosphorylation across 4 kinase families.</p

Passenger Queuing Analysis Method of Security Inspection and Ticket-Checking Area without Archway Metal Detector in Metro Stations

In order to avoid the congestion in front of the entrance gate units, it is necessary to analyse and optimise the queuing situation at the planning and design stage. The security inspection area and the ticket-checking area were jointly considered, and a queuing congestion analysis method was proposed. Firstly, the research problem was stated. Then, the problem of calculating the number of passengers in each subarea at any time was transformed into the problem of calculating the transit time of each passenger in each subarea. The transit time was divided into basic transit time and additional transit time. Based on the velocity-density relationship, a quantisation method for basic transit time was proposed related to passenger arrival time. The additional transit time was determined by the moment when the passengers left the subarea according to the sequence of arrival of passengers, the number of queuing passengers in the subarea and the congestion of the subarea to be entered. Finally, the queuing situation of passengers in each subarea at any moment was obtained through passenger flow recursion. Examples showed that the proposed method can deal with multiple working conditions and avoid the tedious and time-consuming scene construction process of the microsimulation software

Soft Actor-Critic Learning-Based Joint Computing, Pushing, and Caching Framework in MEC Networks

To support future 6G mobile applications, the mobile edge computing (MEC) network needs to be jointly optimized for computing, pushing, and caching to reduce transmission load and computation cost. To achieve this, we propose a framework based on deep reinforcement learning that enables the dynamic orchestration of these three activities for the MEC network. The framework can implicitly predict user future requests using deep networks and push or cache the appropriate content to enhance performance. To address the curse of dimensionality resulting from considering three activities collectively, we adopt the soft actor-critic reinforcement learning in continuous space and design the action quantization and correction specifically to fit the discrete optimization problem. We conduct simulations in a single-user single-server MEC network setting and demonstrate that the proposed framework effectively decreases both transmission load and computing cost under various configurations of cache size and tolerable service delay

Solar UV Radiation Drives CO 2 Fixation in Marine Phytoplankton: A Double-Edged Sword

Photosynthesis by phytoplankton cells in aquatic environmentscontributes to more than 40% of the globalprimary production (Behrenfeld et al., 2006). Withinthe euphotic zone (down to 1% of surface photosyntheticallyactive radiation [PAR]), cells are exposed notonly to PAR (400–700 nm) but also to UV radiation(UVR; 280–400 nm) that can penetrate to considerabledepths (Hargreaves, 2003). In contrast to PAR, which isenergizing to photosynthesis, UVR is usually regardedas a stressor (Ha¨der, 2003) and suggested to affect CO2-concentrating mechanisms in phytoplankton (Beardallet al., 2002). Solar UVR is known to reduce photosyntheticrates (Steemann Nielsen, 1964; Helbling et al.,2003), and damage cellular components such as D1proteins (Sass et al., 1997) and DNA molecules (Bumaet al., 2003). It can also decrease the growth (Villafan˜ eet al., 2003) and alter the rate of nutrient uptake(Fauchot et al., 2000) and the fatty acid composition(Goes et al., 1994) of phytoplankton. Recently, it hasbeen found that natural levels of UVR can alter themorphology of the cyanobacterium Arthrospira (Spirulina)platensis (Wu et al., 2005b).On the other hand, positive effects of UVR, especiallyof UV-A (315–400 nm), have also been reported.UV-A enhances carbon fixation of phytoplankton underreduced (Nilawati et al., 1997; Barbieri et al., 2002)or fast-fluctuating (Helbling et al., 2003) solar irradianceand allows photorepair of UV-B-induced DNAdamage (Buma et al., 2003). Furthermore, the presenceof UV-A resulted in higher biomass production of A.platensis as compared to that under PAR alone (Wuet al., 2005a). Energy of UVR absorbed by the diatomPseudo-nitzschia multiseries was found to cause fluorescence(Orellana et al., 2004). In addition, fluorescentpigments in corals and their algal symbiont are knownto absorb UVR and play positive roles for the symbioticphotosynthesis and photoprotection (Schlichter et al.,1986; Salih et al., 2000). However, despite the positiveeffects that solar UVR may have on aquatic photosyntheticorganisms, there is no direct evidence to whatextent and howUVR per se is utilized by phytoplankton.In addition, estimations of aquatic biological productionhave been carried out in incubations consideringonly PAR (i.e. using UV-opaque vials made of glass orpolycarbonate; Donk et al., 2001) without UVR beingconsidered (Hein and Sand-Jensen, 1997; Schippersand Lu¨ rling, 2004). Here, we have found that UVR canact as an additional source of energy for photosynthesisin tropical marine phytoplankton, though it occasionallycauses photoinhibition at high PAR levels. WhileUVR is usually thought of as damaging, our resultsindicate that UVR can enhance primary production ofphytoplankton. Therefore, oceanic carbon fixation estimatesmay be underestimated by a large percentageif UVR is not taken into account.Fil: Gao, Kunshan. Shantou University; ChinaFil: Wu, Yaping. Xiamen University; ChinaFil: Villafañe, Virginia Estela. Fundación Playa Unión. Estación de Fotobiología Playa Unión; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Helbling, Eduardo Walter. Fundación Playa Unión. Estación de Fotobiología Playa Unión; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Identification of Properties Important to Protein Aggregation Using Feature Selection

Background: Protein aggregation is a significant problem in the biopharmaceutical industry (protein drug stability) and is associated medically with over 40 human diseases. Although a number of computational models have been developed for predicting aggregation propensity and identifying aggregation-prone regions in proteins, little systematic research has been done to determine physicochemical properties relevant to aggregation and their relative importance to this important process. Such studies may result in not only accurately predicting peptide aggregation propensities and identifying aggregation prone regions in proteins, but also aid in discovering additional underlying mechanisms governing this process. Results: We use two feature selection algorithms to identify 16 features, out of a total of 560 physicochemical properties, presumably important to protein aggregation. Two predictors (ProA-SVM and ProA-RF) using selected features are built for predicting peptide aggregation propensity and identifying aggregation prone regions in proteins. Both methods are compared favourably to other state-of-the-art algorithms in cross validation. The identified important properties are fairly consistent with previous studies and bring some new insights into protein and peptide aggregation. One interesting new finding is that aggregation prone peptide sequences have similar properties to signal peptide and signal anchor sequences. Conclusions: Both predictors are implemented in a freely available web application (http://www.abl.ku.edu/ProA/ webcite). We suggest that the quaternary structure of protein aggregates, especially soluble oligomers, may allow the formation of new molecular recognition signals that guide aggregate targeting to specific cellular sites

Two stage Robust Nash Bargaining based Benefit Sharing between Electric and HCNG Distribution Networks Bridged with SOFC

Hydrogen-enriched compressed natural gas (HCNG) networks have potentized sustainability and efficiency of integrated electricity and natural gas systems. However, paucity of benefit sharing risks the IENGS's development in multiple entities and bottlenecks its efficacy. To fill the gap, a robust Nash bargaining-based benefit sharing mechanism for HCNG-enabled IENGS is proposed

Characterizing Immunoglobulin Repertoire from Whole Blood by a Personal Genome Sequencer

In human immune system, V(D)J recombination produces an enormously large repertoire of immunoglobulins (Ig) so that they can tackle different antigens from bacteria, viruses and tumor cells. Several studies have demonstrated the utility of next-generation sequencers such as Roche 454 and Illumina Genome Analyzer to characterize the repertoire of immunoglobulins. However, these techniques typically require separation of B cell population from whole blood and require a few weeks for running the sequencers, so it may not be practical to implement them in clinical settings. Recently, the Ion Torrent personal genome sequencer has emerged as a tabletop personal genome sequencer that can be operated in a time-efficient and cost-effective manner. In this study, we explored the technical feasibility to use multiplex PCR for amplifying V(D)J recombination for IgH, directly from whole blood, then sequence the amplicons by the Ion Torrent sequencer. The whole process including data generation and analysis can be completed in one day. We tested the method in a pilot study on patients with benign, atypical and malignant meningiomas. Despite the noisy data, we were able to compare the samples by their usage frequencies of the V segment, as well as their somatic hypermutation rates. In summary, our study suggested that it is technically feasible to perform clinical monitoring of V(D)J recombination within a day by personal genome sequencers