Cross-lingual Text Reuse Detection Using Translation Plus Monolingual Analysis for English-Urdu Language Pair

Cross-Lingual Text Reuse Detection (CLTRD) has recently attracted the attention of the research community due to a large amount of digital text readily available for reuse in multiple languages through online digital repositories. In addition, efficient machine translation systems are freely and readily available to translate text from one language into another, which makes it quite easy to reuse text across languages, and consequently difficult to detect it. In the literature, the most prominent and widely used approach for CLTRD is Translation plus Monolingual Analysis (T+MA). To detect CLTR for English-Urdu language pair, T+MA has been used with lexical approaches, namely, N-gram Overlap, Longest Common Subsequence, and Greedy String Tiling. This clearly shows that T+MA has not been thoroughly explored for the English-Urdu language pair. To fulfill this gap, this study presents an in-depth and detailed comparison of 26 approaches that are based on T+MA. These approaches include semantic similarity approaches (semantic tagger based approaches, WordNet-based approaches), probabilistic approach (Kullback-Leibler distance approach), monolingual word embedding-based approaches siamese recurrent architecture, and monolingual sentence transformer-based approaches for English-Urdu language pair. The evaluation was carried out using the CLEU benchmark corpus, both for the binary and the ternary classification tasks. Our extensive experimentation shows that our proposed approach that is a combination of 26 approaches obtained an F 1 score of 0.77 and 0.61 for the binary and ternary classification tasks, respectively, and outperformed the previously reported approaches [ 41 ] ( F 1 = 0.73) for the binary and ( F 1 = 0.55) for the ternary classification tasks) on the CLEU corpus.

Towards a generic prototyping approach for therapeutically-relevant peptides and proteins in a cell-free translation system

Advances in peptide and protein therapeutics increased the need for rapid and cost-effective polypeptide prototyping. While in vitro translation systems are well suited for fast and multiplexed polypeptide prototyping, they suffer from misfolding, aggregation and disulfide-bond scrambling of the translated products. Here we propose that efficient folding of in vitro produced disulfide-rich peptides and proteins can be achieved if performed in an aggregation-free and thermodynamically controlled folding environment. To this end, we modify an E. coli-based in vitro translation system to allow co-translational capture of translated products by affinity matrix. This process reduces protein aggregation and enables productive oxidative folding and recycling of misfolded states under thermodynamic control. In this study we show that the developed approach is likely to be generally applicable for prototyping of a wide variety of disulfide-constrained peptides, macrocyclic peptides with non-native bonds and antibody fragments in amounts sufficient for interaction analysis and biological activity assessment.

Chloroplast-localized translation for protein targeting in Chlamydomonas reinhardtii

Translation is localized within cells to target proteins to their proper locations. We asked whether translation occurs on the chloroplast surface in Chlamydomonas and, if so, whether it is involved in co-translational protein targeting, aligned spatially with localized translation by the bacterial-type ribosomes within this organelle, or both. Our results reveal a domain of the chloroplast envelope which is bound by translating ribosomes. Purified chloroplasts retained ribosomes and mRNAs encoding two chloroplast proteins specifically on this translation domain, but not a mRNA encoding a cytoplasmic protein. Ribosomes clusters were seen on this domain by electron tomography. Activity of the chloroplast-bound ribosomes is supported by results of the ribopuromycylation and puromycin-release assays. Co-translational chloroplast protein import is supported by nascent polypeptide dependency of the ribosome-chloroplast associations. This cytoplasmic translation domain aligns localized translation by organellar bacterial-type ribosomes in the chloroplast. This juxtaposition the dual translation systems facilitates the targeting and assembly of the polypeptide products.

Errors in machine translation from German into Russian (based on articles of German-language media and their translations)

The article is devoted to the study of errors and inaccuracies made by machine translation systems. The reasons for the appearance of errors of various types in the texts of machine translations of German-language articles of well-known mass media into Russian, made by popular translation programs, are analyzed. A classification of errors is given. The lexical-semantic and lexical-stylistic, normative-usual, grammatical, punctuation and spelling errors are highlighted. Typical “weaknesses” of machine translation from German into Russian are revealed, which should be paid attention to during post-editing of the text of such a translation. It is pointed out that the analysis of typical errors in automatic translation can also be taken into account in the process of improving the algorithm of their work by the developers of machine translation systems.

Directed-evolution of translation system for efficient unnatural amino acids incorporation and generalizable synthetic auxotroph construction

Site-specific incorporation of unnatural amino acids (UAAs) with similar incorporation efficiency to that of natural amino acids (NAAs) and low background activity is extremely valuable for efficient synthesis of proteins with diverse new chemical functions and design of various synthetic auxotrophs. However, such efficient translation systems remain largely unknown in the literature. Here, we describe engineered chimeric phenylalanine systems that dramatically increase the yield of proteins bearing UAAs, through systematic engineering of the aminoacyl-tRNA synthetase and its respective cognate tRNA. These engineered synthetase/tRNA pairs allow single-site and multi-site incorporation of UAAs with efficiencies similar to those of NAAs and high fidelity. In addition, using the evolved chimeric phenylalanine system, we construct a series of E. coli strains whose growth is strictly dependent on exogenously supplied of UAAs. We further show that synthetic auxotrophic cells can grow robustly in living mice when UAAs are supplemented.

AN ONLINE REPOSITORY OF PYTHON RESOURCE FOR TEACHING MACHINE TRANSLATION TO TRANSLATION STUDENTS

This paper presents an online repository of Python resources aimed at teaching the technical dimension of machine translation to students of translation studies programmes. The Python resources provided in this repository are Jupyter notebooks. These are web-based computational environments in which students can run commented blocks of code in order to perform MT-related tasks such as exploring word embeddings, preparing MT training data, training open-source machine translation systems or calculating automatic MT quality metrics such as BLEU, METEOR, BERTScore or COMET. The notebooks are prepared in such a way that students can interact with them even if they have had little to no prior exposure to the Python programming language. The notebooks are provided as open-source resources under the MIT License and can be used and modified by translator training institutions which intend to make their students familiar with the more technical aspects of modern machine translation technology. Institutions who would like to contribute their own Python-based teaching resources to the repository are welcome to do so. Keywords: translation technology, machine translation, natural language processing, translation didactics, Jupyter notebooks, Python programming

Efficient multi-gene expression in cell-free droplet microreactors

Cell-free transcription and translation systems promise to accelerate and simplify the engineering of proteins, biological circuits and metabolic pathways. Their encapsulation on microfluidic platforms can generate millions of cell-free reactions in picoliter volume droplets. However, current methods struggle to create DNA diversity between droplets while also reaching sufficient protein expression levels. In particular, efficient multi-gene expression has remained elusive. We here demonstrate that co-encapsulation of DNA-coated beads with a defined cell-free system allows high protein expression while also supporting genetic diversity between individual droplets. We optimize DNA loading on commercially available microbeads through direct binding as well as through the sequential coupling of up to three genes via a solid-phase Golden Gate assembly or BxB1 integrase-based recombineering. Encapsulation with an off-the-shelf microfluidics device allows for single or multiple protein expression from a single DNA-coated bead per 14 pL droplet. We envision that this approach will help to scale up and parallelize the rapid prototyping of more complex biological systems.

The challenges of machine translation of academic publications

Clear translation remains a major challenge to better communication and understanding of the international academic literature, despite advances in Machine Translation (MT). Automatic translation systems which captured the detail and the sense of any manuscript in any language for a reader from any other linguistic background would find global applications.In this article, we discuss the current opportunities and constraints to the wider use of machine translation and computer-assisted human translation (CAT). At the present stage of technology development, these instruments offer a number of advantages to specialists working with scientific texts. These include the facility to skim and scan large amounts of information in foreign languages, and to act as digital dictionaries, thesauri and encyclopedias. Word-to-word and phrase-to-phrase translation between many languages and scripts is now well advanced.The availability of modern machine translation has therefore changed the work of specialist scientific translators, placing greater emphasis on more advanced text and sense editing skills. However, machine translation is still challenged by the nuances of language and culture from one society to another, particularly in the freestyle literature of the arts and humanities. Scientific papers are generally much more structured, but the quality of machine translation still largely depends on the quality of the source text. This varies considerably between different scientific disciplines and from one author to another.The most advanced translation systems are making steady progress. It is timely to revisit traditional training programmes in the field of written translation to focus on the development of higher-level research competencies, such as terminology search, and so to make best use of evolving machine translation technologies.More widely, we consider that there is a challenge across the higher education systems in all countries to develop a simple, clear and consistent “international” writing style to assist fast, reliable and low-cost machine translation and hence to advance mutual understanding across the global scientific literature.

La constitución de una memoria terminológica: elaboración de terminologías bilingües en programas de memoria de traducción

Computer-aided translation systems (CAT) based on Translation Memories (TM) are a widely diffused technology that uses database and code-protection features to improve the quality, efficiency and consistency of the human translation process. These systems basically consist of a textual database in which each source sentence of a translation is stored together with the target sentence (this is called a translation memory “unit”). New and changed translation proposals will then be stored in the database for future use. This textual database – the kernel of the system – is combined with a terminological database (TDB), which is used by translators to store independently, terminological equivalences or translation units of particular value.In this paper the authors outline a first draft of a methodology that describes the preparation of a bilingual terminology from – and within – TM applications. The bilingual corpus produced is called the ‘terminological memory’ of the translator.