scholarly journals Meaningful Translation and Transliteration for Marathi Language

2021 ◽  
pp. 111-114
Author(s):  
Mahendra Prabhakar Shinde
Keyword(s):  
Language Translation ◽  
Morphological Structure ◽  
Human Memory ◽  
Multiple Use ◽  
Single Word ◽  
Neuron Network ◽  
Novel Approach ◽  
Complete Translation ◽  
Np Problem ◽  
Correct Translation

Meaningful translation and transliteration is NP problem in case of languages like Marathi language as there are so many word disambiguation and multiple use and meaning of single word in different context is available. That is why identifying correct informational need and translating text into meaningful information is a tedious and error prone task. Google translate works on machine neuron network and WorldNet is an online reference system works on psycholinguistic theory of human memory. Both approaches are promising tools for language translation. Complete translation of Marathi text to English or English to Marathi also having problem of more complicated meaningless or tedious translation. Proposed algorithm is taking into consideration meaningful translation or transliteration as per user’s informational need. This novel approach consider machine neuron network for meaningful formation of translated sentence and morphological structure for correct translation of word based on ontological analysis of word.

TRANSLATION TECHNIQUES OF STYLISTIC PHENOMENA IN A TV INTERVIEWER’S SPEECH

2020 ◽  
Vol 2020 (31) ◽  
pp. 312-327
Author(s):  
Olexandra Popova ◽  
Oleg Bolgar ◽  
Tomashevska Anastasiia
Keyword(s):  
Foreign Language ◽  
Native Language ◽  
Language Translation ◽  
Speech Segment ◽  
Pragmatic Function ◽  
Conversational Style ◽  
Translation Techniques ◽  
Television Interview ◽  
Linguistic Units ◽  
Correct Translation

The work is devoted to the study of translation peculiarities of stylistic features of a TV interviewer’s English speech into Ukrainian. The correct translation of the content of a speech segment requires good knowledge of vocabulary, and the capability to recognize the stylistic features of a foreign language in communication, and the techniques used to translate them into the native language. Translation of metaphors, metonymy, comparisons is of particular difficulty for the translator, however, it is the ability to use various techniques in translation that helps the translator to convey the meaning of the statement to the listener adequately. The television interview is characterized as an independent journalistic genre, is a kind of television communication, a purposeful individual-social speech phenomenon, which consists of the organized interaction detween the speakers and finds its expression in a specific dialogically constructed form. The results of this study show that each translated stylistic unit is characterized by a set of transformations typical for it. In most cases, these transformations involve lexical and syntactic stylistic devices. At the level of vocabulary, the speech of a TV interviewer is characterized by a significant number of colloquialisms, colloquial cliches, phraseological units. At the level of syntax, the typical indicators of the conversational style of the TV nterviewer are parallel constructions, repeated requests, elliptical sentences, repetitions, unfinished phrases, and the absence of inversion in interrogative sentences. The information obtained as the result of convergence of stylistic devices as a set of components participating together with other linguistic units in the formation of expressiveness, emotiveness and evaluation is one of the important sources of the language pragmatic function.

scholarly journals Novel in vitro booster vaccination to rapidly generate antigen-specific human monoclonal antibodies

2017 ◽  
Vol 214 (8) ◽  
pp. 2471-2490 ◽  
Author(s):  
Irene Sanjuan Nandin ◽  
Carol Fong ◽  
Cecilia Deantonio ◽  
Juan A. Torreno-Pina ◽  
Simone Pecetta ◽  
...  
Keyword(s):  
B Cells ◽  
Plasma Cells ◽  
Vaccine Development ◽  
Influenza Infection ◽  
Booster Vaccination ◽  
Human Memory ◽  
Influenza Hemagglutinin ◽  
Novel Approach ◽  
Antigenic Exposure

Vaccines remain the most effective tool to prevent infectious diseases. Here, we introduce an in vitro booster vaccination approach that relies on antigen-dependent activation of human memory B cells in culture. This stimulation induces antigen-specific B cell proliferation, differentiation of B cells into plasma cells, and robust antibody secretion after a few days of culture. We validated this strategy using cells from healthy donors to retrieve human antibodies against tetanus toxoid and influenza hemagglutinin (HA) from H1N1 and newly emergent subtypes such as H5N1 and H7N9. Anti-HA antibodies were cross-reactive against multiple subtypes, and some showed neutralizing activity. Although these antibodies may have arisen as a result of previous influenza infection, we also obtained gp120-reactive antibodies from non–HIV-infected donors, indicating that we can generate antibodies without prior antigenic exposure. Overall, our novel approach can be used to rapidly produce therapeutic antibodies and has the potential to assess the immunogenicity of candidate antigens, which could be exploited in future vaccine development.

scholarly journals Abduction by Non-Experts

10.29007/pz3t ◽  
2018 ◽  
Author(s):  
Nikolaj Bjorner ◽  
Dejan Jovanović ◽  
Tancrède Lepoint ◽  
Philipp Rümmer ◽  
Martin Schäf
Keyword(s):  
Natural Language ◽  
Software Verification ◽  
Language Translation ◽  
Horn Clause ◽  
Large Problem ◽  
Horn Clauses ◽  
Success Stories ◽  
Novel Approach ◽  
Verification Process ◽  
Problem Instances

Crowdsourcing promises to quasi-automate tasks that cannot be automated otherwise. Success stories like natural language translation or recognition of cats in images show that carefully crafted crowdsourcing tasks solve large problem instances which could not be solved otherwise. To utilize crowdsourcing, one has to define the problem in a way that is easy to split into small tasks, that the tasks are easy to solve for humans and hard to solve for a machine, and that the machine can efficiently check if the solution is correct.In this paper we discuss a novel approach of using crowdsourcing to assist software verification. We argue that Horn clauses form a good base for crowdsourcing since they are easy to subdivide, and that logic abduction is a suitable task since it is hard to find abductive inferences for Horn clauses automatically, but it is easy to check if an inference makes a Horn clause valid. We describe a prototype implementation, we show how crowdsourcing integrates in the verification process, and present preliminary results.

scholarly journals Verbose exponence: integrating the typologies of distributed and multiple exponence

2021 ◽  
Author(s):  
Matthew J Carroll
Keyword(s):  
Common Ground ◽  
Morphological Structure ◽  
Single Word ◽  
Common Information ◽  
Formal Definitions ◽  
The Common ◽  
Precise Interpretation

Multiple exponence is the multiple marking of the same feature or category within a single word. Distributed exponence is the occurrence of morphological structure such that providing a precise interpretation of a category can only be determined after considering more than one morphological formative. I propose the term verbose exponence to capture the common ground between these phenomena, i.e. all situations involving multiple morphological formatives sensitive to some common information. From this definition, a typology based on informational overlap emerges with types of verbose exponence corresponding to types of set interactions. The typology incorporates known related phenomena, such as overlapping exponence, while providing a sophisticated framework for describing previously unnamed phenomena. This typology is naturally cast in set-theoretic terms and formal definitions are provided for all assumptions and points in the typology. Such an approach provides precise articulations of the typological space but also of morphological redundancy, a property often associated with multiple exponence.

Forward Reaction Prediction as Reverse Verification: A Novel Approach to Retrosynthesis

2020 ◽  
Author(s):  
Ling Wang ◽  
Chengyun Zhang ◽  
Renren Bai ◽  
Jianjun Li ◽  
Hongliang Duan
Keyword(s):  
Language Translation ◽  
Human Language ◽  
Synthetic Route ◽  
Intuitive Knowledge ◽  
Forward Reaction ◽  
Combined Model ◽  
Reaction Prediction ◽  
Novel Approach ◽  
Model Approach

Pupils' intuitive knowledge can lead them to verify multiplication by means of division. Based on this analogy, this study introduces the basic reverse verification concept to verify retrosynthesis through forward reaction. In this work, we present a "combined" model approach for retrosynthetic reaction prediction, where the first model is applied to retrosynthesis, and the second model, which is a "verified" model, is applied to the forward reaction prediction to verify the top-n reactants predicted by the retrosynthetic model. Using a "combined" model borrowed from human language translation, sequence-to-sequence (seq2seq) + transformer models, we improve the top-1 accuracy of retrosynthetic prediction by 4.3% (37.4% vs 41.7%). The application of the similarity + seq2seq models increases the top-1 accuracy by 4.6% (52.9% vs 57.5%). In this way, we can not only improve the accuracy but also automate the evaluation of the synthetic route.

scholarly journals Exercise as a model to identify microRNAs linked to human cognition: a role for microRNA-409 and microRNA-501

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria Goldberg ◽  
Md Rezaul Islam ◽  
Cemil Kerimoglu ◽  
Camille Lancelin ◽  
Verena Gisa ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Memory Function ◽  
Human Memory ◽  
Experimental Manipulation ◽  
Model Systems ◽  
Human Cognition ◽  
Human Brain Tissue ◽  
Healthy Humans ◽  
Novel Approach ◽  
Highly Correlated

AbstractMicroRNAs have been linked to synaptic plasticity and memory function and are emerging as potential biomarkers and therapeutic targets for cognitive diseases. Most of these data stem from the analysis of model systems or postmortem tissue from patients which mainly represents an advanced stage of pathology. Due to the in-accessibility of human brain tissue upon experimental manipulation, it is still challenging to identify microRNAs relevant to human cognition, which is however a key step for future translational studies. Here, we employ exercise as an experimental model for memory enhancement in healthy humans with the aim to identify microRNAs linked to memory function. By analyzing the circulating smallRNAome we find a cluster of 18 microRNAs that are highly correlated to cognition. MicroRNA-409-5p and microRNA-501-3p were the most significantly regulated candidates. Functional analysis revealed that the two microRNAs are important for neuronal integrity, synaptic plasticity, and morphology. In conclusion, we provide a novel approach to identify microRNAs linked to human memory function.

Forward Reaction Prediction as Reverse Verification: A Novel Approach to Retrosynthesis

2020 ◽  
Author(s):  
Ling Wang ◽  
Chengyun Zhang ◽  
Renren Bai ◽  
Jianjun Li ◽  
Hongliang Duan
Keyword(s):  
Language Translation ◽  
Human Language ◽  
Synthetic Route ◽  
Intuitive Knowledge ◽  
Forward Reaction ◽  
Combined Model ◽  
Reaction Prediction ◽  
Novel Approach ◽  
Model Approach

Pupils' intuitive knowledge can lead them to verify multiplication by means of division. Based on this analogy, this study introduces the basic reverse verification concept to verify retrosynthesis through forward reaction. In this work, we present a "combined" model approach for retrosynthetic reaction prediction, where the first model is applied to retrosynthesis, and the second model, which is a "verified" model, is applied to the forward reaction prediction to verify the top-n reactants predicted by the retrosynthetic model. Using a "combined" model borrowed from human language translation, sequence-to-sequence (seq2seq) + transformer models, we improve the top-1 accuracy of retrosynthetic prediction by 4.3% (37.4% vs 41.7%). The application of the similarity + seq2seq models increases the top-1 accuracy by 4.6% (52.9% vs 57.5%). In this way, we can not only improve the accuracy but also automate the evaluation of the synthetic route.

Priming and persistence in bilinguals: What codeswitching tells us about lexical priming in sentential contexts*

2021 ◽  
pp. 1-13
Author(s):  
Michael A. Johns ◽  
Laura Rodrigo ◽  
Rosa E. Guzzardo Tamargo ◽  
Aliza Winneg ◽  
Paola E. Dussias
Keyword(s):  
Language Translation ◽  
Spreading Activation ◽  
Single Word ◽  
Lexical Priming ◽  
Language Identity ◽  
Word Level ◽  
Translation Priming ◽  
Speech Corpora ◽  
Identity Priming ◽  
Do So

Abstract Most studies on lexical priming have examined single words presented in isolation, despite language users rarely encountering words in such cases. The present study builds upon this by examining both within-language identity priming and across-language translation priming in sentential contexts. Highly proficient Spanish–English bilinguals read sentence-question pairs, where the sentence contained the prime and the question contained the target. At earlier stages of processing, we find evidence only of within-language identity priming; at later stages of processing, however, across-language translation priming surfaces, and becomes as strong as within-language identity priming. Increasing the time between the prime sentence and target question results in strengthened priming at the latest stages of processing. These results replicate previous findings at the single-word level but do so within sentential contexts, which has implications both for accounts of priming via automatic spreading activation as well as for accounts of persistence attested in spontaneous speech corpora.

High-resolution topographic SEM and radiation damage: The rationale for using low beam voltage

1992 ◽  
Vol 50 (2) ◽  
pp. 1278-1279
Author(s):  
James Pawley ◽  
David Joy
Keyword(s):  
High Resolution ◽  
Imaging Techniques ◽  
Morphological Structure ◽  
Radiation Sensitivity ◽  
Beam Specimen ◽  
Measured Signal ◽  
Practical Consideration ◽  
Interaction Volume ◽  
Impact Area ◽  
Signal Contrast

The scanning electron microscope (SEM) builds up an image by sampling contiguous sub-volumes near the surface of the specimen. A fine electron beam selectively excites each sub-volume and then the intensity of some resulting signal is measured and then plotted as a corresponding intensity in an image. The spatial resolution of such an image is limited by at least three factors. Two of these determine the size of the interaction volume: the size of the electron probe and the extent to which detectable signal is excited from locations remote from the beam impact area. A third limitation emerges from the fact that the probing beam is composed of a number of discrete particles and therefore that the accuracy with which any detectable signal can be measured is limited by Poisson statistics applied to this number (or to the number of events actually detected if this is smaller). As in all imaging techniques, the limiting signal contrast required to recognize a morphological structure is constrained by this statistical consideration. The only way to overcome this limit is to increase either the contrast of the measured signal or the number of beam/specimen interactions detected. Unfortunately, these interactions deposit ionizing radiation that may damage the very structure under investigation. As a result, any practical consideration of the high resolution performance of the SEM must consider not only the size of the interaction volume but also the contrast available from the signal producing the image and the radiation sensitivity of the specimen.

Copper-dependent ATP7B up-regulation drives the resistance of TMEM16A-overexpressing head-and-neck cancer models to platinum toxicity

2019 ◽  
Vol 476 (24) ◽  
pp. 3705-3719 ◽  
Author(s):  
Avani Vyas ◽  
Umamaheswar Duvvuri ◽  
Kirill Kiselyov
Keyword(s):  
Oxidative Stress ◽  
Head And Neck ◽  
Transcriptional Activation ◽  
Platinum Resistance ◽  
Mrna Levels ◽  
Strong Positive Correlation ◽  
Platinum Compounds ◽  
Copper Chelation ◽  
Novel Approach ◽  
Cancer Models

Platinum-containing drugs such as cisplatin and carboplatin are routinely used for the treatment of many solid tumors including squamous cell carcinoma of the head and neck (SCCHN). However, SCCHN resistance to platinum compounds is well documented. The resistance to platinum has been linked to the activity of divalent transporter ATP7B, which pumps platinum from the cytoplasm into lysosomes, decreasing its concentration in the cytoplasm. Several cancer models show increased expression of ATP7B; however, the reason for such an increase is not known. Here we show a strong positive correlation between mRNA levels of TMEM16A and ATP7B in human SCCHN tumors. TMEM16A overexpression and depletion in SCCHN cell lines caused parallel changes in the ATP7B mRNA levels. The ATP7B increase in TMEM16A-overexpressing cells was reversed by suppression of NADPH oxidase 2 (NOX2), by the antioxidant N-Acetyl-Cysteine (NAC) and by copper chelation using cuprizone and bathocuproine sulphonate (BCS). Pretreatment with either chelator significantly increased cisplatin's sensitivity, particularly in the context of TMEM16A overexpression. We propose that increased oxidative stress in TMEM16A-overexpressing cells liberates the chelated copper in the cytoplasm, leading to the transcriptional activation of ATP7B expression. This, in turn, decreases the efficacy of platinum compounds by promoting their vesicular sequestration. We think that such a new explanation of the mechanism of SCCHN tumors’ platinum resistance identifies novel approach to treating these tumors.

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