991 resultados para Translation model
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Mode of access: Internet.
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Objectives: This pilot study describes a modelling approach to translate group-level changes in health status into changes in preference values, by using the effect size (ES) to summarize group-level improvement. Methods: ESs are the standardized mean difference between treatment groups in standard deviation (SD) units. Vignettes depicting varying severity in SD decrements on the SF-12 mental health summary scale, with corresponding symptom severity profiles, were valued by a convenience sample of general practitioners (n = 42) using the rating scale (RS) and time trade-off methods. Translation factors between ES differences and change in preference value were developed for five mental disorders, such that ES from published meta-analyses could be transformed into predicted changes in preference values. Results: An ES difference in health status was associated with an average 0.171-0.204 difference in preference value using the RS, and 0.104-0.158 using the time trade off. Conclusions: This observed relationship may be particular to the specific versions of the measures employed in the present study. With further development using different raters and preference measures, this approach may expand the evidence base available for modelling preference change for economic analyses from existing data.
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The Symbolic Analysis Laboratory (SAL) is a suite of tools for analysis of state transition systems. Tools supported include a simulator and four temporal logic model checkers. The common input language to these tools was originally developed with translation from other languages, both programming and specification languages, in mind. It is, therefore, a rich language supporting a range of type definitions and expressions. In this paper, we investigate the translation of Z specifications into the SAL language as a means of providing model checking support for Z. This is facilitated by a library of SAL definitions encoding the Z mathematical toolkit.
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Eukaryotic translation elongation factor 3 (eEF3) is a fungal-specific ATPase proposed to catalyze the release of deacylated-tRNA from the ribosomal E-site. In addition, it has been shown to interact with the aminoacyl-tRNA binding GTPase elongation factor 1A (eEF1A), perhaps linking the E and A sites. Domain mapping demonstrates that amino acids 775-980 contain the eEF1A binding sites. Domain III of eEF1A, which is also involved in actin-related functions, is the site of eEF3 binding. The binding of eEF3 to eEF1A is enhanced by ADP, indicating the interaction is favored post-ATP hydrolysis but is not dependent on the eEF1A-bound nucleotide. A temperature-sensitive P915L mutant in the eEF1A binding site of eEF3 has reduced ATPase activity and affinity for eEF1A. These results support the model that upon ATP hydrolysis, eEF3 interacts with eEF1A to help catalyze the delivery of aminoacyl-tRNA at the A-site of the ribosome. The dynamics of when eEF3 interacts with eEF1A may be part of the signal for transition of the post to pre-translocational ribosomal state in yeast.
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This work explores the relevance of semantic and linguistic description to translation, theory and practice. It is aimed towards a practical model of approach to texts to translate. As literary texts [poetry mainly] are the focus of attention, so are stylistic matters. Note, however, that 'style', and, to some extent, the conclusions of the work, are not limited to so-called literary texts. The study of semantic description reveals that most translation problems do not stem from the cognitive (langue-related), but rather from the contextual (parole-related) aspects of meaning. Thus, any linguistic model that fails to account for the latter is bound to fall short. T.G.G. does, whereas Systemics, concerned with both the 'Iangue' and 'parole' (stylistic and sociolinguistic mainly) aspects of meaning, provides a useful framework of approach to texts to translate. Two essential semantic principles for translation are: that meaning is the property of a language (Firth); and the 'relativity of meaning assignments' (Tymoczko). Both imply that meaning can only be assessed, correctly, in the relevant socio-cultural background. Translation is seen as a restricted creation, and the translator's encroach as a three-dimensional critical one. To encompass the most technical to the most literary text, and account for variations in emphasis in any text, translation theory must be based on typology of function Halliday's ideational, interpersonal and textual, or, Buhler's symbol, signal, symptom, Functions3. Function Coverall and specific] will dictate aims and method, and also provide the critic with criteria to assess translation Faithfulness. Translation can never be reduced to purely objective methods, however. Intuitive procedures intervene, in textual interpretation and analysis, in the choice of equivalents, and in the reception of a translation. Ultimately, translation, theory and practice, may perhaps constitute the touchstone as regards the validity of linguistic and semantic theories.
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It has been widely recognised that an in-depth textual analysis of a source text is relevant for translation. This book discusses the role of discourse analysis for translation and translator training. One particular model of discourse analysis is presented in detail, and its application in the context of translator training is critically examined.
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The yeast Saccharomyces cerevisiae is an important model organism for the study of cell biology. The similarity between yeast and human genes and the conservation of fundamental pathways means it can be used to investigate characteristics of healthy and diseased cells throughout the lifespan. Yeast is an equally important biotechnological tool that has long been the organism of choice for the production of alcoholic beverages, bread and a large variety of industrial products. For example, yeast is used to manufacture biofuels, lubricants, detergents, industrial enzymes, food additives and pharmaceuticals such as anti-parasitics, anti-cancer compounds, hormones (including insulin), vaccines and nutraceuticals. Its function as a cell factory is possible because of the speed with which it can be grown to high cell yields, the knowledge that it is generally recognized as safe (GRAS) and the ease with which metabolism and cellular pathways, such as translation can be manipulated. In this thesis, these two pathways are explored in the context of their biotechnological application to ageing research: (i) understanding translational processes during the high-yielding production of membrane protein drug targets and (ii) the manipulation of yeast metabolism to study the molecule, L-carnosine, which has been proposed to have anti-ageing properties. In the first of these themes, the yeast strains, spt3?, srb5?, gcn5? and yTHCBMS1, were examined since they have been previously demonstrated to dramatically increase the yields of a target membrane protein (the aquaporin, Fps1) compared to wild-type cells. The mechanisms underlying this discovery were therefore investigated. All high yielding strains were shown to have an altered translational state (mostly characterised by an initiation block) and constitutive phosphorylation of the translational initiation factor, eIF2a. The relevance of the initiation block was further supported by the finding that other strains, with known initiation blocks, are also high yielding for Fps1. A correlation in all strains between increased Fps1 yields and increased production of the transcriptional activator protein, Gcn4, suggested that yields are subject to translational control. Analysis of the 5´ untranslated region (UTR) of FPS1 revealed two upstream open reading frames (uORFs). Mutagenesis data suggest that high yielding strains may circumvent these control elements through either a leaky scanning or a re-initiation mechanism. In the second theme, the dipeptide L-carnosine (ß-alanyl-L-histidine) was investigated: it has previously been shown to inhibit the growth of cancer cells but delay senescence in cultured human fibroblasts and extend the lifespan of male fruit flies. To understand these apparently contradictory properties, the effects of L-carnosine on yeast were studied. S. cerevisiae can respire aerobically when grown on a non-fermentable carbon source as a substrate but has a respiro-fermentative metabolism when grown on a fermentable carbon source; these metabolisms mimic normal cell and cancerous cell metabolisms, respectively. When yeast were grown on fermentable carbon sources, in the presence of L-carnosine, a reduction in cell growth and viability was observed, which was not apparent for cells grown on a non-fermentable carbon source. The metabolism-dependent mechanism was confirmed in the respiratory yeast species Pichia pastoris. Further analysis of S. cerevisiae yeast strains with deletions in their nutrient-sensing pathway, which result in an increase in respiratory metabolism, confirmed the metabolism-dependent effects of L-carnosine.
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The article presents an algorithm for translation the system, described by MSC document into Petri Net modulo strong bisimulation. Obtained net can be later used for determining various systems' properties. Example of correction error in original system with using if described algorithm presented.
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The paper presents a short review of some systems for program transformations performed on the basis of the internal intermediate representations of these programs. Many systems try to support several languages of representation of the source texts of programs and solve the task of their translation into the internal representation. This task is still a challenge as it is effort-consuming. To reduce the effort, different systems of translator construction, ready compilers with ready grammars of outside designers are used. Though this approach saves the effort, it has its drawbacks and constraints. The paper presents the general idea of using the mapping approach to solve the task within the framework of program transformations and overcome the disadvantages of the existing systems. The paper demonstrates a fragment of the ontology model of high-level languages mappings onto the single representation and gives the example of how the description of (a fragment) a particular mapping is represented in accordance with the ontology model.
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Тодор П. Чолаков, Димитър Й. Биров - Тази статия представя цялостен модел за автоматизиран реинженеринг на наследени системи. Тя описва в детайли процесите на превод на софтуера и на рефакторинг и степента, до която могат да се автоматизират тези процеси. По отношение на превода на код се представя модел за автоматизирано превеждане на код, съдържащ указатели и работа с адресна аритметика. Също така се дефинира рамка за процеса на реинженеринг и се набелязват възможности за по-нататъшно развитие на концепции, инструменти и алгоритми.
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English has been taught as a core and compulsory subject in China for decades. Recently, the demand for English in China has increased dramatically. China now has the world's largest English-learning population. The traditional English-teaching method cannot continue to be the only approach because it merely focuses on reading, grammar and translation, which cannot meet English learners and users' needs (i.e., communicative competence and skills in speaking and writing). ^ This study was conducted to investigate if the Picture-Word Inductive Model (PWIM), a new pedagogical method using pictures and inductive thinking, would benefit English learners in China in terms of potential higher output in speaking and writing. With the gauge of Cognitive Load Theory (CLT), specifically, its redundancy effect, I investigated whether processing words and a picture concurrently would present a cognitive overload for English learners in China. ^ I conducted a mixed methods research study. A quasi-experiment (pretest, intervention for seven weeks, and posttest) was conducted using 234 students in four groups in Lianyungang, China (58 fourth graders and 57 seventh graders as an experimental group with PWIM and 59 fourth graders and 60 seventh graders as a control group with the traditional method). No significant difference in the effects of PWIM was found on vocabulary acquisition based on grade levels. Observations, questionnaires with open-ended questions, and interviews were deployed to answer the three remaining research questions. A few students felt cognitively overloaded when they encountered too many writing samples, too many new words at one time, repeated words, mismatches between words and pictures, and so on. Many students listed and exemplified numerous strengths of PWIM, but a few mentioned weaknesses of PWIM. The students expressed the idea that PWIM had a positive effect on their English teaching. ^ As integrated inferences, qualitative findings were used to explain the quantitative results that there were no significant differences of the effects of the PWIM between the experimental and control groups in both grade levels, from four contextual aspects: time constraints on PWIM implementation, teachers' resistance, how to use PWIM and PWIM implemented in a classroom over 55 students.^
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English has been taught as a core and compulsory subject in China for decades. Recently, the demand for English in China has increased dramatically. China now has the world’s largest English-learning population. The traditional English-teaching method cannot continue to be the only approach because it merely focuses on reading, grammar and translation, which cannot meet English learners and users’ needs (i.e., communicative competence and skills in speaking and writing). This study was conducted to investigate if the Picture-Word Inductive Model (PWIM), a new pedagogical method using pictures and inductive thinking, would benefit English learners in China in terms of potential higher output in speaking and writing. With the gauge of Cognitive Load Theory (CLT), specifically, its redundancy effect, I investigated whether processing words and a picture concurrently would present a cognitive overload for English learners in China. I conducted a mixed methods research study. A quasi-experiment (pretest, intervention for seven weeks, and posttest) was conducted using 234 students in four groups in Lianyungang, China (58 fourth graders and 57 seventh graders as an experimental group with PWIM and 59 fourth graders and 60 seventh graders as a control group with the traditional method). No significant difference in the effects of PWIM was found on vocabulary acquisition based on grade levels. Observations, questionnaires with open-ended questions, and interviews were deployed to answer the three remaining research questions. A few students felt cognitively overloaded when they encountered too many writing samples, too many new words at one time, repeated words, mismatches between words and pictures, and so on. Many students listed and exemplified numerous strengths of PWIM, but a few mentioned weaknesses of PWIM. The students expressed the idea that PWIM had a positive effect on their English teaching. As integrated inferences, qualitative findings were used to explain the quantitative results that there were no significant differences of the effects of the PWIM between the experimental and control groups in both grade levels, from four contextual aspects: time constraints on PWIM implementation, teachers’ resistance, how to use PWIM and PWIM implemented in a classroom over 55 students.
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Stroke is a prevalent disorder with immense socioeconomic impact. A variety of chronic neurological deficits result from stroke. In particular, sensorimotor deficits are a significant barrier to achieving post-stroke independence. Unfortunately, the majority of pre-clinical studies that show improved outcomes in animal stroke models have failed in clinical trials. Pre-clinical studies using non-human primate (NHP) stroke models prior to initiating human trials are a potential step to improving translation from animal studies to clinical trials. Robotic assessment tools represent a quantitative, reliable, and reproducible means to assess reaching behaviour following stroke in both humans and NHPs. We investigated the use of robotic technology to assess sensorimotor impairments in NHPs following middle cerebral artery occlusion (MCAO). Two cynomolgus macaques underwent transient MCAO for 90 minutes. Approximately 1.5 years following the procedure these NHPs and two non-stroke control monkeys were trained in a reaching task with both arms in the KINARM exoskeleton. This robot permits elbow and shoulder movements in the horizontal plane. The task required NHPs to make reaching movements from a centrally positioned start target to 1 of 8 peripheral targets uniformly distributed around the first target. We analyzed four movement parameters: reaction time, movement time (MT), initial direction error (IDE), and number of speed maxima to characterize sensorimotor deficiencies. We hypothesized reduced performance in these attributes during a neurobehavioural task with the paretic limb of NHPs following MCAO compared to controls. Reaching movements in the non-affected limbs of control and experimental NHPs showed bell-shaped velocity profiles. In contrast, the reaching movements with the affected limbs were highly variable. We found distinctive patterns in MT, IDE, and number of speed peaks between control and experimental monkeys and between limbs of NHPs with MCAO. NHPs with MCAO demonstrated more speed peaks, longer MTs, and greater IDE in their paretic limb compared to controls. These initial results qualitatively match human stroke subjects’ performance, suggesting that robotic neurobehavioural assessment in NHPs with stroke is feasible and could have translational relevance in subsequent human studies. Further studies will be necessary to replicate and expand on these preliminary findings.
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This research investigated annular field reversed configuration (AFRC)devices for high power electric propulsion by demonstrating the acceleration of these plasmoids using an experimental prototype and measuring the plasmoid's velocity, impulse, and energy efficiency. The AFRC plasmoid translation experiment was design and constructed with the aid of a dynamic circuit model. Two versions of the experiment were built, using underdamped RLC circuits at 10 kHz and 20 kHz. Input energies were varied from 100 J/pulse to 1000 J/pulse for the 10 kHz bank and 100 J/pulse for the 20 kHz bank. The plasmoids were formed in static gas fill of argon, from 1 mTorr to 50 mTorr. The translation of the plasmoid was accomplished by incorporating a small taper into the outer coil, with a half angle of 2°. Magnetic field diagnostics, plasma probes, and single-frame imaging were used to measure the plasmoid's velocity and to diagnose plasmoid behavior. Full details of the device design, construction, and diagnostics are provided in this dissertation. The results from the experiment demonstrated that a repeatable AFRC plasmoid was produced between the coils, yet failed to translate for all tested conditions. The data revealed the plasmoid was limited in lifetime to only a few (4-10) μs, too short for translation at low energy. A global stability study showed that the plasma suffered a radial collapse onto the inner wall early in its lifecycle. The radial collapse was traced to a magnetic pressure imbalance. A correction made to the circuit was successful in restoring an equilibrium pressure balance and prolonging radial stability by an additional 2.5 μs. The equilibrium state was sufficient to confirm that the plasmoid current in an AFRC reaches a steady-state prior to the peak of the coil currents. This implies that the plasmoid will always be driven to the inner wall, unless it translates from the coils prior to peak coil currents. However, ejection of the plasmoid before the peak coil currents results in severe efficiency losses. These results demonstrate the difficulty in designing an AFRC experiment for translation as balancing the different requirements for stability, balance, and efficient translation can have competing consequences.
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Natural Language Processing (NLP) has seen tremendous improvements over the last few years. Transformer architectures achieved impressive results in almost any NLP task, such as Text Classification, Machine Translation, and Language Generation. As time went by, transformers continued to improve thanks to larger corpora and bigger networks, reaching hundreds of billions of parameters. Training and deploying such large models has become prohibitively expensive, such that only big high tech companies can afford to train those models. Therefore, a lot of research has been dedicated to reducing a model’s size. In this thesis, we investigate the effects of Vocabulary Transfer and Knowledge Distillation for compressing large Language Models. The goal is to combine these two methodologies to further compress models without significant loss of performance. In particular, we designed different combination strategies and conducted a series of experiments on different vertical domains (medical, legal, news) and downstream tasks (Text Classification and Named Entity Recognition). Four different methods involving Vocabulary Transfer (VIPI) with and without a Masked Language Modelling (MLM) step and with and without Knowledge Distillation are compared against a baseline that assigns random vectors to new elements of the vocabulary. Results indicate that VIPI effectively transfers information of the original vocabulary and that MLM is beneficial. It is also noted that both vocabulary transfer and knowledge distillation are orthogonal to one another and may be applied jointly. The application of knowledge distillation first before subsequently applying vocabulary transfer is recommended. Finally, model performance due to vocabulary transfer does not always show a consistent trend as the vocabulary size is reduced. Hence, the choice of vocabulary size should be empirically selected by evaluation on the downstream task similar to hyperparameter tuning.