Innovation Translation Research Articles

A Scoping Review of Implementation Science Studies in the Field of Traumatic Brain Injury: State of the Science and Future Directions.

Implementation research is essential to accelerating the public health benefits of innovations in health settings. However, the US National Academies of Sciences, Engineering, and Medicine 2022 report identified a lag in published implementation research applied to traumatic brain injury (TBI). Our objectives were to characterize implementation science studies published to date in TBI clinical care and rehabilitation and provide recommendations for future directions. A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Articles published between 2011 and 2023 were identified (MEDLINE, PubMed, PsychInfo, and Web of Science), and included if the study focused on the TBI population, measured at least one Proctor (2011) implementation outcome and aligned with implementation research designs. Data were charted using an extraction template. Of the 38 articles, 76% were published between 2018 and 2023. About 37% of articles were in the pre-implementation phase, and 57.9% were in the implementation phase. Over half of articles used a theory, model, or framework to guide the research. Fifteen studies were descriptive, 10 were qualitative, 7 were mixed methods, and 4 were randomized controlled trials. Most studies investigated implementation outcomes regarding national guidelines following TBI or TBI symptom management. Adoption (42.1%) and fidelity (42.1%) were the most commonly studied implementation outcomes, followed by feasibility (18.4%), acceptability (13.2%), and penetration (10.5%). Only 55% of studies used or tested the effectiveness of one or more implementation strategies, with training and education used most commonly, followed by data warehousing techniques. Future research should prioritize the selection and investigation of implementation strategy effectiveness and mechanisms across contexts of care and use implementation research reporting standards to improve study rigor. Additionally, collaborative efforts between researchers, community partners, individuals with TBI, and their care partners could improve the equitable translation of innovations across service contexts.

From ''Dependent Translation" to "Creative Translation'' by Taha Abdurrahman

This paper undertakes a critical and analytical examination of the transformative dimensions of translation as conceptualized by the Moroccan philosopher Taha Abdurrahman. Central to Abdurrahman’s intellectual project is the call to transcend the pervasive Eurocentrism that characterizes contemporary translation theories. Abdurrahman offers a nuanced critique of the translation methodologies employed during the Abbasid period, particularly the uncontextualized appropriation of Greek philosophy. He contends that this approach led to the marginalization of Islamic philosophy, reducing it to a mode of mere transmission and dependency, initially on ancient Greece and subsequently on the modern West. To address these historical inadequacies, Abdurrahman advocates for an innovative translation strategy termed taʾṣīliyya, which translates literally to “authenticating.” This strategy emphasizes a transformative process whereby the source text is integrated into the receiving culture, aligning with its specific epistemic and cultural needs, irrespective of the original context. Abdurrahman posits that this method is essential for fostering an autonomous Arab/Islamic philosophical tradition, one that is not subsumed under external theoretical paradigms, even if this necessitates deviating from conventional criteria of accuracy and faithfulness. This paper critically engages with the theoretical foundations and proposes practical applications of Abdurrahman’s translation paradigm. It situates his framework within the broader historical trajectory of translation in the Arabic intellectual tradition and contemporary translation studies. Furthermore, it interrogates the theoretical and methodological ramifications of eschewing conventional norms of fidelity and accuracy, notwithstanding their entrenched and restrictive nature.

On the Relationship Between University Translator Training Programs and the Translation Market Requirements: The Case of English Translation Graduates and Postgraduates of Imam Reza International University

The training of specialized human resources and the utilization of their expertise represent the primary concerns of universities and the higher education system. The efficacy of translator training programs has been increasingly scrutinized, with a particular emphasis on the explicit delineation of the link between their curricula and the market in which their graduates are ultimately employed. The objective of the present study was to ascertain the relationship between the university translator training programs at Imam Reza International University and the requirements of the translation market, with specific focus on the occupational status of translation graduates, and their attitudes towards the academic training, over the past 20 years. The study was mixed-methods with the online survey completed by 100 graduates by convenience sampling technique. Subsequently, through a snowballing approach, 23 graduates were selected for the semi-structured interview. Data analysis was performed in SPSS version 27; then, the data of interviews were analyzed based on the grounded theory in MAXQDA version 2020. The findings suggest that the majority of graduates perceive themselves to be inadequately prepared to enter the workforce. This sentiment is attributed to the absence of practical coursework, including innovative translation techniques and marketing skills aligned with the demands of the contemporary translation industry. So, there is a need for greater interaction between training and the market. The findings also indicated that modern translation technology and updated resources are not used to meet the market’s need. Inviting employers and entrepreneurs to talk in the classes, holding specialized workshops, and having work placement components in the curriculum can be effective in creating a foundation for students' subsequent employment.

Navigating blockchain adoption: An examination of actor alignment with the Diffusion of Innovation principles

Blockchain technology has garnered substantial interest due to its capacity to transform numerous industries by amplifying transparency and bolstering security measures. Despite the increasing interest, there is a void in existing literature regarding the alignment of actors with the Diffusion of Innovation (DOI) principles in the context of blockchain adoption. This gap restricts comprehension of the factors influencing adoption. This research addresses this void by investigating how actors align with the DOI principles in making decisions about blockchain adoption. The DOI model is combined with the innovation translation concept derived from Actor-Network Theory (ANT) to explore these complex dynamics in more detail. The results indicate that the decision-making process for blockchain adoption corresponds to the knowledge, persuasion, and decision stages, mirroring the phases found in the innovation translation approach. This research offers theoretical insights and practical knowledge that can be beneficial to individuals and organisations looking to promote the successful implementation of blockchain technology.

Applying the Cognitive Walkthrough for Implementation Strategies Methodology to Inform the Redesign of a Selection-Quality Implementation Toolkit for Use in Schools.

Implementation strategies are key to enhancing translation of new innovations but there is a need to systematically design and tailor strategies to match the targeted implementation context and address determinants. There are increasing methods to inform the redesign and tailoring of implementation strategies to maximize their usability, feasibility, and appropriateness in new settings such as the Cognitive Walkthrough for Implementation Strategies (CWIS) approach. The aim of the current project is to apply the CWIS approach to inform the redesign of a multifaceted selection-quality implementation toolkit entitled ACT SMARTS for use in middle and high schools. We systematically applied CWIS as the second part of a community-partnered iterative redesign of ACT SMARTS for schools to evaluate the usability and inform further toolkit redesign areas. We conducted three CWIS user testing sessions with key end users of school district administrators, school principals, and educators. Our CWIS application revealed that end users found ACT SMARTS acceptable and relevant but anticipate usability issues engaging in the ACT SMARTS process. Results informed the identification of eleven usability issues and corresponding redesign solutions to enhance the usability of ACT SMARTS for use in middle and high schools. Results indicated the utility of CWIS in assessing implementation strategy usability in service of informing strategy tailoring and redesign to improve alignment with user and setting needs. Recommendations regarding the use of this participatory approach are discussed.

A Systematic Translation Validation Framework for MLIR-Based Compilers

This paper introduces an innovative translation validation framework designed for MLIR-based compilers, which has garnered considerable prominence in fields such as machine learning, high-performance computing and hardware design. Despite rigorous testing, compilers based on MLIR might still induce incorrect results and undefined behaviors, necessitating verification work. Our framework first takes a pair of MLIR programs as inputs and check their function signature’s compatibility before encoding them into SMT expressions. Then it uses the Z3 SMT solver to check whether the target program refines the source program. Our framework transcends the dialect limitations of past solutions, thereby providing validation support to a wider range of MLIR-based compilers. We demonstrate its effectiveness through evaluations on prominent open-source MLIR-based compilers, where we identified bugs and undefined behaviors. We further demonstrate the capability of this framework by validating two practical deep-learning accelerator designs.

Strategies, processes, outcomes, and costs of implementing experience sampling-based monitoring in routine mental health care in four European countries: study protocol for the IMMERSE effectiveness-implementation study

BackgroundRecent years have seen a growing interest in the use of digital tools for delivering person-centred mental health care. Experience Sampling Methodology (ESM), a structured diary technique for capturing moment-to-moment variation in experience and behaviour in service users’ daily life, reflects a particularly promising avenue for implementing a person-centred approach. While there is evidence on the effectiveness of ESM-based monitoring, uptake in routine mental health care remains limited. The overarching aim of this hybrid effectiveness-implementation study is to investigate, in detail, reach, effectiveness, adoption, implementation, and maintenance as well as contextual factors, processes, and costs of implementing ESM-based monitoring, reporting, and feedback into routine mental health care in four European countries (i.e., Belgium, Germany, Scotland, Slovakia).MethodsIn this hybrid effectiveness-implementation study, a parallel-group, assessor-blind, multi-centre cluster randomized controlled trial (cRCT) will be conducted, combined with a process and economic evaluation. In the cRCT, 24 clinical units (as the cluster and unit of randomization) at eight sites in four European countries will be randomly allocated using an unbalanced 2:1 ratio to one of two conditions: (a) the experimental condition, in which participants receive a Digital Mobile Mental Health intervention (DMMH) and other implementation strategies in addition to treatment as usual (TAU) or (b) the control condition, in which service users are provided with TAU. Outcome data in service users and clinicians will be collected at four time points: at baseline (t0), 2-month post-baseline (t1), 6-month post-baseline (t2), and 12-month post-baseline (t3). The primary outcome will be patient-reported service engagement assessed with the service attachment questionnaire at 2-month post-baseline. The process and economic evaluation will provide in-depth insights into in-vivo context-mechanism-outcome configurations and economic costs of the DMMH and other implementation strategies in routine care, respectively.DiscussionIf this trial provides evidence on reach, effectiveness, adoption, implementation and maintenance of implementing ESM-based monitoring, reporting, and feedback, it will form the basis for establishing its public health impact and has significant potential to bridge the research-to-practice gap and contribute to swifter ecological translation of digital innovations to real-world delivery in routine mental health care.Trial registrationISRCTN15109760 (ISRCTN registry, date: 03/08/2022).

A Novel Web-Based Application for Influenza and COVID-19 Outbreak Detection and Response in Residential Aged Care Facilities.

The use of innovative digital health technologies in public health is expanding quickly, including the use of these tools in outbreak response. The translation of a digital health innovation into effective public health practice is a complex process requiring diverse enablers across the people, process, and technology domains. This paper describes a novel web-based application that was designed and implemented by a district-level public health authority to assist residential aged care facilities in influenza and COVID-19 outbreak detection and response. It discusses some of the challenges, enablers, and key lessons learned in designing and implementing such a novel application from the perspectives of the public health practitioners (the authors) that undertook this project.

ENHANCING TRANSLATION EDUCATION WITH RATPRO: A CAT TOOLS-BASED LEARNING MODEL

The translation process greatly determines the translation results. The translated text should have the same meaning as the source text but still maintain the natural elements. A creative translation model that can help translators produce good translations that have equivalence in meaning and good grammar is essential, considering that the translation process is not just a change of language but is a process of transferring meaning from the source language to the target language (Indonesian-English). RATPro (Read, Analyze, Transfer, Produce) Translation Model that is based on Computer Assisted Translation (CAT) Tools can be used as a creative and innovative translation model that can help translation students transfer the language of scientific article manuscripts from the source language to the target language while maintaining the equivalence of meaning and naturalness of the language through excellent and correct grammar. RATPro (Read, Analyze, Transfer, Produce) Translation Model based on Computer Assisted Translation (CAT) Tools can also make it easier for students to translate because it is based on digital recording. This research aims to develop a RATPro translation model based on Computer Assisted Translation (CAT) Tools that are creative and innovative in translating scientific articles by students. The research model used is Research and Development (RnD), where research data is analyzed critically and validated to obtain valid and reliable results. The designedtranslation model will also be well used in translating authentic manuscripts in different manuscript fields.

Characteristics and translation of metaphorical language in traditional Chinese medicine texts

This article is devoted to the study of the characteristics of metaphorical language and its translation in the texts of traditional Chinese medicine. The research subject of this article is metaphorical language in TCM texts. The characteristics of the metaphorical language of TCM texts determine that translation should focus on cross-cultural communication and meaning interpretation. The purpose of the study is to investigate, learn how to accurately decipher metaphorical language and convey the connotation of these metaphorical expressions, so as to promote the effective dissemination of TCM culture in intercultural communication. And also - to reduce misunderstandings caused by cultural and linguistic differences, to improve the quality and accuracy of translations of TCM texts, to build a better linguistic bridge for TCM to the world. In terms of research methodology, this paper uses the method of literature study - extensive collection of relevant information and detailed interpretation of typical metaphorical expressions, as well as the method of comparative analysis - comparing the differences in the use of metaphorical language in different literatures. Scientific novelty is reflected in the in-depth interpretation and translation of TCM metaphors. Through an in-depth study of TCM theories and practices, the scientific principles underlying metaphors are revealed and presented to readers in a clearer and more accurate way. At the same time, innovative translation methods such as the method of literal translation with commentary, the free translation method, etc., allow readers to better understand the unique meaning of TCM metaphors. Through in-depth analysis, it is found that metaphorical language has important characteristics such as imagery, cultural relevance and polysemy, and is an important cognitive approach and tool in Chinese medicine and at the same time not only embodies a special description of physiological phenomena, but also a unique cognitive marker of alternative psychophysiological communication.

Innovation within teaching (EnglishSpanish) legal translation: hypernymy as a (sub)estimated translation technique

Globally, the pursuit of translation items is a highly complex, time-consuming issue within international legal settings. It is directly linked to legal systems, with their own lexicon, and meaning. In this article, we seek to show and argue how translators of Law may also resort to a somewhat innovative translation technique, such as hypernymy, to provide a wider lexical equivalent. To achieve our objective, we will generate a list of 18 (North American and Briths) legal items defined by their Spanish translation complexity – parting from our UAM University legal translation students’ outcomes (from a teaching innovation project) – and by their relationship to tribunals and courts decisions. These terms will be looked up (and compared) in both print and online dictionaries, and we will then provide one (or more) hypernym for each of them. By researching and discussing this issue, we will illustrate how helpful hypernyms are in providing innovative translation alternatives.

A new era in the science and care of kidney diseases.

Notable progress in basic, translational and clinical nephrology research has been made over the past five decades. Nonetheless, many challenges remain, including obstacles to the early detection of kidney disease, disparities in access to care and variability in responses to existing and emerging therapies. Innovations in drug development, research technologies, tissue engineering and regenerative medicine have the potential to improve patient outcomes. Exciting prospects include the availability of new drugs to slow or halt the progression of chronic kidney disease, the development of bioartificial kidneys that mimic healthy kidney functions, and tissue engineering techniques that could enable transplantable kidneys to be created from the cells of the recipient, removing the risk of rejection. Cell and gene therapies have the potential to be applied for kidney tissue regeneration and repair. In addition, about 30% of kidney disease cases are monogenic and could potentially be treated using these genetic medicine approaches. Systemic diseases that involve the kidney, such as diabetes mellitus and hypertension, might also be amenable to these treatments. Continued investment, communication, collaboration and translation of innovations are crucial to realize their full potential. In addition, increasing sophistication in exploring large datasets, implementation science, and qualitative methodologies will improve the ability to deliver transformational kidney health strategies.

Landscape of toxin-neutralizing therapeutics for snakebite envenoming (2015-2022): Setting the stage for an R&D agenda.

Progress in snakebite envenoming (SBE) therapeutics has suffered from a critical lack of data on the research and development (R&D) landscape. A database characterising this information would be a powerful tool for coordinating and accelerating SBE R&D. To address this need, we aimed to identify and categorise all active investigational candidates in development for SBE and all available or marketed products. In this landscape study, publicly available data and literature were reviewed to canvas the state of the SBE therapeutics market and research pipeline by identifying, characterising, and validating all investigational drug and biologic candidates with direct action on snake venom toxins, and all products available or marketed from 2015 to 2022. We identified 127 marketed products and 196 candidates in the pipeline, describing a very homogenous market of similar but geographically bespoke products and a diverse but immature pipeline, as most investigational candidates are at an early stage of development, with only eight candidates in clinical development. Further investment and research is needed to address the shortfalls in products already on the market and to accelerate R&D for new therapeutics. This should be accompanied by efforts to converge on shared priorities and reshape the current SBE R&D ecosystem to ensure translation of innovation and access.

Many Models, Little Adoption-What Accounts for Low Uptake of Machine Learning Models for Atrial Fibrillation Prediction and Detection?

(1) Background: Atrial fibrillation (AF) is a major risk factor for stroke and is often underdiagnosed, despite being present in 13-26% of ischemic stroke patients. Recently, a significant number of machine learning (ML)-based models have been proposed for AF prediction and detection for primary and secondary stroke prevention. However, clinical translation of these technological innovations to close the AF care gap has been scant. Herein, we sought to systematically examine studies, employing ML models to predict incident AF in a population without prior AF or to detect paroxysmal AF in stroke cohorts to identify key reasons for the lack of translation into the clinical workflow. We conclude with a set of recommendations to improve the clinical translatability of ML-based models for AF. (2) Methods: MEDLINE, Embase, Web of Science, Clinicaltrials.gov, and ICTRP databases were searched for relevant articles from the inception of the databases up to September 2022 to identify peer-reviewed articles in English that used ML methods to predict incident AF or detect AF after stroke and reported adequate performance metrics. The search yielded 2815 articles, of which 16 studies using ML models to predict incident AF and three studies focusing on ML models to detect AF post-stroke were included. (3) Conclusions: This study highlights that (1) many models utilized only a limited subset of variables available from patients' health records; (2) only 37% of models were externally validated, and stratified analysis was often lacking; (3) 0% of models and 53% of datasets were explicitly made available, limiting reproducibility and transparency; and (4) data pre-processing did not include bias mitigation and sufficient details, leading to potential selection bias. Low generalizability, high false alarm rate, and lack of interpretability were identified as additional factors to be addressed before ML models can be widely deployed in the clinical care setting. Given these limitations, our recommendations to improve the uptake of ML models for better AF outcomes include improving generalizability, reducing potential systemic biases, and investing in external validation studies whilst developing a transparent modeling pipeline to ensure reproducibility.

Public health genomics research in Italy: an overview of ongoing projects.

Public health genomics (PHG) aims to integrate advances in genomic sciences into healthcare for the benefit of the general population. As in many countries, there are various research initiatives in this field in Italy, but a clear picture of the national research portfolio has never been sketched. Thus, we aimed to provide an overview of current PHG research projects at the national or international level by consultation with Italian institutional and academic experts. We included 68 PHG projects: the majority were international projects in which Italian researchers participated (n = 43), mainly funded by the European Commission, while the remainder were national initiatives (N = 25), mainly funded by central government. Funding varied considerably, from € 50,000 to € 80,803,177. Three main research themes were identified: governance (N = 20); precision medicine (PM; N = 46); and precision public health (N = 2). We found that research activities are preferentially aimed at the clinical application of PM, while other efforts deal with the governance of the complex translation of genomic innovation into clinical and public health practice. To align such activities with national and international priorities, the development of an updated research agenda for PHG is needed.

Strategies for applying shape grammar to wooden furniture design: Taking traditional Chinese Ming-style recessed-leg table as an example

This paper uses shape grammar to conduct strategic research and innovative translation of existing wooden furniture designs. A traditional Chinese Ming-style recessed-leg table was used as an example to demonstrate its feasibility. The paper applies biological DNA genetic information to furniture products, and combines shape grammar to evolve and mutate them, thereby creating new forms of wooden furniture that maintain the original genes. A DNA gene pool of recessed-leg table was constructed, and an architectural queti replacement pool was constructed based on the rules of shape grammar as backup for subsequent experiments to replace part of the designed genes of the recessed-leg table. Shape grammar was used to deduce the recessed-leg table and generate three plans. A consumer questionnaire was established through the semantic differential method. After evaluating these three design plans, an optimal plan that meets market demand was selected, and modeling, rendering, and concept elaboration were performed. Finally, the paper takes Ming-style recessed-leg table as an example to demonstrate that it is effective and feasible to use shape grammar to guide the design and research of domestic wooden furniture.

Integration and Innovation of Artificial Intelligence and Traditional English Translation Methods

Abstract In this study, we employ autoregressive and neural machine translation models to process natural language. Our exploration of AI translation workflows encompasses three key aspects: the encoder-decoder framework, text feature representation, and translation derivation methodologies. Subsequently, we identify the core evaluation indices essential for assessing intelligent translation systems. An innovative translation model is constructed by amalgamating AI-driven and traditional English translation techniques. This model is scrutinized for its effectiveness through various lenses, including the quality of English-to-Chinese poetry translations and manual evaluations. Comparative analysis of the proposed translation method with other extant methods across diverse datasets reveals superior performance metrics: the BLEU score consistently exceeds 4.5 across all three test sets, and the METEOR score ranges between 4.3 and 4.6, surpassing competing methods. Additionally, translation accuracy for sentences of varying lengths in the source language is maintained between 85% and 96%. The objective of this research is to conduct a comprehensive examination of the integration of AI English translation with conventional methodologies, aiming to foster innovative theoretical contributions and practical advancements in the field.

A Study of Modern Poetry Translation under the Perspective of Discourse Function: T.S. Eliot's The Waste Land in Multiple Translations as an Example

From the discourse function perspective of Halliday's Systemic Functional Linguistics, this paper compares and analyzes two Chinese translations of The Waste Land by Zhao Luorui and Zha Liangzheng (Mudan), exploring how the different translations creatively interpret and reconstruct the original text in accordance with the cultural context and aesthetic preferences of the target language. It further investigates how this reconstruction impacts and shapes the target readers' understanding and acceptance process. The study reveals that the translators' distinct orientations in translation strategies lead to significant differences in the translations regarding expressive effects and readers' experiences. Zhao's translation effectively maintains the discourse structure and linguistic style of the original text through a conservative and traditional translation approach. Conversely, Mudan's translation notably enhances the readability and acceptability of the translation with a flexible and innovative translation style. Overall, the latter translation is better suited to the aesthetic habits and cultural background of Chinese readers.

The Role of Actors in Blockchain Adoption Decisions – An Innovation Translation Perspective

An overview of challenges around blockchain adoption has revealed that there is little understanding of the process of blockchain adoption decisions, including who needs to be involved and consulted at various stages. When systems are designed to intentionally protect privacy or to obscure actors, such as blockchain platforms, it can be challenging to identify them and to understand their roles. To do this we used an Innovation Translation approach from Actor-Network Theory (Latour, 2007) which looks at the roles of both human and non-human actors. To understand the interactions among the actors involved, multiple rounds of interviews were conducted with Blockchain experts, utilising the qualitative Delphi method. The findings of this study propose a framework that provides insight into the decision-process by exploring the actors involved and their roles as they implement strategies to adopt blockchain and to convince other actors. The outcomes will assist blockchain practitioners and researchers to have an understanding of pre-adoption decisions and stakeholder involvement. Organisations considering implementing blockchain will benefit from this research as they will know where to start, who to engage, and which stakeholders are needed during the decision-making process.

A Framework for Assessing and Improving Decision-Making in the Translation of Research and Innovation for Impact

The successful translation of research and innovation into impact has never been more important to solve the complex problems facing societies and existential threats to our planet. University research and innovation holds a key to unlock solutions. Innovation practitioners and university research translation offices seeking to support and foster promising innovations face a challenge in determining which innovations have sound prospects for development through to the market. Approaches such as mission-oriented innovation; as well as open innovation, entrepreneurial universities, and educating the educators considered in previous letters all may help, but how can we be sure that our assessments of any given initiative are sound? What are the requisites for successful translation to impact, and what tools might aid in decision making for complex endeavours? There are many theories, tools and methods in use; yet the performance of research translation efforts at universities around the world vary wildly with only a very small number clearly successful and the vast majority, achieving at best, modest results, that are well below their expected potential. At our university, we assembled a multidisciplinary team bringing together research translation expertise and innovation researchers with a record of entrepreneurial success to consider tools that can aid identification and assessment of promising innovations, with a view to best aligning university support. Reflecting on existing translation readiness assessment tools and practitioner knowledge, we argue that a more encompassing and dynamic framework is needed to aid universities in early and ongoing assessment of innovations to effectively steward their development and enhance their potential for success. We provide an early outline of this multi-dimensional assessment tool.