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The advancement in technology has changed the workflow and the role of human translator in recent years. The impact from the trend of technology-mediated translation prompted the ratification of technology literacy as a major competence for modern translators. Consequently, teaching of translation technology including but not limited to Computer-aided Translation (CAT) and Machine Translation (MT) became part of comprehensive curricula for translation training programs. However, in many institutions, the teaching of translation technology was haunted by issues such as: narrow scope of curriculum design, outdated technologies, and unbalance between theories and practices in teaching. The study was the pilot evaluation of a tailored course to foster translation trainees' knowledge and abilities of data science. The course was designed to be a fundamental step toward sophisticated translation technologies. During the pilot evaluation of the 8-week course, 85 students ( = 85) were recruited as participants. The study adopted a mix-method design by employing a survey to investigate student's level of satisfaction toward the course and focus group discussion to understand students' attitudes and perceptions of key aspects of the course. By interpreting the results from statistical analysis of the survey (5.39/7) and thematic analysis of the focus group discussion, the course of data science for translators was well received among participants. The evaluation project manifested the feasibility and effectiveness of a translator-oriented data science course.
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http://dx.doi.org/10.3389/fpsyg.2022.939689 | DOI Listing |
JMIR Res Protoc
September 2025
State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
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View Article and Find Full Text PDFJMIR Rehabil Assist Technol
September 2025
Department of Computer Science, Faculty of Technology, Art and Design, OsloMet - Oslo Metropolitan University, Oslo, Norway.
Background: Over the past decade, the proportion of the world's population aged ≥65 years has grown exponentially, presenting significant challenges, such as social isolation and loneliness among this population. Assistive technologies have shown potential in enhancing the quality of life for older adults by improving their physical, cognitive, and communication abilities. Research has shown that smart televisions are user-friendly and commonly used among older adults.
View Article and Find Full Text PDFJMIR Public Health Surveill
September 2025
Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States.
Background: In recent years, social media has emerged as a pivotal tool in implementation science efforts to address the HIV epidemic. Engaging community partners is essential to ensure the successful and equitable implementation of social media strategies. There is a notable lack of scholarship addressing the operational considerations for studies using social media strategies in community-partnered HIV research.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Department of Chemistry, Delaware State University, Dover, Delaware 19901, United States.
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly and time-consuming. Machine Learning (ML) offers a cost-effective and rapid alternative, enabling efficient predictions of HOMO-LUMO gap values across large data sets without the need for extensive QM computations or experiments. ML models facilitate the screening of diverse molecules, providing valuable insights into complex chemical spaces and integrating seamlessly into high-throughput workflows to prioritize candidates for experimental validation.
View Article and Find Full Text PDFAm J Public Health
October 2025
Alexander Furuya, Asa Radix, Adam Whalen, Jessica Contreras, Jenesis Merriman, Krish J. Bhatt, Roberta Scheinmann, and Dustin T. Duncan are with the Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY. Yusuf Ransome is with the Department of Social and Behav
To examine how one's community connectedness may act as a source of resilience and promote HIV prevention and care behaviors among transgender women of color. We analyzed survey data from 313 transgender women of color living in New York City collected from August 2020 to November 2022. The Community Connectedness Scale asks participants about their baseline feelings of connection, feelings of inclusion, feelings of belonging, feelings of isolation, and feelings of being unlike in relation to the transgender community.
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