DNA data storage is a promising technology that utilizes computer simulation and offers high-density and durable digital information storage. It is challenging to store massive image data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the durability of stored data. This work proposes a novel approach (RFS-codec) comprising an image fraction strategy and an innovative codec method to split and encode image data into DNA storage, respectively. The fraction strategy contributes by delivering a cost-effective solution for image storage in DNA. The codec method offers an encryption mechanism to convert binary d... More >

Artificial intelligence (AI) is transforming personalized medicine through its potential. However, implementing AI-driven healthcare solutions remains inconsistent because of certain social factors, i.e., cultural beliefs, trust issues, and major accessibility elements. This study focuses on the key social determinants involved in the acceptance and implementation of AI-driven medicine, with a prime focus on hurdles such as algorithmic bias, transparency issues, and public skepticism. A quantitative approach was employed in the research, and survey data were collected among healthcare professionals, policymakers, and patients. Statistical analyses were performed, including chi-square tests a... More >

As a carrier of genetic information, the precise design and optimization of nucleic acid (DNA or RNA) sequences are of critical importance for the realization of specific biological functions. From synthesizing genes to designing novel nucleic acid drugs, from constructing efficient expression vectors to modifying microbial metabolic pathways, all are inseparable from the fine regulation of nucleic acid sequences. The primary purpose of nucleic acid sequence design is to generate new sequences tailored to specific requirements for gene expression, function prediction, drug development, and other applications. In this paper, we first review the theoretical basis of nucleic acid sequence desig... More >

Social media has significantly transformed the digital landscape by enabling an unprecedented expansion of content, further accelerated by the COVID-19 pandemic, which increased the demand for online classes, virtual meetings, and recorded conferences. While major technology companies have previously employed sentiment analysis and opinion mining to gauge user feedback, this study proposes a novel framework for emotion-based video content analysis. The proposed method extracts audio from social media videos and applies Speech-to-Text (STT) conversion. The extracted text is then processed using a pre-trained BERT model, leveraging its fine-tuned capabilities and 110 million parameters to enha... More >

Presents the inaugural editorial for this issue of the publication. More >