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Blockchain is a novel data architecture characterized by a chronological sequence of blocks in a decentralized manner. We aimed to evaluate the real-world feasibility of a blockchain-based dynamic consent platform (METORY) in a decentralized and multicenter trial. The study consisted of three visits (i.e., screening and 2 follow-up visits) with a 2-week interval. Each subject was required to report the self-measured body temperatures and take a virtual investigational drug by entering the unique drug code on the application. To simulate real-world study settings, two major (i.e., changes in the schedule of body temperature measurement) and three minor protocol amendments (i.e., nonsignificant changes without any changes in the procedures) were set. Overall study completion rates, proportion of consent, and response time to each protocol amendment and adherence were evaluated. A total of 60 subjects (30 in each center) were enrolled in two study centers. All subjects completed the study, and the overall proportion of consent to each protocol amendment was 95.7 ± 13.7% (mean ± SD), with a median response time of 0.2 h. Overall, subjects took 90.8% ± 19.2% of the total drug, whereas compliance with the schedule was 69.1% ± 27.0%. Subjects reported 96.7% ± 4.2% of the total body temperature measurements whereas the adherence to the schedule was 59.0% ± 25.0%, which remarkably decreased after major protocol amendments. In conclusion, we evaluated a blockchain-based dynamic consent platform in real clinical trial settings. The results suggested that major changes should be avoided unless subjects' proper understanding is warranted.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099134 | PMC |
http://dx.doi.org/10.1111/cts.13246 | DOI Listing |
J Vis Exp
August 2025
School of Cyberspace Security, Zhengzhou University.
In the context of the rapid development of large language models (LLMs), contrastive learning has become widely adopted due to its ability to bypass costly data annotation by leveraging vast amounts of network data for model training. However, this widespread use raises significant concerns regarding data privacy protection. Unlearnable Examples (UEs), a technique that disrupts model learning by perturbing data, effectively prevents unauthorized models from misusing sensitive data.
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August 2025
Mechanical Engineering Department, College of Engineering in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia.
This study presents a techno-economic optimization of hydrogen production using hybrid wind-solar systems across six Australian cities, highlighting Australia's green hydrogen potential. A hybrid PV-wind-electrolyzer-hydrogen tank (PV-WT-EL-HT) system demonstrated superior performance, with Perth achieving the lowest Levelized Cost of Hydrogen (LCOH) at $0.582/kg, Net Present Cost (NPC) of $27.
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August 2025
Faculty of Engineering and Technology, Multimedia University, Melaka, 75450, Malaysia.
Confidentiality and access control are essential to protect sensitive data, prevent cyber threats, ensure compliance, and avoid risks like identity theft. Hence, a framework towards secure patient Data access using Hybrid Integrated Hashing Method is introduced to ensure patient confidentiality and efficient data access in healthcare systems. Unlike conventional solutions that rely solely on standard blockchain and secure hash algorithm 256 for data protection, this proposed method integrates a multi-layer hybrid hashing approach combining dynamic hash chaining with temporal entropy encoding, making hash collisions virtually infeasible.
View Article and Find Full Text PDFSensors (Basel)
August 2025
Beijing University of Posts and Telecommunications-China Mobile Communications Group Co., Ltd. Joint Institute, Beijing 100876, China.
With the explosive growth of Internet of Things (IoT) devices, massive amounts of heterogeneous data are continuously generated. However, IoT data transactions and sharing face multiple challenges such as limited device resources, untrustworthy network environment, highly sensitive user privacy, and serious data silos. How to achieve fine-grained access control and privacy protection for massive devices while ensuring secure and reliable data circulation has become a key issue that needs to be urgently addressed in the current IoT field.
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August 2025
Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.
Vehicle-to-everything (V2X) communication is a fundamental technology in the development of intelligent transportation systems, encompassing vehicle-to-vehicle (V2V), infrastructure (V2I), and pedestrian (V2P) communications. This technology enables connected and autonomous vehicles (CAVs) to interact with their surroundings, significantly enhancing road safety, traffic efficiency, and driving comfort. However, as V2X communication becomes more widespread, it becomes a prime target for adversarial and persistent cyberattacks, posing significant threats to the security and privacy of CAVs.
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