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On-Chip Metamaterial-Enhanced Mid-Infrared Photodetectors with Built-In Encryption Features.
Adv Sci (Weinh)
January 2025
College of Physics and Optoelectronic Engineering, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, No. 1, Sub-Lane Xiangshan, Xihu District, Hangzhou, 310024, China.
The integration of mid-infrared (MIR) photodetectors with built-in encryption capabilities holds immense promise for advancing secure communications in decentralized networks and compact sensing systems. However, achieving high sensitivity, self-powered operation, and reliable performance at room temperature within a miniaturized form factor remains a formidable challenge, largely due to constraints in MIR light absorption and the intricacies of embedding encryption at the device level. Here, a novel on-chip metamaterial-enhanced, 2D tantalum nickel selenide (Ta₂NiSe₅)-based photodetector, meticulously designed with a custom-engineered plasmonic resonance microstructure to achieve self-powered photodetection in the nanoampere range is unveiled.
View Article and Find Full Text PDFEmotional analysis of operating room nurses in acute care hospitals in Japan: insights using ChatGPT.
BMC Nurs
January 2025
Department of Healthcare Management Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8677, Japan.
Aim: This study aimed to explore the emotions of operating room nurses in Japan towards perioperative nursing using generative AI and human analysis, and to identify factors contributing to burnout and turnover.
Methods: A single-center cross-sectional study was conducted from February 2023 to February 2024, involving semi-structured interviews with 10 operating room nurses from a national hospital in Japan. Interview transcripts were analyzed using generative AI (ChatGPT-4o) and human researchers for thematic, emotional, and subjectivity analysis.
Contribution of Video Directly Observed Therapy (VDOT) to Tuberculosis Treatment in Brazil.
J Med Syst
January 2025
Department of Public Health, Ribeirão Preto Medical School, University of São Paulo (USP), Ribeirão Preto, São Paulo, Brazil.
Directly Observed Treatment (DOT) involves the administration of medication and in-person monitoring by a healthcare team alongside the patient to improve adherence to tuberculosis (TB) treatment. Implementing DOT requires healthcare professionals, transportation, time dedication, and presence at the patient's residence. Meeting all these conditions is not always possible to address the high demand of TB patients who would benefit from this supervision.
View Article and Find Full Text PDFAn optimized LSTM-based deep learning model for anomaly network intrusion detection.
Sci Rep
January 2025
Department of Electrical and Electronics Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India.
The increasing prevalence of network connections is driving a continuous surge in the requirement for network security and safeguarding against cyberattacks. This has triggered the need to develop and implement intrusion detection systems (IDS), one of the key components of network perimeter aimed at thwarting and alleviating the issues presented by network invaders. Over time, intrusion detection systems have been instrumental in identifying network breaches and deviations.
View Article and Find Full Text PDFMachine learning boosts wind turbine efficiency with smart failure detection and strategic placement.
Sci Rep
January 2025
Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura, 35111, Egypt.
The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analysis or by using Supervisory Control and Data Acquisition (SCADA) data of wind turbines, wherein conventional fault pattern identification is a time-consuming, guesswork process. This work proposed an intelligent automated approach to early fault detection through the implementation of the HARO (Huber Adam Regression Optimizer) model, which combines Transformer networks with Lasso Regression and the Adam optimizer.
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