The flexible and portable paper-based sensors have a broad potential application in electronic detection and devices. In this work, a flexible thermoresponsive paper sensor was reported by writing on A4 paper with composite pencil leads which contain thermoresponsive pyrene-based ionic liquid [Pyrmim][Br]. The [Pyrmim][Br] was transferred onto the A4 paper surface with graphite by pencil writing for the facile preparation of thermal-sensitive paper chips. The as-prepared paper sensor was very sensitive to the NIR irradiation and warm objects. What is more, the pliable paper chip also had regular responses along with the varication of the folding angles, which could be employed for the angle goniometer of electronic robots.
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http://dx.doi.org/10.1021/acsami.7b08737 | DOI Listing |
PLoS One
January 2025
College of Physics and Electronic Engineering, Hainan Normal University, HaiKou, China.
We have successfully prepared a significant number of nanowires from non-toxic silicon sources. Compared to the SiO silicon source used in most other articles, our preparation method is much safer. It provides a simple and harmless new preparation method for the preparation of silicon nanowires.
View Article and Find Full Text PDFAdv Healthc Mater
January 2025
College of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou, 310014, P. R. China.
Nowadays, gastroesophageal reflux disease (GERD) has emerged as one of the major hazards to the health of the upper gastrointestinal tract, and there is an urgent need for a low-cost, user-friendly, and non-invasive detection method. Herein, a paper-based sensor (CP sensor) for the non-invasive screening of GERD is proposed. The sensor is structured as a specially shaped cellulose paper strip embedded with fluorescent colloids, which are self-assembled from a cleavable synthetic fluorescent polymer (P4).
View Article and Find Full Text PDFSleep
January 2025
Courant Institute of Mathematical Sciences, New York University, New York, 10012, USA.
Study Objectives: This paper validates TipTraQ, a compact home sleep apnea testing (HSAT) system. TipTraQ comprises a fingertip-worn device, a mobile application, and a cloud-based deep learning artificial intelligence (AI) system. The device utilizes PPG (red, infrared, and green channels) and accelerometer sensors to assess sleep apnea by the AI system.
View Article and Find Full Text PDFSci Rep
January 2025
School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, JL431, China.
Multimodal sentiment analysis (MSA) aims to use a variety of sensors to obtain and process information to predict the intensity and polarity of human emotions. The main challenges faced by current multi-modal sentiment analysis include: how the model extracts emotional information in a single modality and realizes the complementary transmission of multimodal information; how to output relatively stable predictions even when the sentiment embodied in a single modality is inconsistent with the multi-modal label; how can the model ensure high accuracy when a single modal information is incomplete or the feature extraction performance not good. Traditional methods do not take into account the interaction of unimodal contextual information and multi-modal information.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh, 11543, Saudi Arabia.
Underwater environmental exploration using sensor nodes has emerged as a critical endeavor fraught with challenges such as localization errors, energy, and costs attributed to the dynamic nature of underwater environments. This paper proposes a KNN-based cost-efficient machine-learning algorithm aimed at optimizing underwater context acquisition with sensor nodes. By addressing existing localization challenges, the algorithm minimizes localization errors, energy consumption and Time costs while significantly enhancing localization accuracy to 99.
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