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With the rapid development of quantum computers and quantum computing, Internet of Things (IoT) networks equipped with traditional cryptographic algorithms have become very weak against quantum attacks. This paper focuses on the privacy-preserving problem in IoT networks and proposes a certificateless ring signature (CLRS) scheme. This CLRS is constructed with lattice theories, which show promising advantages in resisting quantum attacks. Meanwhile, the certificateless mechanism reduces the key control ability of the key generation center (KGC) by adding personal secret keys to the private key generated by the system. Meanwhile, the ring signature mechanism protects users' privacy information through a non-central control mechanism. Next, the security proof in a random oracle model is given, which shows that this CLRS scheme can obtain unforgeability and ensure the signer's anonymity. Its security properties include non-repudiation, traceability, and post-quantum security. Then, the efficiency comparison and performance results show that this CLRS scheme is more efficient and practical than similar schemes. Moreover, this work presents an exploration of the post-quantum cryptographic algorithm and its application in IoT networks.
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http://dx.doi.org/10.3390/s25051321 | DOI Listing |
Mol Divers
September 2025
Department of Biotechnology, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492001, India.
Traditional drug discovery methods like high-throughput screening and molecular docking are slow and costly. This study introduces a machine learning framework to predict bioactivity (pIC₅₀) and identify key molecular properties and structural features for targeting Trypanothione reductase (TR), Protein kinase C theta (PKC-θ), and Cannabinoid receptor 1 (CB1) using data from the ChEMBL database. Molecular fingerprints, generated via PaDEL-Descriptor and RDKit, encoded structural features as binary vectors.
View Article and Find Full Text PDFScience
September 2025
Dipartimento di Scienze della Terra, dell'Ambiente e delle Risorse, Universita`degli Studi di Napoli Federico II, Napoli, Italy.
We used a retrained machine learning workflow to enhance the performance of the seismic monitoring network at Campi Flegrei caldera (CFc) for improved tracking of the evolution of volcanic unrest. We analyzed the recent (1/21/22 - 03/20/25) continuous seismic data, which showed a sharp increase in seismicity at the highly populated CFc. Our analysis expanded the seismicity catalog from around 12,000 to over 54,000 earthquakes.
View Article and Find Full Text PDFBiology (Basel)
July 2025
National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, School of Life Science, Henan University, Kaifeng 475000, China.
SPX () family genes play a pivotal role in phosphorus signaling, phosphorus uptake, and phosphorus translocation in plants. However, to date, the SPX family genes have not been systematically investigated in cotton. In this study, we conducted a genome-wide analysis and identified 44 SPX family genes in , classifying them into four subfamilies (SPX, SPX-MFS, SPX-EXS, and SPX-RING) based on conserved domains.
View Article and Find Full Text PDFMedicine (Baltimore)
August 2025
Department of Health Medical Big Data Office, Statistical Information Center of the National Health Commission, Beijing, China.
This study developed a prognostic risk prediction model for endometrial carcinoma (EC) by integrating data from The Cancer Genome Atlas and Gene Expression Omnibus for bioinformatics analysis. The relevant data of EC were downloaded from The Cancer Genome Atlas database and the GSE17025 dataset of the Gene Expression Omnibus database. Based on the R language, the differentially expressed genes (DEGs) and weighted gene co-expression network analysis were used to identify the gene modules with the strongest correlation with clinical features, and intersected with the DEGs of GSE17025 dataset.
View Article and Find Full Text PDFbioRxiv
August 2025
School of Biochemistry and Immunology, Trinity College Dublin, Dublin 2, Ireland.
Inherited mutations in VPS35 and the kinase LRRK2 lead to hyperphosphorylation of Rab GTPases and promote the formation of phospho-Rab signalling complexes. A subset of RH2 domain-containing proteins from the RILP-homology family, including RILP, RILPL1, RILPL2, JIP3, and JIP4 are Rab effectors that recognize the LRRK2-phosphorylated switch 2 threonine of phospho-Rab8A and phospho-Rab10. More recently, phospho-Rabs have been found on lysosomal membranes within multi-protein assemblies involving TMEM55B and RILPL1.
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