The blockchain-enabled internet of medical things (IoMT) is an emerging paradigm that could provide strong trust establishment and ensure the traceability of data sharing in the IoMT networks. One of the fundamental building blocks for Blockchain is Elliptic Curve Digital Signature Algorithm (ECDSA). Nevertheless, when processing a large number of transactions, the verification of multiple signatures will incur cumbersome overhead to the nodes in Blockchain. Although batch verification is able to provide a promising approach that verifies multiple signatures simultaneously and efficiently, the upper bound of batch size is limited to small-scale and the efficiency will drop rapidly as the batch size grows in the state-of-the-art ECDSA batch schemes. Meanwhile, most of the existing researches only focus on improving the efficiency of batch verification algorithms in various cryptosystem while ignoring the identification of invalid signatures, which could cause severe performance degradation when the batch verification fails. Motivated by these observations, this paper proposes an efficient and large-scale batch verification scheme with group testing technology based on ECDSA. The application of the presented protocols in Bitcoin and Hyperledger Fabric has been analyzed as supportive and effective. When the batch verification returns a false result, we utilize group testing technology to improve the efficiency of identifying invalid signatures. Comprehensive simulation results demonstrate that our protocol outperforms the related ECDSA batch verification schemes.
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http://dx.doi.org/10.1109/JBHI.2021.3112693 | DOI Listing |
J Immunother Cancer
January 2025
Providence Portland Medical Center, Portland, Oregon, USA.
Objectives: Multiplex immunohistochemistry and immunofluorescence (mIHC/IF) are emerging technologies that can be used to help define complex immunophenotypes in tissue, quantify immune cell subsets, and assess the spatial arrangement of marker expression. mIHC/IF assays require concerted efforts to optimize and validate the multiplex staining protocols prior to their application on slides. The best practice guidelines for staining and validation of mIHC/IF assays across platforms were previously published by this task force.
View Article and Find Full Text PDFJ Vet Res
December 2024
Department of Omics Analysis, National Veterinary Research Institute, 24-100 Puławy, Poland.
Introduction: In Europe, veterinary vaccines are strictly controlled by the Official Medicines Control Laboratories (OMCLs) of the General European OMCL Network, coordinated by the European Directorate for the Quality of Medicines & HealthCare. Despite a meticulous verification programme for immunological veterinary medicinal products (IVMPs), the products' genomic composition has not yet been subject to evaluation in veterinary pharmacy.
Material And Methods: A study was carried out on Poland's poultry vaccines containing the infectious bronchitis virus which have the greatest market penetration.
J Clin Lab Anal
December 2024
Department of Laboratory Medicine at the Fourth Affiliated Hospital, Harbin Medical University, Harbin, China.
Background: To establish a dual immunoassay based on inductively coupled plasma mass spectrometry (ICP-MS) with stable element labeling antibodies for the simultaneous detection of alpha-fetoprotein (AFP) and prostate-specific antigen (PSA) in serum and evaluate its performance and clinical sample validation.
Methods: The immunoassay system based on the double antibody sandwich method was established using magnetic beads as solid-phase carriers and rare earth elements europium (Eu) and samarium (Sm) as element tags. The test conditions were optimized.
Network
December 2024
Department of Electronics and Communication Engineering, Dronacharya Group of Institutions, Greater Noida, UP, India.
Speaker verification in text-dependent scenarios is critical for high-security applications but faces challenges such as voice quality variations, linguistic diversity, and gender-related pitch differences, which affect authentication accuracy. This paper introduces a Gender-Aware Siamese-Triplet Network-Deep Neural Network (ST-DNN) architecture to address these challenges. The Gender-Aware Network utilizes Convolutional 2D layers with ReLU activation for initial feature extraction, followed by multi-fusion dense skip connections and batch normalization to integrate features across different depths, enhancing discrimination between male and female speakers.
View Article and Find Full Text PDFPLoS One
December 2024
Faculty of Data Science and Information Technology, INTI International University, Nilai, Malaysia.
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