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Development and Application of a Fully Automated Chemiluminescence Enzyme Immunoassay for the Detection of Antibodies Against Porcine Circovirus 3 Cap.

Viruses

December 2024

State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Center for Swine Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China.

Porcine circovirus 3 (PCV3) is a small non-enveloped circovirus associated with porcine dermatitis and nephropathy syndrome (PDNS). It has occurred worldwide and poses a serious threat to the pig industry. However, there is no commercially available vaccine.

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Prehospital medical care is a major challenge for both civilian and military situations as resources are limited, yet critical triage and treatment decisions must be rapidly made. Prehospital medicine is further complicated during mass casualty situations or remote applications that require more extensive medical treatments to be monitored. It is anticipated on the future battlefield where air superiority will be contested that prolonged field care will extend to as much 72 h in a prehospital environment.

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Mitigating Data Leakage in a WiFi CSI Benchmark for Human Action Recognition.

Sensors (Basel)

December 2024

Nokia Bell Labs, 1082 Budapest, Hungary.

Human action recognition using WiFi channel state information (CSI) has gained attention due to its non-intrusive nature and potential applications in healthcare, smart environments, and security. However, the reliability of methods developed for CSI-based action recognition is often contingent on the quality of the datasets and evaluation protocols used. In this paper, we uncovered a critical data leakage issue, which arises from improper data partitioning, in a widely used WiFi CSI benchmark dataset.

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Endpoint Distribution Modeling-Based Capture Algorithm for Interfering Multi-Target.

Sensors (Basel)

December 2024

The State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China.

In physical spaces, pointing interactions cannot rely on cursors, rays, or virtual hands for feedback as in virtual environments; users must rely solely on their perception and experience to capture targets. Currently, research on modeling target distribution for pointing interactions in physical space is relatively sparse. Area division is typically simplistic, and theoretical models are lacking.

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This study presents a blockchain-based traceability system designed specifically for the olive oil supply chain, addressing key challenges in transparency, quality assurance, and fraud prevention. The system integrates Internet of Things (IoT) technology with a decentralized blockchain framework to provide real-time monitoring of critical quality metrics. A practical web application, linked to the Ethereum blockchain, enables stakeholders to track each stage of the supply chain via tamper-proof records.

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