•Mueller reflected polarimetric imaging detects SARS-CoV-2 models in dry droplets.•Initial proof-of-concept, two synthetic viral models in artificial saliva.•Polarization features quantified at ...per-pixel and per-droplet levels.•Potential to improve fast, non-contact analysis of multiple samples simultaneously.
To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging.
Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380–420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples.
The angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations.
Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.
Obstructive failure of implanted shunts is the most common complication in the treatment of hydrocephalus. Biological material and debris accumulate in the inner walls of the valve and catheters ...block the normal flow of the drained cerebrospinal fluid causing severe symptoms with high morbidity and mortality. Unfortunately, at present, there is no effective preventive protocol or cleaning procedure available.
To assess whether externally applied, focused ultrasound beams can be used to resuspend deposits accumulated in brain shunts safely.
A computational model of an implanted brain shunt was implemented to test the initial design parameters of a system comprising several ultrasound transducers. Under laboratory conditions, configurations with 3 and 4 transducers were arranged in a triangle and square pattern with their radiation axis directed towards a target model of the device, 2 catheters and a brain shunt filled with water and deposited graphite powder. The ultrasound beams were then concentrated on the device across a head model.
The computational model revealed that by using only 3 transducers, the acoustic field intensity on the valve was approximately twice that on the brain surface suggesting that acoustic cavitation could be selectively achieved. Resuspension of graphite deposits inside the catheters and the valve were then physically demonstrated and video-recorded with no temperature increase.
The technology presented here has the potential to be used routinely as a noninvasive, preventive cleaning procedure to reduce the likelihood of obstruction-related events in patients with hydrocephalus treated with an implanted shunt.
Abstract
Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) ...spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·
$$\upmu$$
μ
L
−1
. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.
This study proposes the use of an Autonomous Surface Vehicle (ASV) fleet with water quality sensors for efficient patrolling to monitor water resource pollution. This is formulated as a Patrolling ...Problem, which consists of planning and executing efficient routes to continuously monitor a given area. When patrolling Lake Ypacaraí with ASVs, the scenario transforms into a Partially Observable Markov Game (POMG) due to unknown pollution levels. Given the computational complexity, a Multi-Agent Deep Reinforcement Learning (MADRL) approach is adopted, with a common policy for homogeneous agents. A consensus algorithm assists in collision avoidance and coordination. The work introduces exploration and reinforcement phases to the patrolling problem. The Exploration Phase aims at homogeneous map coverage, while the Intensification Phase prioritizes high polluted areas. The innovative introduction of a transition variable, <inline-formula> <tex-math notation="LaTeX">\nu </tex-math></inline-formula>, efficiently controls the transition from exploration to intensification. Results demonstrate the superiority of the method, which outperforms a Single-Phase (trained on a single task) Deep Q-Network (DQN) by an average of 17% on the intensification task. The proposed multitask learning approach with parameter sharing, coupled with DQN training, outperforms Task-Specific DQN (two DQNs trained on separate tasks) by 6% in exploration and 13% in intensification. It also outperforms the heuristic-based Lawn Mower Path Planner (LMPP) and Random Wanderer Path Planner (RWPP) algorithms, by 35% and 20% on average respectively. Additionally, it outperforms a Particle Swarm Optimization-based Path Planner (PSOPP) by an average of 26%. The algorithm demonstrates adaptability in unforeseen scenarios, giving users flexibility in configuration.
This paper focuses on the steady-state response of existing methods for computing the reference current of active power filters. For each class of methods, the main source of discrepancy between the ...load harmonic current and the computed reference current is identified and the frequency spectrum of the resulting error is analytically determined. Although this topic has been partially addressed in previous publications, the proposed frequency-domain approach provides valuable qualitative information about how the errors are produced and distributed, which is masked when the analysis is carried out in the time domain. First, the frequency-domain formulation is separately presented for each method. Then, a comparison of the resulting errors is performed on a case study. Finally, some experimental results are given to validate the proposed frequency-domain analysis.
Objective: To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. Methods: Two ...SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were preparations in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-{\mu}L droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry of 87 samples at 405 nm and 514 nm. A polarimetric camera was used for simultaneous imaging of several samples under 380-420 nm illumination at angles similar to those of maximal DLP. A per-pixel image analysis included quantification and combination of polarization feature descriptors in other 475 samples. Results: The angles (from sample surface) of maximal DLP were 3 degrees for 405 nm and 6 degrees for 514 nm. Similar viral particles that differ only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned from polarimetric image analysis at 10-degree and 15-degree configurations. Conclusion: Polarimetric imaging in the visible spectrum has the potential for non-contact, reagent-free detection of viruses in multiple dry fluid residues simultaneously. Further analysis including real SARS-CoV-2 in human samples -- particularly, fresh saliva -- are required. Significance: Polarimetric imaging under visible light could contribute to fast, cost-effective screening of SARS-CoV-2 and other pathogens.
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