Contactless non-invasive method to identify abnormal tongue area using K-mean and problem identification in COVID-19 scenario

Due to the spread of COVID-19 all around the world, there is a need of automatic system for primary tongue ulcer cancerous cell detection since everyone do not go to hospital due to the panic and fear of virus spread. These diseases if avoided may spread soon. So, in such a situation, there is global need of improvement in disease sensing through remote devices using non-invasive methods. Automatic tongue analysis supports the examiner to identify the problem which can be finally verified using invasive methods. In automated tongue analysis image quality, segmentation of the affected region plays an important role for disease identification. This paper proposes mobile-based image sensing and sending the image to the examiner, if examiner finds an issue in the image, the examiner may guide the user to go for further treatment. For segmentation of abnormal area, K-mean clustering is used by varying its parameters.Copyright © 2022 Inderscience Enterprises Ltd.

Reverse Genetics of Avian Coronavirus Infectious Bronchitis Virus

We have developed a reverse genetics system for the avian coronavirus infectious bronchitis virus (IBV) in which a full-length cDNA corresponding to the IBV genome is inserted into the vaccinia virus genome under the control of a T7 promoter sequence. Vaccinia virus as a vector for the full-length IBV cDNA has the advantage that modifications can be introduced into the IBV cDNA using homologous recombination, a method frequently used to insert and delete sequences from the vaccinia virus genome. Here, we describe the use of transient dominant selection as a method for introducing modifications into the IBV cDNA;that has been successfully used for the substitution of specific nucleotides, deletion of genomic regions, and the exchange of complete genes. Infectious recombinant IBVs are generated in situ following the transfection of vaccinia virus DNA, containing the modified IBV cDNA, into cells infected with a recombinant fowlpox virus expressing T7 DNA dependant RNA polymerase. Copyright © Springer Science+Business Media New York 2016.

Contactless non-invasive method to identify abnormal tongue area using K-mean and problem identification in COVID-19 scenario

Due to the spread of COVID-19 all around the world, there is a need of automatic system for primary tongue ulcer cancerous cell detection since everyone do not go to hospital due to the panic and fear of virus spread. These diseases if avoided may spread soon. So, in such a situation, there is global need of improvement in disease sensing through remote devices using non-invasive methods. Automatic tongue analysis supports the examiner to identify the problem which can be finally verified using invasive methods. In automated tongue analysis image quality, segmentation of the affected region plays an important role for disease identification. This paper proposes mobile-based image sensing and sending the image to the examiner, if examiner finds an issue in the image, the examiner may guide the user to go for further treatment. For segmentation of abnormal area, K-mean clustering is used by varying its parameters.

High Sensitivity and Label-Free Detection of the SARS-CoV-2 S1 Protein Using a Terahertz Meta-Biosensor

High sensitivity and quantitative detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein (S protein) is of great significance for the diagnosis and treatment of coronaviruses. Here, we utilized terahertz time-domain spectroscopy (THz-TDS) integrated with a metamaterial (MM)-based biosensor and biological modification technology to demonstrate a high accuracy and label-free detection of the SARS-CoV-2 S1 protein by comparing the changes of the dielectric environment before and after binding the S1 protein. To confirm the sensing characteristics observed in the experiments and provide a further insight into the sensing mechanisms, we performed numerical simulations through varying the thickness, quantity, position, and refractive index of analyte aggregates. The sensitivity increases with the increase of the number of gaps and the amount of analyte near the gaps, which convincingly proves that the frequency shift and sensing performance are strongly influenced by the field enhancement and near-field coupling at the gap area. Copyright © 2022 Niu, Zhang and Yang.

Remote testing: Sensory test during Covid-19 pandemic and beyond.

Restrictions adopted by many countries in 2020 due to Covid-19 pandemic had severe consequences on the management of sensory and consumer testing that strengthened the tendency to move data collection out of the laboratory. Remote sensory testing, organized at the assessor's home or workplace and carried out under the live online supervision of the panel leader, represents a trade-off between adequate control and the convenience of conducting testing out of the lab. The Italian Sensory Science Society developed the "Remote sensory testing" research project aimed at testing the effectiveness and validity of the sensory tests conducted remotely through a comparison with evaluations in a classical laboratory setting. Guidelines were developed to assist panel leaders in setting up and controlling the evaluation sessions in remote testing conditions. Different methods were considered: triangle and tetrad tests, Descriptive Analysis and Temporal Dominance of Sensations tests, all of which involved trained panels, and Check-All-That-Apply and hedonic tests with consumers. Remote sensory testing provided similar results to the lab testing in all the cases, with the exception of the tetrad test run at work. Findings suggest that remote sensory testing, if conducted in strict compliance with specifically developed sensory protocols, is a promising alternative to laboratory tests that can be applied with both trained assessors and consumers even beyond the global pandemic.