Covid-19 X-Ray Image Detection using ResNet50 and VGG16 in Convolution Neural Network

COVID-19 is an outbreak of disease which is created by China. COVID-19 is originated by coronavirus (CoV), generally created mutation pattern with 'SARS-CoV2' or '2019 novel coronavirus'. It is declared by the World Health Organization of 2019 in December. COVID-19 is a contagious virus and contiguous disease that will create the morality of life. Even though it is detected in an early stage it can be incurable if the severity is more. The throat and nose samples are collected to identify COVID-19 disease. We collected the X-Ray images to identify the virus. We propose a system to diagnose the images using Convolutional Neural Network (CNN) models. Dataset used consists of both Covid and Normal X-ray images. Among Convolutional Neural Network (CNN) models, the proposed models are ResNet50 and VGG16. RESNET50 consists of 48 convolutional, 1 MaxPool, and Average Pool layers, and VGG16 is another convolutional neural network that consists of 16 deep layers. By using these two models, the detection of COVID-19 is done. This research is designed to help physicians for successful detection of COVID-19 disease at an early stage in the medical field. © 2022 IEEE.

A phenoxy-bridged trinuclear Ni(ii) complex: synthesis, structural elucidation and molecular docking with viral proteins

A novel phenoxy-bridged trinuclear nickel(ii) complex [Ni3(mu-L)2(bipy)3](1) (where H3L= (E)-2-hydroxy-N-(2-hydroxy-3,5-diiodophenyl)-3,5-diiodobenzohydrazonic acid, bipy = 2,2'-bipyridyl) has been designed and synthesized as a potential antivirus drug candidate. The trinuclear Ni(ii) complex [Ni3(mu-L)2(bipy)3](1) was fully characterized via single crystal X-ray crystallography. The unique structure of the trinuclear nickel(ii) complex crystallized in a trigonal crystal system with P3221 space group and revealed distorted octahedral coordination geometry around each Ni(ii) ion. The X-ray diffraction analysis established the existence of a new kind of trinuclear metal system containing nickel(ii)-nickel(ii) interactions with an overall octahedral-like geometry about the nickel(ii) atoms. The non-bonded Ni-Ni distance seems to be 3.067 and 4.455 A from the nearest nickel atoms. The detailed structural analysis and non-covalent supramolecular interactions are also investigated by single crystal structure analysis and computational approaches. Hirshfeld surfaces (HSs) and 2D fingerprint plots (FPs) have been explored in the crystal structure to investigate the intermolecular interactions. The preliminary analysis of redox and magnetic characterization was conducted using cyclic voltammetry measurements and a vibrating sample magnetometer (VSM), respectively. This unique structure shows good inhibition performance for SARS-CoV-2, Omicron and HIV viruses. For insight into the potential application of the Ni(ii) coordination complex as an effective antivirus drug, we have examined the molecular docking of the trinuclear Ni(ii) complex [Ni3(mu-L)2(bipy)3](1) with the receptor binding domain (RBD) from SARS-CoV-2 (PDB ID: 7MZF), Omicron BA.3 variant spike (PDB ID: 7XIZ), and HIV protease (PDB ID: 7WCQ) viruses. This structure shows good inhibition performance for SARS-CoV-2, Omicron S protein and HIV protease viruses;the binding energies (DELTAG) and the respective Ki/Kd (inhibition/dissociation constants) correlation values are -8.9 (2.373 muM or 2373 nM), -8.1 (1.218 muM or 1218 nM) and -7.9 (0.874 muM or 874 nM), respectively. The results could be used for rational drug design against SARS-CoV-2 Omicron variant and HIV protease viruses.Copyright © 2023 The Royal Society of Chemistry.

Multiple Fano Resonances in Plasmonic Waveguide Based Cavity and Detection of Pathogenic Virus

A technique is implemented for the generation of multiple Fano-resonances in a plasmonic waveguide based rectangular cavity. A rectangular cavity provides four Fano peaks which can further be increased to nine by inserting the metallic bars in it. The trapped surface plasmon polaritons by metallic bars cause the generation of multiple Fano peaks over the wavelength range of 450 nm - 1300 nm. The obtained response is validated through Fano profile and Fano shape parameter is calculated for each resonance peak. The performance of the proposed device is numerically studied as refractive index sensor and method for analyzing the detection of pathogenic virus like SARS-Cov-2 is reported. Out of nine Fano peaks, the best values of sensing performance indices are obtained with full-width, half-maxima of 1.7 nm, quality factor of 405, sensitivity of 1145.71 nm/RIU and figure of merit of 393.25 RIU-1. IEEE

DFT, molecular docking and ADME prediction of tenofovir drug as a promising therapeutic inhibitor of SARS-CoV-2 M-pro

In the present work, at first, DFT calculations were carried out to study the molecular structure of the tenofovir at B3LYP/MidiX level of theory and in the water as solvent. The HOMO/LUMO molecular orbitals, excitation energies and oscillator strengths of investigated drug were also calculated and presented. NBO analysis was performed to illustrate the intramolecular rehybridization and electron density delocalization. In the following, a molecular docking study was performed for screening of effective available tenofovir drug which may act as an efficient inhibitor for the SARS-CoV-2 M-pro. The binding energy value showed a good binding affinity between the tenofovir and SARS-CoV-2 Mpro with binding energy of-47.206 kcal/mol. Therefore, tenofovir can be used for possible application against the SARS-CoV-2 M-pro.

Novel Cuckoo Search-Based Metaheuristic Approach for Deep Learning Prediction of Depression

Depression is a common illness worldwide with doubtless severe implications. Due to the absence of early identification and treatment for depression, millions of individuals worldwide suffer from mental illnesses. It might be difficult to identify those who are experiencing mental health illnesses and to provide them with the early help that they need. Additionally, depression may be associated with thoughts of suicide. Currently, there are no clinically specific diagnostic biomarkers that can identify the severity and type of depression. In this research paper, the novel particle swarm-cuckoo search (PS-CS) optimization algorithm is proposed instead of the traditional backpropagation algorithm for training deep neural networks. The backpropagation algorithm is widely used for supervised learning in deep neural networks, but it has limitations in terms of convergence speed and the possibility of getting trapped in local optima. These problems were addressed by using a deep neural network architecture for depression detection tasks along with the PS-CS optimization technique. The PS-CS algorithm combines the strengths of both particle swarm optimization and cuckoo search algorithms, which allows for a more efficient and effective optimization of the network parameters. We also evaluated how well the suggested methods performed against the most widely used classification models, including (K-nearest neighbor) KNN, (support vector regression) SVR, and decision trees, as well as the most widely used deep learning models, including residual neural network (ResNet), visual geometry group (VGG), and simple neural network (LeNet). The findings show that the suggested method, PS-CS, in conjunction with the CNN model, outperformed all other models, achieving the maximum accuracy of 99.5%. Other models, such as the KNN, decision trees, and logistic regression, achieved lower accuracies ranging from 69% to 97%.

On ISGG's 30th Agenda: Legacy and Challenges

According to Robert E. Schofield, looking back to the golden age of Scientific Societies we discover that, from the middle of XVII to the XIX century, rather than academic institutions they were considered as the proper alma mater by scientists [1]. Over time, the general reform of the university has gradually reversed this state of things, with few exceptions. This paper proposes some brief reflections on being a Scientific Society (of Geometry and Graphics) nowadays (in its 30th year), including a glance at the present COVID-19 pandemic impact.

The Use of Public Space During the Epidemic

At the beginning of this article, it was shown that the indicators of the current so-called social distance determined by decision-makers at various stages of the epidemic development are imprecise, do not sufficiently take into account spatial relations, are unclear in public perception, and do not contain specific practical solutions. Therefore, this study undertakes the task of giving the term "social distancing"precise features, defined on the basis of geometry, and providing solutions in typical cases of the living space of the population. The geometry of the distribution of people in various situations of everyday life was considered: people standing during concerts or religious ceremonies, sitting during meals in collective catering rooms and participating in lectures, cultural, entertainment or sports events. In the latter group of tasks, the concept of building a people-distribution scheme must be adapted to the existing, arbitrary grid of real places of a lecture hall, theater hall, cinema, or stadium. The article contains some practical examples with comments and an evaluation of benefits, both in terms of ensuring safety and in terms of effective use of space. © 2023 Anna Marta Barańska et al., published by Sciendo.

Overcoming Chip Shortages: Low-Cost Open-Source Parametric 3-D Printable Solderless SOIC to DIP Breakout Adapters

The COVID-19 pandemic exposed the vulnerability of global supply chains of many products. One area that requires improved supply chain resilience and that is of particular importance to electronic designers is the shortage of basic dual in-line package (DIP) electronic components commonly used for prototyping. This anecdotal observation was investigated as a case study of using additive manufacturing to enforce contact between premade, off-the-shelf conductors to allow for electrical continuity between two arbitrary points by examining data relating to the stock quantity of electronic components, extracted from Digi-Key Electronics. This study applies this concept using an open hardware approach for the design, testing, and use of a simple, parametric, 3-D printable invention that allows for small outline integrated circuit (SOIC) components to be used in DIP package circuits (i.e., breadboards, protoboards, etc.). The additive manufacture breakout board (AMBB) design was developed using two different open-source modelers, OpenSCAD and FreeCAD, to provide reliable and consistent electrical contact between the component and the rest of the circuit and was demonstrated with reusable 8-SOIC to DIP breakout adapters. The three-part design was optimized for manufacturing with RepRap-class fused filament 3-D printers, making the AMBB a prime candidate for use in distributed manufacturing models. The AMBB offers increased flexibility during circuit prototyping by allowing arbitrary connections between the component and prototyping interface as well as superior organization through the ability to color-code different component types. The cost of the AMBB is CAD $0.066/unit, which is a 94% saving compared to conventional PCB-based breakout boards. Use of the AMBB device can provide electronics designers with an increased selection of components for through-hole use by more than a factor of seven. Future development of AMBB devices to allow for low-cost conversion between arbitrary package types provides a path towards more accessible and inclusive electronics design as well as faster prototyping and technical innovation.

Measures of Greenspace Exposure and Their Association to Health-Related Outcomes for the Periods before and during the 2020 Lockdown: A Cross-Sectional Study in the West of England

Greenspaces are argued to be one of the important features in the urban environment that impact the health of the population. Previous research suggested either positive, negative, or no associations between greenspaces and health-related outcomes. This paper takes a step backward to, first, explore different quantitative spatial measures of evaluating greenspace exposure, before attempting to investigate the relationship between those measures and health-related outcomes. The study uses self-reported health data from an online cross-sectional survey conducted for residents in the West of England. This yielded data of greenspace use, physical activity, wellbeing (ICECAP-A score), and connectedness to nature for 617 participants, divided into two sets: health outcomes for the period before versus during the 2020 lockdown. The study uses the participants' postcodes (provided in the survey) to calculate eleven spatial measures of greenspace exposure using the software ArcGIS Pro 2.9.5. A total of 88 multivariate regression models were run while controlling for eleven confounders of the participants' characteristics. Results inferred 57 significant associations such that six spatial measures of greenspace exposure (NDVI R200m, NDVI R300m, NDVI R500m, Network Distance to nearest greenspace access, Euclidean Distance to nearest greenspace access, and Euclidean Distance to nearest 0.5 ha doorstep greenspace access) have significant association to at least one of the four health-related outcomes, suggesting a positive impact on population health when living in greener areas or being closer to greenspaces. Moreover, there are further significant associations between the frequency of use of greenspaces and increasing physical activity or feeling more connected to nature. Still, the residents' patterns of using greenspaces significantly changed during versus before lockdown and has impacted the relationships between health outcomes and the greenspace exposure measures.

Computed Tomography Simulator (Ctlab)

University of Oulu and Oulu University of Applied Sciences have established a unique medical imaging teaching and testing laboratory in collaboration with Oulu University Hospital in a European Regional Development Fund -project. Virtually implemented medical imaging devices (CT, MRI, radiography) are unique features of the lab. Many of the virtual tools have been developed by the universities themselves. One of the virtual tools implemented during the project is the CTlab simulator, which can be widely used in computed tomography training for all professionals who use radiation in their work. The CTlab provides fast, comprehensive, and efficient solutions for numerical CT simulations with low hardware requirements. The simulator has been developed to introduce the basic operations and workflow behind the CT imaging modality and to illustrate how the polychromatic x-ray spectrum, various imaging parameters, scan geometry and CT reconstruction algorithm affect the quality of the detected images. Key user groups for the simulator include medical physics, engineering, and radiographer students. CTlab has been created with MATLAB's app designer feature. It offers its user the opportunity to select the virtual imaging target, to adjust CT imaging parameters (image volume, scan angles, detector element size and detector width, noise, algorithm/geometry specific parameters), to select specific scan geometry, to observe projection data from selected imaging target with polychromatic x-ray spectrum, and to select the specific algorithm for image reconstruction (FBP, least squares, Tikhonov regularization). The CTlab has so far been used at a postgraduate course on computed tomography technology with encouraging feedback from the students. At the course, teaching of CT modality were performed by using the simulator, giving students unlimited opportunity to practice the use of virtual imaging device and participate demonstrations remotely during the Covid-19 pandemic. Using CTlab in teaching enhances and deepens the learning experience in the physics behind computed tomography. CTlab can be used remotely (https://www.oulu.fi/fi/projektit/laaketieteellisen-kuvantamisen-opetus-ja-testilaboratorio-0), which makes teaching and training of CT scanner usage successful regardless of time and place. The simulator enables more illustrative and in-depth teaching and offers cost-effectiveness, versatility, and flexibility in education. CTlab can also be used to support teaching in special situations, such as during the Covid-19 pandemic when simulator is utilized remotely to perform teaching-related demonstrations flexibly and safely.Copyright © 2023 Southern Society for Clinical Investigation.

THE POTENTIAL OF MOBILE AUGMENTED REALITY AS A DIDACTIC AND PEDAGOGICAL SOURCE IN LEARNING GEOMETRY 3D

The COVID-19 pandemic in Indonesia requires teachers and students to perform learning activities online. Meanwhile, teachers use a variety of technology products in the classroom without paying attention to the didactic, pedagogical, and content aspects. This is due to time constraints and short learning adjustments that should be flexible to this pandemic. Therefore, this research provides an alternative by exploring the potential of augmented reality as a didactic and pedagogical source in learning geometry. An exploratory case study design was used to reveal this potential, while three mathematics teachers and twenty-six students from three schools in Indramayu Regency, Indonesia, participated in the research. Data from observations and documentation were checked, extracted, entered verbatim, and coded. The results of the interview data were analyzed using the content analysis method, while those from the geometry understanding test and student response questionnaires used descriptive analysis. Consequently, the research results showed that augmented reality was useful as an alternative didactic and pedagogical source of learning geometry during the COVID-19 pandemic. This conclusion was based on the reason, first characteristically augmented reality technology can be integrated with textbooks or certain learning methods. Second, the results of the geometry understanding test showed that there were more students who answered the questions correctly than the students who answered incorrectly. Third, the results of questionnaires and interviews showed that students had a positive attitude during the geometry learning process. Therefore, the researcher believes that the use of augmented reality is worthy of being an alternative didactic and pedagogical source and has the potential to be applied to other subjects both during the COVID-19 pandemic and after the COVID-19 pandemic © 2023,Journal of Technology and Science Education. All Rights Reserved.

Assessing the impact of hyperviscosity on stenosis shape in COVID patients

Recent studies have proven that the shape of the stenosis greatly affects the flow characteristics. The 2D rigid wall model examined in this research is analyzed mathematically using various principles and results of functional analysis for the existence and uniqueness of the solution. The model taken into consideration for the current study has also been used to examine the consequences of hyperviscosity in COVID-19 cases. The results of the investigation surmise that the maximum peak velocity of 3.155m/s and the minimum trough pressure of 7041.538Pa were manifested in the high slope geometry. Also, the number of spots over the upper wall of high slope geometry bearing the least wall shear stress was considerably high when compared to the other geometries. The study deduced that the arterial segment bearing dual high slope stenosis was more susceptible to new plaques, plaque ruptures, and hyper viscous syndrome. © 2023 THE AUTHORS

Study of Air Recirculation Zones in Shared Spaces

The Air borne transmission is a very big concern for highly infectious diseases like Covid-19 and other airborne diseases. A micro droplet and aerosol can be carried out in the air and can remain flowing in air over a distance in a confined space, leading to affecting high number of people getting prone to infection and it is very dangerous in enclosed spaces or shared spaces. Public places, shared facilities are the areas, where infectious aerosol can be present in the air for a long duration. Ventilation of closed spaces, shared spaces is the need of hour to have analysed and deep study in context of infectious airborne diseases. Introduction of fresh air into the enclosed environment at regular interval of times may lead to fast dilution of air present in the enclosed space. The prominent building codes and HVAC guidelines allows as to calculate ACPH (Air changes per hour) in an enclosed space as per the occupancy and flow rate. The age of air is the criteria to define the amount of air residing in the enclosed space when it enters the space till its exhaust from that space. The more the age of air in the particular area the more can be the infection probability among the occupants. It is predominant to study the airflow pattern caused due to ventilation which can be collaborated with age of air to know about the infection probability. Typically, a classroom geometry is assumed with inlet outlet boundary conditions where exhaust fan is playing a major role of displacement ventilation. Study of air recirculation zones and dead zones is the point of interest of this study. Computational fluid dynamics is the most powerful tool in the present era to study the air flow pattern in enclosed and shared spaces.Copyright © 2022, Anka Publishers. All rights reserved.

A Study on Digital Signature in Blockchain Technology

In the recent trends, block chain technology plays a vital role due to its secured methodology. Since many parts of the world severely affected by COVID pandemic situation, people used to perform more of digital transactions day by day. To provide more security for all online transactions, Block chain Technology is one of the solutions that many countries have started to utilize. Every block in a block chain should be validated and verified by the secured hash algorithms and digital signatures. Since Hacking is difficult in Block Chain Technology, due to its secure hash process, many people started using it for various applications. This article discusses about the working of Digital Signatures especially about Elliptic Curve Digital Signature Algorithm - ECDSA. Digital signatures are signatures done digitally for the purpose of security. ECDSA works on the mechanism of Elliptic Curve and Cryptography algorithms of Elliptic curve. The proposed research work has selected the private key as a random point, which is of type integer ranging between 1 and n-1 in Elliptic curve to sign documents. Then Public key is calculated by multiplying a point from elliptic curve with the Private key. Using this Public key, our digital signature is verified. This is much secured because no one can crack/hack private key. This process is used to verify digital transactions in the block chain technology. Our study helps researcher in block chain technologies to proceed ahead. © 2023 IEEE.

Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients

In this paper, we propose to quantitatively compare the loss of human lung health under the influence of the illness with COVID-19, based on the fractal-analysis interpretation of the chest-pulmonary CT pictures, in the case of small datasets, which are usually encountered in medical applications. The fractal analysis characteristics, such as fractal dimension and lacunarity measured values, have been utilized as an effective advisor to interpretation of pulmonary CT picture texture.

Parent's experience in remote learning during COVID-19 with digital and physical mathematical modelling

In reaction to the COVID-19 pandemic, the government of Luxembourg suspended in-school teaching and learning towards remote teaching. A survey conducted by the Ministry of Education after three weeks of confinement, showed that more than half of the parents faced difficulties when using remote teaching with their students. To tackle this new challenge, we adapted our research to the use of augmented reality, digital and physical mathematical modelling in remote mathematics education for elementary schools. The elementary school students (aged 5 to 12) created cultural artifacts (i.e., Easter egg cups) during the confinement. In this paper, we will describe mathematical modelling in remote teaching and further concentrate on parents' perspectives, who played an essential role in assisting their children. Moreover, we will discuss different didactical principles that emerged from the task design during the study through parents' eyes. Thus, understanding parents' perspectives became highly important in enabling us to improve task designs and related pedagogical approaches in remote teaching. The data collected in this study included semi-structured interviews with students, parents, and teachers as well as questionnaires and field notes. We followed an exploratory stance with our data analyses, primarily utilizing grounded theory (Corbin & Strauss, 1990, 2014) approaches. Through the insights we gained from our findings, we aim to explain how the parents perceived teaching and learning mathematical modelling in our experiments, how they scaffolded the given tasks, and what support they required and would need in future remote teaching. © The Author(s).

SAVES US: Suppression of Airborne Viral Epidemic Spread by Ultraviolet light barriers

Despite the gradual return to pre-pandemic conditions, the spreading of COVID-19 (SARS-CoV-2) left several open issues. Nowadays it is know that airborne infections, including COVID-19, are conveyed by particles having the size of >5 mum (droplets) and <5 mum (droplets nuclei), ejected by coughing and sneezing [1]. While droplets undergo to dehydration and precipitation, droplet nuclei persist in air for long time after their ejection, contributing to infection spreading. Actual prevention strategies are based on non-pharmaceutical interventions act to reduce droplets diffusion and spacing from Personal Protective Equipment, such as facial masks, and social distancing measure. Nevertheless, for the new endemic phase of COVID-19 the development of new strategies for airborne infections' containment becomes unavoidable. In this project, we propose a new device for the suppression of Airborne Viral Aerosols designed to work in situations with constrained geometries (e.g. public transportation, offices, waiting rooms etc.) not allowing social distancing. The device, devised to perform photokilling of viral aerosols in air in presence of humans, has its core in an UV illumination system operating at 222 nm. It is know from literature that UV radiation alters the genetic material of viruses and bacteria whose maximum absorption wavelengths are in the far-UV range (UVC, 100-280 nm), the most effective for sterilization [2]. Differently from the operative wavelength of most commercial systems (254 nm), the higher tissue absorption prevents the 222 nm radiation to travel over the very first epidermal layers [3] constituting a minor health risk for applications in presence of people. The device combines the UV illumination system with a vertical flux of air that conveys exhaled particles to the light source and controls humidity and temperature, crucial parameters for virus diffusion. After its development, the device prototype will be tested in model experiments. Initially, its safety will be verified by monitoring in particular the UVC-induced ozone production. Then, in vitro photokilling experiments will be performed in two steps: (i) on a layer of immobilized SARS-Cov-2 virus act to obtain optimal UV doses for an effective sterilization;(ii) on SARS-Cov-2 aerosol models. For this last experiment, a model viral aerosol miming the characteristics of cough and sneeze particles will be preliminary studied and supported by synthetic data to characterize the optical properties of the reference scenario. The resulting information will be crucial for the final design of the device itself. As a last step, we will test the device in in vivo experiments. An air flux, harvesting exhaled air by infected mice, will be illuminated by the device and will be sent to healthy mice. Finally, the infectiveness of exhaled air after the UV treatment will be evaluated, providing more information for further applications in the presence of humans.Copyright © 2023

Geometrical Tolerances Android Application Developed for Student for a Better Understanding of Orientation Tolerances According to the Latest ISO Standards

In the year 2021, a virtual reality training application has been developed, specifically for the Oculus Quest 2 headset, in order to allow the users to view and analyse 3D models for a wide variety of geometrical tolerances, tolerance zones and even the conformity condition and the datum features. This application allows the students to better understand the geometrical tolerances in accordance with the latest ISO GPS standards by using different 3D interactive models in order to highlight different types of geometrical tolerances and tolerance zones. In order to try to make the virtual reality training application more mobile and accessible for students, a mobile application, designed for the android operating system smartphones, has been developed. This application can facilitate better learning outcomes within the teaching-learning process by enabling the students to visualize a wide variety of 3D models representing different types of geometrical tolerances. Due to the dramatic evolution of technology in the past 20 years and the need to constantly keep up with it, the learning and teaching process suffered a massive change. The Covid pandemic has closed Universities all over the world and so, for the teaching process to continue, a sudden shift from traditional teaching to a more modern one involving the digital world was needed. Thanks for the fact that, nowadays, students are more inclined to use different types of mobile devices, the shift to the new learning paradigm has not left a great "scar” on student and teachers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Molecular Insights into Resveratrol and Its Analogs as SARS-CoV-2 (COVID-19) Protease Inhibitors

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is plaguing the entire world. Amidst the pandemic, research and development efforts are fo-cused on the challenges associated with the SARS-CoV-2 structure. Material(s) and Method(s): Efficient computational methodologies are applied to screen the available FDA-approved drugs/datasets/libraries to identify potent molecules. In the present study, we have carried out ab initio quantum chemical studies, including relativistic effects followed by molecular docking with the SARS-CoV-2 protease target by employing a tailor-made library consisting of molecular analogs of Resveratrol, a natural bioflavonoid. Result(s): The derived docking results were validated with ab initio quantum computations that in-cluded both density functional level (DFT) and Moller-Plesset second order perturbation theories (MP2). We found to be that Resveratrol and its analogs (R8 and R17) bind to the SARS-CoV-2 protease target. In addition to this, the computed IR spectrum is found in agreement with the report-ed experimental spectra for Resveratrol complexes and thus validates the modeling and reliability of proposed geometries. The solvation energies in the aqueous phase obtained using enhanced aug-cc-pVTZ basis sets confirm enhancement of bioavailability for Resveratrol through piperine, a natural alkaloid. Conclusion(s): The potential of the natural bioflavonoid Resveratrol and its analogs to be investigated through in vivo and in vitro SARS-CoV-2 protease models is concluded. The study investigated the potential of natural polyphenols as promising anti-viral therapeutics.Copyright © 2021 Bentham Science Publishers.

Anatomical and Vision-Guided Path Generation Method for Nasopharyngeal Swabs Sampling

Due to the global COVID-19 pandemic, there is a strong demand for pharyngeal swab sampling and nucleic acid testing. Research has shown that the positive rate of nasopharyngeal swabs is higher than that of oropharyngeal swabs. However, because of the high complexity and visual obscuring of the interior nasal cavity, it is impossible to obtain the sampling path information directly from the conventional imaging principle. Through the combination of anatomical geometry and spatial visual features, in this paper, we present a new approach to generate nasopharyngeal swabs sampling path. Firstly, this paper adopts an RGB-D camera to identify and locate the subject's facial landmarks. Secondly, the mid-sagittal plane of the subject's head is fitted according to these landmarks. At last, the path of the nasopharyngeal swab movement in the nasal cavity is determined by anatomical geometry features of the nose. In order to verify the validity of the method, the location accuracy of the facial landmarks and the fitting accuracy of mid-sagittal plane of the head are verified. Experiments demonstrate that this method provides a feasible solution with high efficiency, safety and accuracy. Besides, it can solve the problem that the nasopharyngeal robot cannot generate path based on traditional imaging principles. It also provides a key method for automatic and intelligent sampling of nasopharyngeal swabs, and it is of great clinical value to reduce the risk of cross-infection. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.