An ultrasensitive electrochemiluminescence immunosensor for SARS-CoV-2 nucleocapsid protein detection based on signal amplification strategy of DMSN@QDs

Based on signal amplification strategy of dendritic mesoporous silica nanospheres loaded with CdSe/ZnS quantum dots (DMSN@QDs), an ultrasensitive electrochemiluminescence (ECL) immunosensor with magnetic separation was constructed for the detection of SARS-CoV-2 nucleocapsid protein (NP). DMSN, a mesoporous material with abundant radial pores, large specific surface area and high porosity, can increase the loading capacity of QDs and hinder their aggregation as the nanocarrier. DMSN@QDs with good ECL efficiency were used as signal labels to construct a sandwich immunosensor. The designed ECL immunosensor displayed a good linear relationship for NP concentrations ranging from 0.005 ng mL(-1) to 50 ng mL(-1), with a limit of detection of 3.33 pg mL(-1). The ECL immunosensor was successfully applied to detect NP in human serum samples with satisfactory recovery. This strategy provided a new method for detecting NP and expanded the application field of DMSN.

Extending Learning and Collaboration in Quantum Information with Internet Support: A Future Perspective on Research Education beyond Boundaries, Limitations, and Frontiers

Quantum information is an emerging scientific and technological discipline attracting a growing number of professionals from various related fields. Although it can potentially serve as a valuable source of skilled labor, the Internet provides a way to disseminate information about education, opportunities, and collaboration. In this work, we analyzed, through a blended approach, the sustained effort over 12 years to involve science and engineering students in research education and collaboration, emphasizing the role played by the Internet. Three main spaces have been promoted, workshops, research stays, and a minor, all successfully developed through distance education in 2021-2022, involving students from various locations in Mexico and the United States. The success of these efforts was measured by research-oriented indicators, the number of participants, and their surveyed opinions. The decisive inclusion of the Internet to facilitate the blended approach has accelerated the boost in human resources and research production. During the COVID-19 pandemic, the Internet played a crucial role in the digital transformation of this research education initiative, leading to effective educative and collaborative experiences in the "New Normal".

Enhanced BB84 quantum cryptography protocol for secure communication in wireless body sensor networks for medical applications.

Wireless body sensor network (WBSN) is an interdisciplinary field that could permit continuous health monitoring with constant clinical records updates through the Internet. WBAN is a special category of wireless networks. Coronavirus disease 2019 (COVID-19) pandemic creates the situation to monitor the patient remotely following the social distance. WBSN provides the way to effectively monitor the patient remotely with social distance. The data transmitted in WBSN are vulnerable to attacks and this is necessary to take security procedure like cryptographic protocol to protect the user data from attackers. Several physiological sensors are implanted in the human body that will collect various physiological updates to monitor the patient's healthcare data remotely. The sensed information will be transmitted wirelessly to doctors all over the world. But it has too many security threats like data loss, masquerade attacks, secret key distribution problems, unauthorized access, and data confidentiality loss. When any attackers are attacking the physiological sensor data, there is a possibility of losing the patient's information. The creation, cancellation, and clinical data adjustment will produce a mass effect on the healthcare monitoring system. Present-day cryptographic calculations are highly resistant to attacks, but the only weak point is the insecure movement of keys. In this paper, we look into critical security threats: secure key distribution. While sharing the secret key between communicating parties in the wireless body sensor networks in the conventional method like via phone or email, the attackers will catch the private key. They can decrypt and modify more sensitive medical data. It can cause a significant effect like death also. So need an effective, secure key distribution scheme for transmission of human body health related data to medical professional through wireless links. Moreover, a new enhanced BB84 Quantum cryptography protocol is proposed in this paper for sharing the secret key among communicating parties in a secure manner using quantum theory. Besides, a bitwise operator is combined with quantum concepts to secure the patient's sensed information in the wireless environment. Instead of mail and phone via sharing secret key, quantum theory with the bitwise operator is used here. Therefore, it is not possible to hack the secret key of communication. The body sensor's constrained assets as far as battery life, memory, and computational limit are considered for showing the efficiency of the proposed security framework. Based on experimental results, it is proven that the proposed algorithm EBB84QCP provides high secure key distribution method without direct sharing the secret key and it used the quantum mechanism and bitwise operator for generating and distributing secret key value to communicating parties for sensitive information sharing in the wireless body sensor networks.

Remora Namib Beetle Optimization Enabled Deep Learning for Severity of COVID-19 Lung Infection Identification and Classification Using CT Images.

Coronavirus disease 2019 (COVID-19) has seen a crucial outburst for both females and males worldwide. Automatic lung infection detection from medical imaging modalities provides high potential for increasing the treatment for patients to tackle COVID-19 disease. COVID-19 detection from lung CT images is a rapid way of diagnosing patients. However, identifying the occurrence of infectious tissues and segmenting this from CT images implies several challenges. Therefore, efficient techniques termed as Remora Namib Beetle Optimization_ Deep Quantum Neural Network (RNBO_DQNN) and RNBO_Deep Neuro Fuzzy Network (RNBO_DNFN) are introduced for the identification as well as classification of COVID-19 lung infection. Here, the pre-processing of lung CT images is performed utilizing an adaptive Wiener filter, whereas lung lobe segmentation is performed employing the Pyramid Scene Parsing Network (PSP-Net). Afterwards, feature extraction is carried out wherein features are extracted for the classification phase. In the first level of classification, DQNN is utilized, tuned by RNBO. Furthermore, RNBO is designed by merging the Remora Optimization Algorithm (ROA) and Namib Beetle Optimization (NBO). If a classified output is COVID-19, then the second-level classification is executed using DNFN for further classification. Additionally, DNFN is also trained by employing the newly proposed RNBO. Furthermore, the devised RNBO_DNFN achieved maximum testing accuracy, with TNR and TPR obtaining values of 89.4%, 89.5% and 87.5%.

Plastic Waste-Derived Carbon Dots: Insights of Recycling Valuable Materials Towards Environmental Sustainability.

Carbon dots (CDs) or carbon quantum dots (CQDs) have emerged as rising stars in the carbon family due to their diverse applications in various fields. CDs are spherical particles with a well-distributed size of less than 10 nm. Functional CDs are promising nanomaterials with low toxicity, low cost, and enormous applications in the field of bioimaging, optoelectronics, photocatalysis, and sensing. Plastic is non-biodegradable and hazardous to the environment, however extremely durable and used in abundance. During the COVID-19 pandemic, the use of plastic waste, particularly masks, goggles, face shields, and shoe cover, has increased tremendously. It needs to be recycled in a productive way as plastic wastes take hundreds or thousands of years to degrade naturally. The conversion of plastic waste into magnificent CDs has been reported as one of the key alternatives for environmental sustainability and socio-economic benefits. In this review, synthetic routes for the conversion of plastic wastes into CDs utilizing hydrothermal, solvothermal, pyrolysis, flash joule heating, and characterization of these CDs using different techniques, such as Fourier-transform infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and transmission electron microscope, have been discussed. Furthermore, potential applications of these plastic-derived CDs in sensing, catalysis, agronomics, and LED lights are summarized herein.

Synthesis Strategy of Tetrapyrrolic Photosensitizers for Their Practical Application in Photodynamic Therapy

This review presents a wide range of tetrapyrrole photosensitizers used for photodynamic therapy (PDT), antimicrobial photodynamic therapy, photoinactivation of pathogens. Methods of synthesis and design of new photosensitizers with greater selectivity of accumulation in tumor tissue and increased photoinduced antitumor activity are considered. The issues of studying the properties of new photosensitizers, their photoactivity, the ability to generate singlet oxygen, and the possibility of using targeted photodynamic therapy in clinical practice are discussed. The review examines the work on PDT by national and foreign researchers.

IARD 2022 The 13th Biennial Conference on Classical and Quantum Relativistic Dynamics of Particles and Fields

PrefaceThe International Association for Relativistic Dynamics was organized in February 1998 in Houston, Texas, with John R. Fanchi as president. Although the subject of relativistic dynamics has been explored, from both classical and quantum mechanical points of view, since the work of Einstein and Dirac, its most striking development has been in the framework of quantum field theory. The very accurate calculations of spectral and scattering properties, for example, of the anomalous magnetic moment of the electron and the Lamb shift in quantum electrodynamics, and many qualitative features of the strong and electroweak interactions, demonstrate the very great power of description achieved in this framework. Yet, many fundamental questions remain to be clarified, such as the structure of classical relativistic dynamical theories on the level of Hamilton and Lagrange in Minkowski space as well as on the curved manifolds of general relativity. There, moreover, remain the important questions of the covariant classical description of systems at high energy for which particle production effects are not large, such as discussed in Synge's book, The Relativistic Gas, and in Balescu's book on relativistic statistical mechanics, and the development of a consistent single and many body relativistic quantum theory. In recent years, highly accurate telescopes and advanced facilities for computation have brought a high level of interest in cosmological problems, such as the structure of galaxies (dark matter) and the apparently anomalous expansion of the universe (dark energy). Some of the papers reported here deal with these problems, as well as other fundamental related issues.It was for this purpose, to bring together researchers from a wide variety of fields, such as particle physics, astrophysics, cosmology, foundations of relativity theory, and mathematical physics, with a common interest in relativistic dynamics, to investigate fundamental questions of this type, that this Association was founded. The second meeting took place in 2000 at Bar Ilan University in Israel, the third, in 2002, at Howard University in Washington, D.C., and the fourth, in 2004, in Saas Fee, Switzerland. Subsequent meeting took place in 2006 at the University of Connecticut Storrs, in 2008 at Aristotle University of Thessalonica, in 2010 at National Dong Hwa University, Hualien, Taiwan, in 2012 at the Galileo Galilei Institute for Theoretical Physics (GGI) in Florence, in 2014 as the University of Connecticut Storrs, Connecticut, in 2016 at Jožef Stefan Institute in Ljubljana, Slovenia, and in 2018 in Mérida, Yucatán, Mexico, under the sponsorship of the Instituto Politécnic Nacional. The 2020 meeting, planned for Czech Technical University in Prague, was successfully held online at the height of the Covid-19 pandemic, and the physical meeting in Prague was delayed to 2022.The 2022 meeting forms the basis for the Proceedings that are recorded in this issue of the Journal of Physics: Conference Series. Along with the work of some of the founding and newer but already much engaged members of the Association, we were fortunate to have lecturers from application areas that provided strong challenges for further developments in quantum field theory, cosmological problems, and in the dynamics of systems subject to accelerations and the effects of general relativity. Topics treated in this issue include studies in general relativity and astrophysics, relativistic dynamics and electrodynamics, quantum theory and particles, and foundations of relativistic dynamics.This first physical meeting of the Covid-19 era took place 6 - 9 June at Czech Technical University in Prague, as originally planned for 2020. The meeting was divided into seven plenary sessions over four days. As a result of continued travel restrictions in some areas, a small number of talks were delivered by videoconferencing. The papers presented in this volume represent extensions and refinements to the conference talks, building on feedback and discussions associated with the lect re . We once again express our gratitude to Czech Technical University, and especially the local conference chair Petr Jizba, for their generous hospitality.List of Scientific Advisory Committee, International Organizing Committee and Editorial Board of the proceedings, Dedication are available in this Pdf.

Estimation of infection fields and pathways for SARS-CoV-2 and its variant based on the relationship among dose-response function parameter, quantum emission rate, and basic reproductive number

The theoretical model of the relationship among dose-response function parameters, quantum emission rate, and basic reproductive number for SARS-CoV-2 was constructed. Then, using this model, infection fields and pathways for SARS-CoV-2 and its variant were estimated. The parameters of the time activity, the number of contacts by the microenvironments and groups, and the COVID-19 risk from multiple pathways in near and far fields were used. Consequently, in lower transmissibility, droplet spray transmission in the near field was dominant, whereas in higher transmissibility, transmission from inhalation of smaller aerosols in the far field was dominant. Moreover, it was suggested that transmission from droplet spray, indirect contacts, and inhalation of smaller aerosols in the near field and inhalation of smaller aerosols in the far field was dominant for the wild-type strain, while transmission from inhalation of smaller aerosols in the far field were dominant for the Delta variant. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Evaluating the quality consistency of antiviral oral liquid by high-performance liquid chromatography five-wavelength matched average fusion fingerprint combined with electrochemical fingerprint and ultraviolet spectral quantum fingerprint.

The antiviral oral liquid (AOL) was an antiviral drug currently in clinical trials against coronavirus disease 2019. This study aimed to improve its quality consistency evaluation method using fingerprint techniques from several aspects. First, the five-wavelength matched average fusion fingerprint (FMAFFP) for HPLC, electrochemical fingerprint (ECFP), and ultraviolet spectral quantum fingerprint (UVFP) was established for 22 samples, respectively. Their quality was then assessed using the average linear quantitative fingerprint method, and 22 samples were classified into eight quality grades. OPLS and PCA were then used further to explore the characteristic parameters of these three fingerprints. Five compounds were quantified simultaneously for the first time, and then the relationship between the average linear quantitative similarity (PL) and the sum of the five quantitative components (P5c) was investigated. A linear correlation (r ≥ 0.9735) between PL and P5c suggested that PL may be used to predict chemical content. Finally, to investigate the antioxidant potential of the AOL, correlation analyses were performed for FMAFFP peaks-PEC and UVFP peaks-PEC, respectively, where the PEC value was defined as the quantitative similarity of ECFP. The Pearson correlation coefficient and gray correlation analysis were consistent, allowing us to initially explore the antioxidant capacity of the unidentified components of the samples. This study researched AOL using multidimensional fingerprints to provide a comprehensive and reliable method for quality consistency control of herbal compound preparations.

Carbon Nanomaterials-Based Screen-Printed Electrodes for Sensing Applications.

Electrochemical sensors consisting of screen-printed electrodes (SPEs) are recurrent devices in the recent literature for applications in different fields of interest and contribute to the expanding electroanalytical chemistry field. This is due to inherent characteristics that can be better (or only) achieved with the use of SPEs, including miniaturization, cost reduction, lower sample consumption, compatibility with portable equipment, and disposability. SPEs are also quite versatile; they can be manufactured using different formulations of conductive inks and substrates, and are of varied designs. Naturally, the analytical performance of SPEs is directly affected by the quality of the material used for printing and modifying the electrodes. In this sense, the most varied carbon nanomaterials have been explored for the preparation and modification of SPEs, providing devices with an enhanced electrochemical response and greater sensitivity, in addition to functionalized surfaces that can immobilize biological agents for the manufacture of biosensors. Considering the relevance and timeliness of the topic, this review aimed to provide an overview of the current scenario of the use of carbonaceous nanomaterials in the context of making electrochemical SPE sensors, from which different approaches will be presented, exploring materials traditionally investigated in electrochemistry, such as graphene, carbon nanotubes, carbon black, and those more recently investigated for this (carbon quantum dots, graphitic carbon nitride, and biochar). Perspectives on the use and expansion of these devices are also considered.

Accessing isotopically labeled proteins containing genetically encoded phosphoserine for NMR with optimized expression conditions

Phosphoserine (pSer) sites are primarily located within disordered protein regions, making it difficult to experimentally ascertain their effects on protein structure and function. Therefore, the production of 15N- (and 13C)-labeled proteins with site-specifically encoded pSer for NMR studies is essential to uncover molecular mechanisms of protein regulation by phosphorylation. While genetic code expansion technologies for the translational installation of pSer in Escherichia coli are well established and offer a powerful strategy to produce site-specifically phosphorylated proteins, methodologies to adapt them to minimal or isotope-enriched media have not been described. This shortcoming exists because pSer genetic code expansion expression hosts require the genomic DELTAserB mutation, which increases pSer bioavailability but also imposes serine auxotrophy, preventing growth in minimal media used for isotopic labeling of recombinant proteins. Here, by testing different media supplements, we restored normal BL21(DE3) DELTAserB growth in labeling media but subsequently observed an increase of phosphatase activity and mis-incorporation not typically seen in standard rich media. After rounds of optimization and adaption of a high-density culture protocol, we were able to obtain >=10 mg/L homogenously labeled, phosphorylated superfolder GFP. To demonstrate the utility of this method, we also produced the intrinsically disordered serine/arginine-rich region of the SARS-CoV-2 Nucleocapsid protein labeled with 15N and pSer at the key site S188 and observed the resulting peak shift due to phosphorylation by 2D and 3D heteronuclear single quantum correlation analyses. We propose this cost-effective methodology will pave the way for more routine access to pSer-enriched proteins for 2D and 3D NMR analyses. GCE4All Biomedical Technology Development and Dissemination Center was supported by National Institute of General Medical Science, OSU NMR Facility funded in part by the National Institutes of Health, the Medical Research Foundation at OHSU and the Collins Medical Trust, National Science Foundation EAGER, and by the M. J. Murdock Charitable Trust.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Demystifying quantum blockchain for healthcare

The healthcare industry and the battle against the COVID‐19 pandemic are two areas where blockchain technology might be useful. In this study, blockchain's significance is examined. Blockchain technology and related procedures will be used in future healthcare systems for collecting sensor data, automated patient monitoring, and safe data storage. Because it can store a large amount of data in a dispersed and secure way and provide access whenever and wherever it is needed, this technology greatly simplifies the process of carrying out activities. The advantages of quantum computing, such as the speed with which patients can be found and monitored, may be fully used with the help of quantum blockchain. Quantum blockchain is an additional resource that may be used to safeguard the veracity, integrity, and availability of stored information. Combining quantum computing with blockchain technology may allow faster and more secure medical information processing. In this research, the authors examine the potential uses of blockchain and quantum technology in the healthcare industry. Quantum technologies, blockchain‐based technologies, and other cutting‐edge ICTs (such as ratification intelligence, machine learning, drones, and so on) were investigated and contrasted in this article. [ FROM AUTHOR] Copyright of Security & Privacy is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Structural and Computational Studies of Cobalt(II) and Copper(II) Complexes with Aromatic Heterocyclic Ligand

Two coordination complexes, a cobalt(II) complex tris(1,10-phenanthroline)-cobalt perchlorate hydrate, [Co(phen)3]·(ClO4)2·H2O(1), and a copper(II) complex tris(1,10-phenanthroline)-copper perchlorate 4-bromo-2-{[(naphthalene-1-yl)imino]methyl}phenol hydrate, [Cu(phen)3]·(ClO4)2·HL·[O] (2), [where, phen = 1,10-phenathroline as aromatic heterocyclic ligand, HL = 4-bromo-2-((Z)-(naphthalene-4-ylimino) methyl) phenol] have been synthesized and structurally characterized. Single crystal X-ray analysis of both complexes has revealed the presence of a distorted octahedral geometry around cobalt(II) and copper(II) ions. density functional theory (DFT)-based quantum chemical calculations were performed on the cationic complex [Co(phen)3]2+ and copper(II) complex [Cu(phen)3]2+ to get the structure property relationship. Hirshfeld surface and 2-D fingerprint plots have been explored in the crystal structure of both the metal complexes. To find potential SARS-CoV-2 drug candidates, both the complexes were subjected to molecular docking calculations with SARS-CoV-2 virus (PDB ID: 7BQY and 7C2Q). We have found stable docked structures where docked metal chelates could readily bound to the SARS-CoV-2 Mpro. The molecular docking calculations of the complex (1) into the 7C2Q-main protease of SARS-CoV-2 virus revealed the binding energy of −9.4 kcal/mol with a good inhibition constant of 1.834 µM, while complex (2) exhibited the binding energy of −9.0 kcal/mol, and the inhibition constant of 1.365 µM at the inhibition binding site of receptor protein. Overall, our in silico studies explored the potential role of cobalt(II) complex (1), and copper(II) complex (2) complex as the viable and alternative therapeutic solution for SARS-CoV-2.

XXII International Conference and School on Quantum Electronics: "Laser Physics and Applications”

The International School on Quantum Electronics "Laser Physics and Applications” was held for the first time as far back as 1980. Since then it has taken place biennially and has become an important international event in the field of laser physics and laser applications attracting participants from many countries, especially from south-eastern Europe. Traditionally, its program includes lectures delivered by prominent scientists dealing with investigations of basic physical phenomena, processes of interaction of laser radiation with matter and latest scientific results obtained in the research areas of quantum electronics and optics, as well as the technological practical applications of new ideas, devices, instruments and laser systems. Special attention is paid to the active participation of students and young scientists who have the opportunity to present their results and meet and share experience with outstanding professionals in their particular fields of research.The topics include the following:• Laser-matter interactions• Laser spectroscopy and metrology• Laser remote sensing and ecology• Lasers in biology and medicine• Laser systems and nonlinear optics• Alternative techniques for material synthesis and processingThe 22nd edition of the ICSQE was held as a virtual forum due to the restrictions related to COVID-19 pandemic from September 19th to 23rd, 2022. The Institute of Electronics, Bulgarian Academy of Sciences, located in Sofia, Bulgaria, hosted the conference organization. The Big Blue Button on-line system was used as a technical platform for the meeting. The technical sessions of the International School on Quantum Electronics included 22 invited talks (30 min + 5 min Q&A), a Mini-Symposium "Extreme light infrastructure”, 11 oral contributions (30 min + 5 min Q&A) and in total 51 poster presentations divided into 5 sessions (1 hour each). The platform was available 24 hours, allowing discussions in addition to the technical program. The total number of participants was 90 from 16 countries.The XXII International Conference and School on Quantum Electronics: "Laser Physics and Applications” was held by the financial support from the Bulgarian National Science Fund under Project No. KP-06-MNF/4, 20.07.2022.List of Committees, International Advisory Committee, Program Committee, Local Organizing Committee, Lecturers, Oral Presentations, Poster Presentations are available in this pdf.

GIREP Malta Webinar 2021

PrefaceAfter the success of the GIREP Malta Webinar 2020, both GIREP Board members and the organisers/hosts from the University of Malta decided to plan for another meeting for GIREP members, to be organised in 2021. Restrictions due to the COVID-19 pandemic had automatically led the organisers of the first meeting to decide in favour of organising a webinar. There was hope, from both organisers and participants, that the 2nd meeting would be held face-to-face in Malta. But even this idea had to be abandoned in 2021. So a second webinar was organised instead. Seeing that participants of the first webinar indicated the need for further discussion related to physics teacher education, this being such an important topic, the GIREP Board decided that Webinar 2021 would still focus on ‘Physics Teacher Education: What matters?' This was the title of the GIREP Malta Webinar 2021.During the Webinar, various keynote speeches were presented. Participants were then sub-divided into groups, according to the workgroups of their interest. The workgroups dealt with specific topics for discussion, led by experts in the field. Participants had time at their disposal to present their work and research. They actively interacted with each other and the group leaders, during discussions. A number of papers were submitted, post-webinar. Each paper was independently and anonymously reviewed by two experts.The workgroups dealt specifically with the following topics:• Preparing teachers for TPACK (technological, pedagogical and content knowledge) and Lab work;• Developing and evaluating teacher PCK (Pedagogical Content Knowledge) in Quantum Mechanics (tools and approaches);• In-service Physics teacher education for early childhood and primary levels;• Pre-service Physics teacher education at all levels;• In-service Physics teacher professional learning for second and higher level education.The topic titles shown above have been used as Section Titles for this Journal of Physics: Conference Series publication. Published papers have been sectioned according to the working group in which they were originally presented.Once again, we must admit that organising the GIREP Malta Webinar 2021 and finalising the editing process for the post webinar publications has been quite a challenge. We have worked with passion and enthusiasm. We firmly believe that discussions, interactions and publications of this kind can help improve teaching and learning at all levels, offering creative ideas that can be used personally by teachers to enhance the class environment, both physically and mentally, as well as creating the important link between theory and practice. We would like to thank all those who contributed to the publication of these papers, including the GIREP board, the authors and reviewers. Thank you for your time and effort.List of International Advisory Committee and Scientific Programme Committee, Local Organising Committee, The Editors are available in this Pdf.

Artificial Intelligence Based COVID-19 Detection and Classification Model on Chest X-ray Images.

Diagnostic and predictive models of disease have been growing rapidly due to developments in the field of healthcare. Accurate and early diagnosis of COVID-19 is an underlying process for controlling the spread of this deadly disease and its death rates. The chest radiology (CT) scan is an effective device for the diagnosis and earlier management of COVID-19, meanwhile, the virus mainly targets the respiratory system. Chest X-ray (CXR) images are extremely helpful in the effective diagnosis of COVID-19 due to their rapid outcomes, cost-effectiveness, and availability. Although the radiological image-based diagnosis method seems faster and accomplishes a better recognition rate in the early phase of the epidemic, it requires healthcare experts to interpret the images. Thus, Artificial Intelligence (AI) technologies, such as the deep learning (DL) model, play an integral part in developing automated diagnosis process using CXR images. Therefore, this study designs a sine cosine optimization with DL-based disease detection and classification (SCODL-DDC) for COVID-19 on CXR images. The proposed SCODL-DDC technique examines the CXR images to identify and classify the occurrence of COVID-19. In particular, the SCODL-DDC technique uses the EfficientNet model for feature vector generation, and its hyperparameters can be adjusted by the SCO algorithm. Furthermore, the quantum neural network (QNN) model can be employed for an accurate COVID-19 classification process. Finally, the equilibrium optimizer (EO) is exploited for optimum parameter selection of the QNN model, showing the novelty of the work. The experimental results of the SCODL-DDC method exhibit the superior performance of the SCODL-DDC technique over other approaches.

COVID-19 diagnosis prediction using classical-to-quantum ensemble model with transfer learning for CT scan images

At present, there are problems of low detection efficiency and accuracy in chest CT images of COVID-19 as well as limited computational power of deep learning model training. Developing a classical-to-quantum (CQ) ensemble model with transfer learning to efficiently detect patients with COVID-19 using chest CT images.: Attributes were extracted from chest CT scans using pre-trained networks ResNet50, VGG16 and AlexNet, while dressed quantum circuits were used as classifiers. The overall accuracy of the CQ method based on three aforementioned networks on the chest CT dataset is 83.2%, 86.2% and 85.0%, respectively. The proposed ensemble model has a precision of 89.0% for pneumonia samples, an overall accuracy of 88.6% and a pneumonia class recall rate of 83.0%. In addition, to further verify the robustness of the ensemble model, breast ultrasound and brain tumour images were used in it. The suggested ensemble approach is effective for classifying and detecting medical pictures with complicated features, particularly for detecting COVID-19 patients using chest CT images.

Intelligent optimization design of electron barrier layer for AlGaN-based deep-ultraviolet light-emitting diodes

AlGaN-based deep-ultraviolet light-emitting diodes (DUV LEDs) are widely used in sterilization, sensing,water purification, medical treatment, non-line of sight (NLOS) communication and many other fields.Especially it has been reported that the global novel coronavirus (COVID-19) can be effectively inactivated bythe DUV light with a wavelength below 280 nm (UVC) within a few seconds, which has also attracted greatattention. However, the external quantum efficiency (EQE) of UVC LED is still at a low level, generally notmore than 10%. As an important component of EQE, internal quantum efficiency (IQE) plays a crucial role inrealizing high-performance DUV-LED. In order to improve the IQE of AlGaN-based DUV-LED, this workadopts an electron blocking layer (EBL) structure based on InAlGaN/AlGaN superlattice. The results showthat the superlattice EBL structure can effectively improve the IQE compared with the traditional single-layerand double-layer EBL structure for the DUV-LED. On this basis, the optimization method based on JAYAintelligent algorithm for LED structure design is proposed in this work. Using the proposed design method, theInAlGaN/AlGaN superlattice EBL structure is further optimized to maximize the LED' s IQE. It isdemonstrated that the optimized superlattice EBL structure is beneficial to not only the suppression of electronleakage but also the improvement of hole injection, leading to the increase of carrier recombination in the activeregion. As a result, the IQE of the DUV-LED at 200 mA injection current is 41.2% higher than that of thesingle-layer EBL structure. In addition, the optimized structure reduces IQE at high current from 25% to 4%.The optimization method based on intelligent algorithm can break through the limitation of the current LEDstructure design and provide a new method to improve the efficiency of AlGaN-based DUV-LED.

Synthesis, spectroscopic, crystallographic, quantum and molecular docking investigations of cis-4,5-diphenylimidazolidine-2-thione

We present the synthesis and characterization of stereoselective thione. The synthetic procedure includes readily available starting materials and minimum side products. The reaction of meso‑stilbenediamine with carbon disulphide in the presence of strong base gave cis-4,5-diphenylimidazolidine-2-thione (DPIT) in an excellent yield. The thione compound was characterized via FT-IR and mass spectroscopy. In addition, the crystal structure of it was determined by single crystal X-rays diffraction analysis which inferred that the molecular configuration was stabilized by intramolecular π⋯π stacking interaction. The crystal packing was mainly stabilized by N-H⋯S bonding. Hirshfeld surface analysis was performed for the exploration of the intermolecular interactions. Void analysis was carried out to predict the mechanical stability. Interaction energy between the molecular pairs is calculated which showed that the dispersion energy played a dominant role in the stabilization of the crystal packing. Moreover, the quantum computational methods were used to study the molecular structure and electronic properties of entitled compound. The molecular geometries were optimized for possible thione and thiole tautomeric structures. A comparison of total energy of molecular tautomers indicates that thione tautomer possesses lower total energy which is about 20.18 Kcal/mol lower than thiole tautomer. The electronic properties of thione derivative were studied including 3-D wavefunction delocalization of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) orbitals and their orbital energy gap. The HOMO-LUMO energy gap for DPIT was found to be 4.874 eV. The delocalization of wavefunction indicates the probable presence of HOMO and HOMO-1 are mainly localized over C-S bond owing to the presence of lone pair of electrons in the sulfur atom. Additionally, the molecular docking study was also carried out for main protease (Mpro) of SARS-CoV-2. The binding energy calculation and investigation of intermolecular interactions highlighted the probable inhibition tendency of DPIT for SARS-CoV-2. The present experimental and computational studies indicate a significant potential of entitled molecule for electronic and biological perspectives.

A smarter, tactical approach for combating Covid-19

As human beings, we communicate with each other just like other creatures. In the same way we need to communicate, COV-ID-19 has to communicate with other viruses. Following the latest Pandemic, combating COVID-19 has become a major need today. Several theories are being formulated and tested for the efficient prevention and treatment of the virus. Vaccination is the ultimate solution but access to the vaccine and getting vaccinated is limited. The purpose of this review paper is to present a new approach. This approach is based on the Quorum sensing of viruses like bacteria. Bacteria use this for communication and it has recently been proven for viruses too. It can be used as a new way or strategy to stop viral communication, therefore restricting the viral spread will possibly help people around the world or reduce the disease's side effects. This new tactic in-volves the use of functionalized Quantum dots nanoparticles, and when they are coupled with carbon atoms and put to use in different delivery forms, these will be useful for maximum efficacy. The use of carbon quantum dots can be useful to minimize certain possible toxic effects. This may be greatly enhanced by doping boron atoms to the structure to trigger their synergistic effects. We suggest here that the inhaler form of this proposed drug delivery system should simultaneously provide a fairly high efficiency and a less toxic solution.