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Artificial Intelligence (AI) has great potential in diverse real-time mission-critical applications and one such application is telesurgery or robotic surgery. However, some issues like security, throughput, reliability, trust, and transparency are still challenging in an AI-enabled telesurgery system. Motivated from these challenges, in this paper, we propose a blockchain and AI-empowered telesurgery system towards 6G called BATS, which is a self-manageable, secure, transparent, and trustable system with massive Ultra-Reliable Low-Latency Communication (mURLLC). BATS uses AI algorithms such as eXtreme Gradient Boosting (XGBoost) to classify the disease with their criticality score ranging from 0 to 1. Moreover, BATS uses UAVs to transport light-weight healthcare items such as medicines and surgical tools in an emergent situation (during surgical procedures) to avoid the road-traffic congestions.Results show that BATS achieves better prediction accuracy, high throughput when the number of users increases, extremely low packet loss ratio, low storage cost, high mining profit, and low bandwidth consumption by nterPlanetary File System (IPFS) compared to the traditional schemes.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or COVID-19), outbreak was first reported in December 2019 in the Wuhan, China. COVID-19 managed to spread worldwide and so far more than 9.1 million cases and more than 4.7 lakh death has been reported globally. Children, pregnant women, elderly population, immunocompromised patients, and patients with conditions like asthma, diabetes, etc. are highly vulnerable to COVID infection. Currently, there is no treatment available for COVID-19 infection. Traditional medicinal plants have provided bioactive molecules in the past that are efficiently used during conditions like cancer, malaria, microbial infections, immune-compromised states, etc. AYUSH India has recommended the use of Curcuma longa, Allium sativum, Ocimum tenuiflorum, and Withania somnifera for immune-boosting during SARS-CoV-2 infection. In the present study, we investigated the potential of 63-major bioactive molecules of these plants against SARS-CoV-2 main protease (Mpro) through docking studies and compared the results with known inhibitor 11a. Our results proposed cuscohygrine, γ-Glutamyl-S-allylcysteine, anahygrine, and S-allylcystein as the potent inhibitors against Mpro identified using molecular docking and molecular simulation dynamics. Interestingly, these molecules are from A. sativum, and W. somnifera, which are known for their antimicrobial and immunomodulatory potential. None of the proposed molecules have earlier been reported as antiviral molecules. Our results predict very strong potential of these four-molecules against SARS-CoV-2 Mpro, especially γ-glutamyl-S-allylcysteine, as all four form hydrogen bonding with Glu166 that is a crucial residue for the formation of the biologically active dimeric form of Mpro. Therefore, we strongly recommend further research on these biomolecules against SARS-CoV-2.

Polyhydroxyalkanoates (PHAs) are bio-polyesters of hydroxyalkanoates that accumulate intracellularly in case of prokaryotes, as cytoplasmic granules, under carbon rich and paucity of nitrogen, phosphorous, sulphur and oxygen where it can serve as carbon and energy source under nutrient limiting condition and/or environmental stress conditions. In adverse growth conditions, many bacteria have ability to store nutrients in form of PHA granules using their specific metabolic pathways during stationary growth phase, in the presence of high levels of carbon containing nutrient sources. Bacterial PHAs have generated attention as an alternative to petroleum derived synthetic plastics. It possesses the characteristic physico-chemical properties comparable to the synthetic plastics. These properties of PHAs can be improved by blending of PHAs with other natural polymer like starch, cellulose and semisynthetic polymers like poly lactic acids and polycaprolactones. Being eco-friendly, biodegradable and biocompatible; major PHAs such as, Polyhydroxybutyrate (PHB) and Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) have found numerous vital applications in pharmaceutical, biomedical, textile, cosmetic, agricultural, treatment of waste water and have been successfully employed for Food packaging industries. This review provides a comprehensive knowledge about the world of PHAs covering its major aspects, namely its chemical nature and structure, biosynthesis, various methods of screening of potential PHA producing bacteria along with properties, several techniques used for its recovery and further characterization.

Microbes possess a tremendous potential to interact with their surroundings and have continued to shape the future of all life forms existing on earth. Of all the groups of microbes, viruses are the most nefarious creatures which cannot be solely classified as living or non-living but still pose the greatest threats to the biosphere. Viruses are minuscule, diverse and are probably the only entities that exhibit non-mutualistic association with other lifeforms while retaining their ability to infect and hijack any of the existing living being on the planet. The latest global devastation, caused by novel SARS-CoV-2, is unparalleled in the last century. This review encompasses the mysterious origin of this virus by tracking its lineage, which may help to decode the conundrum of SARS-CoV-2 and shed more light on its epidemiology. The implications and the challenge posed by this virus to the scientific community to the medical community and the economy at large are reflected. Also discussed is the paradigm shift brought upon by the COVID-19 pandemic on the human psyche and their behaviour. Graphic Abstract

The COVID-19 pandemic situation has proved to be disastrous for humanity throughout the world. However, during this period, people must take precautions for safety purposes. One of the essential steps towards eliminating or reducing the effect of COVID-19 is maintaining social distancing while in public places. Some people are neglecting the social distancing norms while on the move. Still, no surveillance system exists, which monitors the people’s movement for social distancing and securely & efficiently shares the information with the concerned administration department. There also exists no penalty system which forces the people to ensure social distancing. Motivated from the aforementioned facts, in this paper, we present a blockchain and artificial intelligence (AI)-envisioned scheme for monitoring social distancing to combat COVID-19 situations. The proposed scheme uses fast region-based convolutional neural networks (RCNN) and you only look once (YOLO) models for the object (i.e., human) detection through the live video feed captured from the static CCTV cameras as well as lens-equipped drones. Further, the efficient euclidean distance calculation is embedded for calculating the distance between two humans. Blockchain technology ensures the secure and trusted exchange of information between the entities at the physical layer and the administration departments. Blockchain wallets are also used to pay the fine when people do not follow social distance norms. The performance of the proposed scheme is evaluated based on three broad parameters such as (i) human detection and violation identification, (ii) blockchain simulation and analysis, and (iii) network performance comparison. The parameters considered for (i) is confidence score, for (ii) are scalability, hash rate, and simulation interface, and for (iii) are network bandwidth, throughput, packet loss rate, and network latency. By analyzing all the parameters mentioned above, we observe the proposed scheme outperforms the traditional approaches.

Peptide Nucleic Acid (PNA) serves as an artificial functional analog of DNA. Being immune to enzymatic degradation and possessing strong affinity towards DNA and RNA, it is an ideal candidate for many medical and biotechnological applications that are of antisense and antigene in nature. PNAs are anticipated to have its application in DNA and RNA detection as well as quantification, to serve as antibacterial and antiviral agents, and silencing gene for developing anticancer strategies. Although, their restricted entry in both eukaryotic and prokaryotic cells limit their applications. In addition, aggregation of PNA in storage containers reduces the quality and quantity of functional PNA that makes it inadequate for their mass production and storage. To overcome these limitations, researchers have modified PNA either by the addition of diverse functional groups at various loci on its backbone, or by synthesizing chimeras with other moieties associated with various delivery agents that aids their entry into the cell. Here, this review article summarizes few of the structural modifications that are performed with PNA, methods used to improve their cellular uptake and shedding light on the applications of PNA in various prospects in biological sciences.

Purpose The development of a new class of engineering materials is the current demand for aircraft and automobile companies. In this context metal, composite materials have a widespread application in different areas of manufacturing sectors. Design/methodology/approach In this paper, an attempt is made to develop the aluminium-based nano metal matrix composite reinforced with graphene nanoparticles (GNP) by using the stir casting method. Different weight percentage (0.4%, 0.8% and 1.2% by weight) of GNPs are used to fabricate metal matrix composites (MMCs). The developed nanocomposites were further validated by density calculation and optical microstructures to discuss the distribution of GNPs. The tensile test was conducted to determine the strength of the developed MMCs and also supported by fractographic analysis. In addition to it, the Rockwell hardness test and impact test (toughness) with fracture analysis were also conducted to strengthen the present work. Findings The results reveal the uniform distribution of GNPs into the matrix material. The yield strength and ultimate tensile strength obtained a maximum value of 155.67 MPa and 170.28 MPa, respectively. The hardness value (HRB) is significantly increased and 84 HRB was obtained for the sample with AA1100/0.4% GNP, while maximum hardness value (94 HRB) was obtained for the sample AA1100/1.2% GNP. The maximum value of toughness 14.3 Jules/cm2 is recorded for base alloy AA1100 while increasing the reinforcement percentage, it decreases up to 9.7 Jules/cm2 for AA1100/1.2% GNP. Originality/value Graphene nanoparticles are used to develop nanocomposites, which is one of the suitable alternatives for heavy engineering materials such as steels and cast irons. It has improved microstructural and mechanical properties which makes it preferable for many engineering and structural applications.

The novel SARS-CoV-2 is the etiological agent causing the Coronavirus disease 2019 (COVID-19), which continues to become an inevitable pandemic outbreak. Over a short span of time, the structures of therapeutic target proteins for SARS-CoV-2 were identified based on the homology modelled structure of similar virus, SARS-CoV that transmitted rapidly in 2003. Since the outset of the disease, the research community has been looking for a potential drug lead. Out of all the known resolved structures related to SARS-CoV-2; 3-chymotrypsin (3 C) like protease (3CLpro) is considered as an attractive anti-viral drug compound on the grounds of its role in viral replication and probable non-interactive competency to bind to any viral host protein. To the best of our knowledge, till date only one compound has been identified and tested in-vitro as a potent inhibitor of 3CLpro protein, addressed as N3 (PubChem Compound CID: 6323191) and is known to bind irreversibly to 3CLpro suppressing its activity. Using computational approach, we intend to identify a probable natural fungal metabolite to interact and inhibit 3CLpro. Here after performing docking and molecular dynamics of various small molecules derived as a secondary metabolite from fungi, we propose Flaviolin as potent inhibitor of 3CLpro of novel Coronavirus SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

Modern globalisation has escalated anthropocentric sources for heavy metal contamination in diverse natural habitats. Pernicious nature of heavy metals poses a major threat to all life forms in the environment. Heavy metals are not degradable like the organic pollutants but could be transformed to be persistent in a less toxic form. Microbes are the cheap tool as they evolve rapidly to combat heavy metal stress by developing various survival strategies, for instance sequestration or active transportation of metal. Their short generation time, large surface area and ease of genetic manipulation makes them ideal candidates to use for the bioremediation process. Many heavy metal resistant microbes such as species of Bacillus, Pseudomonas, Acidothiobacillus, Saccharomyces, Geobacter and Rhizophus have been used for remediation of heavy metal contaminated sites. The effectiveness of bioremediation technique depends upon various factors, including biotic as well as abiotic, which mainly determine bio-availability of metal for remediation. The different metal microbe interactions such as sorption, accumulation, mineralization, transformation and solubilization are responsible for tapering heavy metal concentration at various loci or sites. The review emphasizes on the different interactions of the microbes with heavy metals, their survival strategies and the applications of the resistant strains in remediation.

Quorum sensing in bacteria is a cell density-dependent phenomenon in which, a community of cells communicate with each other using signalling molecules belonging to various families of which N-acyl homoserine lactone (AHL) is one. AHL acts via ligand-receptor interaction where receptors of AHL differ from species to species, and possess great degree of similarity in conformation at the active site. A macromolecule, LasR, is a receptor protein that binds to N-(3-oxododecanoyl)-L-homoserinelactone (OdDHL), a type of AHL, viz. responsible for biofilm formation in Pseudomonas aeruginosa. Similar macromolecule LuxR, like LasR, found in Vibrio sp. identifies a different AHL, N-(3-oxohexanoyl)-L-homoserine lactone (OhHSL), responsible for the phenomenon of bioluminescence. In silico study depicted that curcumin could bind to both LasR and LuxR by unique sets of hydrogen bonding and hydrophobic interactions that can lead to the inactivation of these proteins, enabling this plant-derived organic AHL antagonist to be categorized as a quorum sensing inhibitor (QSI). To prove this hypothesis, curcumin was treated on P. aeruginosa to access the reduction in biofilm formation and on V. alginolyticus to check its efficacy to reduction in bioluminescence by inhibition of QS. The results of these studies proved curcumin to be an efficient QSI.

Plastic comprises of variety of polymers and has many applications, but the waste generated by plastic pose threat to environment and marine life. Plastic can be classified into two types: thermoplastics and thermosetting and are divided into 7 different categories: (Polyethylene Terephthalate [PETE], High-Density Polyethylene [HDPE], Polyvinyl Chloride [PVC], Low-Density Polyethylene [LDPE], Polypropylene [PP], Polystyrene or Styrofoam [PS]Polycarbonate or ABS [others]). To curb the deleterious effects of plastic waste various methods have been devised and utilized that include chemical, physical and biological treatments. One of the aspects primarily focused by the researchers is the phenomenon of biodegradation and there are many microorganisms (bacteria) that have the ability to carry out this particular process. These bacteria assist biodegradation by production of several enzymes like PETases and MHETases. There are few microorganisms that have been listed which cannot be applied for industrial use due to its low biodegradation capacity. To overcome this problem, PHA is one of the alternatives to replace the synthetic plastic due to its high degrading capacity.

Life expectancy (LE) models have vast effects on the social and financial structures of many countries around the world. Many studies have suggested the essential implications of Life expectancy predictions on social aspects and healthcare system management around the globe. These models provide many ways to improve healthcare and advanced care planning mechanism related to society. However, with time, it was observed that many present determinants were not enough to predict the longevity of the generic set of population. Previous models were based upon mortality-based knowledge of the targeted sampling population. With the advancement in forecasting technologies and rigorous work of the past, individuals have proposed this fact that other than mortality rate, there are still many factors needed to be addressed in order to deduce the standard Predicted Life Expectancy Models (PrLE). Due to this, now Life expectancy is being studied with some additional set of interests into educational, health, economic, and social welfare services. In the Analysis, the authors have implemented different machine learning algorithms and have achieved better accuracy based on pertinent features of the dataset.

The COVID-19 pandemic has adversely affected the lives of millions of people worldwide. With an alarming increase in COVID-19 cases, it is important to detect and diagnose COVID-19 in its early stages to prevent its spread. To diagnose remote patients, the Internet can be useful for accessing data of that patient. But, the Internet has also had issues related to data security, reliability, and privacy. Motivated by these challenges, in this paper, we propose a Blockchain (BC) based COVID-19 detection scheme (BCovX) for fast and reliable diagnosis of COVID-19 using chest X-Ray (CXR) images. For fast and accurate detection of COVID-19 using CXR, BCovX consists of a Convolutional Neural Network (CNN) model, using which a patient can be diagnosed for COVID-19 remotely. CNNs have performed successfully in medical imaging classification. BCovX provides reliable and secure data access and exchange using BC and smart contracts (SC). To solve issues related to data storage and its associated cost, the InterPlanetary File System (IPFS) protocol is used to store medical data. We also present a real-time SC developed in Solidity to govern the transaction between the patient and the doctor. The SC has been compiled and deployed on Remix Integrated Development Environment (IDE). Finally, we have evaluated the performance of BCovX with traditional schemes in terms of storage cost, bandwidth requirements, and accuracy of the CNN model.

With the advent of the Internet, the gaming industry has grown tremendously in business, which also raises concerns for cheating and unfair gameplay. In this paper, we propose a novel approach (GiNA) using Blockchain technology to address a few problems with online Peer-to-Peer (P2P) games. GiNA uses two different data packet transfer schemes to ensure the security and authenticity of the data packet sent and received by game clients. More sensitive data uses a Smart contract-based ON-CHAIN data packet transfer solution and less sensitive data uses an OFF-CHAIN data packet transfer solution with end-to-end encryption for data security. A marketplace where peers can buy and sell purchasable assets with the help of Gicoins. Gicoins is a stable token with compliance with the ERC 20 token of Etheruem Blockchain. Later, a low cost and low bandwidth utilization data storage solution is proposed for storing data in a decentralized and distributed manner. Results show that the performance of the proposed approach GiNA is better in comparison to the traditional approaches with parameters such as latency, scalability, packet loss percentage, Blockchain (BC) performance, and data storage comparison.

Financial institutions have made lives easier for a lot of individuals and organizations that would earlier use to face capital shortage now and then. Therefore, it becomes necessary to make the financial systems more reliable, secure, time-conserving, and cost-effective. Although several approaches have already been proposed, all of these tend to fail on at least one of the key features, i.e., trust. Motivated by this, in this paper, we propose DeLend, an Ethereum blockchain-based peer-to-peer (P2P) lending system. In DeLend, the problems of security, trust, and reliability have been solved with the help of Ethereum-based smart contracts (SCs). To make the system middlemen-free and much more cost-effective, we use the interplanetary file system (IPFS) protocol as a data storage. Through extensive simulation, we show that DeLend requires less bandwidth, which makes it a suitable enabling technology for the next generation of cellular networks, i.e. 6G. Finally, DeLend’s performance evaluation demonstrates its efficacy compared to traditional lending schemes.

The rapid growth and advancement of technology in industries provide a better quality of services to the end-user in the industrial Internet of Things (IIoT). The digital twin (DT) is an innovative technology recently developed in Industry 4.0 to provide a virtual representation of physical components, products, or equipment such as computer numerical control (CNC) machines. It can be used to run simulations before manufacturing. However, traditional DT platforms lack data privacy, traceability, immutability, authentication of stakeholders. Moreover, manual prediction of the wearing of the tool condition of the CNC machine is challenging. Motivated from these gaps, in this paper, we propose a six-layered architecture for DT of CNC, which predicts CNC tool wear detection using a novel ensemble technique based soft voted prediction model consisting of XGBoost, random forest, and AdaBoost models. The proposed architecture also incorporates the public Ethereum blockchain (BC) to maintain the aforementioned issues of authentication, traceability, and transparency through constraints and automation programmed into the smart contracts (SC) developed. We evaluate the proposed scheme’s performance through simulation and compare it with other traditional approaches concerning several performance parameters (accuracy, F1-score, precision, and recall). The result shows that the proposed approach outperforms the traditional approaches on these same performance parameters such as accuracy, F1-score, precision, and recall.

Generally, to make a campaign,startup, or any innovative idea successful requires some amount of donation. Fundraising or let us say Crowdfunding is an efficient way to raise money for your ideas, campaigns, startups etc. There are a lot of platforms available online and they provide space for setting up your own campaign so that you can gets funds for your campaign. people can go and contribute to any idea they like and get benefit from the pledge that you make. Certainly, there are lot of drawbacks to this model. There is no transparency and no assurance that your money is being put to the right use, there are charges to use the platform and many other issues. We try to over come these issues by making a fundraising platform using smart contract in solidity. This will be more secure as it uses Ethereum blockchain to make all the transactions and all the transactions are ethereum based. Not only this but the contributors have the right to vote for a transaction and only when a minimum consensus is achieved the requested transaction can be made.Contributors can have their own pool of contributors which can be achieved by multi-signature wallet.By creating a multisigned wallet , there will be two factor authentication mechanism to access funds, which are related more to security concerns. This not only enables a transparent transaction but also develops trust in the users of the platform. This not only resolves major drawbacks faced in the current live non blockchain based platforms like Kickstarter but also brings in more efficient platform to serve the purpose.”

Microorganisms can utilize an extensive assortment of carbon and nitrogen sources as well as various added nutrients ranging from simple to complex. Depending on the microbe and the metabolic pathway they undergo, these nutrients are efficiently converted into complex and diverse biopolymers with varied physico-chemical properties. Exopolysaccharides (EPS) are biopolymers that primarily contain- carbohydrates. The extensively studied EPS producing bacteria include Leuconostoc mesenteroides, Xanthomonas campestris, Acinetobacter calcoaceticus, Lactobacillus sp. and Alkaligenes sp. However, some prominent fungal exopolysaccharides produced by Aspergillus niger, Lentinula edodes, Fusarium solani, Botryosphaeria rhodina, Coriolus versicolor have also been put to commercial use. While the microbes may vary substantially in their physiology, the production of EPS depends largely on the optimization of the growth by varying various parameters influencing growth and the meticulous designing of its production media. EPS acts as an invaluable asset for the producing microbe by providing manifold benefits including but not restricted to: protection against- desiccation, starvation, phagocytosis, UV radiation, environmental stress and water retention. Being eco-friendly and biodegradable, major microbial EPS such as; dextran, xanthan, alginate, hyaluronan, pullulan, chitosan and lentinam have found numerous vital applications in pharmaceutical, agriculture, food and cosmetics industries. This review provides an inclusive insight into the world of microbial exopolysaccharides covering its major aspects, namely- its types, biosynthesis and the factors that influence its production along with various techniques used for its recovery and further characterization. Special emphasis is placed on the applications of EPS in various large-scale commercial and industrial sectors.

Radionuclides are present in minute concentrations in soils, especially around atomic power stations. Several microorganisms have been reported to grow in presence of radionuclides and even extreme gamma-radiation. Deinococcus radiodurans serves as the model radioresistant bacterium owing to its tolerance to extreme levels of gamma-radiation. In the present study, the soil sample was randomly collected from the area around Kakrapar Atomic Power Station, Surat (India) and was characterized physico-chemically. Based on the inductively coupled plasma-optical emission spectrometry (ICP-OES) analysis, the soil was found to be rich in iron, titanium and magnesium. The nutrient medium was used for the cultivation and isolation of indigenous bacterial flora which were then characterized for their biochemical and metabolic potential. Twenty-five isolates were isolated which were sequentially screened to five. Furthermore, the five screened-in isolates exhibited the ability to produce exopolysaccharide (EPS) and biofilm, serving as one of the criteria for secondary screening of two isolates. The two screened bacteria were then identified as Providencia vermicola AM3 and Ochrobactrum sp. AM7 by 16S partial rRNA sequencing and their nucleotide sequences have been submitted to GenBank (NCBI). Additional optimization of medium components supporting the growth as well as facilitating the production of EPS by isolates P. vermicola AM3 and Ochrobactrum sp. AM7 is required for their potential application in bioremediation of radionuclide containing waste.

Microbial enzymes are increasingly finding applications as therapeutics due to their targeted activity and minimal side effects. Serratiopeptidase, also known as a miracle enzyme, has already proved its potential as an anti-inflammatory, mucolytic, fibrinolytic, analgesic in many studies. A cost effective, bioreactor level production process has been described here comprising of the fed-batch fermentation to produce recombinant serratiopeptidase protein expressed as a fusion construct. High yield of cell mass as well as protein was obtained by the optimization of bioreactor parameters. The downstream solubilization and purification processes were also optimized to achieve maximum yield of pure, active serratiopeptidase protein. A final yield of 2.5 ± 0.764 g L−1 of protein was obtained, having 8382 ± 291 U mg−1 of specific caseinolytic activity. Additionally, a novel, unexpected self-proteolytic activity of the enzyme that cleaves the N-terminal 6× His-SUMO fusion tag along with the enzyme propeptide, thus yielding a mature serratiopeptidase, was also found.

Graphic abstract The latest global outbreak of 2019 respiratory coronavirus disease (COVID-19) is triggered by the inception of novel coronavirus SARS-CoV2. If recent events are of any indicators of the epidemics of past, it is undeniable to state a fact that the SARS-CoV2 viral infection is highly transmissible with respect to its previously related SARS-CoV’s. Papain-like protease (PLpro) is an enzyme that is required by the virus itself for replicating into the host system; and it does so by processing its polyproteins into a functional replicase complex. PLpro is also known for downregulating the genes responsible for producing interferons, an essential family of molecules produced in response to viral infection, thus making this protein an indispensable drug target. In this study, PLpro inhibitors were identified through high throughput structure-based virtual screening approach from NPASS natural product library possessing ~ 35,000 compounds. Top five hits were scrutinised based on structural aromaticity and ability to interact with a key active site residue of PLpro, Tyr268. For second level of screening, the MM-GBSA End-Point Binding Free Energy Calculation of the docked complexes was performed, which identified Caesalpiniaphenol A as the best hit. Caesalpiniaphenol A not only possess a double ring aromatic moiety but also has lowest minimum binding energy, which is at par with the control GRL0617, the only known inhibitor of SARS-CoV2 PLpro. Details of the Molecular Dynamics (MD) simulation and ADMET analysis helped to conclusively determine Caesalpiniaphenol A as potentially an inhibitor of SARS-CoV2 PLpro.

The flexibility of microbes to undergo or adapt to the changes in their physiology and genotypical traits has enabled the microbes acquiring resistance to latest or recently discovered drugs which have consequently led to the menace of multidrug resistance (MDR). There is a surge in the discovery of novel antibiotics to counter the rising MDR phenomena, and in such a quest, for investigating an efficient alternative mechanism or compound to combat MDR, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) has piqued the interests of the researchers across the globe. CRISPR-Cas9 technology is a genome-editing tool with successful widespread applications in cell lines, plants, animals, and even in human clinical trials, and it is seriously being considered as a potential candidate for countering MDR. This review encompasses the broad scope of CRISPR-Cas9 along with its various variations, underlying principles, mechanisms, as well as applications. Furthermore, the implications of recent advancements in various disciplines are highlighted to enhance the applicability of this technique. Consequently, its research gaps and challenges are also identified so that they can be addressed in the possible future thereby further expanding the lore of CRISPR-Cas9 technique.

The textile industry is a complex commercial avenue which deals with multiple processes that can lead to significant pollution. Pretreatment of textile, coloring, and decolorization requires complex chemical processes that develop noxious compounds which cause pollution in the environment. For instance, several alkali and acids are used during the pretreatment of textile products which are not environment-friendly. To overcome such limitations, scientists across the globe have made a progress by making use of microorganisms at various stages in the textile industry to curb the production of contaminants. There are varieties of microbes that possess a plethora of abilities to thrive in different environments which have enabled then to produce a variety of enzymes. Of the gazillions enzymes known to be produced by microbes, amylase, protease, lipase, pectinase, xylanase, ligninase, and cellulase are most been exploited in the textile industry for the pretreatment of textile. These enzymes can substitute several hazardous chemicals used for the same processes. Microbes are also known to produce a variety of pigments which have shown the potentials to replace persistent azo dyes. Of all the most important applications of microbes in textile industries, microbes have found significant applications in the effluent treatment process that make use of its wide and varied abilities to encounter with harmful compounds. The microbes have also shown to degrade azo dyes, making them degradable, bringing down their BOD and COD levels, remediating heavy metals from the effluents, and making these microbially treated effluents to be safe for environmental disposal, without disturbing the ecosystem. Microbially mediated processes at various stages in the textile industry best complement the green chemistry.

The next-generation energy system, i.e., Smart Grid (SG), empowers the real-time transfer of information using advanced metering infrastructure (AMI) and smart meter (SM) between end-consumers and grid. It accelerates various services such as automatic meter reading, time-of-use (TOU) pricing, demand-response management, and many more. Though it has growing security and privacy concerns and the detection of malicious activity is a critical security task that sacrifices the overall Quality-of-Service (QoS) of SG and Quality-of-Experience (QoE) for customers. To address the aforementioned issues, we propose a data analytics Scheme ArMor for malicious activity detection on the blockchain (BC)-based SG system. The ArMor detects data integrity issues in real-time like false data injection attack and SM failure. Here, we proposed a unique ARIMA-based malicious activity detection model and classified the customer. Then, we proposed a Smart Contract (SC)-based incentive mechanism for utility providers handling the malicious activity at their end. It prevents the entry of malicious data into the SG system as transactional data once stored in BC, it is secured using SC. The obtained results are compared against parameters like prediction accuracy, latency, and data storage cost compared to the state-of-the-art approaches to designate the efficacy of the proposed scheme.

Blockchain technology has emerged to provide immense security solutions and create trust between the stakeholders. In a multi-application scenario, fair resource allocation is complex and challenging. Various Resource Allocation Schemes (RAS) have been proposed by the researchers across the globe, but these solutions are not sufficient to handle the security, trust, latency, and bandwidth issues in the network, which introduces vulnerabilities in the system. Motivated from the aforementioned issues, this paper proposes Block-RAS, a blockchain-based RAS to manage the demand-supply of resources between the users and resource providing companies (RPC) in a secured and trusted environment. Block-RAS provides a highly reliable, low-latency, and bandwidth optimum communication between users and RPC with embedded 6G network infrastructure. In Block-RAS, the security, trust, and transparency are achieved using ethereum blockchain, whereas the cost-effective and optimum bandwidth utilization is achieved using the Interplanetary File System (IPFS). Finally, the performance evaluation of Block-RAS is done by a comparative analysis of the proposed approach with traditional approaches that are dependent on centralized 5G based schemes where the Block-RAS outperforms in terms of delay, packet-loss, blockchain block-size, scalability, and network bandwidth utilization.

Online teaching has become mandatory across the globe during the COVID-19 pandemic situations. Hence, there is a need to uplift the online teaching technology for data privacy preservation and transparency in the system. Various online teaching schemes have been proposed by various authors, but they lack in handling decentralised governance, transparency, trust and communication issues. Blockchain (BC) Technology has emerged to provide decentralised solution in solving the real-time problems. Motivated by these facts, in this paper, we propose a BC-based decentralised online teaching scheme known as BDoTs. The security and data privacy issues in BDoTs are resolved by developing smart contracts (SCs) over BC. Moreover, the data storage cost issues are handled by the Inter Planetary File System (IPFS) protocol for Off-Chain data storage. Moreover, we present a real-time BC simulation and deployment of SC in Truffle suite. Results show that the proposed scheme performs better in comparison to the state-of-the-art schemes in terms of scalability, data storage cost, and packet loss.

The novel SARS-CoV-2 is the etiological agent causing the Coronavirus disease 2019 (COVID-19), which continues to become an inevitable pandemic outbreak. Over a short span of time, the structures of therapeutic target proteins for SARS-CoV-2 were identified based on the homology modelled structure of similar virus, SARS-CoV that transmitted rapidly in 2003. Since the outset of the disease, the research community has been looking for a potential drug lead. Out of all the known resolved structures related to SARS-CoV-2; 3-chymotrypsin (3 C) like protease (3CL

Unmanned aerial vehicle (UAV) is used in various smart applications, such as defense, civilian, and healthcare services. As data in these applications flow through an open channel, i.e., the Internet, so security and privacy always a challenging issue. Though many solutions exist for this problem in literature, but these solutions are not adequate to handle security, privacy, latency, and efficient real-time delivery of healthcare services remotely over the wireless communication channel. Moreover, the existing UAV systems have security, reliability, latency, and storage cost issues, which restricts their applicability shortly. Motivated from these facts, this paper proposes VAHAK, an Ethereum Blockchain (BC) based secure outdoor healthcare medical supplies using UAVs. VAHAK provides reliable communication between the UAVs and the entities in a decentralized manner, which ensures the early delivery of required medical supplies to the critical patients. In VAHAK, security, privacy, and reliability issues have been resolved using Ethereum smart contract (ESC), while storage cost issues are handled with IPFS protocol. The security vulnerabilities of the VAHAK are tested on MyThril open-source tool. VAHAK is efficient in terms of data storage cost as it uses the InterPlanetary File System (IPFS) for healthcare record storage and 5G-enabled Tactile Internet (TI) for communication, respectively. Finally, VAHAK performance evaluation demonstrates its effectiveness as compared to the traditional systems where it outperforms the existing schemes with respect to various performance evaluation metrics, such as scalability, latency, and network bandwidth.

A smart grid (SG) system offers many services to the end-users, such as load management, load forecasting, and energy trading (ET). As data among different devices in SG environment flows through an open channel, i.e., Internet, so, security and privacy always remains a challenging issue. Though many solutions exist for this problem in literature but these solutions are not adequate to handle security, privacy, latency, real-time settlement of ET. Moreover, most of the solutions reported in the literature are based upon the centralized architecture having single point of failure. Motivated from these facts, this paper proposes a scheme ET-DeaL, which is a Smart Contract-based Secure Energy Trading scheme for SG system for peer-to-peer (P2P) ET. ET-DeaL uses Ethereum smart contract (ESC) and Inter Planetary File System (IPFS) for the P2P ET management. Moreover, it manages the energy load of residential houses, industries, and electric vehicles (EVs). In ET-DeaL, security and privacy issues have been resolved using ESC, while storage cost issues are handled with IPFS protocol. We implemented a real time ESC and deploy it in Truffle suite. The security bugs of the ET-DeaL are tested on MyThril open-source tool. Finally, ET-DeaL performance evaluation demonstrates its effectiveness as compared to the traditional systems where it outperforms the existing schemes with respect to various performance evaluation metrics.

Telesurgery (TS) with 5G-enabled Tactile Internet (TI) has enormous potential to deliver real-time ultra-responsive surgical services remotely with high quality and accuracy. It is quite beneficial for society in the prospect of highly precise surgical diagnosis. However, the existing TS systems have security, privacy, latency, and blockchain (BC) storage cost issues, which restricts its applicability in surgical procedures across the world in the near future. To mitigate the above-mentioned issues, in this paper, we propose an approach named AaYusH (Ethereum smart contract (ESC) and IPFS-based TS system). The security and privacy issues in AaYusH can be resolved through ESC, whereas storage cost issues with the InterPlanetary File System (IPFS) protocol. Moreover, we present a real-time SC written in Solidity and deployed in Truffle suite. We test the security bugs of AaYusH in MyThril open-source tool and detect no issues. Finally, we evaluate the performance of AaYusH in context to latency and data storage cost, and it outperforms as compared to the traditional telesurgery system.

The novel SARS-CoV-2 is the etiological agent causing the Coronavirus disease 2019 (COVID-19), which continues to become an inevitable pandemic outbreak. Over a short span of time, the structures of therapeutic target proteins for SARS-CoV-2 were identified based on the homology modelled structure of similar SARS-CoV transmission of 2003. Since the onset of the disease, the research community has been looking for a potential drug lead. Out of all the known resolved structures related to SARS-CoV, Main protease (Mpro) is considered an attractive anti-viral drug target on the grounds of its role in viral replication and probable non-interactive competency to bind to any viral host protein. To the best of our knowledge, till date only one compound has been identified and tested in-vivo as a potent inhibitor of Mpro protein, addressed as N3 (PubChem Compound CID: 6323191) and is known to bind irreversibly to Mpro suppressing its activity. Using computational approach, we intend to identify a probable natural fungal metabolite to interact and inhibit Mpro. After screening various small molecules for molecular docking and dynamics simulation, we propose Pyranonigrin A, a secondary fungal metabolite to possess potent inhibitory potential against the Main protease (Mpro) expressed in SARS-CoV-2 virus., Graphical abstract Unlabelled Image, Highlights • Searching inhibitor for Main Protease (Mpro) of SARS-CoV2 • Purpose to block viral replication and packaging in host • Mpro interaction with fungal metabolite- Pyranonigrin A • Studies involving docking and molecular dynamics

Smart contracts are essential in maintaining the trust between the members of the blockchain. Its verification is of utmost importance, as it is unmodifiable once deployed. Moreover, a malicious user can deploy vulnerable smart contracts to breach the blockchain data. To restrict this, we propose a deep learning-based scheme to detect the vulnerabilities and rate them as safe/vulnerable based on probability value 0 . 5 / ≥ 0 . 5 respectively. An open Google BigQuery dataset with 7000 samples was used to train the classifier. We train artificial neural networks (ANN), long-short term memory (LSTM), and gated recurrent unit models (GRU) and compare their accuracy, precision, recall, and receiver operating characteristic (ROC) curve values. Results show the LSTM model outperforms ANN and GRU. Then, we simulate the LSTM to classify the smart contracts before their deployment in the blockchain. Also, the efficacy of the blockchain is justified with the proposed system’s data storage cost and scalability.

Ethylene, being deleterious to plant in some instances like stress, is essential for ripening of fruits, overcoming seed dormancy and initiation of germination, however, ethylene can inhibit root elongation post germination. For plants, 1-aminocyclopropane-1-carboxylic acid (ACC) serves as precursor of ethylene however, for microbes ACC acts as chemoattractant. This establishes a scenario in the rhizosphere where, ACC utilizing microbes dominate the rhizospheric microbiome. A dynamic equilibrium of ACC concentration exists among root, rhizosphere, and bacterium; for such microbes ACC serves as source of nutrition for which they produce an enzyme ACC deaminase (ACCD) which in turn also benefits plants by reducing the levels of ACC and thereby reducing ethylene production in root. The basic function of ACCD is to degrade ACC in to α-ketobutyrate and ammonia, which is then absorbed by bacteria and plants, respectively. The reservoir of ACC in plants is huge, which on experiencing any sort of biotic and abiotic stress is converted to ethylene. Ethylene when overproduced in this way under stress, suddenly induces plant death. The rationale of using microbes with ACCD activity is, sought to decrease the magnitude of ethylene produced in plant under stresses. Because of such phenomenon of ethylene reduction in plant by the rhizospheric microbes, their use in agriculture has a unique stature as it benefits the agrarian society by sustaining high yields even during stress. This review emphasizes to portray the various aspects of ACCD producing microbes.

Industry 4.0-based oil and gas supply-chain (OaG-SC) industry automates and efficiently executes most of the processes by using cloud computing (CC), artificial intelligence (AI), Internet of things (IoT), and industrial Internet of things (IIoT). However, managing various operations in OaG-SC industries is a challenging task due to the involvement of various stakeholders. It includes landowners, Oil and Gas (OaG) company operators, surveyors, local and national level government bodies, financial institutions, and insurance institutions. During mining, OaG company needs to pay incentives as a royalty to the landowners. In the traditional existing schemes, the process of royalty transaction is performed between the OaG company and landowners as per the contract between them before the start of the actual mining process. These contracts can be manipulated by attackers (insiders or outsiders) for their advantages, creating an unreliable and un-trusted royalty transaction. It may increase disputes between both parties. Hence, a reliable, cost-effective, trusted, secure, and tamper-resistant scheme is required to execute royalty contract transactions in the OaG industry. Motivated from these research gaps, in this paper, we propose a blockchain-based scheme, which securely executes the royalty transactions among various stakeholders in OaG industries. We evaluated the performance of the proposed scheme and the smart contracts’ functionalities and compared it with the existing state-of-the-art schemes using various parameters. The results obtained illustrate the superiority of the proposed scheme compared to the existing schemes in the literature.

Currently, radioactive waste is disposed primarily by burial in a deep geological repository. Microorganisms thriving in such contaminated environment show tolerance to radionuclides. In the present study the bacterial flora, from soil sample collected from an area around atomic power station exposed to radionuclides and heavy metals, was cultivated and assessed for thorium (Th) tolerance. Of all the isolates, strain AM7 identified as O. intermedium was selected since it could thrive at high levels of Th (1000 mg L−1). AM7 was characterized physico-chemically and its culture medium was optimized using central composite design of response surface methodology for assessing its growth properties in presence of Th. The strain also showed exceptional exopolysaccharide (EPS) production and its yield was further analyzed using one factor study to investigate the influence of each medium component. On supplementing the EPS medium with Th, no significant decrease in yield was observed. FTIR spectroscopy revealed the functional groups of EPS involved in EPS-Th binding. To the best of our knowledge, this is the first report showing exceptional Th-tolerance by any bacteria. Such study will help other researchers to strategize an environment-friendly way of radwaste disposal.

Regular up-gradation in the standards of the wireless networks and to sustain in the market with the best services, are the key challenges to the services providers of the telecommunication industries. Traditional mobile number portability system (TMNPS) is based on the manual process, in which existing service provider and the new service provider have to undergo certain transfers once a porting request is generated by the user. Slow processing of request, lack of transparency among the entities involved, and delay during the verification are the major challenges in the TMNPS. Moreover, a third-party is required to ensure the security of the stored and regulated data. Motivated from these facts, in this paper, we propose a blockchain-based mobile number portability scheme, which uses an Ethereum blockchain technology and call routing mechanism to handle the request of the user. The secured royalty contract transactions and secure call routing mechanism are the potential part of the proposed scheme. We then evaluated the performance of the proposed scheme and functionalities of the proposed smart contracts (SCs) using experimental setup with respect to various parameters. Results show that the transition time taken by the proposed scheme is only 4 seconds for 200 blocks and TMNPS took 6 seconds to execute the 200 blocks.

The current study depicts the isolation of luminescent bacteria from fish and squid samples that were collected from Veraval fish harbour. From Indian mackerel, total 14 and from squid, total 23 bioluminescent bacteria were isolated using luminescence agar medium. Two bioluminescent bacteria with highest relative luminescence intensity PBR1 and PBL1 were selected. These two isolates were subjected to detailed biochemical characterization and were tested positive for 5 out of 13 biochemical tests. Furthermore, both PBR1 and PBL1 were able to ferment cellobiose, dextrose, fructose, galactose, maltose, mannose, sucrose and trehalose with acid production. Based on 16S rRNA partial gene sequence analysis, PBR1 was identified as Vibrio alginolyticus and PBL1 as V. rotiferianus. Antibiotic susceptibility test using paper-disc method showed that PBR1 and PBL1 were sensitive to chloramphenicol, ciprofloxacin, co-trimoxazole, gatifloxacin, levofloxacin, linezolid ad roxithromycin out of 18 antibiotics tested. Moreover, both strains were evaluated for their exopolysachharide (EPS) producing ability where PBR1 and PBL1 were able to yield 1.34 g% (w/v) and 2.45 g% (w/v) EPS respectively from 5 g% (v/v) sucrose concentration. Heavy metal toxicity assessment was carried out using agar well diffusion method with eight heavy metals and both the strains were sensitive to As(III), Cd(II), Ce(II), Cr(III), Cu(II), Hg(II) and while they showed resistance to Pb(II) and Sr(II). Based on these results, a study was conducted to demonstrate bio-removal of Pb and Sr by EPS of PBR1 and PBL1. Fourier transform infrared (FTIR) spectra revealed the functional groups of EPS involved in interaction with the heavy metals. Owing to the sensitivity for the remaining heavy metals, these bioluminescent bacteria can be used further for the development of luminescence-based biosensor.

The phenomenon of bioluminescence is the most widely investigated model of quorum sensing (QS) that occurs in various strains of Vibrio. Of lately, most of the virulence exhibited by other microbes is also attributed by similar quorum sensing pathways. Any leap towards blocking of such mechanisms is the need of the hour which is hypothesized to be achieved by interfering with normal QS interactions between ligands and their receptors. Gingerol, a pungent oil easily available from ginger is a structural analog of N-acylhomoserine lactone (AHL), which is an actual signalling ligand of QS-receptor LuxR responsible for initiating a cascade of reactions leading to bioluminescence. In-silico study suggested the antagonistic binding of gingerol to LuxR by hydrogen bonding and hydrophobic interactions which should, in theory, reduce bioluminescence. This was corroborated experimentally by rigorous image analysis of luminescence using hue, saturation and luminescence (HSL) values. Hence, we conclude gingerol as a potent QS-inhibitor for LuxR that may also inhibit the other members of AHL-receptor family.

Due to globalization, privatization and liberalization; sugar industry has to face the domestic as well as international competition. Thus, for survival of the industry, cost effectiveness and economics of by-products become very vital. The aim of this work is to assess the potential, in the short term, for fuel ethanol production by using intermediate molasses in a sugar plant in central India. The by-product plant can support the existing plant to improve the general economy, financial viability, economic status of sugarcane growers and workers by way of paying higher prices for sugarcane crop and also create more employment opportunities in the rural areas by setting up industries based on sugarcane by-products. For assessing the amount of Ethanol production an experimental study has been carried out which find out the amount of ethanol production via fermentation process of molasses sample acquired from the plant. It gives more fine results as the quality of sugarcane changes from place to place.

There has been a significant surge in consumption of radionuclides for various academic and commercial purposes. Correspondingly, there has been a considerable amount of generation of radioactive waste. Bacteria and archaea, being earliest inhabitants on earth serve as model microorganisms on earth. These microbes have consistently proven their mettle by surviving extreme environments, even extreme ionizing radiations. Their ability to accept and undergo stable genetic mutations have led to development of recombinant mutants that are been exploited for remediation of various pollutants such as; heavy metals, hydrocarbons and even radioactive waste (radwaste). Thus, microbes have repeatedly presented themselves to be prime candidates suitable for remediation of radwaste. It is interesting to study the behind-the-scenes interactions these microbes possess when observed in presence of radionuclides. The emphasis is on the indigenous bacteria isolated from radionuclide containing environments as well as the five fundamental interaction mechanisms that have been studied extensively, namely; bioaccumulation, biotransformation, biosorption, biosolubilisation and bioprecipitation. Application of microbes exhibiting such mechanisms in remediation of radioactive waste depends largely on the individual capability of the species. Challenges pertaining to its potential bioremediation activity is also been briefly discussed. This review provides an insight into the various mechanisms bacteria uses to tolerate, survive and carry out processes that could potentially lead the eco-friendly approach for removal of radionuclides.

Cytosolic nucleotidase II (cN-II) from Legionella pneumophila (Lp) catalyzes the hydrolysis of GMP and dGMP displaying sigmoidal curves, whereas catalysis of IMP hydrolysis displayed a biphasic curve in the initial rate versus substrate concentration plots. Allosteric modulators of mammalian cN-II did not activate LpcN-II although GTP, GDP and the substrate GMP were specific activators. Crystal structures of the tetrameric LpcN-II revealed an activator-binding site at the dimer interface. A double mutation in this allosteric-binding site abolished activation, confirming the structural observations. The substrate GMP acting as an activator, partitioning between the allosteric and active site, is the basis for the sigmoidicity of the initial velocity versus GMP concentration plot. The LpcN-II tetramer showed differences in subunit organization upon activator binding that are absent in the activator-bound human cN-II structure. This is the first observation of a structural change induced by activator binding in cN-II that may be the molecular mechanism for enzyme activation. Database The coordinates and structure factors reported in this paper have been submitted to the Protein Data Bank under the accession numbers 2BDE and 4G63. The accession number of GMP complexed LpcN-II is 4OHF. Structured digital abstract LpcN-II and LpcN-II bind by molecular sieving (View interaction) LpcN-II and LpcN-II bind by x-ray crystallography (View interaction) [Structured digital abstract was added on 5 March 2014 after original online publication]

In this paper, an adaptive framework for audio retrieval in live teleconferencing environments with multiple participants is proposed. The framework uses a non reference anchor array (NRA) to capture the interfering speech sources, in addition to the primary array that captures the speech source of interest (SOI). A linearly constrained-minimum variance (LC-MV) beamformer is used herein such that the signal coming from the look direction is preserved while interferences coming from the non look direction are nulled. Additionally, the reverberant component of the speech acquired by this framework is removed by a novel method that uses the linear prediction (LP) residual cepstrum. This method does not require the computation of the acoustic impulse response (AIR) of the teleconferencing room and hence is computationally efficient. The NRA framework is therefore able to remove correlated noise coming from the direction of the SOI and also dereverberating the noise free signal. The performance of the proposed framework is evaluated by conducting experiments on clean speech acquisition from distant microphone arrays. Experiments on distant speech recognition are also conducted using the TIMIT and MONC databases. Experimental results obtained from the proposed framework indicate a reasonable improvement over correlation, subspace and standard minimum variance beamforming methods. The application of the framework in audio retrieval in a live teleconferencing environment with multiple participants is also discussed.