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The Smart Grid is an advanced digital two-way power flow power system capable of self-healing, adaptive, resilient and sustainable with foresight for prediction under different uncertainties. In this paper, a survey on various Smart Grid enabling technologies, Smart Grid metering and communication, cloud computing in Smart Grid and Smart Grid applications are explored in detail. Opportunities and future of Smart Grid is also described in this paper. For Smart grid enabling technologies Smart meters, smart sensors, vehicle to grid, plug in hybrid electric vehicle technology, sensor and actuator networks are explored. Advanced metering infrastructure, intelligent electronic devices, phasor measurement units, wide area measurement systems, local area network, home access network, neighborhood area network, wide area networks and cloud computing are explored for Smart Grid metering and communication. Home and building automation, smart substation, feeder automation is explored for smart grid applications. Associations of initial studies for the next step in smart grid applications will provide an economic benefit for the authorities in the long term, and will help to establish standards to be compatible with every application so that all smart grid applications can be coordinated under the control of the same authorities. Therefore, this study is expected to be an important guiding source for researchers and engineers studying the smart grid. It also helps transmission and distribution system operators to follow the right path as they are transforming their classical grids to smart grids.

Fig. 1 and the Graphical Abstract were created by Heno Hwang, scientific illustrator at King Abdullah University of Science and Technology (KAUST). The research reported in this publication was supported by funding from KAUST. The funding support from Department of Science and Technology’s Technology Mission Division (No. OST/TM O(EWO)/OWUIS20IS/TS-03 (G)) under the program “Optimal Water Use in Industrial Sector” is greatly acknowledged.

Concerns over environment and increased demand for energy have led the world to think about alternate energy sources such as the wind, hydro, solar and fuel cells. Out of these photovoltaic (PV) generation systems (PGS) become increasingly important all over the world due to its availability, cleanness, low maintenance cost, and inexhaustible nature. The probability of partial shading conditions (PSC) is also high for large PGS. Under PSC, the P–V curve of PGS exhibits multiple peaks, which reduces the effectiveness of conventional maximum power point tracking (MPPT) methods. In this paper, an improved particle swarm optimization (PSO) based MPPT algorithm for PGS operating under PSC is proposed. Conventional PSO is modified to meet practical consideration of PGS operating under PSC. Problem formulation, design details, and experimental results are discussed in detail. The proposed technique is independent of system, it is easy to implement, tracking efficiency is high and performance under PSC is good. The effectiveness of the proposed method is validated by analyzing the experimental results obtained from 110 W solar power generation systems.

The advent of COVID-19 has kept the whole world on their toes. Countries are maximizing their efforts to combat the virus and to minimize the infection. Since infectious microorganisms may be transmitted by variety of routes, respiratory and facial protection is required for those that are usually transmitted via droplets/aerosols. Therefore this pandemic has caused a sudden increase in the demand for personal protective equipment (PPE) such as gloves, masks, and many other important items since, the evidence of individual-to-individual transmission (through respiratory droplets/coughing) and secondary infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). But the disposal of these personal protective measures remains a huge question mark towards the environmental impact. Huge waste generation demands proper segregation according to waste types, collection, and recycling to minimize the risk of infection spread through aerosols and attempts to implement measures to monitor infections. Hence, this review focuses on the impact of environment due to improper disposal of these personal protective measures and to investigate the safe disposal methods for these protective measures by using the safe, secure and innovative biological methods such as the use of Artificial Intelligence (AI) and Ultraviolet (UV) lights for killing such deadly viruses.

Conventional maximum power point tracking (MPPT) algorithms fails to track peak power from a solar photovoltaic panel (SPV) effectively under rapidly changing atmospheric and partial shading conditions (PSC). To track peak power more effectively under these conditions, low cost, powerful soft computing (SC) have been introduced by the researchers. Due to the ability to solve non-linear problems, flexibility and adaptive nature, SC based MPPT techniques can track peak power under varying atmospheric conditions. Various SC based MPPT techniques have been proposed by researchers till date. Comprehensive studies on all these techniques are not available. This work summarizes working principle of various SC-MPPT techniques and are compared each other based on the certain parameters like accuracy, tracking efficiency, SPV array dependency, convergence time, complexity of algorithm, hardware implementation, ability to handle PSC’s and variables used. The information that is gathered and summarized in this paper will help researchers for future studies in this area.

Crank Shaft is one of the important components of an IC Engine. As the mechanical property of the crankshaft directly influence the trustability and longevity of the engine, the rigidity of the crankshaft acted upon by the alternative loads must be guaranteed in design. So it is required very much to untangle the model of crankshaft through the stress analysis using ANSYS software. In this paper, first the 3D model of the engine parts are built in the software ‘CATIA V5’ and are then transferred to ‘ANSYS’. The analysis of crank throw distortion and stress provides a conceptual support to enhance the design by weigh reduction.

A series of oxime ester-derivatives were prepared by utilizing the schizandrin (1), a major compound isolated from Schisandra grandiflora, which is deployed in different traditional system of medicine. The in vitro antiproliferative activities of the synthesized compounds were assessed against a selected panel of human cancer cell lines (A549, RKO P3, DU145 and Hela) and normal cell (HEK293). Several of these derivatives were found more potent in comparison to parent compound, schizandrin (1). Particularly, 4a and 4b demonstrated potent activity against DU-145 and RKOP3 cell lines with IC50 values of 3.42 µM and 3.35 µM respectively. To characterize the molecular mechanisms involved in antitumoral activity, these two compounds, 4a and 4b were selected for further studies. Cell cycle analysis revealed that both the compounds were able to induce apoptosis and cell cycle arrest at G0/G1 phase. To know the extent of apoptosis in DU145 and RKOP3 cell lines, Annexin V-FITC were performed. Moreover, the tubulin polymerization assay indicated that 4a and 4b exhibits potent inhibitory effect on the tubulin assembly. Molecular docking studies and competitive binding assay also indicated that 4a and 4b effectively bind at the colchicine binding site of the tubulin.

In the present study, inorganic bulk and nano nutrients of zinc oxide, titanium oxide, and silver nanoparticles were synthesized using the chemical reduction method and invigourated with chilli seeds cv. PKM 1 each at 750, 1000 and 1250 mg kg−1 by using template-free aqueous solution. After nanoparticles invigouration, the seeds were analyzed for various parameters such as germination (%), shoot length, root length, and seedling vigour. Other important parameters, such as electrical conductivity and antioxidant enzyme activity (catalase and lipid peroxidase), were also analyzed, which in turn reflected the enhancement of seed quality of chilli seeds when they were invigourated with ZnO, TiO2 and silver nanoparticles. The results indicated that the chilli seeds invigourated with ZnO nanoparticles at 1000 mg kg−1 enhanced the germination and seedling vigour in aged seeds.

In continuation of our investigation of pharmacologically-motivated natural products, we have isolated bergenin (1) as a major compound from Mallotus philippensis, which is deployed in different Indian traditional systems of medicine. Here, a series of bergenin-1,2,3-triazole hybrids were synthesized and evaluated for their potentials against a panel of cancer cell lines. Several of the hybrid derivatives were found more potent in comparison to parent compound bergenin (1). Among them, 4j demonstrated potent activity against A-549 and HeLa cell lines with IC50 values of 1.86 µM and 1.33 μM, respectively, and was equipotent to doxorubicin. Cell cycle analysis showed that 4j arrested HeLa cells at G2/M phase and lead to accumulation of Cyclin B1 protein. Cell based tubulin polymerization assays and docking studies demonstrated that 4j disrupts tubulin assembly by occupying colchicine binding pocket of tubulin.

Ground water is the principal source for drinking water and other activities in Kozhikode town. Monitoring the ground water quality therefore is of utmost importance. In this paper a multivariate statistical analysis of quality of ground water has been carried out, based on thirty data points of water shed in Kozhikode city, Kerala, India. The parameters examined were PH, Electric conductivity, Total Dissolved Solids, Total Hardness, Chlorides, Calcium and Magnesium, Sodium, Potassium, Bicarbonates and Sulphates. A methodology for characterizing ground water quality of watersheds based on the above data that mingle multiple linear regression, principal component analysis and structural equation modeling is presented. The aim of this work is to analyze hydro chemical data in order to explore the groundwater samples and the origin of water mineralization, using mathematical method and modeling. Thus, with the help of MATLAB, a regression equation is explored for the sampled ground water. The structural equation modeling which has been carried out using IBM-SPSS Amos, allows a simultaneous analysis of the entire system of parameters.