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The Giant Metrewave Radio Telescope (GMRT) is today a frontline international facility for low-frequency radio astronomy, that has produced several exciting and important new results in the 15 years that it has been operational. To keep the GMRT competitive in the global arena in the future, a major upgrade of the observatory is nearing completion that will increase its sensitivity by up to three times and make it a more powerful and versatile facility. We describe the main goals of this upgrade, highlight the technical features and challenges, outline the science potential and update the current status of this venture.

The Internet of Things (IoT) is a rapidly evolving and user-friendly technology that connects everything and enables effective communication between linked things. In hospitals and other healthcare centers, healthcare monitoring systems have exploded in popularity over the last decade, and wireless healthcare monitoring devices using diverse technologies have a huge interest in several countries worldwide. The existing studies in healthcare IoT met a few shortcomings in terms of privacy, security, higher data dimensionality, higher cost, larger execution time, and so on. To tackle these issues, we proposed a novel IoT-enabled and secured healthcare monitoring framework (IoT-SHMF) for heart disease prediction. The data are taken from the Cleveland Heart Disease database. First, authentication is performed through registration, login, and patient data verification. The Matrix-based RSA encryption technology and a blockchain-based data storage concept provide safe data transmission and authorization. Subsequently, the secured data is downloaded by the hospital management (HM) system. The HM system scrutinizes the decrypted data. Finally, the Deep Convolutional Neural Network-based Archimedes Optimization (DCNN-AO) algorithm classifies the normal and abnormal classes of heart disease. The implementation work of the proposed model is simulated using JAVA software with different performance measures. Various performance metrics with state-of-art methods validate the effectiveness of the proposed model. The proposed IoT-based system ensures better security by about 98%. The decryption time of our proposed approach, when the sensor nodes are equal to 25, is 37 seconds.

Extremely heavy rainfall occurred over Kerala, southwest coast of India, during mid-August 2018 resulting in devastating floods. This flood may be called “the flood of the century” as the state has not experienced a flood of this magnitude since the 1924 flood. The rainfall over Kerala during June, July and August 2018 was 15%, 18% and 164% above normal. To examine the reasons for this anomalous phenomenon, the meteorological conditions during this period are studied by analysing different parameters, such as wind, rainfall, potential evaporation, latent heat, outgoing longwave radiation, etc., and it is found that a combination of several rain favouring conditions prevailed at that time. The positive phase of Madden–Julian Oscillation (MJO) coupled with a monsoon depression in the Bay of Bengal and a weak trough in the south-eastern Arabian Sea strengthened the monsoon Low-Level Jet (LLJ) bringing moisture-laden winds over Kerala. The rising limb of Walker and Hadley circulations was also found over Kerala, which gave favourable updraft for cloud formation. In addition, the core of the Tropical Easterly Jet (TEJ) was found over the Kerala and Karnataka region. The cyclonic circulation in the mid-troposphere observed around the monsoon depression extended up to the west coast of India. Spatial variation of different weather parameters and their anomalies showed that many of the parameters were anomalously high during the second week of August 2018, when the torrential rainfall occurred. The simultaneous occurrence of all these conditions could have contributed to the extreme rainfall events and severe floods over Kerala.

The present study focuses on the heat transfer within a ventilated porous enclosure saturated with a hybrid nanofluid, with the added influence of a magnetic field. The working hybrid nanofluid used in the study is consisting of copper and alumina nanoparticles suspended in water. This research covers two different types of geometries based on their opening ports. The cavity contains two vertical heating baffles placed near the inlet and outlet ports. The objective of this research is to understand how the presence of these heated obstacles, along with the distinct properties of the hybrid nanofluid and porous medium in the existence of magnetic field, influence the heat transfer and flow patterns within the cavity. The discretized governing equations are solved using finite difference method along with the boundary conditions. Irrespective of various parameters such as Solid volume fraction (ϕ), Darcy number (Da), Hartmann number (Ha), length of heating baffles (hb) and Rayleigh number (Ra), configuration BT consistently demonstrates higher heat transfer. The heat transfer near the heated baffle is maximized when Ra=103 and Da=10-4 in configuration BT. For Ra=103 and 104 in configuration BT, the highest heat transfer along the right sidewall is achieved with 25%; while, hb=35% is optimal at Ra=105. The findings derived from this investigation hold significant relevance for a multitude of engineering domains, encompassing energy systems, heat exchangers, and the extraction of geothermal energy.

Hydrogen sulfide (H 2 S) is a poisonous gas and corrosive with a characteristic rotten egg smell. Exposure to a higher concentration of H 2 S gas leads to death. Research groups across the globe have been working on developing a gas sensor composed of novel sensing materials to monitor deadly H 2 S gas for over a decade. Carbon-based materials such as single-wall carbon nanotubes, multi-wall carbon nanotubes, graphene, and graphene derivatives have been incorporated with metal oxides to improve H 2 S gas sensing properties. Carbon-based composites have unique physicochemical properties which provide the sensor possessing superior sensitivity, selectivity, stability, quick response time, etc. This review highlights the importance of H 2 S sensors based on rGO/MOx and CNT/MOx, their enhanced sensitivity and selectivity to H 2 S.

PurposeVentral hernia risk score (VHRS) is a risk assessment tool for predicting the development of surgical site infection (SSI) developed in the Veterans Affairs population by Berger et al. The score was externally validated by the same study group in a diverse population in another study. It was also shown to be better than the existing Centre for Diseases (CDC) wound class and Ventral Hernia Working Group (VHWG) models. Our study aims to test the performance of the score in an Asian-Indian population.MethodsA prospective database of ventral hernia repairs done in a tertiary care centre between February 2019 and December 2020 was utilized for the study. All patients with a minimum follow-up of 1-month period were included in the study. The CDC definition of SSI was used. The VHRS, VHWG, and CDC class of each of the patients was determined. Receiver-Operating curves (ROC) of the scores and area under the curves (AUC) were used to compare the three scores.ResultsA total of 120 patients were included. During the course of our study, a total of 33 patients developed SSI (27.5%). Important factors which seemed to predict SSI were median operating time, CDC incision class, concomitant hernia repair, and creating skin flaps. The AUC of the VHRS score was 0.76 which was higher than those of VHWG (0.61) and CDC (0.58).ConclusionOur study externally validates the novel VHRS which outperforms both CDC incision class and VHWG in predicting SSI following open ventral hernia repair, especially in a group with lower BMI compared to the previous reports.Trial registration No CTRI/2020/07/026289 registered on 01/07/2020.

The effect of an imposed alternating current (A.C) electric field on the onset of convective instability in a horizontal triply diffusive fluid layer is investigated. Analytical solutions are obtained for steady and oscillatory onset when imposed gradients of the stratifying agencies are constant and vertical. It was found that A.C electric Rayleigh number did not affect the necessary conditions for oscillatory convection. The stability boundaries are drawn and it is observed that an increase in the A.C electric field strength is to hasten the onset of convection. The evolution of neutral curves is analyzed in detail by varying the A.C electric Rayleigh number and other physical parameters. For certain choices of physical parameters, it is noted that the oscillatory part will give rise to two oscillatory neutral solutions for each wave number and closed disconnected neutral curves are found to exist, suggesting the requirement for three critical Rayleigh numbers to specify the linear stability criterion.

The genus Parapercis Bleeker ( 1863 ) is widely reported, with three recent new records from Indian waters. During the biodiversity assessment surveys, Black dotted sand perch, Parapercis millepunctata (Günther  1860 ), is collected from the outer reef slope of Kavaratti Island, Lakshadweep, India. The present record forms the report from the west coast of India, with voucher specimen and abridges the gap in the continuous distribution of P. millepunctata, from Andaman and Nicobar Islands in the east through the east coast of India and the Maldives to Mauritius in the West, in the Indian Ocean, by providing an intermediary occurrence in Lakshadweep. An annotated checklist of fourteen species reported from Indian waters is provided, with a detailed account of the distribution and comments on earlier reports.

Avenue plantation produces a significant amount of leaf litter throughout the year, and sustainable management is a primary concern in various establishments. Mesua ferrea L. (MF) is a widely grown avenue tree species that produces enormous amounts of leaf litter throughout the year. The litter remains undecomposed in natural conditions for a long time (2-3 years), requiring labour-intensive management. The rate of decomposition, nutrient dynamics and microbial species involved in the decomposition process has been studied by the modified litterbag method in natural conditions using intact and shredded MF leaf litter. The results of the study revealed 50% biomass loss from intact and shredded MF leaf litter within 120 days as compared to the negligible biomass loss in the control treatment. The percentage of nutrients released followed the same pattern as biomass loss for intact and shredded MF samples. The decay constant values were observed as 1.99, 1.92 and 0.33 for shredded, intact and control treatments, respectively. Penicillium with 12 isolates was recorded as the most dominant cellulose-degrading fungi during the decomposition of MF leaf litter. The study observed that the embedding of shredded MF leaf litter in soil significantly reduced the time required for the decomposition of litter. It is concluded that embedding shredded MF leaf litter in the soil can enhance rapid decomposition while improving soil fertility. The proposed technique may be employed in the sustainable management of MF leaf litter in particular and other litter in general.

Wireless body area networks (WBANs) have great potential to supply society with vital technical services, but the low power of network nodes severely hampers their development. To solve this problem, Energy-Efficient, a low-power cluster-based routing system intended for precise biological data gathering in WBANs, is presented in this study. This approach comprises three main stages: data aggregation, cluster head (CH) selection, and cluster creation. The suggested approach balances biosensor energy and optimizes energy usage by utilizing the modified snake swarm optimization algorithm (MSSOA) for routing and the adaptive binary bird swarm optimization algorithm (ABBSOA) for cluster formation and CH selection. The suggested technique outperforms the most recent WBAN routing protocols, including MT-MAC, ALOC, DHCO, and M-GWO, by using a power-balancing routing tree and considering biosensor distance and remaining energy. The experimental results demonstrate that the proposed ABBSOA-MSSOA model achieves a jitter protocol value of 0.3 ms at 100 nodes, a buffer occupancy ratio of 2.5%, a cluster lifetime of 600 s, a cluster building time of 12.2 s, an energy consumption of 42 mJ, a communication overhead of 8.3%, a packet delivery ratio of 98.2%, and an average end-to-end delay of 25 ms compared to other existing methods.