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Nonthermal radio transients from the quiet Sun have been recently discovered and it has been hypothesized using rough calculations that they might be important for coronal heating. It is well realized that energy calculations using coherent emissions are often subject to poorly constrained parameters and hence have large uncertainties. However, energy estimates using observations in the extreme ultraviolet (EUV) and soft X-ray bands are routinely done and the techniques are pretty well established. This work presents the first attempt to identify the EUV counterparts of these radio transients and then use them to estimate the energy deposited into the corona during the event. I show that the group of radio transients studied here is associated with a brightening observed in the EUV waveband and is produced by an energy release of ≈ 10 25  ergs. The fact that the flux density of the radio transient is only ≈ 2  mSFU suggests that it might be possible to do large statistical studies in the future for understanding the relationship between these radio transients and other EUV and X-ray counterparts, as well as for understanding their importance in coronal heating.

Presently, rice-fallows are targeted for cropping intensification in South Asia. Rice - fallows a rainfed mono-cropping system remain fallow after rice due to lack of irrigation facilities and poor socio-economic condition of the farmers. Nevertheless, there is the scope of including ecologically adaptable winter crops in water-limited rice-fallow conditions with effective moisture conservation practices. The study aimed to identify the winter-crops that are adaptable and productive in rice-fallow conditions and to evaluate the different tillage-based crop establishment practices for soil moisture conservation, grain yield, economics, and sustainability parameters. Six different crop establishment and residue management (CERM) practices viz ., zero - tillage direct seeded rice (ZTDSR), zero-tillage transplanted rice (ZTTPR), puddled transplanted rice (PTR), ZTDSR with rice residue retention (ZTDSR R+ ), ZTTPR with rice residue retention (ZTTPR R+ ), PTR with rice residue retention (PTR R+ ) as main-plot treatment and five winter crops (chickpea, lentil, safflower, linseed, and mustard) as sub-plot treatment were evaluated in a split-plot design. The productivity of grain legumes (chickpea and lentil) was higher over oilseed crops in rice-fallow conditions with an order of chickpea > lentil > safflower > mustard > linseed. Among the CERM practices, ZTDSR R+ and ZTDSR treatments increased the grain yield of all the winter crops over PTR treatment, which was primarily attributed to higher soil moisture retention for an extended period. Grain yield increment with conservation tillage practices was highly prominent in safflower (190%) followed by lentil (93%) and chickpea (70%). Rice grain yield was higher (7–35%) under PTR treatment followed by ZTDSR treatment. Conservation tillage practices (ZTDSR, ZTTPR) reduced energy use (11–20%) and increased the energy ratio over conventional tillage practice (PTR), higher in rice-safflower, rice - lentil and rice - chickpea rotations. Higher net return was attained in rice - safflower and rice - chickpea rotations with ZTDSR R+ treatment. Predicted emission of greenhouse gases was markedly reduced in ZTDSR treatment (30%) compared to ZTTPR and PTR treatments. Hence, the study suggests that cropping intensification of rice-fallows with the inclusion of winter crops like chickpea, lentil, and safflower following conservation tillage practices (ZTDSR R+ in particular) could be the strategic options for achieving the higher system productivity, economic returns, and energy use efficiency with the reduced emission of greenhouse gases.

Approximately eight decades ago, during World War II, the concept of intelligent robots capable of independent arm movement began to emerge as computer science and electronics merged with advancements in mechanical engineering. This marked the starting point of a thriving industry focused on research and development in mobile robotics. In recent years, there has been a growing association between robotics and artificial intelligence, aiming to enable robots to make autonomous decisions akin to human cognition. To achieve this objective, researchers are actively exploring the integration of artificial neural networks with mechatronic robots. These intelligent and self-decision-making robots possess the potential to revolutionize human capabilities and elevate our intelligence to unprecedented levels. In various physical service sectors such as cleaning, security, and other tasks that don't require creative or analytical thinking, these robots can efficiently carry out the assigned responsibilities. Moreover, robots have the potential to play a significant role in military operations, eliminating the need for human lives to be sacrificed in warfare. This review article aims to explore the advancements in mobile robotics since their inception nearly 80 years ago. It will delve into the detailed applications of these robots across different sectors and discuss their profound effects on contemporary human lives and industrial landscapes.

In South Asian and Sub-Saharan African nations, climate change offers numerous hurdles to growth and development. These regions are susceptible to climate change due to their vast population reliance on agriculture, high demand for natural resources, and comparatively limited strategies for coping. Reduced food grain yields, crop losses, feed scarcity, lack of potable water for livestock during the summer, forceful animal migrations, and severe losses in the poultry and fishery industries have all been documented, posing a threat to the lives of the rural poor. As global food security and agricultural productivity become increasingly vulnerable, the focus has shifted towards adopting climate-smart agricultural practices and techniques. The present study discussed the need to identify and prioritize regionally evolving climate-smart farming practices and the enabling environment required for CSA uptake. The popular CSA practices in South Asia and Sub-Saharan Africa are crop rotation, cultivation of drought/flood-tolerant crops, legume intercropping, changing planting dates, rainwater harvesting, agroforestry, micro-irrigation technologies, minimum tillage, and integrated crop-livestock farming. A solid institutional structure, policy environment, infrastructure, agricultural insurance, climate information services, and gender and social inclusion provide the required enabling environment to alleviate farmer issues, lower CSA adoption obstacles, and improve operational sustainability. Highlights of the study are: This study examines how climate-smart farming practices are evolving in South Asia and SubSaharan Africa. We used a systematic approach to categorize and characterize agricultural adaptation alternatives to climate change. Our specific goals are to gain knowledge of the CSA adoption-enabling environments and the climate-smart agriculture practices employed in South Asia and Sub-Saharan Africa

Conservation agriculture (CA), which encompasses minimum soil disturbance, residue retention either through crop residue, or cover crops and crop diversification-based crop management practices can modify the status of pest dynamics and activities under the changing climatic scenarios. CA has been advocated extensively to optimize the use of available resources, maintain the environmental quality, enhance crop productivity, and reduce the climate change impacts. Information related to the impacts of long-term CA-production systems under rice-based cropping systems on pest status is lacking, particularly in middle Indo-Gangetic Plains (MIGP). Under CA, puddling is completely avoided, and rice is directly sown or transplanted to maintain better soil health. Different sets of experimentations including farmers practice, partial CA and full CA (CA) as treatments in rice-based cropping systems, were established from 2009, 2015 and 2016 to understand the long-term impacts of CA on pest dynamics. In this study, direct and indirect effects of tillage (zero, reduced and conventional tillage), residue retention and cropping sequences on abundance and damage by pests were investigated. After 4–5 years of experimentation, populations of oriental armyworm [ Mythinma (Leucania) (Pseudaletia) separata (Wlk.)] in wheat , mealybug [ Brevennia rehi (Lindinger)] and bandicoot rat [ Bandicota bengalensis (Gray)] in rice were found to increase abnormally in CA-based production systems. Conventionally tilled plots had a significant negative effect while residue load in zero-tilled plots had a significant positive effect on larval population build-up of M. separata . Zero tillage had a higher infestation of mealybug (52–91% infested hills) that used grassy weeds ( Echinochloa colona , Echinochloa crusgalli , Cynodon dactylon , Leptochloa chinensis and Panicum repense ) as alternate hosts. Cropping sequences and no disturbance of soil and grassy weeds had higher live burrow counts (4.2 and 13.7 burrows as compared to 1.47 and 7.53 burrows per 62.5 m 2 during 2019–2020 and 2020–2021, respectively) and damaged tillers (3.4%) in CA-based practices. Based on the present study, pest management strategies in CA need to be revisited with respect to tillage, residue retention on soil surface, grassy weeds in field and cropping sequences to deliver the full benefits of CA in MIGP to achieve the sustainable development goals under the climate change scenarios.

Evaluating the submarine groundwater discharge (SGD) derived strontium (Sr) flux from the Bengal Basin to the Bay of Bengal (BoB) and determining its isotopic composition is crucial for understanding the marine Sr isotopic evolution over time. Measurements of spatially and temporally distributed water samples collected from the BoB show radiogenic 87 Sr/ 86 Sr, high Sr, calcium (Ca) concentrations and high salinity in samples collected dominantly from 100–120 m depth, which can be explained only by the contribution of saline groundwater from the Bengal Basin. These results provide a direct evidence of the SGD-Sr flux to the BoB. This SGD-Sr flux is however, spatially heterogeneous and using conservative hydrological estimates of the SGD flux to the BoB, we suggest a SGD Sr flux of 13.5–40.5 × 10 5 mol/yr to the BoB. Mass balance calculations using Sr concentrations and 87 Sr/ 86 Sr suggest up to 7% contribution of SGD to the 100–120 m BoB water samples. The identification of SGD at 100–120 m depth also provides an explanation for the anomalous variations in barium (Ba) concentrations and the δ 18 O-salinity relationship in intermediate depths of the BoB.

Having access to potable water is a fundamental right to well-being. Despite this, 3.4 million people die from diseases caused by water each year, and 1.1 billion people lack access to potable drinking water. Although industrialization, durable infrastructure, and rapid development have increased living standards, the water problem has left humanity defenseless. As different human activities have contaminated these water reserves, according to an estimate, water is the cause of 80% of ailments. As a result, it is necessary to permit enough infrastructure to ensure the security of a reliable supply of potable water. Thus, a real-time WBPCB dataset with 17 features and a proposed IoT-based system to collect data are used in this research to address the issue. The research paper provides a system for predicting diseases and forecasting long-term trends. Classification is performed using Random Forest, XGBoost, and AdaBoost, which have accuracy rates of 99.66%, 99.52%, and 99.64%, respectively. Forecasting is performed using LSTM, which has an MSE value for the pH parameter of 0.1631. The paper introduces TS-SMOTE, a novel hybridized time-series SMOTE data augmentation approach. Additionally, it offers an IoT system that uses H-ANFIS to gather data in real-time and identify attacks.

Silver nanoparticles (AgNPs) is of great importance to scientific community due to their plethora of applications. Several plant extracts have been reported for synthesis of AgNPs. In this study, lemon grass was used as a reducing and capping agent to prepare AgNPs. The formation of AgNPs was confirmed by using UV–Vis spectra as AgNPs show a characteristic peak around 400 nm. Effect of pH, temperature and lemon grass extract to silver nitrate ratio was optimized using response surface methodology (RSM). Characterization of AgNPs was done using X-Ray Diffraction (XRD), Energy Dispersive X-Ray spectroscopy (EDX), Trasmission Electron Microscopy (TEM) and Dynamic Light Scattering (DLS). Gas Chromatography-Mass spectrometry (GC–MS), Energy Dispersive X-Ray spectroscopy and Fourier Transform-Infrared (FT-IR) spectroscopic analysis showed involvement of metabolites of lemon grass in the formation of AgNPs. Photo-catalytic activity of synthesized AgNPs was evaluated through degradation of organic pollutant methylene blue dye.Graphic abstract

The CoVID-19 infections began rising worldwide during the initial weeks of March 2020, reacting to which the Government of India called for nationwide lockdown for ~ 3 weeks. The concentration of pollutants during the lockdown were compared with pollution levels recorded during the preceding year for the same time frame. A direct relationship was established between the high level of air pollutants (PM 2.5 , PM 10 , NO 2 and SO 2 ) and CoVID-19 infections being reported in the Indian cities. The correlation indicates that the air pollutants like PM 2.5 , PM 10 , NO 2 and SO 2 are aggravating the number of casualties due to the CoVID-19 infections. The transmission of the virus in the air is in the form of aerosols; and hence places which are highly polluted may see a proportionate rise in CoVID-19 cases The high-level exposure of PM 2.5 over a long period is found to be significantly correlated with the mortality per unit confirmed CoVID-19 cases as compared to other air pollutant parameters like PM 10 , NO 2 and SO 2 .