Lightning, a climate-related highly localized natural phenomenon, claims lives and damage properties. These losses could only be reduced by the identification of active seasons and regions of ...lightning. The present study identifies and correlates the lightning-prone regions with the number of casualties reported over India at the state/union territory level. The seasonal and monthly composite satellite data of Lightning Imaging Sensor for the duration of 16 years (1998–2013) have been analyzed in this study for the identification of the major lightning-prone seasons and regions over India. The casualties due to lightning have also been estimated using data from Accidental Deaths and Suicides in India, National Crime Record Bureau report of India. The spatial distribution analysis reveals that lightning occurs mostly in hilly regions over India throughout the year (26 flash/sq. km/yr) and, however, causes lesser casualties because of the sparse population over the hilly terrain. The seasonal analysis reveals the most lightning phenomena occur during the pre-monsoon period (40–45 flash/sq. km/yr) over the northeast region of India. During the winter period, the lightning dominates over the northern parts of India such as Jammu and Kashmir. The state-wise casualties’ study reveals that maximum casualties are reported in Madhya Pradesh (313 deaths), Maharashtra (281 deaths) and Orissa (255 deaths) on an average per annum. The favorable climatic conditions, such as availability of moisture content, unstable atmosphere and strong convection, cause severe cases of lightning over the regions of Orissa and Maharashtra.
Electronic Health Records (EHRs) have become an increasingly significant source of information for healthcare professionals and researchers. Two technical challenges are addressed: motivating ...federated learning members to contribute their time and effort, and ensuring accurate aggregation of the global model by the centralized federated learning server. To overcome these issues and establish a decentralized solution, the integration of blockchain and federated learning proves effective, offering enhanced security and privacy for smart healthcare. The proposed approach includes a gamified element to incentivize and recognize contributions from federated learning members. This research work offers a solution involving resource management within the Internet of Medical Things (IoMT) using a newly proposed trust decentralized loop federated learning consensus blockchain. The obtained raw data is pre-processed by using handling missing values and adaptive min-max normalization. The appropriate features are selected with the aid of hybrid weighted-leader exponential distribution optimization algorithm. Because, data with multiple features exhibits varying levels of variation across each feature. The selected features are then forwarded to the training phase through the proposed pyramid squeeze attention generative adversarial networks to classify the EHR as positive and negative. The proposed classification model demonstrates high flexibility and scalability, making it applicable to a wide range of network architectures for various computer vision tasks. The introduced model provides better outcomes in terms of 98.5% in the training accuracy and 99% in the validation accuracy over Medical Information Mart for Intensive Care III (MIMIC-III) dataset, which is more efficient than the other traditional methods.
•Internet of Medical Things (IoMT) becomes increasingly complicated.•Creating and deploying Federated Learning (FL) model that prioritize privacy while connecting outstanding IoT services.•System's efficacy is assessed via comparison of privacy leakage & computational efficiency.
The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating episodic Heat Wave (HW) events of 2015 and 2016 with varied horizontal resolutions of 27 km for ...the entire India (d01), 9 km for the North West (NW (d02)) and South East (SE (d03)) domain. Study compares the maximum temperature (T
) simulated by WRF model, using six different combination of parameterization schemes, with observations from the India Meteorological Department (IMD) during the HW events. Among the six experiments, Exp2 (i.e., combination of WSM6 microphysics (MP) together with radiation parameterization CAM, Yonsei (PBL), NOAH land surface and Grell-3D convective schemes) is found closest to the observations in reproducing the temperature. The model exhibits an uncertainty of ± 2 °C in maximum temperature (T
) for both the regions, suggesting regional temperature is influenced by the location and complex orography. Overall, statistical results reveal that the best performance is achieved with Exp2. Further, to understand the dynamics of rising HW intensity, two case studies of HW days along with influencing parameters like T
, RH and prevailing wind distribution have been simulated. Model simulated T
during 2015 reaches up to 44 °C in NW and SE part of India. In 2016, HW is more prevailing towards NW, while in SE region T
reaches upto 34-38 °C with high RH (60-85%). The comparative research made it abundantly evident that these episodic events are unique in terms of duration and geographical spread which can be used to assess the WRF performance for future projections of HW.
The present study investigates the accelerating factors for extreme flash flood at Chamoli district of Uttarakhand on 7 February 2021. The Sentinel-2A and 2B satellite data have been used to depict ...changes in pre-flood (16th of January) i.e., 5 years of 2016 to 2021 to post-flood (10 February, 2021) situation over the study domain. Vegetation and snow-cover from 2016 to 2021 has been obtained using Normalized Difference Vegetation Index (NDVI) classification over study area. Normalized Difference Water Index (NDWI) is used to extract the pre and post-flood water pixels for flood inundation mapping. The Cartosat-1 digital elevation model (DEM) product is used for drainage pattern and stream order mapping. Correlation between the meteorological parameters such as snowfall, wind speed and wind direction of Nanda Gunti peak during the time of flood with the flood event is analysed. The overall results indicate heavy snowfall (4.22 mm/day) over Nanda Gunti hills followed by high wind speed (23 km/hr.) that might have led to initiation of avalanche/landslide, giving rise to massive flash flood and eroded approximately 0.0263 km
3
volume of landmass along with snow cover. Further, the 5 years NDVI analysis shows decrease in vegetation near Rishiganga and Alaknanda, a higher order river streams, is also crucial factor for flood intensification that caused massive destruction within the study area. The work highlights the importance of mapping of intense events and underline factors to reduce the impact and losses in case of future events.
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•Probiotic lactic acid bacteria isolated from milk and milk products act as natural metal adsorbents.•The bacterial cell pellet, rather than the supernatant, is used to demonstrate ...the lead-lactobacilli binding.•Bacterial cell number, lead concentration, and pH affect lead- lactobacilli binding to a greater extent.•All the selected strains tolerated a minimum of 700 mg/L lead concentration.•SEM analysis revealed that the lead binding occurred on the bacterial surface.
Probiotic lactic acid bacteria exhibit metal ion binding properties, which can be employed as metal bio-adsorbents in the human system. Lead is a prevalent dietary contaminant that causes lead toxicity in humans, especially children. In the present investigation, we evaluated the indigenous lactobacilli for their lead bioadsorption potential that can offer a pre-emptive approach for bioremediating lead toxicity. After standardizing the lead bioadsorption assay, ten probiotic lactobacilli showing lead retention of >80% in the pellet were selected. Statistical correlation analysis on lead bioadsorption assay, factors affecting lead and lead resistance profiling revealed L. plantarum HD 51 as the most potent lead adsorber. Scanning electron microscopy of L. plantarum HD 51 demonstrated that the binding occurred on the bacterial cell wall. Hence L. plantarum HD-51 could be used as a biotherapeutic agent to reduce the body’s burden on lead by sequestering it out of the human body.
We have examined the air quality over China, India and demonstrated marked differences in levels of air pollution resulted from the COVID-19 restrictions during December-April, 2019-20 to that of 11 ...years mean of 2009-19. The criteria air quality indicators i.e., nitrogen dioxide (NO_2), sulphur dioxide (SO_2), Aerosol Index (AI) and aerosol optical depth (AOD) data are retrieved from the Ozone Monitoring Instrument (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and MODerate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra and Aqua satellites, respectively. Over China, during COVID-19 lockdown a significant drop in columnar abundances of tropospheric NO_2 (-37%), SO_2 (-64%) and AOD (-8%) for 2020 in comparison to 11 years mean (2009-19) has been observed. A noticeable difference in NO_2 column burden is seen over SE (-35%), NE (-33%), NW (-13%) and SW (-5%) China. Over the SE and NE China, both NO_2 and SO_2 levels decreased dramatically in 2020 from that of 2009-19, by more than 40% and 65%, respectively, because of both stricter regulations of emissions and less traffic activity due to reduced social and industrial activities during COVID-19 restrictions. In contrast, the curve of monthly mean tropospheric columnar burden of NO_2 and SO_2 over India has shown moderate reduction of 16% and 20%, respectively because lockdown came into effect much later in March 2020. The mean NO_2 and SO_2 over IGP region is found to be 25% higher than whole India's mean concentration due to large scale urban settlement and crop burning events. The statistical t-test analysis results confirm significant (p ＜ 0.05) improvements in AQ during lockdown. The COVID-19 pandemic provided an unprecedented opportunity to investigate such large-scale reduction in emissions of trace gases and aerosols. Therefore, it is important to further strengthen environmental policies to tackle air quality, human health, and climate change in this part of the world.
This study aimed to identify the impact of an annular solar eclipse i.e., 21 June 2020 on the variation of meteorological parameters along with trace gases using statistical analyses. The study site ...is located at Poornima University, Jaipur (26.7796°N, 75.8771°E), Rajasthan, India. The observational analysis indicates a rapid decrease in solar direct radiation (SDR) which varied between 706 and 79 W/m
2
during the eclipse. SDR was reduced to 79 W/m
2
at the maximum peak of the solar eclipse at 11:55 a.m. at the study location. The comparative analysis shows the variation of SDR during the solar eclipse day, the previous day, and the day after the event. A strong dip was observed in SDR during the annular eclipse day concerning before (734.31 W/m
2
) and after (734.375 W/m
2
) eclipse event. Furthermore, the impact of the solar eclipse on temperature (Ts) and Relative Humidity (RH) was analyzed over Jaipur. The statistical analyses demonstrate an apparent decrease in temperature of about 2°C while RH shows a slight increment (3.45%) during the solar eclipse event. The results show an inverse correlation between the solar eclipse and trace gases variations during the eclipse due to the changes in solar radiation, surface temperature, and variation in winds that might affect the photochemical processes.
In the present study, the first systematic performance evaluation of aerosol optical depth (AOD) products retrieved using two satellite sensors i.e., Visible Infrared Imaging Radiometer Suite (VIIRS) ...and Aqua-Moderate-Resolution Imaging Spectroradiometer (MODIS) is carried out over India. We have used ground-based AOD from AERONET at 550 nm wavelength for inter-comparison with MODIS Aqua version C6.1 (C061) Deep Blue (DB) aerosol product and VIIRS/SNPP collection version 1.1 (V1.1) DB aerosol product over the time span of 7-year (2014–2020) observation periods. For validation, the average value of satellite pixels falling within the box of 50 Km x 50 Km keeping the AERONET station at the center is retrieved. The average daily data from the AERONET sun photometer (2014–2019) were obtained within ±15 min of satellite overpass time. Statistical parameters like correlation coefficient (R), RMSE, MAE, and RMB were calculated. The uncertainty of satellite AOD is evaluated using an envelope of Expected Error (EE = ±0.05 + 0.15 AOD for land). Statistical analysis shows that the MODIS AOD product outperforms VIIRS-retrieved AOD. The AOD retrieved from both sensors yields a high correlation (0.86—Jaipur, 0.79—Kanpur, 0.84—Gandhi College, and 0.74—Pune for MODIS and 0.75—Jaipur, 0.77—Kanpur, 0.49—Gandhi College, and 0.86—Pune for VIIRS) and low MAE (0.12—Jaipur, 0.20—Kanpur, 0.15—Gandhi College, and 0.09—Pune for MODIS and 0.13—Jaipur, 0.13—Kanpur, 0.26—Gandhi College, and 0.10—Pune for VIIRS). Other statistical measures such as RMSE, RMB, and P also suggest similar performance. More than 66% of the total data fall within the range of EE for both the satellite products at each station. Spatial comparison exhibits the same AOD pattern seasonally as well as annually having a minimum bias from −0.3 to +0.3 between MODIS and VIIRS. Slight underestimation and overestimation are observed in all the stations by MODIS, whereas VIIRS continuously underestimates AOD with increase in optical depth, suggesting improvements in the aerosol model and surface reflection in retrieval. Overall, the comparison of ground AERONET AOD reveals better accuracy of MODIS AOD with that of VIIRS satellite datasets over India.
In present scenario, there is need to develop adsorbent based and cost-effective water purifier for removal of radiological and toxic metal ion contaminants viz. cesium, strontium and cobalt from ...contaminated water. In this regard, modified montmorillonite was prepared using reaction with hydrogen peroxide and potassium di-hydrogen phosphate and obtained product was characterized by different spectroscopic techniques viz. Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The obtained modified montmorillonite was evaluated for removal of Cd(II), Co(II), Cs(I), Ni(II) and Sr(II) from contaminated water. Various factors which affect adsorption of metal ions on modified montmorillonite viz. contact time, initial concentration of metal ions and pH were studied. The batch method has been employed to determine adsorption capacity for metal ions in solution from 1000–10 000 μg/L, contact time 5–30 min, pH 4–10 and material quantities 50–200 mg at room temperature. The obtained adsorption data were fitted to Freundlich and Langmuir isotherm models; both models were found applicable for the metal ions adsorption on modified montmorillonite. The adsorption data were shown to follow pseudo second order reaction kinetics as per kinetic studies. The maximum adsorption capacity obtained 1.65–2.82 mg/g for Cd(II), Co(II), Cs(I), Ni(II) and Sr(II) metal ions. The results show that modified montmorillonite have great potential to remove Cd(II), Co(II), Cs(I), Ni(II) and Sr(II) from aqueous solutions through chemisorption and physio-sorption. Modified montmorillonite can be used for removal of radiological and toxic metal ion contaminants from contaminated water.
A colorimetric material was prepared and evaluated for simple and rapid detection of copper ion and other toxic metal ions. In this study, a colorimetric 1-(2-pyridylazo)-2-naphthol entrapped ...polyacrylamide (PAN-PAA) hydrogels was successfully prepared through polymerization and characterized by FT-IR. PAN-PAA hydrogels were evaluated for naked eye detection of Cu(II) ions in water. A yellow colour solution change into pink visual colour was observed within 20 min when hydrogel treated with Cu(II) ions at 300 μg L
–1
(ppb). The colour ntensity increased with increasing concentration of Cu(II) ions. The reaction time of colour change observed less time when concentration of metal ion is increasing such as1 mg L
–1
(15 min), 2 mg L
–1
(10 min) and 3 mg L
–1
(5 min). UV-visible spectra of PAN-PAA hydrogel shows absorbance at wavelength 560 nm with copper ions without interference of other metal ions viz. Cd(II), Co(II), Ni(II), Fe(II), Hg(II) and Pb(II). The hydrogels can be regenerated with 1 N HCl after reaction of Cu(II) ions. In conclusion, PAN-PAA hydrogel can be used as a potential colorimetric material for detection of Cu(II) ions in water. Colorimetric methods have their own advantages such as simplicity, high sensitivity and a short response time. In particular, these methods can be monitored by the naked eye and potential application in on-site detection owing to their simplicity and potability.
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