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Education acts as an important catalyst for socioeconomic and democratic evolution in society and is a critical tool for building an equitable system. In our paper, we have historicized one of the most important educational policies, viz. Samagra Shiksha Abhiyan (SAMSA) in India that carries large expectations to minimize the educational divide. We have studied the policy through the lens of Political Economy and have further critiqued it through the framework of Critical Discourse Analysis. We find in our paper that the budget allocated to SAMSA was revised in 2022, from its preceding years with a 28 per cent slash. We critically reflect on the principles mentioned in the policy and find that although there has been an attempt to mitigate the hazards of banking education the 'Public-Private Partnership' initiative reinforces struggles for equitable education, and further, the privatization sets the government free from any accountability. Moreover, a constitutional right like the Right to Education (RTE) is not sufficient enough to meet the goals of universalisation of education. Besides, we analyse the principles such as 'Education for All', 'Equity', 'Equal Opportunity', 'Access', 'Gender Concern', 'Centrality of teacher', 'Moral Compulsion', and 'Convergent and integrated system of education management', and argue that although some of the facets of societal structural inequalities are addressed, however, there exists hardly a proper roadmap that could be monitoring the process of creating an inclusive educational paradigm.

Lightning is one of the most severe weather events causing significant loss of human lives and resources. Increasing number of lightning fatalities due to recent climatic changes is emerging out to be a serious concern for India during last few years. Proper characterization and parameterization of the same, therefore, is extremely crucial. However, lightning is an extremely dynamic phenomenon having enormous spatio‐temporal inhomogeneity especially over such a vast country like India with varied topographic and climatological features. Therefore, proper parameterization of lightning activity over India needs consideration of different lightning climatologies. This study has attempted to resolve the issue by regionalizing Indian subcontinent in different lightning climatologies based on lightning density and associated atmospheric variables that is, CAPE, specific humidity at different pressure levels, temperature, k index and cloud particle size and identified seven distinct lightning climatologies over India. A regression model is proposed for estimating the annual and seasonal (monsoon and pre‐monsoon) lightning activities over the seven resulting lightning zones based on the said atmospheric variables using machine learning techniques. Four machine learning models have been tested among which Random forest has shown the best accuracy. The regression model has shown an R‐squared score of 0.81 during monsoon season and 0.71 during the pre‐monsoon. The atmospheric features based on their influences on the lightning activity in these seven climatologies has been ranked which presented the evidences of largely varied interplay between different atmospheric variables and lightning over different parts of the country and during different seasons. [ABSTRACT FROM AUTHOR]

The effect of climate change on precipitation pattern is emerging out as a serious global challenge. However, the quantification and assessment of the climate change effect on precipitation are a challenging issue given the spatio-temporal inhomogeneity of rainfall. Previous studies mostly used only rain intensity information for the identification of climate change signature by selecting homogeneous rain regions. Rain climatology, however, has several other important characteristics like occurrence of multiple rain type, occurrence of extreme rain events and their spatial distribution. The present study provides a novel approach to combine satellite data with ground measurements for addressing this issue. In this study, the Indian subcontinent has been divided into homogeneous regions based on six different rain features, obtained from ground observations and TRMM satellite measurements of 12 years, using K-medoid clustering technique. The rain features showed distinguishable patterns in the resulting nine homogeneous rain zones and distinct behavioural patterns in the inter-relationships between the various rain features. To verify the consistency of the proposed regionalization, the recent changes in mean monsoon rain rates are then studied using 40 years of rain gauge measurements for these regions. Increasing trends in monsoon rain are observed in two homogeneous regions whereas five of them have shown decreasing signature of rain intensity. Although the present study focused only on monsoon rain over India, the results indicate the suitability of the proposed method as an efficient technique of identifying homogeneous region for other seasons and locations as well. [ABSTRACT FROM AUTHOR]

Collisional drop breakup is one of the important processes during evolution of the rain drops and leads to modified shape of the drop size distribution (DSD), which is a primary parameter in rain retrieval in remote sensing techniques. Though several experimental and observational studies have been performed in the recent past on this aspect, the impact of the same in natural rain, particularly in orographic rain, is still poorly represented. The present study aims to examine and identify the rain conditions in which collisional drop breakup is prominent and is capable of modifying the shape of DSD in orographic rain over north-eastern India. The 2-min averaged DSDs from four hilly locations are studied in both stratiform and convective rain types separately using ground-based DSD measurements. Even though drop breakup in intense to moderate rain seemed to be in notable percentage (0.2% - 11.2%), the low intensity rain also showed a considerable break-up signature (2.5% - 9%), depending upon the locations. The overall results showed that collisional breakup was more prominent in convective rain (1%–11%) than in stratiform rain (4%–5%), however, breakup is also seen primarily during stratiform rain in two of the locations. The Z -R coefficients are found to be significantly different for the break-up and non-break up cases. For breakup cases, both convective and stratiform rainfall shows an increase in intercept parameter for all locations. For stratiform rain types, the coefficient a and b ranged from 307.6 to 321.4 (167.1–178.7) and 1.27–1.37 (1.31–1.34) for rain with break-up (without break-up), respectively. In the case of convective rain, the coefficients were found to be in the range of 377.5–654.7 (270.4–641.3) and 1.28–1.42 (1.14–1.31) with break-up (without break-up), respectively. The results suggest that collisional breakup is an important process in orographic rain over North-Eastern India and it has to be taken care of, while studying rainfall over these regions, particularly in conventional radar derived quantitative precipitation estimates (QPE). [Display omitted] • Collisional drop breakup in orographic rain has been explored in four tropical Indian locations. • Breakup occurs mainly in convective rain at two locations, while the other two show notable breakup in stratiform rain. • Occurrence of equilibrium DSD registered highest in low rain intensity for all locations. • The Z -R coefficient "A" was consistently higher across all locations and rain types in situations involving collisional drop breakup in comparison to scenarios with no breakup. [ABSTRACT FROM AUTHOR]

• A detail study of rain fade at Ka band over tropical region has been done. • Performance comparison of experimental link at 20/30 GHz with ITU-R model done. • "s" parameter relating fade slope to filter characteristics is calculated. Dynamic characteristics of Ka band rain fade (or rain attenuation) over tropical region are relatively less studied, though they are essential for implementation of suitable fade mitigation techniques. In this paper, dynamic characteristics of rain fade at 20 GHz and 30 GHz from GSAT-14 satellite are reported with experimental measurements at Ahmedabad, India. ITU-R model for fade slope probability distribution has been analyzed in this paper and Ka band rain fade has been investigated based on this fade-slope analysis. The ITU-R model is found to closely match 20 GHz measurements, though differences increase at 30 GHz. Fade slopes are found to be within ±0.5 dB/s at both 20 and 30 GHz. Both positive and negative slopes of the fade slope distributions are quasi-similar. ITU-R model's s parameter, relating fade slope to filter characteristics, is found to be very close to the measured value for this region. Distributions of fade slopes are also found to be dependent on the standard deviation values similar to ITU-R recommendation at 20 GHz, but significant deviation is observed at 30 GHz. This observed frequency dependency might be due to increase in cloud attenuation at high frequencies or may be due to limited data set. Results indicate needs of further experimental data at high frequencies from other tropical regions to gain further insight into the fade slope characteristics. This will ultimately help in designing a better prediction model in future. [ABSTRACT FROM AUTHOR]

India though being the birthplace of the ancient science of sex, it is really a matter of shame that the post British India, considers it a taboo, to talk and discuss it in the public. Like many other ancient scriptures and technologies that were all initiated by India, but are now used and further developed by the western world, India, in this case too only boasts itself of having just invented this, but, with little implications in their modern life. Like the Vedas, Upansihadas, Ayurveda, Yoga, Mathematics, Kamasutra or the science of sex, had also developed in this part of the world first, but, is considered obscene in present day India. What is even more insane is that there are numerous, monuments, buildings of the ancient and medieval history still present in this country, which openly depicts sex in the form of sculptures and paintings, and are popular tourist destinations, but watching the same over electronic media has been labelled illicit. [ABSTRACT FROM AUTHOR]

Abstract: The effect of the earth's atmosphere on radio waves propagating over an earth-space path is a major concern in the design and performance of satellite communications systems. Some characteristics of cloud and its effect on signal propagation has been studied using multi-wavelength radiometer at a tropical location of Kolkata, India. The liquid water content profile shows high values at higher altitude during pre-monsoon season indicating the presence of cloud above zero degree isotherm. Significant change in attenuation value is observed for same liquid water content due to change in temperature and accordingly a suitable relationship is obtained for the present location. The measurements indicate that ~4dB and ~12dB attenuation is caused due to cloud at 0.01% outage probability at the Ka and V band, respectively. ITU-R model is found to be overestimating the cloud attenuation over this location and indicate the need for more experimental measurement from tropical region. [Copyright &y& Elsevier]

Abstract: Melting layer height, which is normally assumed to be the limits of rain region, is an important parameter to consider the performance of earth space communication link above 10GHz. In this paper, the variation of melting layer observed by a vertically looking Micro Rain Radar (MRR) for 3years has been presented for two different climatic locations in Indian tropical region — Shillong (25°34′ N, 91°53′ E, 1050m) and Trivandrum (8°29′ N, 76°57′ E, 4m). The analyses show that the variation is quite significant for different months in Shillong but not for Trivandrum. The height of melting layer shows a strong correlation with ground temperature of these locations. The results agree well with the long term Tropical Rainfall Measuring Mission (TRMM) measurements of melting layer indicating suitability of using TRMM data for such study. A comparison of MRR with the nearest Radiosonde measurement indicates that MRR can have potential application in the study of zero degree isotherm height in rainy conditions. Results also clearly indicate that the assumption of constant rain height is not a valid one for all tropical locations. [Copyright &y& Elsevier]

Abstract: The microstructure of rain has been studied with observations using a vertical looking Micro Rain Radar (MRR) at Ahmedabad (23.06°N, 72.62°E), a tropical location in the Indian region. The rain height, derived from the bright band signature of melting layer of radar reflectivity profile, is found to be variable between the heights 4600m and 5200m. The change in the nature of rain, classified on the basis of radar reflectivity, is also observed through the MRR. It has been found that there are three types of rain, namely, convective, mixed and stratiform rain, prevailing with different vertical rain microstructures, such as, Drop Size Distribution (DSD), mean drop size, rain rate, liquid water content and average fall speed of the drops at different heights. It is observed that the vertical DSD profile is more inhomogeneous for mixed and stratiform type rain than for convective type rain. It is also found that the large number of drops of size <0.5mm is present in convective rain whereas in stratiform rain, drops concentration is appreciable up to 1mm. A comparison of measurements taken by ground based Disdrometer and that from the 200m level obtained from MRR shows good agreement for rain rate and DSD at smaller rain rate values. The results may be useful for understanding rain structures over this region. [Copyright &y& Elsevier]

In the U.S. Wide Area Augmentation System, European Geostationary Navigation Overlay Service, and Indian Global Positioning System Aided Geo Augmented Navigation, a near real-time grid-based single-shell model is proposed to correct the ionospheric delay at the user aircrafts. The single-shell model is based on the assumption that the whole ionosphere is compressed at a fixed altitude at 350 km. This assumption may not be appropriate for the Indian region, which falls in the Equatorial Ionospheric Anomaly belt. In this paper, a two-shell model which incorporates two different shells, at 300- and 500-km altitudes, having different weights at different time domains has been implemented. A statistical comparison between single- and two-shell models has been done for all quiet days of year 2005. Based on the results, it is observed that there is at least 60% improvement in the performance of the two-shell model in comparison to the single-shell model for the Indian region. [ABSTRACT FROM AUTHOR]

Increasing lightning fatalities over India is a concerning subject. Especially, it is pretty crucial over North-Eastern part of the country where lightning is extremely frequent. Given the complex nature of the problem, machine learning can be an excellent option in such forecasting scenarios. However, such dynamic processes seek proper transparency of the model. The current work attempts to devise a model for short range prediction (one month ahead) of lightning density based on primary atmospheric parameters from satellite data with a lead time of one month over North –Eastern and Eastern part of the country. Random Forest regression seems to outperform other models explored, with a R2 of 0.86 and an MAE of 0.0071. The interpretation of the model output using SHAP index reveals that 2 m temperature at previous two months and CAPE and K-index at previous month has a positive impact on the output of the model whereas, instantaneous surface heat flux of previous month and two month prior K-index has an inhibiting effect on model's output. The use of machine learning techniques for atmospheric predictions without the shed of the black box can be of importance to the scientific community. Such studies especially over lightning prone tropical regions can be crucial in meteorological forecasting applications. • The study focuses on predicting lightning densities over North Eastern part of India. • It uses machine learning regression for the forecasting. • The study attempts to predicts monthly lightning activities with one month lead time. • The results were interpreted with the help of SHAP index. [ABSTRACT FROM AUTHOR]