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Low height embankments are widely used as road embankments for highways and rural roads in India. Sometimes, the construction of such types of embankments on soft foundation soil becomes mandatory. In addition to the problematic soft foundation soil, seismic excitation might also play a significant role in the stability of such an embankment. The present study analyses the response of a low height embankment with soft foundation soil under earthquake loading. Numerical simulations have been performed using FLAC2D program. A stiffer half-space with higher shear wave velocity (Vs) has been considered below the soft foundation soil and the earthquake loading has been applied at the bottom of this stiffer half-space. Simulation has been performed considering two different thicknesses of soft foundation soil. In addition to that, three different levels of earthquake shaking and Vs of the stiffer half-space have been considered in the analysis. Results have been presented in the form of PGA amplification, excess pore water pressure, horizontal, vertical static/seismic displacement, etc.

Working with the secondary sources of empirical data (2009–10 to 2018–19), the present study tries to show the status of agricultural credit facility with special reference to horticultural sector in India. Tabular analysis with simple compound annual growth rate (CAGR) has been done in 2020. In case of crop loan (short-term credit), agriculture and horticulture have no difference and the system of delivery is also similar. Horticulture finance includes loans for development of fruit orchard, poly-house, green house development and marketing of such produce. Agricultural credit is vital in India for 86.2% small and marginal farmers for capital formation. Financial support in horticulture was lacking. Productivity credit inter alia as evinced in term of growth rates of area (CAGR=1.56%), production (CAGR=2.72%) and productivity (CAGR=1.28%) shows better performances compared to agriculture. But fund allotment in government (govt.) budget for horticulture remains almost constant (CAGR=0.86%). Study suggested for more investment (public and private) in horticulture since it contributes 29.2% of agricultural GDP and provides nutritional security. Popularization of microcredit, farmers’ awareness and improve technologies for delivery of institutional loan can be ensured. Diversion of crop loan must be checked. Study also highlights different govt. schemes for overall development of the horticulture sector.

Human coronaviruses like MERS CoV are known to utilize dipeptidyl peptidase 4 (DPP4), apart from angiotensin-converting enzyme 2(ACE2) as potential co-receptor for viral cell entry. DPP4, ubiquitous membrane-bound aminopeptidase is closely associated with elevation of disease severity in comorbidities. In SARS-CoV-2, there is inadequate evidence for combination of spike protein variants with DPP4, and underlying adversity in COVID19. To elucidate this mechanistic basis, we have investigated interaction of spike protein variants with DPP4 through molecular docking and simulation studies. The possible binding interactions between receptor binding domain (RBD) of different spike variants of SARS-CoV-2 and DPP4 have been compared with interactions observed in experimentally determined structure of complex of MERS-CoV with DPP4. Comparative binding affinity confers that Delta-CoV-2:DPP4 shows close proximity with MERS-CoV:DPP4, as depicted from accessible surface area, radius of gyration, number of hydrogen bonding and energy of interactions. Mutation in delta variant, L452R and T478K, directly participate in DPP4 interaction enhancing DPP4 binding. E484K in alpha and gamma variant of spike protein is also found to interact with DPP4. Hence, DPP4 interaction with spike protein gets more suitable due to mutation especially due to L452R, T478K and E484K. Furthermore, perturbation in the nearby residues Y495, Q474 and Y489 is evident due to L452R, T478K and E484K respectively. Virulent strains of spike protein are more susceptible to DPP4 interaction and are prone to be victimized in patients due to comorbidities. Our results will aid the rational optimization of DPP4 as a potential therapeutic target to manage COVID-19 disease severity.

Surface wave techniques are widely used to characterize a site based on shear wave velocity (Vs) or stiffness variation with depth. It utilizes the dispersion property of Rayleigh wave in a heterogeneous media. Dispersion curve is obtained from analyzing collected field test data and the final Vs profile is extracted from the inversion of the generated dispersion curve. The varying subsoil structures influence whether one or more Rayleigh modes will participate in the resulting wave propagation phenomenon. So, neglecting the higher mode participation may sometimes results in a completely different velocity profile than the actual existing one. In this paper, a detailed and comprehensive numerical study has been performed using finite element method for different types of soil profiles with different half-space impedances to assess how it affects the surface wave dispersion phenomenon. In addition to that, the effect of different data acquisition parameters on surface wave dispersion has also been studied.

With the advancement in technology, urban transportation systems have been modernized with the construction of underground structures due to restricted movements and inadequate space. Many cities already have or plan to construct underground box structures for metros and subways. These structures may undergo severe damages caused by excessive deformation due to seismic shaking. Hence, it is necessary to have an accurate estimation of deformation and bending moment caused by the movement of the surrounding soil under seismic conditions. In the present investigation, an attempt has been made to carry out a parametric study for a typical box structure 9.6 m wide × 5.8 m high with varying soil parameters from loose to medium, medium to dense and very dense in different seismic zones. The results of the study reveal that about 16–26% of the variation in distortion and 8–12% of the variation in bending moment occur with different subsoil conditions (loose to medium, medium to dense and very dense) under the same seismic conditions. Once seismic conditions change from lower to higher seismic zone (zone-III to zone-IV), the deformation becomes almost double even for the same soil condition (loose to medium or medium to dense or very dense). The findings of the present study may be useful in the design of underground subways and metro box structures for practicing engineers.

This study attempts to review, examine and analysis of present status of direct benefit transfer (DBT) of fertilizer subsidy in India from limited secondary sources of information. Fertilizer is one of the most important input for agriculture. Subsidy on fertilizer will directly deposited into the bank account of the buyers after purchasing from point of sale (PoS) auhenticated by Jandhan-Aadhar-Mobile (JAM). It has many social and economic impacts. Earlier, fertilizer subsidy involves leakages and diversions. DBT on fertilizers came into force in 2016 on pilot basis to some States. It was expected that DBT could reduce pilferage of Government's expenditure on social aspect and help saving (1st year saving by ` 30000 cr.). The NITI Aayog (2018) showed majority of retailers and farmers are satisfied with DBT. However, some key issues such as connectivity and dealer's margins have important roles. The conviction of the implementing authorities, stakeholder's awareness and Infra-structural facilities are very much necessary for effective application of the scheme. Little information have been reported about the progress of DBT for economic analysis since DBT of fertilizer subsidy has been implementing throughout the country only from 2018. Many authors expect its positive impact but others express little bit concern and suggested few measures before implementation. The scheme has the sense for social welfare and, thus, concrete economic analysis will be possible on DBT on fertilizer subsidy when

Low height embankments are widely used for construction of highways and rural roads in India. Sometimes, it becomes necessary to construct such types of embankment on soft foundation soil under unavoidable circumstances. In addition to the stability under static loading, seismic excitation very often plays a major role in the stability of such an embankment. So, to study the behaviour of such embankment under seismic loading becomes very important as the failures may lead to huge loss of property and life. The present study analyses the response of a low height embankment overlying soft foundation soil under seismic loading with the help of finite difference analysis using FLAC. The Mohr-Coulomb failure criterion is used to define the soil constitutive model for both embankment and foundation soil. A stiffer half-space has been considered below the soft foundation soil and the analysis has been performed varying the shear wave velocity of the stiffer half-space. Low to moderate level of shaking has been applied at the base of the stiffer half-space by scaling the original input motion of 1987 Loma Prieta earthquake.

The discovery of drugs and its pipelines formulation is tough, long, and depend on various factors. Machine Learning comes as a savior to this field and supplies different tools and techniques that are used to drastically improve the discovery as well as the decision-making capabilities for questions that have been well specified and already have an abundant amount of high quality data. There are several possibilities in each and every stage of drug discovery to apply Machine Learning tools and techniques. The applications of Machine Learning have proved from time to time that with some of its approaches generating accurate predictions and insights are very easy. Thus its application has not only been limited to the theoretical part of drug discovery, but has also proven that it can be used in practical conditions too. But there are certain challenges that we need to face that come with Machine Learning. Its inadequacy in terms of interpreting and repeating in its results may sometimes pose as a hindrance to their application in some areas. It also requires consistent and comprehensive high-quality data in almost all areas. There are continuous efforts being put to find a solution for such problems and also growing the reach of machine learning to new fields. Machine Learning can boost data-driven decision-making in this field and has the capability to accelerate the whole process and lessen the failure rates in drug discovery and development.

To explore the unmapped biotechnologically important microbial platforms for human welfare, the insect gut system is such a promising arena. Insects, the inhabitant of all ecological niches, harbor a healthy diversified microbial population in their versatile gut environment. This deep-rooted symbiotic relationship between insects and gut microbes is the result of several indispensable microbial performances that include: enzyme production, detoxification of plant defense compounds and insecticides, maintenance of life cycle, host fertility, bioremediation, pest biocontrol, production of antimicrobial compounds, and in addition provide vitamins, amino acids, and lactic acids to their hosts. Insects have developed such symbiotic interactions with different microorganisms for nutritional benefits like the digestion of dietary compounds by the production of several key hydrolytic enzymes viz: amylase, cellulase, lignocellulase, protease, lipase, xylanase, pectinase, chitinase, laccase, etc. The nutritional enrichment offered by these microbes to insects may be the key factor in the evolutionary attainment of this group. Around one million insect species are grouped under 31 orders, however, only ten of such groups' have been studied in relation to enzyme-producing gut microbes. Moreover, insect gut symbionts are a potential source of biotechnologically active biomolecules as these microbes go through a course of selection pressures in their host gut environment. As symbiosis has pronounced potential regarding the production of novel compounds, especially enzymes with multidimensional industrial capabilities, so there are ample scopes to explore this treasure box for human welfare. Biological significance as well as industrially compatible capabilities can categorize these insect gut symbionts as an unexplored biotechnological aspect.

Seismic bed-rock motions get amplified or de-amplified depending on the overlying soil deposit and very often found to cause disaster to the overlying structures. Kolkata city is situated on a deep alluvial deposit of Gangetic basin and consists of distinct soil formations, namely, normal Kolkata deposit, consisting of a thick soft silty clay/clayey silt deposit underlain by stiff clayey soil/silty sand down to considerable depth, and river channel deposit which consists of a deep deposit of medium/dense/very dense sandy soil present mainly along the Adi Ganga channel. So, in such a scenario when sediment thickness is quite high the study of local site effects should be of primary importance. Few studies have been carried out on local site effects of Kolkata soil using equivalent linear ground response analysis. Although for a weaker motion, equivalent linear (EL) criteria may closely predict the nonlinear response of soil, but when a soil is subjected to a strong motion, the EL assumption of soil behavior may not hold true. In this paper, nonlinear ground response analysis has been carried out using DEEPSOIL program to predict ground response of both normal Kolkata deposit and river channel deposit. Synthetic acceleration time history compatible with IS-Code rock level spectra for Zone-III has been used in the study. Variation of peak ground acceleration (PGA), spectral acceleration (SA), and pore water pressure (PWP) has been studied for both the type of deposits. A number of Vs-N correlations have been used to calculate shear wave velocity in the analysis to study their effects on the site response.

As the ground response analysis serves an integral part of site specific seismic hazard study to obtain design ground motion, a proper and accurate estimation should be of prime importance. The paper presents a study on the effect of trapped soft and stiff soil layer on equivalent linear ground response analysis implemented in computer program STRATA. For this purpose, the concept of normally stiff and inversely stiff soil profiles have been introduced. The study clearly indicates the higher impact of a trapped soft soil layer profile, i.e., inversely stiff soil profile with soft layer, in comparison with trapped stiff layer profile, i.e., inversely stiff profile with stiff layer. For low to moderate ground motions, as the depth of the trapped soft layer increases, peak amplification and peak frequency reduces, and for high intensity input ground motion, significant reduction only in the peak frequencies is observed. On the other hand, as the depth of trapped stiff soil layer increases the outcome of ground response analysis remain quite similar. Peak transfer function, peak frequency, peak spectral ratio and peak spectral acceleration are found to exhibit a COV ≤ 60 to 100% for all combinations of IS-Soft profiles, whereas, IS-Stiff profiles exhibit a maximum COV ≤ 15 to 25% for all the considered input ground motions. Computed normalized-root mean square error (Norm-RMSE) values also clearly indicate the higher deviations in the ground response analysis for different combinations of trapped soft soil profiles, from that of normally stiff profile, whereas, trapped stiff layer profiles show lower deviations in the Norm-RMSE values. The profiles with trapped soft layer exhibit a Norm-RMSE value ≤0.8, whereas, trapped stiff layer profiles exhibit a Norm-RMSE value ≤0.2, which clearly demonstrate the large deviations in the outcome of ground response analysis in case of trapped soft layer profiles.

The advantages and emergent interest in organism-derived bioactive molecules have recently renewed scientific research attention in this field. Since 1967, about 52 different derivatives of phthalate ester (PE) have been reported from different taxonomic groups. Anthropogenic derivatives of the PEs are confined to petroleum products, as a plasticizer. These derivatives exhibit a potential toxicity on the living system, particularly those having a reduced molecular weight. An organism-derived PE differs chemically from that of synthetic ones in terms of the abundance of

Purpose The study aims to search for potent cellulase producer from the gut of Gryllotalpa africana as well as to characterize and determine the effect of the purified enzyme on the cellulosic waste materials. Methods The potent cellulolytic strain was identified through morphological, biochemical, physiological, and molecular characterization like 16S rRNA and fatty acid methyl ester profile. After the optimization of cellulase production, the enzyme was purified through DEAE-Sepharose column chromatographic separation. The molecular weight of the purified enzyme was determined by SDS-PAGE analysis. The purified enzyme was characterized in terms of its activity and its effect on cotton fiber, and sawdust was also studied. Result The selected potent strain GAC 16.2 was identified as Acinetobacter junii that was capable to produce enhanced cellulase (112.38 ± 0.87 U/ml) at standardized optimum fermentation conditions. The molecular weight of the purified enzyme was determined as 55 kDa. The utmost activity of the purified enzyme was detected pH 7.0, temperature 50 °C, and in the presence of metal ions like Mg2+ and Mn2+. The substantive degradation of cotton fiber and sawdust has been observed in a reasonably short period. Conclusion Purified cellulase from the selected isolate A. junii GAC16.2, a gut isolate of G. africana, has the potentiality to degrade cellulosic substances. This property can make the isolate a potent candidature for industrial application, as well as an effective biotechnological tool for environmental monitoring through cellulosic waste management.

The effect of data measurement uncertainty and inversion uncertainty on VS,30 estimation is studied in this article. An attempt has also been made to separate out the inversion and data measurement uncertainties, and their effect on VS,30 is quantified separately. A relaxation to the misfit value is introduced to study the consequence of inversion uncertainty, whereas data variation up to one standard deviation is considered to study the effect of data uncertainty. All possible profiles are generated within this limiting misfit value (after relaxation) in case of inversion uncertainty and within measured data uncertainty bound in case of data uncertainty. Finally, few profiles are selected from entire range of generated profiles for VS,30 estimation. For the profiles falling short of 30 m depth, shear wave velocities are extrapolated using a simplified method proposed by Boore (2004) [4]. The VS,30 values show limited variation in terms of CoV (

Shear wave velocity (VS) is an important parameter from geotechnical earthquake engineering perspective. In the absence of the direct measurement of VS, VS–N correlation serves an alternative for evaluating the shear wave velocity (VS) from standard penetration resistance value (SPT-N) at a particular region. In the present study, an attempt has been made to propose generalized VS–N correlation from the globally available correlations for all soil and specific soil type using various regression procedures and genetic algorithm (GA). Various regression procedures along with GA have been used to assess the sensitivity of generalized VS–N correlations in connection with regression methodology. 1D ground response analysis has been carried out at two bore-hole locations in Kolkata city using the VS obtained from generated correlations and site specific response spectra have been generated at those two locations. Finally, performance of some typical buildings have been studied by nonlinear static analysis procedure using those site specific response spectra developed for proposed VS–N relationships for all type of soil and specific type of soil. The performance of the considered typical buildings has been represented in terms of base shear and roof displacement. Chi square ( $$ \chi^{2} $$ ) test has also been conducted to check the confidence level of base shear and roof displacement obtained by using various developed VS–N relationships varies with the results obtained using available site specific relationships proposed by Nath (2016), and it reveals that VS–N relationships developed by GA perform better than the VS–N relationships developed by other regression method.

Kolkata, capital of West Bengal, India, presently congested with moderate to high rise buildings, has undergone low to moderate damages due to past earthquakes. The city is situated on the world’s largest delta island with soft thick alluvial soil layer. In this study, an attempt has been made to study ground response due to a number of past earthquakes, 1897 Shillong earthquake, 1964 Calcutta earthquake and 2011 Sikkim earthquake, for the purpose of preliminary microzonation of the Kolkata city. For this, synthetic ground motions have been generated at bedrock level by stochastic method. By using 1D wave propagation technique, the synthetic ground motion has been computed at surface level for 144 borehole locations in the city. Contours of PGA, PGV and PGD parameters in the city have been drawn for these three earthquakes. Response spectra for these three earthquakes have also been computed and an optimum response spectrum has been determined. A good correlation has been obtained with predicted ground motion at surface level of the city with the reported intensity and damages occurred in buildings of Kolkata during past earthquakes. The scenario of simulated ground motion for the past three earthquakes depicts that Kolkata city is very much prone to damages even due to moderate far and near source earthquakes.