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The adsorption of glucose is theoretically examined using the Density Functional Theory method (DFT) over pure graphene and graphene surface doped with transition metal atoms (silver, gold, copper, nickel, and platinum). The graphene sheets are altered by substitutional doping of silver, gold, copper, nickel, and platinum atoms remarks in altering the electronic properties and actively reassuring glucose absorption. The outcomes revealed that metal atoms doped with graphene sheets improve the reactivity. Our study found that the interaction of glucose with pure graphene is weak when compared to metal-doped graphene flakes. Our studies concluded that due to strong adsorption energies, high bandgap variation, and excellent work function values of metal-doped graphene sheets make them beneficial for glucose sensing devices. The sensitivity and conductivity variations are high for the metal doped graphene sheets except nickel, however the recovery time value is high, suggesting that these sheets can be used as a disposable sensor.

Effective utilization of available weather and climate information is important to develop efficient and sustainable agricultural production systems. National meteorological agencies supported by global and regional centers are trying to generate climate forecasts tailored to sector-specific operational applications for a wide range of potential users. However, the big challenge is to develop a mechanism that will effectively communicate the information in a language that could be easily understood at different levels to obtain the maximum benefits from the information they receive.The International Research and Applications Project (IRAP) was a research experiment aimed at improving the livelihoods of rural farmers in Bihar, India, by producing and providing them with tailored weather and climate information. Forecast Application for Risk Management in Agriculture (FARM) schools were conducted to improve the awareness of farmers about the need for climate information and climate adaptation interventions which was applied for Kharif crops in summer monsoon 2018. A communication mechanism was established with the support of local partners to disseminate the tailored forecast and advisories to farmers. Assessment results revealed that the climate information is strongly valued by farmers if provided through a mechanism that they trust. More vulnerable farmers have limited access and ability to use the information, thus capacity building efforts like FARM schools are immensely helpful. Farmers recognize the critical role of climate variability in determining livelihood outcomes and actively seek out information to manage variability. This intervention helped trained farmers to better adjust their farming decisions through enhanced uptake of weather and climate information.

A voluminous liquid waste stream is generated as sodium nitrate (NaNO3) solution in Spent Nuclear Fuel Reprocessing Plants. Fluidized bed thermal denitration is a strong contender among various disposal options for this stream. In the present work experimental investigations on thermochemical denitration of NaNO3 have been carried out in an 80 NB laboratory scale fluidized bed reactor. Carbon based reductant was utilized to convert NaNO3 to sodium carbonate (Na2CO3) as well as to reduce denitration temperature. The operating parameters were optimized for maximum conversion of NaNO3 and 99.13% denitrification has been achieved. Pressure fluctuation across bed was also recorded and analysed in the state space domain employing attractor comparison technique. This technique computes a statistical metric ‘S’, as a measure of the fluidization state in the fluidized bed reactor and can be used for early detection of agglomeration in the bed. The sensitivity and early agglomeration detection capability of S-statistics are illustrated with experimental results for a liquid-sprayed gas fluidized bed.

A non-invasive ultrasonic technique (UT) is developed to determine gas-liquid-solid composition inside digester of a biogas plant. The technique involves sweeping a contact type UT probe along the wall of pipes to determine the relative fraction of gas, liquid and solid phases under segregated conditions. The technique is validated at laboratory scale for two-phase (air-water) and three-phase (air-water-solid) systems. The average absolute error in prediction of segregated interfaces is ∼2.5%. Field trials are done on horizontal pipe sections (5 coils) of digester in the plant. More than 50% of the top most pipe run is occupied by gas. For second/third pipe runs solid fraction is around 20–25% while gas fraction is 10–15%. However, for the 4th and 5th pipe rows, the solid fraction is around 40–55%. A gradual increase of gas hold up towards the top regions and larger accumulation of solids at the bottom is expected because of waste feeding at the bottom. The described UT based system represents a novel way forward in use of ultrasound technology to detect segregated multiphase phases in digesters of biogas plants.

Understanding the phenomena of formation of single drops is necessary to understand the hydrodynamics in solvent extraction equipment which are used for separation of nuclear materials. In this work, the phenomena of aqueous phase and organic phase drop formation at submerged nozzles are compared by conducting experiments with 30%TBP (v/v) in dodecane as the organic phase and nitric acid as the aqueous phase. Two different nozzles and three different nitric acid concentrations are used. For each nozzle and nitric acid concentration, velocity of the dispersed phase is varied. Drops of aqueous phase formed at downward oriented nozzles submerged in organic phase are observed to be smaller than the drops of organic phase formed at upward oriented nozzles submerged in aqueous phase. Correlations to estimate drop diameter are proposed. Keywords: Dodecane, Drop formation, Nozzle, Nuclear fuel cycle, Solvent extraction, TBP

Herein, we report the use of Multi Wall Carbon Nano Tubes (MWCNTs) as nano-compatibilizers based on their astonishing mechanical properties and ease of processing. To fabricate laminate samples, pure MWCNTs were homogeneously dispersed in the fiber-reinforced plastic (FRP) composite with 0, 0.5, 1 and 1.5 wt. % loading. The laminates were prepared with eight plies (4.0 ± 0.1 mm thickness) using the hand layup technique assisted by the compression moulding method. It was found that the tensile, compressive and inter-laminar shear strength (ILSS) increase by 103.81%, 139.78% and 36.06%, respectively corresponding to 1 wt. % loading of MWCNTs as compared to neat GFRP specimen. However, a rapid decrease in strength beyond 1 wt. % loading of MWCNTs has been noted. Interestingly, the maximum of the tensile strength was higher than that of the compressive strength, and the maximum of the tensile modulus was larger than that of the compressive modulus in the case of 1 wt. % loading of MWCNTs. It was observed that after a certain loading, the mechanical properties of such laminates can only reach the best value with an optimum loading of MWCNTs. In addition, the micromechanical failure modes and effect of MWCNTs loading on internal morphologies of the composites were also intensively explored with the help of Field Emission Scanning Electron Microscopic (FESEM) analysis. Keywords: Mechanical properties, MWCNTs, Fiber-reinforced plastic, Tensile strength, Compressive strength, ILSS properties, Failure modes

DSSAT-CANEGRO model have been used to determine crop potential yield over eight districts (viz; Muzaffarnagar, Shahjahanpur, Agra, Lucknow, Basti, Faizabad, Allahabad and Jhansi) representing different agroclimatic conditions & environmentof Uttar Pradesh state in India. The thirty six years (1980-2016) daily weather data of above districts were used to simulate seasonal yield potentials under the various management conditions and compared with the respective district reported yield. The simulated mean potential yield by the CANEGRO model over different district of the state varied between 77.8 t ha-1 in Muzaffarnagar and 97.8 t ha-1 in Agra, while mean reported yield (fresh stalk mass) varied between 40.1 t ha-1 in Jhansi and 62.8 t ha-1 in Muzaffarnagar within the state. Similarly, the attainable yield by the model was simulated lowest of 65.1 t ha-1 in Shahjahanpur and the highest of 73.6 t ha-1 in Faizabad district. The management yield gap was between 9.0 to 30.0 t ha-1 while sowing yield gap was between 7.0 to 26.0 t ha-1 in different districts under study. Further it is not only interesting & surprising but also encouraging to growers that the trends in total yield gap at all the above districts in various agro-climatic zones were found decreasing (narrowed down) at the rate of 138.8 – 801.2 kg ha–1 year–1. Delayed planting by about 30 days in some of the districts resulted into a decrease in sugarcane yield to the tune of 106.7 to 146.7, 103.3 to 143.3 and 80.0 to 133.0 kg ha–1 day–1, respectively. Findings reveal that DSSAT crop simulation model can be an effective tool to aid in decision support system. Yield gap estimates using the past crop data and subsequent adjustment in planting window may help to achieve close to the potential yields.

The CROPGRO-pigeonpea model embedded in DSSAT v4.7.5 was used to assess the impact of climate change on phenology and grain yield of reference genotype of different pigeonpea maturity groups. The impact of climate change delayed reproductive stages (anthesis, maturity) and decreased grain yield of reference genotype of different pigeonpea maturity groups were evident in all scenarios. Short duration genotypes (MN5, ICPL88039, Prabhat, UPAS120) showed progressively higher decrease in yield as compared to medium (Maruti, Asha, ICP7035) and long (Bahar, MAL13) duration genotypes with each successive increase in scenatio from RCP2.6 to RCP8.5 and projected year from 2010 to 2095. Anthesis was delayed 9 days in MN5 to 20 days in Bahar and maturity delayed 15 days in MN5 to 24 days in Bahar with RCP 8.5 in year 2095 in comparison to RCP2.6 in years 2010, whereas, grain yield was decreased 14% in Bahar to 66% in MN5 among genotypes of different maturity groups.

In recent years, in many parts of the country, indebtedness, crop failures, unpaid prices and poor returns have resulted in agrarian distress. The government has identified and introduced several programs to address these critical issues viz. crop insurance, lending waivers etc. among them. Crop insurance as a concept for risk management in agriculture has emerged in India since the turn of the twentieth century and government has launched various insurance schemes in last three decades like Comprehensive Crop Insurance Scheme (CCIS), National Agricultural Insurance Scheme (NAIS) and Modified NAIS (MNAIS) etc. Apart from these schemes, several other pilot projects such as Seed Crop Insurance, Farm Income Insurance Scheme and Weather Based Crop Insurance Scheme (WBCIS) were implemented from time to time. At present, two most important schemes are functional i.e. Pradhan Mantri Fasal BimaYojna (PMFBY) and Restructured Weather Based Crop Insurance Scheme (RWBCIS) are in operation. This study focused on the performance of the Restructured Weather based Crop Insurance Scheme (RWBCIS) from historical and analytical perspectives and presents recommendation for future scenarios. RWBCIS scheme having two most important challenges. Firstly, weather data related issues by designing a modern scientific approach to develop high resolution secondary data and secondly, modifying the existing design of RWBCIS Products, based on sound agronomic principles.

Multiple regression approach has been used to forecast the crop production widely. This study has been undertaken to evaluate the performance of stepwise and Lasso (Least absolute shrinkage and selection operator) regression technique in variable selection and development of wheat forecast model for crop yield using weather data and wheat yield for the period of 1984-2015, collected from IARI, New Delhi. Statistical parameters viz. R2, RMSE, and MAPE were 0.81, 195.90 and 4.54 per cent respectively with stepwise regression and 0.95, 99.27, 2.7 percentage, respectively with Lasso regression. Forecast models were validated during 2013-14 and 2014-15. Prediction errors were -8.5 and 10.14 per cent with stepwise and 1.89 and 1.64 percent with the Lasso. This shows that performance of Lasso regression is better than stepwise regression to some extent.

Experimentally created forty eight wounds of similar size and shape were randomly divided in to three groups, of 16 wounds in each group. Sunflower seed oil impregnated gauze were subjected to the wounds of goats belonging to group I, while Olive oil (Olea europaea) impregnated gauze were subjected to the wounds of goats of group II and normal saline solution (control) soaked gauze to the wounds of goats of group III. Healing tissues were collected from the junction of wound and intact skin from all the experimental wounds in each of the three groups on 3, 10, 15 and 25 days. Biochemical examinations of healing tissue were done for collagen, elastin, hexosamine and hydroxyproline. The level of collagen, elastin, hexosamine and hydroxyproline were significantly higher in group I followed by group II and then group III. It can be concluded that both sunflower oil and olive oil are effective for acceleration of wound healing and sunflower oil is more effective than olive oil.

Large cardamom (Amomum subulatum Roxb.), a perennial cash crop, cultivated under an agroforestry system in the eastern Himalaya of India, is well recognized as a pollination-dependent crop. Observations on pollinator abundance in Mamlay watershed of Sikkim Himalaya were collected during the blooming season to evaluate the pollinator abundance across sites and time frames, and impact of pollinator abundance on crop yield from 2010 to 2012. The results revealed that the bumblebees and honeybees are most frequent visitors of large cardamom flowers. The abundance of honeybees, however, varied between sites for the years 2010–2012, while that of bumblebees varied for the years 2011 and 2012. The abundance of honeybees resulted in a variation within time frames for 2010 and 2011, while that of bumblebees varied for 2010 and 2012 (p

GFLD-CM3 model was used to generate weather data under RCPs scenario i.e. RCP 2.6, 4.5, 6.0 and 8.5 for years 2010, 2035, 2065 and 2095 for Varanasi, Uttar Pradesh. The generated data were used to assess the impact of climate change on phenology and yield of wheat crop using CERES-Wheat model. The results revealed that the impact climate change hastened reproductive stages (anthesis, maturity) and decreased yield in all scenarios. The impact was highest under RCP 8.5. Days to antheis and days to maturity were projected to reduce by 22 days and 24 days, respectively in 2095 whereas, grain yield decreased by 61.0 per cent.

Human immunodeficiency virus-1 (HIV-1) enters the brain early during infection and leads to severe neuronal damage and central nervous system impairment. HIV-1 envelope glycoprotein 120 (gp120), a neurotoxin, undergoes intracellular trafficking and transport across neurons; however mechanisms of gp120 trafficking in neurons are unclear. Our results show that mannose binding lectin (MBL) that binds to the N-linked mannose residues on gp120, participates in intravesicular packaging of gp120 in neuronal subcellular organelles and also in subcellular trafficking of these vesicles in neuronal cells. Perinuclear MBL:gp120 vesicular complexes were observed and MBL facilitated the subcellular trafficking of gp120 via the endoplasmic reticulum (ER) and Golgi vesicles. The functional carbohydrate recognition domain of MBL was required for perinuclear organization, distribution and subcellular trafficking of MBL:gp120 vesicular complexes. Nocodazole, an agent that depolymerizes the microtubule network, abolished the trafficking of MBL:gp120 vesicles, suggesting that these vesicular complexes were transported along the microtubule network. Live cell imaging confirmed the association of the MBL:gp120 complexes with dynamic subcellular vesicles that underwent trafficking in neuronal soma and along the neurites. Thus, our findings suggest that intracellular MBL mediates subcellular trafficking and transport of viral glycoproteins in a microtubule-dependent mechanism in the neurons.

This paper focuses on the current machining process initiatives, carried out by various researchers relevant to the environmental aspects, thereafter predicting EDM performances. electrical discharge machining (EDM) is widely used unconventional machining method, because of its ability to process very hard material with precision. In thermo-electric process, control spark generation between electrodes causes material removal; however, application of hydrocarbon oil based dielectric fluid is an issue of environmental disruption. Replacement of dielectric to rectify the problem is one of the main concerns in EDM research. This paper highlights dry-EDM, near-dry EDM and EDM in water, conceived as an environment friendly alteration in the oil EDM process referred as a green EDM process. The work provides a thorough review of dry, near-dry EDM and EDM in water as a process, where the target is to endeavor dielectric fluids which could be the alternative to replace hydrocarbon oil. It is perceived that water and gas based dielectrics could take over oil-based fluids in EDM applications. Novel technological advances in dry EDM machining processes, which deliberate the advanced stage of a technology in academic and industrial research is briefly reviewed and an outline for the future work has been paved.

The DSSAT CANEGRO model was calibrated and validated using field experimental data (1997-2013) from four locations of north Indian region.The genetic coefficients for 10 cultivars of sugarcane were estimated.R2 obtained between measured and simulated stalk yield was 0.69 with the nRMSE (7.50%) and D-index (0.91) and R2 between measured and simulated sucrose mass was 0.57 with the nRMSE (11.75%) and D-index (0.85). The model underestimated both the stalk fresh mass as well as sucrose mass by 2 and 6 per cent only, respectively. Hence,the CANEGRO model can be used to simulate the phenology and yield attributes of sugarcane cultivars of north India particularly of Uttar Pradesh region. The model can also be used to evaluate and improve the present practices of sugarcane crop management to obtain increased cane production and sugar recovery.

Decision Support System for Agrotechnology Transfer (DSSAT v4.6.1) was used to study the impact of climate change and variability on productivity of different monsoon (pigeonpea and groundnut) and winter season crops (chickpea, mustard, tomato and potato) at Varanasi. Keeping in view the observed trends in climate variability, productivity of different cash crops were simulated under plausible synthetic climatic scenarios of changes in temperature and carbon dioxide. Productivity of pigeonpea and groundnut in monsoon season and mustard, tomato and potato in winter season decreased with an increase in temperature. Productivity of different pulse, oilseed and vegetable crops increased under expected enhanced CO2 concentrations. Highest productivity decreased in pigeonpea crop (96.0%) in monsoon season and minimum in tomato crop (4.0%) in winter season with an increase of 3.0 °C in temperature above normal. Highest productivity increase in mustard crop (164.0%) in winter season and lowest in pigeonpea crop (33.0%) in monsoon season were simulated under projected enhanced CO2 concentration of 760 ppm. Highest counter-balance in productivity of mustard crop (150%) followed by tomato crop (81%) during winter season and lowest in pigeonpea crop (99%) during monsoon season were simulated when an increase in temperature by 3.0 °C above normal under projected enhanced CO2 concentration of 760 ppm.

Eighteen years (1991-2008) of weather data and yield data of rice and wheat for 9 districts of Eastern Uttar Pradesh was used to develop yield prediction equations. Models were validated with 2 years (2009 and 2010) data. Results indicated that models explained 51 to 79 percent variations for rice yield and 65 to 92 percent variations for wheat yield in different districts. The percent Mean Bias Error (MBE) was between -1.05 (Mau) to 6.17 (Mirzapur) for rice and from -6.56 (Mau) to 0.01 (Varanasi) for wheat crop. The percent Root Mean Square Error (RMSE) was between 6.87 (Jaunpur) to 11.60 (Sant Ravidas Nagar) for rice and from 5.52 (Mirzapur) to 11.11 (Mau) for wheat crop. This revealed that the models can be used to some extent for predicting the yield in different districts of Eastern Uttar Pradesh.

Crop yield forecasts are prepared at District, State and National level under the ongoing project “Forecasting Agricultural output using Space, Agrometeorology and Land based observations (FASAL)”, operational at Ministry of Agriculture, Govt. of India in collaboration with Space Application Centre (SAC), Institute of Economic Growth (IEG) and India Meteorological Department (IMD). As per the mandate of the project, crop yield forecasts are being generated for 13 major crops. Different models are used by these organizations for generation of crop yield forecasts. Under FASAL project, IMD in collaboration with 46 Agromet Field units (AMFU) located at different State Agricultural Universities (SAUs), ICAR institutes, IITs, develops intra-seasonal operational yield forecast for the major crops during kharif and rabi seasons using statistical model. Within IMD, in addition to the Agricultural Meteorology Division, all the Regional Meteorological Centres (RMCs) and Meteorological Centres (MCs), located in different states are also working in this project. Long period crop yield data as well as weekly weather data as per meteorological standard week have been used for development of the district level yield forecast models. For developing the yield forecast, models using composite weather variables have been studied. Simple and weighted weather indices have been prepared for individual weather variables as well as for interaction of two at a time considering throughout the crop growing season. Minimum data set required to develop the statistical model have also been mentioned in this paper. In order to demonstrate the data requirement, methodology for crop yield forecast through regression technique along with the interpretations, the relevant data of West Bengal have been taken up. National level crop yield forecast is prepared by the Mahalanabis National Crop Forecasting Centre (MNCFC) based on the state level forecast generated in IMD.

Fluorescence polarization has been used recently to monitor diverse macromolecular interactions. In this report, the application of fluorescence polarization has been extended to monitor ribozyme reactions in real time. With fluorescently labeled substrate RNAs, group I ribozyme ligation and hammerhead ribozyme cleavage reactions were studied by fluorescence polarization in substrate excess (multiple turnover) conditions. These results also show that fluorescently labeled RNAs remain active substrates for ribozymes. Furthermore, a direct comparison of fluorescence polarization with fluorescence resonance energy transfer showed that both techniques were comparable for monitoring ribozyme reactions.

Climate change is one of the major challenges in 21st century faced by Agriculture in India, more so in the Semi-Arid Tropics (SAT) of the country. In recent years, natural and anthropogenic factors have impacted climate variability and contributed to a large extent to climate change. Based on one degree gridded data of India Meteorological Department (IMD) for 34 years (1971-2004), climatic water balances are computed for 351 pixels in India and used for classifying in to six climate types following Thornthwaite’s moisture regime classification and areas falling under different climatic zones in India are delineated. Considerable changes in the country’s climate area observed between the two periods; 1971-90 and 1991-2004. Increased semi-arid area by 8.45 M ha in five states viz., Madhya Pradesh, Bihar, Uttar Pradesh, Karnataka and Punjab, and decreased semi-arid area by 5 M ha in eleven states, contributed to overall increase in SAT area of 3.45 M ha in the country.Overall, there has been a net reduction of 10.71 M ha in the dry sub-humid area in the country. Results indicated that dryness and wetness are increasing in different parts of the country in the place of moderate climates existing earlier in these regions. ICRISAT’s Hypothesis of Hope through Integrated Genetic and Natural Resources Management (IGNRM) using climate ready crops and Integrated Watershed Management could be a potential adaptation strategy by bridging the yield gaps for developing climate resilient agriculture in the country.

The sugarcane crop growth simulation model was calibrated and validated in Eastern Uttar Pradesh (UP) region of Indo-Gangetic Plains of India using 12 years field experiment data conducted in several places. The results reveal that the CANEGRO Sugarcane model satisfactorily simulated the potential growth and yield of sugarcane crop. The model simulates the stalk height, stalk fresh mass and sucrose yield within ±15 % of range in comparison to the observed values. Therefore the validated CANEGRO Sugarcane model can be further used for applications such as prediction of crop growth, phenology, water management, potential and actual yields, performance of sugarcane under climate variability and change scenarios etc. The model may also be used to improve and evaluate the current practices of sugarcane growth management to achieve enhanced cane production and sugar recovery.

The daily rainfall and temperature data 1969-2000 of Jhansi were analyzed to know seasonal and annual variability. Three distinct crop growth seasons kharif (26-41 SMW), rabi (42-15 SMW) and summer (16-25 SMW) were characterized for seasonal trends. The stable rainfall period was worked out. The annual and kharif rainfall showed a decrease in rainfall in recent decade (1984-1993). Trend analysis on rainfall reflects a decrease of 0.89 and 1.12 mm per year in annual and kharif season during past 35 years whereas no such specific trend was observed for rabi and summer seasons. The temperature variability was small indicating only minor year-to-year variations. However, during recent decade, the minimum temperature showed an increase of 0.05 and 0.13 ° C per year during annual and kharif season.

Rainfall data for the period 1960-2005 is used to analyze the probability of occurrence of deficit /normal / excess rainfall. The mean annual rainfall is 1200 mm with 28 percent variability; with standard deviation of 336 mm. July is the wettest month (average rains- 326.5 mm). Rainfall of August and September months shows lower coefficient variation- 57 percent. Each standard week from 25th to 40th receives a rainfall of more than 40 mm, indicating the crop suitable period from June third week to October 1st week.

Rainfall during monsoon season and its variability govern the cropping system in the Sabour region. Long-term rainfall data is used to analyse the probability of occurrence of deficit /normal /excess rainfall for better crop planning in the region. During the 30 years (1972-01) there were about 13 per-cent drought, 10 per-cent flood and 77 percent normal years. Among drought years southwest monsoon rainfall was the lowest (646 mm) in 1977. Seed sowing in paddy nursery in the Sabour region generally takes place immediately after onset of monsoon rains during 23-25 standard meteorological weeks and transplanting is carried out around 27th or 28th standard week. The tillering, 50 per-cent flowering and dough stage are observed during 32-33rd, 37-38th and 40-41st standard weeks respectively.