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A non-pneumatic tire (NPT) has a unique design that offers certain advantages over the common pneumatic tire. This tire is resistant to punctures and immune to blowouts. The present work aims to improve the aerodynamic design of the NPT by keeping the structure of the spokes hexagonal but varying other design features like tread pattern and adding material and filets. CAD designs were developed using Fusion 360 software and computational fluid dynamics (CFD) analysis is carried out using SimScale software. The variation of camber and yaw angles has been conducted with both tread and material enhancement. There was a decrease in drag and lift when the material was added to all the tires, but for all variations of yaw and camber, an increase in drag and lift was seen. The analysis is further extended to see the effect of a wheel well on the aerodynamic performance of the NPT. A decrease in drag and lift of nearly 33.2% and 94.5%, respectively, were observed with a wheel well.

This paper gives an overview of the research that has been done on wind power forecasting models, which may be used to aid in the optimum integration of Renewable Energy (RE) into electric power networks. Aside from the economic advantages, the variable nature of wind energy production has a variety of negative consequences for the electric grid system, including stability, reliability, and the capacity to plan for future operations, among other things. As a result, precise forecasting of wind power output is critical for grid stability and security, as well as for the promotion of large-scale wind power. To ensure the accuracy of wind energy forecasts, a variety of conventional, artificial intelligence, and hybrid methodologies have been developed. The simplicity and robustness of time-series-based methods have made them popular for forecasting applications. Artificial Neural Networks (ANNs) and Fuzzy Logic have recently been supported by several researchers for forecasting because of their flexibility. This review covers the performance of many wind power forecasting models that are classified according to their categories. It is also offered a critical examination of contemporary studies, which includes statistical model and machine learning models that are based on historical data. Aspects of this study that are taken into consideration include the advantages and disadvantages of various forecasting models, including hybrid models, as well as performance matrices used in assessing the forecasting model. In addition, the possible advantages of model optimization are examined in detail as well.

Maize (Zea mays) is the third major cereal crop in the Indian subcontinent, but the crop yields per hectare of Indian maize cultivars are less than half of the global average due to the impurity of seed lots supplied to farmers. In this study, we discovered high-quality Single Nucleotide Polymorphic markers (SNPs) in two widely cultivated maize hybrids and their parental inbreds. Paired-end double digest restriction site-associated DNA sequencing was used to discover SNPs and a total of 30,764,454 reads with a read length of 151 bp per sample were generated. Genotyping of SNPs for maize hybrids 'MAH 14-5' and 'Hema' revealed a total of 47,812 and 15,815 Genetic Purity Analysis markers, respectively, of which 44,388 and 12,391 were unique with 3,424 being common to both hybrids. Identified SNPs were used to develop primers for Kompetitive Allele-Specific PCR genotyping assays to determine the genetic purity of 10 seed lots and the results were found to correlate with Grow-out-Tests. Thus, the SNPs discovered in this study proved reliable to test the genetic purity of commercial seed lots. Advances in plant molecular breeding tools especially ddRADseq for SNP discovery offer new opportunities to genotype existing cultivars and accelerate the production of genetically pure seeds.

Aim: The aim of this study was to evaluate effectiveness of various microbial compost cultures for aerobic-composting of farm wastes. Place of Study: Three trials were conducted on farmer’s field and one at Krishi Vigyana Kendra (KVK) Ramanagara district. Methodology: During the composting process, days to compost, maturity in terms of changes in temperature, pH and composting dynamics were studied. Compost quality parameters such as macro and micro-nutrients and C:N ratio and stability of the compost were recorded at different intervals. Results: The results showed that the compost culture from IIHR and UASB had taken 90 and 105 days respectively, for complete stabilization; further had relatively higher temperature and pH during the initial phase and reached ambient condition at maturity stage, C:N ratio has showed gradual reduction from 39.65 to 15.98 and 39.75 to 13.66% respectively in IIHR and UASB cultures, they also had high macro, secondary and micro nutrients(IIHR-1.55% N, 0.93% P, 0.95% K, 4.39% Ca, 0.69% Mg, 0.19%S, 930 ppm Fe, 10ppm Cu, 305ppm Mn, 82ppm Zn, 26 ppm B UASB-1.59% N, 0.91% P, 0.97% K, 4.25%Ca, 0.88% Mg, 0.21%S, 948 ppm Fe, 9ppm Cu, 325ppm Mn, 93ppm Zn, 28ppm B) content and resulted in more compost production ( 3.3 and 2.8 t/year, respectively) with B:C ratio of 6.67 and 7.25 respectively when compared to NCOF (T3) and farmers practice (T4). Conclusion: Aerobic-composting of farm waste using microbial culture of UASB and IIHR proved to be an effective technology that aids to convert organic farm waste into valuable organic manure with an advantage of minimizing the environmental contamination associated with burning of residues.

Identification of chilli cultivar is prime importance to ensuring seed quality during seed production, certification and quality control. Fifteen cultivars were subjected to different biochemical tests Viz., phenol test, modified phenol test with FeSO4 and CuSO4, analysis of soluble seed proteins by SDS-PAGE. No single varieties were so distinct in case of phenol colour reaction, while it helped to group the cultivars. Based on modified phenol text with ferrous sulphates 1per cent (FeSO4) and 0.5 per cent copper sulphate (CuSO4) helped in further classification of cultivars. The cultivars Gouribidanur Local and Phule Jyothi showed unique bands at 14 (Rm: 0.624) and 2 (0.191) level of band. All the cultivars were distinct among each other showing SDS-PAGE as efficient method in chilli cultivar identification.

The main objective of this paper is to overcome the problems with conventionally tuned proportional-plus-integral (PI) controller by using TLBO-PI technique, which enhances the dynamic performance. The significant problem is that it is not able to provide optimal parameters, which is overcome by new teaching-learning-based optimization (TLBO) algorithm. This research work develops a new TLBO for multi-level inverter (MLI)-based multi-terminal HVDC (MLI-MT-HVDC) in grid-tied photovoltaic power plants (GTPVPPs). In this, 7-level inverter is replaced by a conventional 3-level, due to its advantage of less number of switching components, less dc source requirement, low total harmonic distortion (THD) and due to main effective reason of application in HVDC transmission. Here two terminals with individual grid integration are interconnected to a common terminal of solar distributed generation (DG). Among those terminals with grid integration, one is faulty and other is healthy terminal, in which the healthy terminal is not affected due to the fault on a faulty terminal. A teacher and students in a class are employed in step-by-step manner to generate an optimal result. The test system is also controlled with a fuzzy logic controller (FLC), adaptive neuro-fuzzy inference system (ANFIS), but due to its simple structure and its application in industries, a PI controller with new optimization method is implemented. Additionally, it is clear that TLBO-PI can reduce the THD to the level as per IEEE 519-2014 standards, improve fault-ride-through (FRT) capability and enhance the dynamic performance better during abnormalities and dynamic load.

Indian seed industry has shown an annual growth rate of 15.7% during 2011-2018 and is further expected to grow at a CAGR of 13.6% during 2019-2024, reaching a value of US $ 9.1 Billion by 2024. For any seed system to be viable and sustainable it requires a great deal of efforts through the right kind of laws, acts and policy framework and interventions as its essential pre-requisites. Due implementation of some progressive policies by the government of India, seed market has witnessed a major restructuring. These policies bought relaxed seed trade norms, reduced import restrictions on germplasm, encouraged foreign investments, supported quality seed production, plant variety protection, farmers and breeders right protection. Covid-19 pandemic and restrictions imposed had tremendous impact on the seed industry. The policy response and initiatives taken up by the government to address the problems by adopting various strategies helped in the uplifting the farming community. By classifying agriculture sector as essential, it eased in the continuous movement of the seed. This review gives insight about how the Indian seed legislation helped to increase the growth rate of Indian seed industry and also impact of covid-19 pandemic on seed sector.

In the past few decades, sophisticated machining industries are rapidly improved to attain the required shape of part within specific time and also not affecting/disturbing material properties. Accuracy of machined components is very important in every industry and geometrical accuracy of hole is vital in case of subassemblies of components. In this perspective, the researchers/experts updated their machinery time to time. In machining process, the mainly affected parameters are environment and time of machining zone, so in this case to overcome these problems encountered it is necessary to consider design of experiments which is having a great use in machining zone. This paper attempts new approach to produce hole within measurements on glass material using modified air abrasive jet machining (MAAJM) setup. Experiments were conducted on nickel material to evaluate the taper in machining. This (MAAJM) experimental work compared to stationary work table process is proven more accurate.

Increasing demand for automobiles is one of the major trends witnessed in the global market. To meet the needs of a customer and to provide customer satisfaction research is going on to modify the existing products or replacing old products with new and advanced material products. Many modifications have taken place to improve the suspension system of a vehicle. In the automobile industry, the suspension system is one of the major research areas and especially leaf springs design play a crucial role in providing suspension to the vehicle. Leaf Spring absorb shocks and bump loads and takes vertical loading to give comfortable experience to the passengers travelling in the wheeled vehicle. In this work, a new leaf spring modelled, a static and transient analysis performed. This leaf spring developed by introducing EPDM rubber in between the steel leaves, which is a synthetic rubber and exhibits hyperelastic nature. Hyperelastic materials are widely used for diverse structural applications in a variety of industries. Modelling of existing and new leaf springs did in NX 11.0; a static and transientanalysis performed using ANSYS Workbench 18.1. Acomparative study is done and presented

Decision of finest machining parameters is very essential factors in any processing of machined parts. This article presents a multi-objective optimization technique, based on WASPAS method toward optimize the machining parameters in abrasive jet machining (AJM) process: pressure, nozzle to tip distance (NTD), and average grain diameter on NICKEL 233 alloy. Three conflicting objectives, Material Removal Rate (MRR), surface roughness (Ra) and taper angle (Ta) are simultaneously considered. The proposed technique weighted aggregated product sum assessment technique is investigation of parametric optimization on AJM process. Its outcome using tool in any ranges of responses in AJM process is the optimal setting of parameters are determined through experiments illustrated. Broad usage of Aerospace industries for NICKEL 233, generating a hole of the machining data first time in this work using AJM will be useful.

Spatial distribution and sequential sampling plan for chilli thrips, Scirtothrips dorsalis Hood were analyzed through Taylor’s power law (TPL) and Iwao’s mean crowding regression (IMC) for rainy and summer seasons during 2016–17 on chilli crop. The results revealed that the mean number of thrips in the field was low (1.07 thrips/plant) at early crop growth stages (32 days after transplanting (DAT)) and increased gradually with a peak (21.53 thrips/plant) at 56 DAT. Inconsistency in the mean number of thrips with shifting variance was noticed. The variance of thrips population increased with increase in its density with the best variance (122.41) observed at 56 DAT. Samples of thrips showed variance to mean ratio (S2/X), Lloyd’s patchiness index (X*/X), as well as Morisita Index more than one, revealing clumped distribution. The data on thrips population was best fit to TPL (a = 0.184, b = 1.27, R2 = 0.66) and the IMC (α = 0.93, β = 1.14, R2 = 0.94). Larger variability in sample size vis-a-vis mean population density was also achieved at 10 and 20% precision levels. Considering TPL parameters, the decisive lines of sequential sampling for S. dorsalis was chosen at d = 13n ± 8.07√n. The sequential sampling plan will thus help in reducing the costs for an effective and efficient management of S. dorsalis on chilli.

Purpose The choice of best machining parameters is an extremely basic factor in handling of any machined parts. The purpose of this paper is to exhibit a multi-objective optimization technique; in view of weighted aggregate sum product assessment (WASPAS) technique toward upgrade the machining parameters in modified air abrasive jet machining (MAAJM) process: injecting pressure, stand-off distance (SOD), and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Three conflicting destinations, material removal rate (MRR), surface roughness (SR) and taper angles (Ta), respectively, are considered at the same time. The proposed procedure uses WASPAS, which is the examination of parametric optimization of the abrasive jet machining (AJM) process. The results was used any scopes of reactions in MAAJM process is the ideal setting of parameters are resolved through investigations represented. There is wide utilization of Nickel 233 in aviation enterprises; machining information on producing a hole utilizing MAAJM for the first time is given in this work, which will be helpful different industries. Design/methodology/approach This paper exhibits a multi-objective optimization technique; in view of WASPAS technique toward upgrade the machining parameters in MAAJM process: injecting pressure, SOD, and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Findings As an outcome of using the tool in any ranges of responses in the AJM process, the optimal setting of parameters is determined through experiments illustrated. The machining data of generating a hole using AJM are studied for the first time in this work, which will be useful for aerospace industries, where Nickel 233 is used broadly. Originality/value A new material in unconventional machining process and also a multi-objective optimization technique are adopted.

Background: The agricultural sector is highly dependent on the availability and quality of seeds for a productive harvest. The global demand for food and water is expected to increase due to population outgrowth, urbanization and climate change. Soilless farming may change the face of agriculture by providing a more sustainable and productive alternative to traditional cultivation and is being largely exploited for vegetable cultivation. Methods: The experiment consisted of 12 treatments. Two parental lines (P1: TAG 1 and P2: TAG 2) were subjected to seed treatment (S1: Untreated and S2: Thiram @ 2g kg-1 and chlorpyrifos @ 3g kg-1) and twenty-eight days old seedlings were transplanted to soil (M1: Conventional) and soilless systems (M2: Hydroponics and M3: Aeroponics). Hybrid seeds were produced in all the system were analysed for the quality and economics of seed production in soilless system was worked out. Result: The results revealed that there was a significant increase in test weight (0.39 g), average seed length (0.52 cm) in the soilless system due to the continuous availability of nutrients at controlled condition. Although the cost incurred was comparatively higher in the soilless method, the gross return was 94.68 per cent higher under aeroponics and 79.22 per cent higher under hydroponics compared to the conventional method. The benefit to cost ratio was found higher in aeroponics (2.08) followed by hydroponics (1.97) and lower under the conventional method (1.87). It is inferred that soilless agriculture could be a promising tool for quality and healthy hybrid tomato seed production throughout the year within protected cultivation.

Unit commitment (UC) is a famous problem in electrical power systems which desire the minimization of total power generation cost at a specific period by determining acceptable scheduling of the generation units. Several methodologies and algorithms have been proposed to solve the UC problem. This research provides a blend of unit commitment problem implemented with genetic algorithm and the dynamic programming and also describes the best technique in solving the same. This problem involves an optimization task that involves schedule ON/OFF of generating units that satisfy various constraints for minimum cost generation of load demand at an hour. This problem improves network reliability and yields a technique to decrease the generation cost. The short-term unit commitment approach requires a quick technique to reduce system changes and scheduled errors. The definite solution for this problem can be achieved by the entire combination of all appropriate generating different combinations focusing on cost optimization. Genetic algorithms are stochastic search algorithms; they will maintain the population solutions to a problem in an encoded form so that the information will evolve in time. The optimal outcomes from the unit commitment problem for this technique are compared with the standard IEEE 10-unit system data.

Endophytes are non-disease causing microbes (bacteria and fungi) surviving in living tissues of plants. Their intimate association and possible coevolution with their plant partners have resulted in them contributing to an array of plant growth benefits ranging from enhanced growth and biomass accumulation, tolerance to abiotic and biotic stresses and in nutrient acquisition. The last couple of decades have witnessed a burgeoning literature on the role of endophytes (Class 3 type) in regulating plant growth and development and their adaptation to abiotic and biotic stresses. Though the underlying mechanisms of plant-endophyte interactions are far from clear, several studies have raised the hope of their potential application in agriculture, especially in mitigating abiotic and biotic stresses. The use of endophytes is envisaged as a route to reduce the production cost and burden on the environment by lessening the dependence on breeding for crop improvement and agrochemicals. Unfortunately, save a few well documented examples of their use, a little of these insights has been translated into actual agricultural applications. Here, we reflect on this paucity and elaborate on some of the important bottlenecks that might stand in way of fully realizing the potential that endophytes hold for crop improvement. We stress the need to study various facets of the endophyte-plant association for their gainful application in agriculture.

In this work, we studied influences on the absorption and fluorescence emission spectra of coumarin-4066 (C-466) with different solvent polarity scale. The spectral shifts reflect the effect of the equilibrium solvents association across the energized solute particle, which adjusts inertially as a result of quick charge realignment upon radiative deactivation to the lowest electronic state. The dipole moments of C-466 are determined by employing the Bakhshiev, Kawski-Chamma-Viallet, Lippert-Mataga and McRae relations. The results from all these methods are, excited state dipole moment of C-466 is higher than the ground state dipole moments and which indicates molecule is less polar in the ground state. Theoretical analysis was also carried out by Density Functional theory (DFT and TD -DFT) employing the BECKE-1998 (exchange)/STO-6G basic set in ethanol solvent and in vacuum medium. The HOMO-LUMO, Solvent Accessible Surfaces (SAS) and Molecular Electrostatic Potential (MEP) were analysed to acquire additional knowledge of the molecular arrangement and electronic properties of C-466. These photophysical properties suggest delineation can be mauled for laying out new luminescent tests for various solvents microenvironment.

The objective of this present work is to investigate the influence of tool geometry on mechanical properties of friction stir welded AA 2014-T6 6mm, thickness plates. In this investigation an attempt is being made to understand the effect of tool traverse speed and tool pin profile at constant tool rotational speed, with varying concave shoulder radius of R2.5, R3 & R3.5 of a straight cylindrical pin on Aluminium Alloy weldments. From the investigation it was found that the joints made by concave shoulder with radius R2.5 resulted in better mechanical properties compared to concave shoulder with radius R3 and R3.5.The microstructure is examined by using optical microscope. Joints made with concave shoulder of radius R2.5 showed finer grains compared to other tool shoulder geometry. The observed mechanical properties were correlated with their microstructures and fracture features.