Search results for: Shital Bangar

Authors: Shital Bangar, G. B. Khandagale

Abstract:

The experimentation was carried out to study the influence of sulphur and boron on growth parameters and productivity of soybean in kharif season of 2009-2010 at Experimental Farm, Department of Agricultural Botany, Marathwada Agricultural University, Parbhani (M.S.). The object was to evaluate the impact of sulphur and boron on growth, development, grain yield and physiological aspects of soybean variety MAUS-81. Nine treatments consisted of three levels of sulphur i.e. 20, 30 and 40 Kg/ha as well as three levels boron i.e.10, 15 and 20 kg boron/ha and the combinations of these two mineral elements i.e. Sulphur @30 kg/ha + Borax @15 kg/ha and Sulphur @40 kg/ha + Borax @ 20 kg/ha with one control treatment in Randomized Block Design (RBD) with three replications. The effect of sulphur and boron on various growth parameters of soybean like relative growth rate (RGR) and net assimilation rate (NAR) were remained statistically on par with each other. However, the application of higher dose of Sulphur @40 kg/ha + Borax @ 20 kg/ha enhanced significantly all the growth parameters. Application of the nutrients increased the dry matter accumulation of the crop plant and hence, other growth indices like RGR and NAR also increased significantly. RGR and NAR values were recorded highest at the initial crop growth stages and decline thereafter. The application of sulphur @40 kg/ha + Borax @ 20 kg/ha recorded significantly higher content of chlorophyll ‘a’ than rest of the treatments and chlorophyll ‘b’ observed higher in boron @15 kg/ha as well as boron@20 kg/ha, whereas total chlorophyll content was maximum in sulphur @40 kg/ha. Oil content was not influenced significantly due to above fertilization. The highest seed yield and total biological yield were obtained with combination of Sulphur @40 kg/ha + Borax @ 20 kg/ha, single sulphur and boron application also showed a significant effect on seed and biological yield.

Keywords: boron, growth, productivity, quality, soybean and sulphur

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Authors: Shital Bangar, Chetana Mandavia

Abstract:

A field experiment was carried out in Factorial Randomized Block Design (FRBD) with three replications at Instructional Farm Krushigadh, Junagadh Agricultural University, Junagadh, India to assess the biochemical parameters of wheat in order to assess the thermotolerance. Nine different wheat varieties GW 433, GW 431, HI 1571, GW 432, RAJ 3765, HD 2864, HI 1563, HD 3091 and PBW 670 sown in timely and late sown conditions (i.e., 22 Nov and 6 Dec 2012) were analysed. All the varieties differed significantly with respect to grain yield morpho-physiological parameters and growth indices for time of sowing, varieties and varieties x time of sowing interactions. The observations on morpho-physiological parameters viz., germination percentage, canopy temperature depression and growth indices viz., leaf area index (LAI), leaf area ratio (LAR) were recorded. Almost all the morpho-physiological parameters, growth indices and grain yield studied were affected adversely by late sowing, registering reduction in their magnitude. Germination percentage was reduced under late sown condition but variety PBW 670 was the best. Varieties GW 432 performed better with respect to canopy temperature depression while sown late. Under late sown condition, variety GW 431 recorded higher LAI while HI 1563 had maximum LAR. Considering yield performance, HD 2864 was best under timely sown condition, while GW 433 was best under late sown condition. Varieties HI 1571, GW 433 and GW 431 could be labelled as thermo-tolerant because there was least reduction in grain yield under late sown condition (1.75 %, 7.90 % and13.8 % respectively). Considering correlation coefficient, grain yield showed very strong significant positive association with germination percentage. Leaf area ratio was strongly and significantly correlated with grain yield but in negative direction. Canopy temperature depression and leaf area index also had positive correlation with grain yield but were non-significant.

Keywords: growth indices, morpho-physiological parametrs, thermo-tolerance, wheat

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Authors: Vinay Patil, Swapnil Kekade, Ashish Supare, Vinayak Pawar, Shital Jadhav, Rajkumar Singh

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In recent days, bainitic steel is used in automobile and non-automobile sectors due to its high strength. Bainitic steel is difficult to machine because of its high hardness, hence in this paper machinability of bainitic steel is studied by using Taguchi design of experiments (DOE) approach. Convectional turning experiments were done by using L16 orthogonal array for three input parameters viz. cutting speed, depth of cut and feed. The Taguchi method is applied to study the performance characteristics of machining parameters with surface roughness (Ra), cutting force and tool wear rate. By using Taguchi analysis, optimized process parameters for best surface finish and minimum cutting forces were analyzed.

Keywords: conventional turning, Taguchi method, S/N ratio, bainitic steel machining

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Authors: Rajesh A. Rane, Shital S. Naphade, Rajshekhar Karpoormath

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Thiozolidin-4-one, a mimic of thiazolobenzimidazole (TBZ) has drawn many attentions due to its potent and selective inhibition against the HIV-1 and low toxicity by binding to the allosteric site of the reverse transcriptase (RT) as a non-nucleoside RT inhibitor (NNRTI). Similarly, marine bromopyrrole alkaloids are well known for their diverse array of anti-infective properties. Hence, we have reported synthesis and in vitro HIV-1 RT inhibitory activity of a series of 4-thiazolidinone-bromopyrrole alkaloid hybrids tethered with amide linker. The results of in vitro HIV-1 RT kit assay showed that some of the compounds, such as 4c, 4d, and 4i could effectively inhibit RT activity. Among them, compounds 4c having 4-chlorophenyl substituted 4-thiazolidione ring was the best one with the IC50 value of 0.26 µM. The sturdy emerges with key structure-activity relationship that pyrrole-NH-free core benefited inhibition against HIV-1 RT inhibition. This study identified conjugate 4c with potent activity and selectivity as promising compound for further drug development to HIV.

Keywords: antiviral drugs, bromopyrrole alkaloids, HIV-1 RT inhibition, 4-thiazolidinone

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Authors: Swastik Karmakar, Prasanta Das, Shital K. Chattopadhyay

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An efficient synthesis of symmetrical 2, 2′-Di-substituted 3, 3′-bisindolylarylmethanes (BIAMs) having different aryl and hetero-aryl moieties has been developed by Ag(I)-catalyzed indolyzation and a sequential deoxygenative addition involving o-alkynylanilines and aryl/hetero-aryl aldehydes as substrates. Alkyne and carbonyl units could be activated by Ag (I) simultaneously which results in a domino 5-endo-dig indole annulation, addition of C3 of this indole nucleus to the carbonyl carbon in addition to second indole annulation, and its dehydroxylative addition to the same carbonyl carbon to furnish BIAMs in excellent yield. As 3, 3′-bisindolylmethanes (BIMs) are biologically significant scaffolds, this moiety with further substitutions at the indole core could find some important use in medicinal chemistry. The methodology developed is atom-economic and involves more accessible silver salts, which could be useful for large-scale synthesis.

Keywords: alkyne, 3, 3′-Bisindolylarylmethanes, carbonyl, domino, 5-endo-dig indole annulation, silver catalyst

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Shital Jhunjhunwala, Shweta Saraf

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Research Question: The study, based on a survey, empirically tests the impact of the board’s engagement in the decision-making process on firm outcomes. It also examines the moderating effect of board leadership and board independence on the relationship. Research Findings: Boards’ engagement in the decision-making process is found to be vital for firm performance, wherein effective monitoring by the board outperforms their strategic guidance role in achieving desired outcomes. The separation of CEO and Chairman positively moderates the board’s engagement in protecting stakeholders’ interests, but lack of independence and passive behaviour of independent directors raises concern on the efficacy of independent directors. Theoretical Implications: The study provides the framework for process-oriented corporate governance research, where investigation of boards’ behaviour inside the boardroom develops a deeper understanding of board processes. Practitioner Implications: The study highlights the necessity of developing boards’ focus in a company on monitoring managerial actions. It suggests the need to separate the position of CEO and Chairman for addressing the interest of all stakeholders. It recommends policymakers review the existing mandate on board independence and create alternate monitoring mechanisms for addressing agency conflict.

Keywords: board, decision-making process, engagement, independence, leadership, innovation, stakeholders, firm performance, qualitative, India

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Lovesh Goyal, Pushkar Dave, Prajyot Jadhav, GonnaYaswanth, Sakshi Giri, Sahil Dharme, Rushika Joshi, Rishabh Verma, Shital Chiddarwar

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With the rising need for human-robot interaction, researchers have proposed and tested multiple models with varying degrees of success. A few of these models performed on aerial platforms are commonly known as Tethered Aerial Systems. These aerial vehicles may be powered continuously by a tether cable, which addresses the predicament of the short battery life of quadcopters. This system finds applications to minimize humanitarian efforts for industrial, medical, agricultural, and service uses. However, a significant challenge in employing such systems is that it necessities attaining smooth and secure robot-human interaction while ensuring that the forces from the tether remain within the standard comfortable range for the humans. To tackle this problem, a hybrid control method that could switch between two control techniques: constant control input and the steady-state solution, is implemented. The constant control approach is implemented when a person is far from the target location, and error is thought to be eventually constant. The controller switches to the steady-state approach when the person reaches within a specific range of the goal position. Both strategies take into account human velocity feedback. This hybrid technique enhances the outcomes by assisting the person to reach the desired location while decreasing the human's unwanted disturbance throughout the process, thereby keeping the interaction between the robot and the subject smooth.

Keywords: unmanned aerial vehicle, tethered system, physical human-robot interaction, hybrid control

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