Browsing by Author "Vijay Kumar Singh"

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A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting suspended sediment concentration
(Nature Research, 2024) Bhupendra Joshi; Vijay Kumar Singh; Dinesh Kumar Vishwakarma; Mohammad Ali Ghorbani; Sungwon Kim; Shivam Gupta; V.K. Chandola; Jitendra Rajput; Il-Moon Chung; Krishna Kumar Yadav; Ehsan Mirzania; Nadhir Al-Ansari; Mohamed A. Mattar
Suspended sediment concentration prediction is critical for the design of reservoirs, dams, rivers ecosystems, various operations of aquatic resource structure, environmental safety, and water management. In this study, two different machine models, namely the cascade correlation neural network (CCNN) and feedforward neural network (FFNN) were applied to predict daily-suspended sediment concentration (SSC) at Simga and Jondhara stations in Sheonath basin, India. Daily-suspended sediment concentration and discharge data from 2010 to 2015 were collected and used to develop the model to predict suspended sediment concentration. The developed models were evaluated using statistical indices like Nash and Sutcliffe efficiency coefficient (NES), root mean square error (RMSE), Willmott’s index of agreement (WI), and Legates–McCabe’s index (LM), supplemented by a scatter plot, density plots, histograms and Taylor diagram for graphical representation. The developed model was evaluated and compared with CCNN and FFNN. Nine input combinations were explored using different lag-times for discharge (Qt-n) and suspended sediment concentration (St-n) as input variables, with the current suspended sediment concentration as the desired output, to develop CCNN and FFNN models. The CCNN4 model with 4 lagged inputs (St-1, St-2, St-3, St-4) outperformed the other developed models with the lowest RMSE = 95.02 mg/l and the highest NES = 0.0.662, WI = 0.890 and LM = 0.668 for the Jondhara Station while the same CCNN4 model secure as the best with the lowest RMSE = 53.71 mg/l and the highest NES = 0.785, WI = 0.936 and LM = 0.788 for the Simga Station. The result shows the CCNN model was better than the FFNN model for predicting daily-suspended sediment at both stations in the Sheonath basin, India. Overall, CCNN showed better forecasting potential for suspended sediment concentration compared to FFNN at both stations, demonstrating their applicability for hydrological forecasting with complex relationships. © The Author(s) 2024.
A curious observation of Pauli-Blocking in MoS2-quantum dots/graphene hybrid system
(American Institute of Physics Inc., 2018) Amulya Nemoori; Himanshu Mishra; Vijay Kumar Singh; P.K. Shukla; Anchal Srivastava; Amritanshu Pandey
In this study, Pauli-Blocking has been observed in a 0D/2D MoS2 quantum dots/graphene (MoS2-QDs/graphene) hybrid system. For the observation of room temperature Pauli-Blocking in the 0D/2D system, a photodetector device based on n-type MoS2-QDs and CVD grown graphene has been fabricated using a facile and lithography free technique. The current-voltage characteristics of the device have been performed at room temperature. The fabricated device shows a negative response under visible light (λ ∼ 400 to 700 nm) illumination. The dark to photo current ratio of the device shows variation up to two orders of magnitude. This negative response, which results decrease in current under visible light illumination, may be attributed to the Pauli-Blocking due to high absorbance of photon energy in visible light range. Furthermore, it is believed that the present study may provide an insight into understanding the Pauli-Blocking in 0D/2D hybrid system at room temperature. © 2018 Author(s).
A new chromosome count for Chara corallina (Klein ex Willd., em.) R.D.W.
(2010) Vijay Kumar Singh; B.R. Chaudhary
The new chromosome count (n=35) has been reported in Chara corallina (Klein ex Willd., em.) R.D.W. Total form % was 36.92. The karyotype formula is (7 m 14 sm 3 s t 2 t) M + (6 sm 1 st 2 t) S.
Biochemical characterization of a peroxidase isolated from Caribbean plant: Euphorbia cotinifolia
(2011) Reetesh Kumar; Kunwar Awaneesh Singh; Vijay Kumar Singh; Medicherla V. Jagannadham
A Caribbean copper plant peroxidase (CCPP) is purified from the latex of Euphorbia cotinifolia, using anion exchange chromatography. The molecular mass and isoelectic point of the enzyme is 43.11 kDa and pH 8.1 respectively. The peroxidase is found to be sensitive towards general phenolic substrates like guaiacol, pyrogallol, α-aminopterin, phloroglucinol, o-phenelenediamine and dianisidine dihydrochloride. The substrate specificity of CCPP was distinct from that of other peroxidases, and the best substrate for CCPP was guaiacol at pH 6.0 and 50°C. Sucrose and Ca2+ enhance the activity whereas the activity is significantly inhibited by NaN3 and Na 2SO3. The strong absorption at 650 nm reveals the presence of Cu ions as a prosthetic group. Spectroscopic studies reveal that CCPP has high α-helicity. The enzyme was found to be very stable at room temperature and retained more than 80% activity even after a period of 2 months and was stable for more than 6 months at 4°C without any additive or preservative. Adequate amount of latex, easy purification method, broad substrate specificity, and high stability against pH, temperature, chaotrophs and organic solvents makes this enzyme a potential candidate in biotechnological and industrial applications. © 2011 Elsevier Ltd. All rights reserved.
Carnein, a serine protease from noxious plant weed Ipomoea carnea (Morning glory)
(2007) Ashok Kumar Patel; Vijay Kumar Singh; Medicherla V. Jagannadham
A new serine protease from the latex of Ipomoea carnea spp. fistulosa (Morning glory), belonging to the Convolvulaceae family, was purified to homogeneity by ammonium sulfate fractionation followed by cation exchange chromatography. The enzyme, named carnein, has a molecular mass of 80.24 kDa (matrix-assisted laser desorption/ionization time-of-flight) and an isoelectric point of pH 5.6. The pH and temperature optima for proteolytic activity were 6.5 and 65°C, respectively. The extinction coefficient (ε 2801%) of the enzyme was estimated as 37.12, and the protein molecule consists of 35 tryptophan, 76 tyrosine, and seven cysteine residues. The effect of several inhibitors such as iodoacetic acid, diisopropylfluorophosphate, phenyl-methanesulfonyl fluoride, chymostatin, soybean trypsin inhibitor, HgCl2, 3S-3-(N-{(S)-1-[N-(4- guanidinobutyl)carbamoyl]3-ethylbutyl}carbamoyl)oxirane-2-carboxylic acid, N-ethyl maleimide, ethylene glycol-bis(α-amino ethyl ether)tetraacetic acid, ethyl-enediamminetetraacetic acid, and o-phenonthroline indicates that carnein belongs to the family of serine proteases. The enzyme is not prone to autolysis even at very low concentrations. The N-terminal sequence of carnein (T-T-H-S-P-E-F-L-G-L-A-E-S-S-G-L-X-P-N-S) exhibited considerable similarity to those of other plant serine proteases; the highest similarity was with alnus AG12, one of the subtilase family endopepetidases. © 2007 American Chemical Society.
Characterizations of nanoscale two-dimensional materials and heterostructures
(Elsevier, 2020) Anchal Srivastava; Chandra Shekhar Pati Tripathi; Vijay Kumar Singh; Rohit Ranjan Srivastava; Sumit Kumar Pandey; Suyash Rai; Ravi Dutt; Amit Kumar Patel
In recent years, two-dimensional (2D) atomically thin crystals ranging from insulator to superconductor such as graphene, hexagonal boron nitride (h-BN), transition metal dichalcogenides (TMDs), etc. have attracted extensive attention due to their exceptional properties and many potential applications in various areas. In this chapter we focus on the experimental characterization of 2D materials and their heterostructures andcover brief introduction and detailed structural, optical, and chemical characterizations of some important 2D materials. © 2020 Elsevier Inc.
Crystallization and preliminary X-ray analysis of carnein, a serine protease from ipomoea carnea
(2009) Ashok Kumar Patel; Niels Van Oosterwijk; Vijay Kumar Singh; Henritte J. Rozeboom; Kor H. Kalk; Roland J. Siezen; Medicherla V. Jagannadham; Bauke W. Dijkstra
Carnein is an 80 kDa subtilisin-like serine protease from the latex of the plant Ipomoea carnea which displays an exceptional resistance to chemical and thermal denaturation. In order to obtain the first crystal structure of a plant subtilisin and to gain insight into the structural determinants underlying its remarkable stability, carnein was isolated from I. carnea latex, purified and crystallized by the hanging-drop vapour-diffusion method. A data set was collected to 2.0 Å resolution in-house from a single crystal at 110 K. The crystals belonged to the trigonal space group P3121 or P3221, with unit-cell parameters a = b = 126.9, c = 84.6 Å, = Β = 90, = 120°. Assuming the presence of one molecule per asymmetric unit, the Matthews coefficient is 2.46 Å3 Da-1, corresponding to a solvent content of 50%. Structure determination of the enzyme is in progress. © 2009 International Union of Crystallography All rights reserved.
Distribution and geochemistry of selected trace elements in the lignites of Cambay basin, Gujarat, western India
(Geological Society of India, 2016) P.K. Singh; Vijay Kumar Singh; Pramod Kumar Rajak; M.P. Singh; A.S. Naik
In the present investigation all the working lignite seams of Cambay basin of Gujarat have been studied to see the distribution and geochemistry of selected major/minor elements like Fe, Ca, Na, K, Mg, and Mn and trace elements like Cu, Co, Cr, Cd, Ni, Pb and Zn. The vertical variation of these elements along the seam profiles has been studied to see the pattern of distribution of these elements and also to know the horizons of their enrichment and the probable cause. Further, these elements have been correlated among themselves and also with organic and inorganic matter of lignite. The correlation study indicates that in Tadkeshwar upper seam Fe has its affinity with huminite while Mg and Na have their affinity with liptinite and in Tadkeshwar lower seam Na has an affinity with liptinite. In Vastan upper seam Mn and Cu are associated with inertinite and Na with huminite while in Vastan lower seam Cu relates to huminite and Cd to liptinite and huminite. In Rajpardi seam Ca and Co are associated with huminite. The study provides information on the mode of occurrence of elements of less studied lignites of western India. © 2016, Geological Society of India.
Distribution of pulse type uniform input in aquifers in tropical regions
(2005) Naveen Kumar; Vijay Kumar Singh; R.R. Yadav
The present work presents mathematical models for the distribution of solute concentration of uniform input of pulse type along sinusoidally varying unsteady longitudinal velocity through such inhomogeneous aquifers of finite as well as semi-infinite extents whose main source of replenishment is infiltration during rains. A new time variable is introduced by using an expression in old time variable. Numerical solutions of such models are obtained using finite difference approximations. At initial stage the dispersion problem is considered steady one in homogeneous aquifer. Its solution is considered as initial condition for the respective unsteady problems. To achieve minimum time period of computation, the parameters of the problem are non-dimensionalized in terms of the existing variables in cases of semi-infinite and finite aquifers separately. The effects of inhomogeneity in both cases are shown through illustrations.
Effect of qGN4.1 QTL for Grain Number per Panicle in Genetic Backgrounds of Twelve Different Mega Varieties of Rice
(Springer New York LLC, 2018) Vijay Kumar Singh; Ranjith Kumar Ellur; Ashok Kumar Singh; M. Nagarajan; Brahma Deo Singh; Nagendra Kumar Singh
Background: Rice is a major source of food, particularly for the growing Asian population; hence, the utilization of genes for enhancing its yield potential is important for ensuring food security. Earlier, we have mapped a major quantitative trait loci (QTL) for the grain number per panicle, qGN4.1, using biparental recombinant inbred line (RIL) populations involving a new plant type Indica rice genotype Pusa 1266. Later, three independent studies have confirmed the presence of a major QTL for spikelet number by three different names (SPIKE, GPS and LSCHL4) in the same chromosomal region, and have implicated the overexpression of Nal1 gene as the causal factor for high spikelet number. However, the effect of qGN4.1 in different rice genetic backgrounds and expression levels of the underlying candidate genes is not known. Results: Here, we report the effect of qGN4.1 QTL in the genetic backgrounds of 12 different high-yielding mega varieties of rice, introgressed by marker assisted-backcross breeding (MABB) using two QTL positive markers for foreground selection and two QTL negative flanking markers for recombinant selection together with phenotypic selection for the recovery of recipient parent genetic background. Analysis of the performance of BC2F3 plants showed a significant increase in the average number of well-filled grains per panicle in all the backgrounds, ranging from 21.6 in CSR 30-GN4.1 to 147.6 in Samba Mahsuri-GN4.1. Furthermore, qGN4.1 caused a significant increase in flag leaf width and panicle branching in most backgrounds. We identified BC3F3qGN4.1 near-isogenic lines (NILs) with 92.0–98.0% similarity to the respective recipient parent by background analysis using a 50 K rice SNP genotyping chip. Three of the NILs, namely Pusa Basmati 1121-GN4.1, Samba Mahsuri-GN4.1 and Swarna-GN4.1, showed a significant yield superiority to their recipient parents. Analysis of differential gene expression revealed that high grain number in these QTL-NILs was unlikely due to the overexpression of Nal1 gene (LOC_Os04g52479). Instead, another tightly linked gene (LOC_Os04g52590) coding for a protein kinase domain-containing protein was consistently overexpressed in the high grain number NILs. Conclusion: We have successfully introgressed the qGN4.1 QTL for high grain number per panicle into 12 different mega varieties of rice using marker-assisted backcross breeding. The advanced near-isogenic lines are promising for the development of even higher yielding versions of these high-yielding mega varieties of rice. © 2018, The Author(s).
Environmental geochemistry of selected elements in lignite from Barsingsar and Gurha mines of Rajasthan, Western India
(Geological Society of India, 2015) Prakash K. Singh; P.K. Rajak; M.P. Singh; A.S. Naik; Vijay Kumar Singh; S.V. Raju; Sanjay Ojha
The present paper contains the result of investigation carried out on selected trace elements in the less studied lignite deposits of Rajasthan, Western India. The study has been made on two new lignite deposits–Barsingsar and Gurha. The former has elevated ash content (mean 20.8%) than the latter one (mean 5.1%) and both of them have high volatile matter (mean 43.7% and 49.9% respectively). The lignite samples have been studied for selected elements like Fe, Ca, Mg, Mn, K, Na, Cu, Co, Ni, Cr, Zn, Pb, Cd and As. The elements like Cd, Co, Ni, Pb and Cu occur in high concentration when compared to the Clarke values for brown coal. Ca and Mg relate positively with organic matter in Barsingsar lignite indicating their organic source while K, Cu, Co, Pb and Cd indicate their inorganic origin. Ca might have come in contact with the organic matter during humification and would have become a part of humate. The elements like Cu, Co, Ni, Cr, Cd and Pb showing strong affinity with inertinite could have got associated with the mineral matter present in the fusinite and funginite macerals. In Gurha lignites Pb and Co have shown their affinity with inorganic matter which could have been drawn from sulphides and clay minerals. © 2015, Geological Society of India.
Human papillomavirus infection & anal cytological abnormalities in HIV-positive men in eastern India
(BioMed Central Ltd., 2018) Abhilasha Gautam; Jaya Chakravarty; Vijay Kumar Singh; Amrita Ghosh; Shashi Bhushan Chauhan; Madhukar Rai; Shyam Sundar
Background: Oncogenic Human papillomavirus (HPV) infections are closely associated with anal cancer which is high among human immunodeficiency virus (HIV) infected males. There are no data regarding anal HPV infection and cytological abnormalities in HIV positive males receiving free therapy in the national program. Thus, this cross-sectional study was performed to assess the prevalence and risk factors of anal HPV infection and cytological abnormalities in HIV positive males. Methods: We screened 126 HIV-positive male patients attending the antiretroviral treatment center (ART) between 2014 and 2015 with anal papanicolaou smear cytology and HPV-DNA testing. HPV-DNA was detected by using polymerase chain reaction (PCR) method with two consensus primer sets E6 and MY09/11 and further analyzed for the presence of various HPV genotype by Sanger sequencing. Risk factors associated with anal cytological abnormalities and HPV infection was analyzed by using univariate and multivariate logistic regression models. Results: Out of 126, 52 were on antiretroviral therapy. 91% were married to female partners but during the study 48 (38%) gave positive history of anal intercourse with other men. Anal cytology was done in 95 patients, out of which 60 (63.15%) had cytological abnormalities. LSIL (low-grade squamous intraepithelial lesions) was present in 27 (45%), ASCUS (atypical squamous cells of undetermined significance) in 31 (52%) and ASC-H (atypical squamous cells cannot exclude a high-grade squamous intraepithelial lesion) in 2 (3.33%). In multivariate analysis, the risk factors for cytological abnormality were presence of history of anal intercourse (OR, 6.1; 95% CI, 2.0-18.7) and WHO stage III & IV (OR, 2.7; 95% CI, 1.1-7.5). HPV-DNA was detected in 33/119 (27.73%) patients. The most prevalent HPV type in the study was HPV-16 (10.08%), other HPV types detected were 18,31,35,17,66,72,52,68 and 107 (17.65%). Conclusions: High prevalence of anal cytological abnormalities in our study suggests that regular anal Pap smear screening should be done in HIV positive males in the ART center. © 2018 The Author(s).
ICChI, a glycosylated chitinase from the latex of Ipomoea carnea
(2009) Ashok Kumar Patel; Vijay Kumar Singh; Ravi Prakash Yadav; A.J.G. Moir; Medicherla V. Jagannadham
A multi-functional enzyme ICChI with chitinase/lysozyme/exochitinase activity from the latex of Ipomoea carnea subsp. fistulosa was purified to homogeneity using ammonium sulphate precipitation, hydrophobic interaction and size exclusion chromatography. The enzyme is glycosylated (14-15%), has a molecular mass of 34.94 kDa (MALDI-TOF) and an isoelectric point of pH 5.3. The enzyme is stable in pH range 5.0-9.0, 80 °C and the optimal activity is observed at pH 6.0 and 60 °C. Using p-nitrophenyl-N-acetyl-β-d-glucosaminide, the kinetic parameters Km, Vmax, Kcat and specificity constant of the enzyme were calculated as 0.5 mM, 2.5 × 10-8 mol min-1 μg enzyme-1, 29.0 s-1 and 58.0 mM-1 s-1 respectively. The extinction coefficient was estimated as 20.56 M-1 cm-1. The protein contains eight tryptophan, 20 tyrosine and six cysteine residues forming three disulfide bridges. The polyclonal antibodies raised and immunodiffusion suggests that the antigenic determinants of ICChI are unique. The first fifteen N-terminal residues G-E-I-A-I-Y-W-G-Q-N-G-G-E-G-S exhibited considerable similarity to other known chitinases. Owing to these unique properties the reported enzyme would find applications in agricultural, pharmaceutical, biomedical and biotechnological fields. © 2009 Elsevier Ltd. All rights reserved.
Impact of climate change induced future rainfall variation on dynamics of arid-humid zone transition in the western province of India
(Academic Press, 2023) Kanhu Charan Panda; R.M. Singh; Vijay Kumar Singh; Saurav Singla; Pradosh Kumar Paramaguru
The transition of the Earth's climate from one zone to another is one of the major causes behind biodiversity loss, rural-urban migration, and increasing food crises. The rising rate of arid-humid zone transition due to climate change has been substantially visible in the last few decades. However, the precise quantification of the climate change-induced rainfall variation on the climate zone transition still remained a challenge. To solve the issue, the Representative Grid Location-Multivariate Adaptive Regression Spline (RGL-MARS) downscaling algorithm was coupled with the Koppen climate classification scheme to project future changes in various climate zones for the study area. It was observed that the performance of the model was better for the humid clusters compared to the arid clusters. It was noticed that, by the end of the 21st century, the arid region would increase marginally and the humid region would rise by 24.28–36.09% for the western province of India. In contrast, the area of the semi-arid and semi-humid regions would decline for the study area. It was observed that there would be an extensive conversion of semi-humid to humid zone in the peripheral region of the Arabian sea due to the strengthening of land-sea thermal contrast caused by climate change. Similarly, semi-arid to arid zone conversion would also increase due to the inflow of dry air from the Arabian region. The current research would be helpful for the researchers and policymakers to take appropriate measures to reduce the rate of climate zone transition, thereby developing the socioeconomic status of the rural and urban populations. © 2022 Elsevier Ltd
Indicain, a dimeric serine protease from Morus indica cv. K2
(2008) Vijay Kumar Singh; Ashok Kumar Patel; A.J. Moir; Medicherla V. Jagannadham
A high molecular mass serine protease has been purified to homogeneity from the latex of Morus indica cv. K2 by the combination of techniques of ammonium sulfate precipitation, hydrophobic interaction chromatography, and size-exclusion chromatography. The protein is a dimer with a molecular mass of 134.5 kDa and with two monomeric subunits of 67.2 kDa and 67.3 (MALDI-TOF), held by weak bonds susceptible to disruption on exposure to heat and very low pH. Isoelectric point of the enzyme is pH 4.8. The pH and temperature optima for caseinolytic activity were 8.5 and 80 °C, respectively. The extinction coefficient (ε2801 %) of the enzyme was estimated as 41.24 and the molecular structure consists of 52 tryptophan, 198 tyrosine and 42 cysteine residues. The enzyme activity was inhibited by phenylmethylsulfonylflouride, chymostatin and mercuric chloride indicating the enzyme to be a serine protease. The enzyme is fairly stable and similar to subtilases in its stability toward pH, strong denaturants, temperature, and organic solvents. Polyclonal antibodies specific to enzyme and immunodiffusion studies reveal that the enzyme has unique antigenic determinants. The enzyme has activity towards broad range of substrates comparable to those of subtilisin like proteases. The N-terminal residues of indicain (T-T-N-S-W-D-F-I-G-F-P) exhibited considerable similarity to those of other known plant subtilases, especially with cucumisin, a well-characterized plant subtilase. This is the first report of purification and characterization of a subtilisin like dimeric serine protease from the latex of M. indica cv. K2. Owing to these unique properties the reported enzyme would find applications in food and pharma industry. © 2008 Elsevier Ltd. All rights reserved.
Multi-ahead electrical conductivity forecasting of surface water based on machine learning algorithms
(Springer Science and Business Media Deutschland GmbH, 2023) Deepak Kumar; Vijay Kumar Singh; Salwan Ali Abed; Vinod Kumar Tripathi; Shivam Gupta; Nadhir Al-Ansari; Dinesh Kumar Vishwakarma; Ahmed Z. Dewidar; Ahmed A. Al‑Othman; Mohamed A. Mattar
The present research work focused on predicting the electrical conductivity (EC) of surface water in the Upper Ganga basin using four machine learning algorithms: multilayer perceptron (MLP), co-adaptive neuro-fuzzy inference system (CANFIS), random forest (RF), and decision tree (DT). The study also utilized the gamma test for selecting appropriate input and output combinations. The results of the gamma test revealed that total hardness (TH), magnesium (Mg), and chloride (Cl) parameters were suitable input variables for EC prediction. The performance of the models was evaluated using statistical indices such as Percent Bias (PBIAS), correlation coefficient (R), Willmott’s index of agreement (WI), Index of Agreement (PI), root mean square error (RMSE) and Legate-McCabe Index (LMI). Comparing the results of the EC models using these statistical indices, it was observed that the RF model outperformed the other algorithms. During the training period, the RF algorithm has a small positive bias (PBIAS = 0.11) and achieves a high correlation with the observed values (R = 0.956). Additionally, it shows a low RMSE value (360.42), a relatively good coefficient of efficiency (CE = 0.932), PI (0.083), WI (0.908) and LMI (0.083). However, during the testing period, the algorithm’s performance shows a small negative bias (PBIAS = − 0.46) and a good correlation (R = 0.929). The RMSE value decreases significantly (26.57), indicating better accuracy, the coefficient of efficiency remains high (CE = 0.915), PI (0.033), WI (0.965) and LMI (− 0.028). Similarly, the performance of the RF algorithm during the training and testing periods in Prayagraj. During the training period, the RF algorithm shows a PBIAS of 0.50, indicating a small positive bias. It achieves an RMSE of 368.3, R of 0.909, CE of 0.872, PI of 0.015, WI of 0.921, and LMI of 0.083. During the testing period, the RF algorithm demonstrates a slight negative bias with a PBIAS of − 0.06. The RMSE reduces significantly to 24.1, indicating improved accuracy. The algorithm maintains a high correlation (R = 0.903) and a good coefficient of efficiency (CE = 0.878). The index of agreement (PI) increases to 0.035, suggesting a better fit. The WI is 0.960, indicating high accuracy compared to the mean value, while the LMI decreases slightly to − 0.038. Based on the comparative results of the machine learning algorithms, it was concluded that RF performed better than DT, CANFIS, and MLP. The study recommended using the current month’s total hardness (TH), magnesium (Mg), and chloride (Cl) parameters as input variables for multi-ahead forecasting of electrical conductivity (ECt+1, ECt+2, and ECt+3) in future studies in the Upper Ganga basin. The findings also indicated that RF and DT models had superior performance compared to MLP and CANFIS models. These models can be applied for multi-ahead forecasting of monthly electrical conductivity at both Varanasi and Prayagraj stations in the Upper Ganga basin. © 2023, The Author(s).
Novel Genetic Algorithm (GA) based hybrid machine learning-pedotransfer Function (ML-PTF) for prediction of spatial pattern of saturated hydraulic conductivity
(Taylor and Francis Ltd., 2022) Vijay Kumar Singh; Kanhu Charan Panda; Atish Sagar; Nadhir Al-Ansari; Huan-Feng Duan; Pradosh Kumar Paramaguru; Dinesh Kumar Vishwakarma; Ashish Kumar; Devendra Kumar; P.S. Kashyap; R.M. Singh; Ahmed Elbeltagi
Saturated hydraulic conductivity (Ks) is an important soil characteristic that controls water moves through the soil. On the other hand, its measurement is difficult, time-consuming, and expensive; hence Pedotransfer Functions (PTFs) are commonly used for its estimation. Despite significant development over the years, the PTFs showed poor performance in predicting Ks. Using Genetic Algorithm (GA), two hybrid Machine Learning based PTFs (ML-PTF), i.e. a combination of GA with Multilayer Perceptron (MLP-GA) and Support Vector Machine (SVM-GA), were proposed in this study. We compared the performances of four machine learning algorithms for different sets of predictors. The predictor combination containing sand, clay, Field Capacity, and Wilting Point showed the highest accuracy for all the ML-PTFs. Among the ML-PTFs, the SVM-GA algorithm outperformed the rest of the PTFs. It was noticed that the SVM-GA PTF demonstrated higher efficiency than the MLP-GA algorithm. The reference model for hydraulic conductivity prediction was selected as the SVM-GA PTF paired with the K-5 predictor variables. The proposed PTFs were compared with 160 models from past literature. It was found that the algorithms advocated were an improvement over these PTFs. The current model would help in efficient spatio-temporal measurement of hydraulic conductivity using pre-available databases. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PHASE TRANSFORMATION STUDIES ON Fe-Co-Sn ALLOYS.
(1985) Vijay Kumar Singh; Mrityunjaya Singh; Suraj Bhan
Phase transformations in (FeCo)//7//5Sn//2//5 alloys have been studied by X-ray diffraction, scanning electron microscopy and hardness measurements. The phases in the quenched alloys are alpha -Fe(Sn), Fe//1//. //3 Sn, Fe//3Sn//2, Co//3Sn//2 and alpha -Co(Sn). The lattice constants have been determined. Preliminary diffraction studies have indicated the necessity of reinvestigation of high temperature phase equilibria.
Purification and characterization of a new chitinase from latex of Ipomoea carnea
(2010) Ashok Kumar Patel; Vijay Kumar Singh; Ravi Prakash Yadav; Arthur J.G. Moir; Medicherla. V. Jagannadham
A novel enzyme with endochitinase/lysozyme activity was purified to homogeneity from latex of Ipomoea carnea subsp. fistulosa using latex collection, gum removal, ammonium sulphate precipitation, hydrophobic interaction, and anion exchange chromatography. The enzyme was glycosylated (5-6%) and homogeneous on SDS-PAGE; has a molecular mass of 30.06 kDa (MALDI-TOF) and an isoelectric point of pH 4.6. The enzyme exhibited chitinase activity for hydrolysis of glycol chitin and the chitinolytic activity was significantly inhibited by allosamidin and mercuric chloride. The enzyme is stable in the pH range of 4.0-9.5, 80 °C and the optimal activity was observed at pH 5.5 and 50 °C. The enzyme consists of 8 tryptophan, 14 tyrosine, 6 cysteine residues forming three disulfide bridges and the extinction coefficient was estimated as 21.35 M-1 cm-1. The polyclonal antibody was raised in rabbit and immunodiffusion suggests that the antigenic determinants are unique. The first 15 N-terminal residues G-E-I-T-I-Y-W-G-Q-N-G-F-E-G-S exhibited high identity to other known plant chitinases. Owing to the economic purification, high yield, unique and extraordinary features, stability and behavior; the enzyme ICChII can be widely employed in agriculture, industry, environmental protection, and in recycling chitinous waste from arthropod shellfish and for chito-oligosaccharide production. © 2010 Elsevier Ltd. All rights reserved.
Rainfall-runoff modeling using artificial neural networks (ANNs) and multiple linear regression (MLR) techniques
(Ecological Society of India, 2016) Vijay Kumar Singh; Pravendra Kumar; Bhaskar Pratap Singh
Runoff prediction has an important role in hydrology, water management, flood prediction and socio-economical concern. The effective flood management is always of great apprehension in the field of hydrology and water resources engineering. The present study shows the comparison of various training algorithms available for training multi-layer perceptron (MLP) in artificial neural networks (ANNs) and multiple linear regressions (MLR) for modeling the rainfall-runoff process. Gamma test (GT) is one of the non-linear modeling tools whereby an appropriate combination from input parameters can be investigated for modeling the output data as well as establishing a smooth model, to develop and evaluate the applicability of the MLP and MLR models by way of training and testing of developed models during monsoon period (June to September). The ANN models were trained using multi-layer perceptron with various types of algorithm namely Momentum, Quickprop, Delta-Bar-Delta, Conjugate Gradient and Levenberg Marquardt. The performance of the models were evaluated qualitatively by visual observation and quantitatively using different performance indices viz. root mean square error (RMSE), correlation coefficient (r), coefficient of efficiency (CE).