Effect of Mechanical Alloying and Sintering Environment on the Crystallographic Evolution, Microstructure, Mechanical and Corrosion Properties of Porous Ti4Al4Co Alloy

Pradeep Singh,Vikas Shrivastava,I. B. Singh,D. P. Mondal 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.6

Three group of porous Ti4Al4Co samples made of (i) unmilled powder and vacuum sintered (S1), (ii) milled powder andvacuum sintered (S2), and (iii) milled powder sintered in open atmosphere (S3) were prepared. Phase change, crystallite sizeand lattice strain variations due to powder milling and sintering were examined by SEM and XRD. To evaluate mechanicalproperty, alloy samples were subjected to the uniaxial compression test. For corrosion analysis, Tafel plot was plotted usingelectrochemical corrosion system in simulated body fluid (SBF) as electrolytic medium. From the obtained results, it wasfound that significant microstructural transformation takes place due to milling and change in sintering atmosphere. SampleS1possessed 139 MPa compressive strength, which was about 48% and 76% higher than samples S2and S3respectively. Corrosion current density for S3was found as 5.5 ± 0.3 μA/cm2 which is 7 and 12 times lower than S2and S1samples.

Phenolic constituents and biological activities of leaf extracts of traditional medicinal plant Plectranthus amboinicus Benth (Lamiaceae)

Pradeep Singh Negi,Sandeep Kumar Gupta,Praveena Bhatt,Gilbert Stanley Joseph,Mandyam Chakravarthy Varadaraj 셀메드 세포교정의약학회 2013 TANG Vol.3 No.4

Plectranthus amboinicus Benth (Lamiaceae) is a medicinal plant native to India, and its leaves are widely used in several traditional medicinal preparations. The purpose of this study was to detect and quantify phenolics present in ethyl acetate and acetone extracts of P. amboinicus leaves, and evaluate their antioxidant, antibacterial, antimutagenic and anticancer activities. The HPLC chromatograms of crude leaf extracts indicated the presence of phenolics like caffeic acid, coumaric acid, rutin, quercetin and gallic acid, which were present in the range of 0.01 - 1.41 mg/g in ethyl acetate and 0.03 - 1.93 mg/g in the acetone extract. The acetone extract showed statistically (p < 0.05) higher antioxidant activity (IC50, 99.59 µg/ml) than ethyl acetate extract (IC50, 149.96 µg/ml). Statistically (p < 0.05) higher antimutagenicity was shown by acetone extract (46.16%) as compare to ethyl acetate extract (12.16%) at 500 µg/plate concentration. The acetone extract showed higher antibacterial activity than ethyl acetate extract, and both the extracts showed highest activity against B. cereus (375 and 625 µg/ml, respectively) and lowest activity against Y. enterocolitica (1000 and 1125 µg/ml, respectively). Both the extracts also showed inhibitory effect on cancer cell lines HCT-15 and MCF-7. These results suggest that the leaves of P. amboinicus possess various biological activities, and validate the traditional use of the leaves of P. amboinicus against cold, infection and ulceration.

Software Fault Prediction at Design Phase

Pradeep Singh,Shrish Verma,O. P Vyas 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.5

Prediction of fault-prone modules continues to attract researcher’s interest due to its significant impact on software development cost. The most important goal of such techniques is to correctly identify the modules where faults are most likely to present in early phases of software development lifecycle. Various software metrics related to modules level fault data have been successfully used for prediction of fault-prone modules. Goal of this research is to predict the faulty modules at design phase using design metrics of modules and faults related to modules. We have analyzed the effect of pre-processing and different machine learning schemes on eleven projects from NASA Metrics Data Program which offers design metrics and its related faults. Using seven machine learning and four preprocessing techniques we confirmed that models built from design metrics are surprisingly good at fault proneness prediction. The result shows that we should choose Naive Bayes or Voting feature intervals with discretization for different data sets as they outperformed out of 28 schemes. Naive Bayes and Voting feature intervals has performed AUC > 0.7 on average of eleven projects. Our proposed framework is effective and can predict an acceptable level of fault at design phases.

Software Fault Prediction at Design Phase

Singh, Pradeep,Verma, Shrish,Vyas, O.P. The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.5

Prediction of fault-prone modules continues to attract researcher's interest due to its significant impact on software development cost. The most important goal of such techniques is to correctly identify the modules where faults are most likely to present in early phases of software development lifecycle. Various software metrics related to modules level fault data have been successfully used for prediction of fault-prone modules. Goal of this research is to predict the faulty modules at design phase using design metrics of modules and faults related to modules. We have analyzed the effect of pre-processing and different machine learning schemes on eleven projects from NASA Metrics Data Program which offers design metrics and its related faults. Using seven machine learning and four preprocessing techniques we confirmed that models built from design metrics are surprisingly good at fault proneness prediction. The result shows that we should choose Naïve Bayes or Voting feature intervals with discretization for different data sets as they outperformed out of 28 schemes. Naive Bayes and Voting feature intervals has performed AUC > 0.7 on average of eleven projects. Our proposed framework is effective and can predict an acceptable level of fault at design phases.

Limited Laminectomy and Restorative Spinoplasty in Spinal Canal Stenosis

Sukhbir Singh Sangwan,Rakesh Garg,Paritosh Gogna,Zile Singh Kundu,Vinay Gupta,Pradeep Kamboj 대한척추외과학회 2014 Asian Spine Journal Vol.8 No.4

Study Design: Prospective cohort study. Purpose: Evaluation of the clinico-radiological outcome and complications of limited laminectomy and restorative spinoplasty in spinal canal stenosis. Overview of Literature: It is critical to achieve adequate spinal decompression, while maintaining spinal stability. Methods: Forty-four patients with degenerative lumbar canal stenosis underwent limited laminectomy and restorative spinoplasty at our centre from July 2008 to December 2010. Four patients were lost to follow-up leaving a total of 40 patients at an average final follow-up of 32 months (range, 24–41 months). There were 26 females and 14 males. The mean±standard deviation (SD) of the age was 64.7±7.6 years (range, 55–88 years). The final outcome was assessed using the Japanese Orthopaedic Association (JOA) score. Results: At the time of the final follow-up, all patients recorded marked improvement in their symptoms, with only 2 patients complaining of occasional mild back pain and 1 patient complaining of occasional mild leg pain. The mean±SD for the preoperative claudication distance was 95.2±62.5 m, which improved to 582±147.7 m after the operation, and the preoperative anterio-posterior canal diameter as measured on the computed tomography scan was 8.3±2.1 mm, which improved to 13.2±1.8 mm postoperatively. The JOA score improved from a mean±SD of 13.3±4.1 to 22.9±4.1 at the time of the final follow-up. As for complications, dural tears occurred in 2 patients, for which repair was performed with no additional treatment needed. Conclusions: Limited laminectomy and restorative spinoplasty is an efficient surgical procedure which relieves neurogenic claudication by achieving sufficient decompression of the cord with maintenance of spinal stability.

A Study on the Drug Classification Using Machine Learning Techniques

Anmol Kumar Singh,Ayush Kumar,Adya Singh,Akashika Anshum,Pradeep Kumar Mallick 중소기업융합학회 2024 산업과 과학 Vol.3 No.2

본 논문에서는 인구통계학적, 생리학적 특성을 기반으로 환자에게 가장 적합한 약물을 예측하는 것을 목표로 하는 약물 분류 시스템을 제시한다. 데이터 세트에는 적절한 약물을 결정하기 위한 목적으로 연령, 성별, 혈압(BP), 콜레스테롤 수치, 나트륨 대 칼륨 비율(Na_to_K)과 같은 속성들이 포함된다. 본 연구에 사용된 모델은 KNN(K-Nearest Neighbors), 로지스틱 회귀 분석 및 Random Forest이다. 하이퍼파라미터를 최적화하기 위해 5겹 교차 검증을 갖춘 GridSearchCV를 활용하였으며, 각 모델은 데이터 세트에서 훈련 및 테스트 되었다. 초매개변수 조정 유무에 관계없이 각 모델의 성능은 정확도, 혼동 행렬, 분류 보고서와 같은 지표를 사용하여 평가되었다. GridSearchCV를 적용하지 않은 모델의 정확도는 0.7, 0.875, 0.975인 반면, GridSearchCV를 적용한 모델의 정확도는 0.75, 1.0, 0.975로 나타났다. GridSearchCV는 로지스틱 회귀 분석을 세 가지 모델 중 약물 분류에 가장 효과적인 모델로 식별했으며, K-Nearest Neighbors가 그 뒤를 이었고 Na_to_K 비율은 결과를 예측하는 데 중요한 특징인 것으로 밝혀졌다. This paper shows the system of drug classification, the goal of this is to foretell the apt drug for the patients based on their demographic and physiological traits. The dataset consists of various attributes like Age, Sex, BP (Blood Pressure), Cholesterol Level, and Na_to_K (Sodium to Potassium ratio), with the objective to determine the kind of drug being given. The models used in this paper are K-Nearest Neighbors (KNN), Logistic Regression and Random Forest. Further to fine-tune hyper parameters using 5-fold cross-validation, GridSearchCV was used and each model was trained and tested on the dataset. To assess the performance of each model both with and without hyper parameter tuning evaluation metrics like accuracy, confusion matrices, and classification reports were used and the accuracy of the models without GridSearchCV was 0.7, 0.875, 0.975 and with GridSearchCV was 0.75, 1.0, 0.975. According to GridSearchCV Logistic Regression is the most suitable model for drug classification among the three-model used followed by the K-Nearest Neighbors. Also, Na_to_K is an essential feature in predicting the outcome.

Hydrogen-Atom Abstraction Reaction of CF₃CH₂OCF₃ by Hydroxyl Radical

Singh, Hari Ji,Mishra, Bhupesh Kumar,Rao, Pradeep Kumar Korean Chemical Society 2010 Bulletin of the Korean Chemical Society Vol.31 No.12

Theoretical investigations are carried out on the title reaction by means of ab-initio and DFT methods. The optimized geometries, frequencies and minimum energy path are obtained at UB3LYP/6-311G(d,p) level. Single point energy calculations are performed at MP2 and MP4 levels of theory. Energetics are further refined by calculating the energy of the species with a modified Gaussian-2 method, G2M(CC,MP2). The rate constant of the reaction is calculated using Canonical Transition State Theory (CTST) utilizing the ab-initio data obtained during the present study and is found to be $5.47{\times}10^{-12}\;cm^3\;molecule^{-1}s^{-1}$ at 298 K and 1 atm.

Enhancing crop health and sustainability: exploring the potential of secondary metabolites and non-thermal plasma treatment as alternatives to pesticides

Singh Himani,Niharika,Lamichhane Pradeep,Gupta Ravi,Kaushik Neha,최은하,Kaushik Nagendra Kumar 한국식물생명공학회 2023 Plant biotechnology reports Vol.17 No.6

Pesticides have been an integral part of modern agriculture as their use ensures good harvests. However, excessive use of pesticides in the last few decades has caused significant environmental degradation. Moreover, excessive use of pesticides causes stress on crops and non-target plants and exhibits toxicity to other organisms including mammals, microbes, and insects. Plants employ various morphological, physiological, and biochemical mechanisms to reduce pesticides toxicity. One such mechanism is production of secondary metabolites that improves stress tolerance of plants. In addition, recent studies have also highlighted a potential role of plasma technology in mitigating various abiotic and biotic environmental stresses. Besides, plasma treatment improves seed germination, physiological processes, and seedling establishment during the early growth stages of a plant under adverse and non-adverse conditions and thus can be used an alternate to the pesticide treatment. This review article summarizes recent advancements in understanding the synthesis, accumulation, and transportation of secondary metabolites which have significant relevance to crop improvement programs. We also present an overview of the effects of plasma treatment on phytopathogenic bacterial cell suspensions and plant responses to metabolic activity. In the future, researchers need to develop innovative ideas to reduce the use of chemical pesticides in farming practices.

Torque Ripples Minimization of DTC IPMSM Drive for the EV Propulsion System using a Neural Network

Singh, Bhim,Jain, Pradeep,Mittal, A.P.,Gupta, J.R.P. The Korean Institute of Power Electronics 2008 JOURNAL OF POWER ELECTRONICS Vol.8 No.1

This paper deals with a Direct Torque Control (DTC) of an Interior Permanent Magnet Synchronous Motor (IPMSM) for the Electric Vehicle (EV) propulsion system using a Neural Network (NN). The Conventional DTC with optimized switching lookup table and three level torque controller generates relatively large torque ripples in an electric vehicle motor drive. For reducing the torque ripples, a three level torque controller is hereby replaced by the five level torque controller. Furthermore, the switching lookup table of the five level torque controller based DTC is replaced with a Neural Network. These DTC schemes of an IPMSM drive are simulated using MATLAB/SIMULINK. The simulated results are compared with the conventional DTC and it is found that the ripples in the torque, as well as in the stator current, are reduced drastically.

Synergistic effect of polypyrrole/BST/RGO/Fe3O4 composite for enhanced microwave absorption and EMI shielding in X-Band

Pradeep Sambyal,S.K. Dhawan,Preeti Gairola,Sampat Singh Chauhan,S.P. Gairola 한국물리학회 2018 Current Applied Physics Vol.18 No.5

Present study focus on the designing of high performance microwave absorbing material against electromagnetic pollution. Herein we synthesize conducting polymer based composite encapsulated with Barium strontium titanate (BST), reduced graphene oxide (RGO), and Fe3O4 nanoparticles via chemical oxidative polymerization of pyrrole. The synthesized composite materials were thoroughly characterized using SEM, FTIR, XRD, TGA, and VSM techniques. The presence of filler materials in conducting polymer matrix leads to absorption dominated shielding effectiveness value of 48 dB in the frequency range of 8.2–12.4 GHz (X-band). Moreover, presence of dielectric and magnetic fillers increases the thermal and chemical stability of the composite material. The obtained shielding effectiveness value is above the recommended limit (30–40 dB) required for the commercial applications, therefore these composite material could be used as effective shield against EM pollution.