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International Journal of Oral Science 2010年第1期2卷 45-52页

作者： suneet khandelwal Monica Charlotte Solomon Jaipur Dental College Jaipur Highway Department of Oral Pathology Manipal College of Dental SciencesManipal University

Aim To analyse the cytomorphological features of kerati- nocytes in smears obtained from the oral mucosa of tobacco users and from oral squamous cell carcinoma lesions. Methodology Oral smears were obtained from clinically, normal appearing mucosa of oral squamous cell carcinoma patients （n=20） and from the mucosa of smokers （n=20）, and apparently healthy individuals （n=20） were used as controls. The smears were histochemically stained and cytomorphological assessment of the keratinocytes was carried out. One-way ANOVA （Analysis of Variance） was used for comparing the parameters among multiple groups and Tukey-HSD test was used to compare the mean values between groups. Results The mean nuclear area of keratinocytes from the mucosa of tobacco users was 46 ± 2.57 and that of the oral squamous cell carcinoma lesion was 81.54±4.31. While there was a significant （P=0.001） reduction in the cellular area of keratinocytes from oral squamous cell carcinoma lesion when compared with those from oral smears of tobacco users. Conclusion Cytomorphometric analysis of keratinocytes can serve as a useful adjunct in the early diagnosis of oral squamous cell carcinomas.

关键词： exfoliative cytology cytomorphometry Feulgen stain tobacco users oral cancer

Upper ocean high resolution regional modeling of the Arabian Sea and Bay of Bengal

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Acta Oceanologica Sinica 2019年第5期38卷 32-50页

作者： Dwivedi suneet Mishra Alok Kumar Srivastava Atul K Banerjee Centre of Atmospheric and Ocean Studies and M N Saha Centre of Space Studies University of Allahabad

In this paper, effort is made to demonstrate the quality of high-resolution regional ocean circulation model in realistically simulating the circulation and variability properties of the northern Indian Ocean(10°S–25°N,45°–100°E) covering the Arabian Sea(AS) and Bay of Bengal(BoB). The model run using the open boundary conditions is carried out at 10 km horizontal resolution and highest vertical resolution of 2 m in the upper *** surface and sub-surface structure of hydrographic variables(temperature and salinity) and currents is compared against the observations during 1998–2014(17 years). In particular, the seasonal variability of the sea surface temperature, sea surface salinity, and surface currents over the model domain is studied. The highresolution model's ability in correct estimation of the spatio-temporal mixed layer depth(MLD) variability of the AS and BoB is also shown. The lowest MLD values are observed during spring(March-April-May) and highest during winter(December-January-February) seasons. The maximum MLD in the AS(BoB) during December to February reaches 150 m (67 m). On the other hand, the minimum MLD in these regions during March-April-May becomes as low as 11–12 m. The influence of wind stress, net heat flux and freshwater flux on the seasonal variability of the MLD is discussed. The physical processes controlling the seasonal cycle of sea surface temperature are investigated by carrying out mixed layer heat budget analysis. It is found that air-sea fluxes play a dominant role in the seasonal evolution of sea surface temperature of the northern Indian Ocean and the contribution of horizontal advection, vertical entrainment and diffusion processes is small. The upper ocean zonal and meridional volume transport across different sections in the AS and BoB is also computed. The seasonal variability of the transports is studied in the context of monsoonal currents.

关键词： Indian Ocean modeling Arabian Sea and Bay of Bengal mixed layer depth transport

High-frequency supercapacitors with phosphorus-doped Ketjen black

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Journal of Energy Chemistry 2023年第7期82卷 464-474,I0010页

作者： Qing Jin Mahima khandelwal Woong Kim Department of Materials Science and Engineering Korea UniversitySeoul 02841Republic of Korea

Compact supercapacitors(SCs)have attracted attention for their great potential to replace bulky aluminum electrolytic capacitors(AECs)in alternating current(AC)line filtering ***,the fabrication of a high-frequency SC is reported using Ketjen black(KB)nanoparticles doped with phosphorus(P)to achieve a high areal capacitance of up to 2.26 mF cm^(-2)along with a high-rate capability,with a phase angle of-80.2°at 120 *** high performance of the phosphorus-doped KB(designated PKB)SC with a 6 M KOH aqueous electrolyte is associated with its increased surface wettability and additional capacitive sites provided by the *** functional theory(DFT)calculations further indicate that the P-doping enhances the interactions between the electrolyte ions and the carbon surface,thus leading to an improved electrochemical *** results suggest that the P-doped carbonbased SC could be highly favored in replacing conventional AECs in various high-frequency electronic devices.

关键词： Phosphorus doping Frequency response Wettability Supercapacitor AC line filtering DFT calculation

Removal and recovery of toxic nanosized Cerium Oxide using eco-friendly Iron Oxide Nanoparticles

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Frontiers of Environmental Science & Engineering 2020年第1期14卷 175-184页

作者： Kanha Gupta Nitin khandelwal Gopala Krishna Darbha Department of Chemical Sciences USER KolkataMohanpurWest BengalPincode 741246India Environmental Nanoscience Laboratory Department of Earth SciencesUSER KolkataMohanpurWest BengalPincode 741246India Center for Climate&Environmental Studies USER KolkataMohanpurWest BengalPincode 741246India

Increasing applications of metal oxide nanoparticles and their release in the natural environment is a serious concern due to their toxic ***,it is essential to have eco-friendly solutions for the remediation of toxic metal oxides in an aqueous *** the present study,eco-friendly Iron Oxide Nanoparticles(IONPs)are synthesized using solvothermal technique and successfully characterized using scanning and transmission electron microscopy(SEM and TEM respectively)and powder X-Ray diffraction(PXRD).These IONPs were further utilized for the remediation of toxic metal oxide nanoparticle,i.e.,*** experiments were also performed in complex aqueous solutions and real water samples to check its applicability in the natural *** study was performed to show *** show that these 200 nm-sized spherical IONPs,as revealed by SEM and TEM analysis,were magnetite(Fe3O4)and contained short-range crystallinity as confirmed from XRD *** experiments show that the composite follows the pseudosecond-order kinetic *** k>0.99 for Langmuir sorption isotherm suggests chemisorption as probable removal mechanism with monolayer sorption of Ce02 NPs on *** than 80%recovery of adsorbed Ce02 NPs through ultrasonication and magnetic separation of reaction precipitate confirms reusability of *** removal%of Ce02 in various synthetic and real water samples was>90%signifying that IONPs are candidate adsorbent for the removal and recovery of toxic metal oxide nanoparticles from contaminated environmental water samples.

关键词： Adsorption toxic metal oxide remediation eco-friendly IONP Iron oxide CeO2 removal

Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algor

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Computers, Materials & Continua 2024年第4期79卷 1727-1755页

作者： Parth khandelwal Harshit Indranil Manna Metallurgical&Materials Engineering Department Indian Institute of TechnologyKharagpurWest Bengal721302India Computer Science&Engineering Department Indian Institute of TechnologyKharagpurWest Bengal721302India Vice Chancellor Office Birla Institute of Technology(BIT)MesraRanchiJharkhand835215India

Metallic alloys for a given application are usually designed to achieve the desired properties by devising experimentsbased on experience, thermodynamic and kinetic principles, and various modeling and simulation ***, the influence of process parameters and material properties is often non-linear and non-colligative. Inrecent years, machine learning (ML) has emerged as a promising tool to dealwith the complex interrelation betweencomposition, properties, and process parameters to facilitate accelerated discovery and development of new alloysand functionalities. In this study, we adopt an ML-based approach, coupled with genetic algorithm (GA) principles,to design novel copper alloys for achieving seemingly contradictory targets of high strength and high electricalconductivity. Initially, we establish a correlation between the alloy composition (binary to multi-component) andthe target properties, namely, electrical conductivity and mechanical strength. Catboost, an ML model coupledwith GA, was used for this task. The accuracy of the model was above 93.5%. Next, for obtaining the optimizedcompositions the outputs fromthe initial model were refined by combining the concepts of data augmentation andPareto front. Finally, the ultimate objective of predicting the target composition that would deliver the desired rangeof properties was achieved by developing an advancedMLmodel through data segregation and data *** examine the reliability of this model, results were rigorously compared and verified using several independentdata reported in the literature. This comparison substantiates that the results predicted by our model regarding thevariation of conductivity and evolution ofmicrostructure and mechanical properties with composition are in goodagreement with the reports published in the literature.

关键词： Machine learning genetic algorithm solid-solution precipitation strengthening pareto front data augmentation

Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors

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International Journal of Mining Science and Technology 2021年第5期31卷 799-812页

作者： Jian Zhou Chao Chen Mingzheng Wang Manoj khandelwal School of Resources and Safety Engineering Central South UniversityChangsha 410083China Bharti School of Engineering Laurentian UniversitySudburyOntarioCanada School of Engineering Information Technology and Physical SciencesFederation University AustraliaBallaratAustralia

Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal *** address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated *** assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual *** corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are *** combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the ***,the established ensemble model is further validated through test samples with 100%*** results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines.

关键词： Coal burst liability(CBL) Unascertained measurement(UM) Analysis hierarchy process Information entropy Synthetic weights Comprehensive evaluation

Recent Developments in Integrated Solar Combined Cycle Power Plants

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Journal of Thermal Science 2020年第2期29卷 298-322页

作者： khandelwal Neelam SHARMA Meeta SINGH Onkar SHUKLA Anoop Kumar Mechanical Engineering Department Amity University Uttar PradeshNoida(U.P.)201313India Mechanical Engineering Department Harcourt Butler Technical UniversityKanpur(U.P.)208002India

Global concern for depleting fossil fuel reserves have been compelling for evolving power generation options using renewable energy sources. The solar energy happens to be a potential source for running the power plants among renewable energy sources. Integrated Solar Combined Cycle(ISCC) power plants have gained popularity among the thermal power plants. Traditional ISCC power plants use Direct Steam Generation(DSG) approach. However, with the DSG method, the ISCC plant’s overall thermal efficiency does not increase significantly due to variations in the availability of solar energy. Thermal Energy Storage(TES) systems when integrated into the solar cycle can address such issues related to energy efficiency, process flexibility, reducing intermittency during non-solar hours. This review work focuses and discusses the developments in various components of the ISCC system including its major cycles and related parameters. The main focus is on CSP technologies, Heat Transfer Fluid(HTF), and Phase Change Material(PCM) used for thermal energy storage. Further, study includes heat enhancement methods with HTF and latent heat storage system. This study will be beneficial to the power plant professionals intending to modify the solar-based Combined Cycle Power Plant(CCPP) and to retrofit the existing Natural Gas Combined Cycle(NGCC) plant with the advanced solar cycle.

关键词： CSP(Concentrated Solar Power) HTF(Heat Transfer Fluid) ISCC(Integrated Solar Combined Cycle) TES(Thermal Energy Storage) PCM(Phase Change Material)

A true triaxial strength criterion for rocks by gene expression programming

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第10期15卷 2508-2520页

作者： Jian Zhou Rui Zhang Yingui Qiu Manoj khandelwal School of Resources and Safety Engineering Central South UniversityChangsha410083China Institute of Innovation Science and SustainabilityFederation University AustraliaBallaratVIC3350Australia

Rock strength is a crucial factor to consider when designing and constructing underground *** study utilizes a gene expression programming(GEP)algorithm-based model to predict the true triaxial strength of rocks,taking into account the influence of rock genesis on their mechanical behavior during the model building process.A true triaxial strength criterion based on the GEP model for igneous,metamorphic and magmatic rocks was obtained by training the model using collected *** to the modified Weibols-Cook criterion,the modified Mohr-Coulomb criterion,and the modified Lade criterion,the strength criterion based on the GEP model exhibits superior prediction accuracy *** strength criterion based on the GEP model has better performance in R2,RMSE and MAPE for the data set used in this ***,the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different *** to the existing strength criterion based on the genetic programming(GP)model,the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength(s1)with intermediate principal stress(s2).Finally,based on the Sobol sensitivity analysis technique,the effects of the parameters of the three obtained strength criteria on the true triaxial strength of the rock are *** general,the proposed strength criterion exhibits superior performance in terms of both accuracy and stability of prediction results.

关键词： Gene expression programming(GEP) True triaxial strength Rock failure criteria Intermediate principal stress

Determination of the effective density and fractal dimension of PM emissions from an aircraft auxiliary power unit

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Journal of Environmental Sciences 2018年第12期30卷 11-18页

作者： Emamode A.Ubogu James Cronly Bhupendra khandelwal Swapneel Roy Low Carbon Combustion Centre University of Sheffield

Gas turbine particulate matter（PM） emissions contribute to air quality degradation and are dangerous to both human health and the environment. Currently, PM mass concentrations determined from gravimetric measurements are the default parameter for gas turbine emissions compliance with PM regulations. The measurement of particle size however, is of significant interest due to its specific effects on health and climate science. The mass concentration can be determined from the number-size distribution measurement but requires the experimental evaluation of effective density of a number of particles to establish the powerlaw relationship. In this study, the effective density of PM emissions from an aircraft Auxiliary Power Unit（APU） with petroleum diesel, conventional aviation fuel（Jet A-1） and a multicomponent surrogate fuel（Banner NP 1014） as combusting fuels have been *** experimental configuration consisting of a Differential Mobility Analyzer, a Centrifugal Particle Mass Analyzer and a Condensation Particle Counter（DMA-CPMA-CPC） was deployed for this purpose. Overall, a decrease in the effective density（220–1900 km-3） with an increase in the particle size was observed and found to depend on the engine operating condition and the type of fuel undergoing combustion. There was a change in the trend of the effective densities between the PM emissions generated from the fuels burnt and the engine operating conditions with increasing particle size.

关键词： Particulate emissions Partiulate size-density analysis Fuel variability

Prediction of flyrock in open pit blasting operation using machine learning method

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International Journal of Mining Science and Technology 2013年第3期23卷 313-316页

作者： Manoj khandelwal M. Monjezi Department of Mining Engineering College of Technology & Engineering Maharana Pratap University of Agriculture and Technology Faculty of Engineering Tarbiat Modares University

Flyrock is one of the most hazardous events in blasting operation of surface mines. There are several empirical methods to predict flyrock. Low performance of such models is due to the complexity of flyrock analysis. Existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict flyrock in blasting operations of Soungun Copper Mine, Iran incorporating rock properties and blast design parameters using support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA), too. Coefficient of determination (CoD) and mean absolute error (MAE) were taken as performance measures. It was found that CoD between measured and predicted flyrock was 0.948 and 0.440 by SVM and MVRA, respectively, whereas MAE between measured and predicted flyrock was 3.11 and 7.74 by SVM and MVRA, respectively.

关键词： Blasting Soungun Copper Mine Flyrock Support vector machine MVRA