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Assessment of active tectonics from geomorphic indices and morphometric parameters in part of Ganga basin

Journal of Mountain Science 2019年第8期16卷 1943-1961页

作者： aditya kumar anand Sarada Prasad PRADHAN Department of Earth Sciences Indian Institute of Technology Roorkee

Ganga river basins exposed to active erosional and deformational processes. The recurrence of landslides, floods, and seismic activities makes it more susceptible to deformational activities. The tectonic analysis using geomorphic indices and morphometric parameters will help in determining the hazard-prone area of the river basin. Geomorphic indices and morphometric parameters are calculated to investigate the role of neotectonic activities, as it acts as a controlling factor in the development of landforms in the tectonically active terrains. Neotectonic activities influence the terrain topography, which significantly affects the drainage system and geomorphological setup of the area. In this study, the assessment of active tectonics of study area was determined using Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER) Global Digital Elevation Model(GDEM) based on Geomorphic Indices(Stream Length Gradient index, Hypsometric integral, Asymmetry factor, Basin shape, Valley floor width to Valley height ratio, Mountain front sinuosity index) cumulatively with Linear, Areal and Relief morphometric parameters on 27 delineated basins of the study area. The combined classification of Relative Tectonic Activity Index(Iat) and morphometric parameters of 27 basins categorized all the zones into four different classes:Class 1 – Very High(2.21;299 km^2). The basins with tectonic activities have a consistent relationship with structural disturbances, basin geometry, and field studies. The tectonically active zonation of a part of Ganga basin using geomorphic indices and morphometric parameters suggest that it has significant influence of neotectonic activities in a part of Ganga basin.

关键词： Linear parameters Areal parameters Relief parameters Geomorphic Indices Relative Tectonic Activity Index Ganga river basins

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Electrochemical sensor for dopamine detection based on multiwalled carbon nanotube/molybdenum disulfide quantum dots with machine learning integration and anti-interference capability

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Tungsten 2025年第1期7卷 137-151页

作者： Geethukrishnan Onkar Apte Kiran kumar Tadi Energy Electrodics and Electrocatalysis (EEE) Lab Department of Chemistry School of Advanced Sciences Vellore Institute of Technology School of Computer Science and Engineering Vellore Institute of Technology

The precise detection and measurement of dopamine（DA）,a crucial neurotransmitter in the human body,plays a significant role in diagnosing,preventing,and treating neurological diseases associated with its levels.A highly sensitive DA electrochemical sensor was constructed by combining molybdenum disulfide quantum dots（MSQDs） with multiwalled carbon nanotubes（MWCNTs）.The MSQDs were synthesized using the shear exfoliation *** sensors consist of MSQDs with Mo-S edge catalytic centers for the DA redox reaction,and MWCNTs amplify the sensor *** linearity of the sensor for the detection of DA was tested in the presence of ascorbic acid(AA,50 μmol·L-1) and uric acid(UA,200 μmol·L-1),and exhibited linearity from 2 to 966 μmol·L-1of DA with 0.097 μA(mol·L-1)-1sensitivity and a low limit of detection of0.6 μmol·L-1（the ratio between signal and noise,S/N=3）.Moreover,the sensitivity and selectivity of the sensor were also studied using *** is no increase in amperometric current after adding the most potentially interfering *** sensor was successfully applied to recover DA in human blood sera ***,machine learning algorithms were operated to aid in the near-precise detection of DA in the heterogeneous mixture containing AA and *** algorithms facilitate the identification and quantification of DA amidst coexisting interferents,including AA,that are commonly present in biological matrices.

关键词： Biosensor Complex mixture Dopamine Machine learning MoS2 Multiwalled carbon nanotubes

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Translocator protein and neurodegeneration: insights from Alzheimer’s disease

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Neural Regeneration Research 2025年第4期20卷 1090-1091页

作者： Arpit kumar Pradhan Rainer Rupprecht Gerhard Rammes Klinik für Anaesthesiologie und Intensivmedizin der Technischen Universität München Klinikum rechts der IsarMunichGermany Graduate School of Systemic Neurosciences Ludwig-Maximilians-Universität MünchenMartinsriedGermany Department of Psychiatry and Psychotherapy University RegensburgRegensburgGermany

The 18 kDa translocator protein(TSPO)located on the outer mitochondrial membrane regulates several key cellular processes including mitochondrial homeostasis,cholesterol transport,apoptosis,cell proliferation,and maintenance of mitochondrial health(Rupprecht et al.,2022,2023).TSPO is expressed in both peripheral organs and the central nervous system,with a more pronounced expression in tissues that produce *** main reason why TSPO has garnered so much attention is because it plays a key role in neurosteroidogenesis by transferring cholesterol from the outer to the inner mitochondrial membrane,which is the rate-limiting step in neurosteroid synthesis.A cholesterol-recognizing amino acid consensus domain has been identified in the cytosolic C terminus of the TSPO protein by both in vitro and site-directed mutagenesis experiments(Li et al.,2001).However,the role of TSPO in the process of neurosteroid synthesis has been challenged by several studies,particularly TSPO knockout models,which suggest that TSPO removal does not affect the phenotype or the system’s viability(Tu et al.,2014).However,ligands targeting TSPO have been shown to enhance levels of neurosteroids which suggests that neurosteroidogenesis is one of the major functional roles mediated by the TSPO protein.

关键词： cholesterol organs

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Determining the relationship between chemical composition and size, shape and effective density of airborne fine particles through concurrent use of inertial and optical based measurements

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Particuology 2016年第5期14卷 93-101页

作者： anand kumar Tarun Gupta Environmental Engineering and Management Program Indian Institute of Technology Kanpur Kanpur 208016 India Institute of Atmospheric and Climate Science Swiss Federal Institute of Technology Zurich Zurich 8092 Switzerland Department of Civil Engineering Indian Institute of Technology Kanpur Kanpur 208016 India

This study presents the development of a medium flow, multiple slit based PM2.5 （particle aerodynamic diameter 〈2.5 μm） inertial impactor. Its performance was compared with that of a light scattering based optical particle sizer in a field study and in controlled lab based experiments using polydisperse dolomite powder as test aerosol. The impactor＇s optimum nozzle configuration had a cutoff size of 2.51 μm （aero- dynamic diameter） at an operating flow rate of 215 L/rain with a pressure drop of 0.35 kPa across the impactor stage. Because the apparent particle density of an ambient aerosol depends on the physical properties and the chemical composition of the particles, the PM2.5 mass concentration was measured with an optical particle sizer and an inertial impactor over a weekday and a weekend day in a field study during which the effective particle shape factor and density were in tandem modified in order to com- pare the results from the two sampling techniques. The correlation of the two instrument results tended towards 1：1 with increasing values of shape factor （irregular shaped） and effective particle density. This observation was supported through chemical investigations of the collected mass, which showed a higher percentage contribution from elements which are mostly of crustal nature （namely, Ca, Fe, and Mg）.

关键词： lmpactor PM2.5 Optical particle counter Effective particle density Shape factor

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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit kumar Dutta Yousef Ibrahim Daradkeh Department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

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Market Drivers in India’s Smart Grid:Responsibilities and Roles of Stakeholders

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Energy Engineering 2025年第1期122卷 101-128页

作者： Abhay Sanatan Satapathy Suresh kumar Sahoo Asit Mohanty Yasser Fouad Manzoore ElahiMohammad Soudagar Erdem Cuce Faculty of Management Studies Sri Sri UniversityCuttack754006India Institute of Power Engineering National Energy UniversityJalan Ikram-UnitenKajangSelangor43000Malaysia Centre of Research Impact and Outcome Chitkara UniversityRajpura140417PunjabIndia Department of Applied Mechanical Engineering College of Applied EngineeringMuzahimiyah BranchKing Saud UniversityRiyadh11421Saudi Arabia College of Engineering Lishui UniversityLishui323000China Department of Mechanical Engineering Graphic Era(Deemed to be University)Dehradun248002UttarakhandIndia Department of Mechanical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia Department of Mechanical Engineering Faculty of Engineering and ArchitectureRecep Tayyip Erdogan UniversityZihni Derin CampusRize53100Turkey Center for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia

The emergence of smart grids in India is propelled by an intricate interaction of market dynamics,regulatory structures,and stakeholder *** study analyzes the primary factors that are driving the widespread use of smart grid technologies and outlines the specific roles and obligations of different stakeholders,such as government entities,utility companies,technology suppliers,and *** activities and regulations are crucial in facilitating the implementation of smart grid technology by offering financial incentives,regulatory assistance,and strategic *** firms have the responsibility of implementing and integrating smart grid infrastructure,with an emphasis on improving the dependability of the grid,minimizing losses in transmission and distribution,and integrating renewable energy *** companies offer the essential hardware and software solutions,which stimulate creativity and enhance *** actively engage in the energy ecosystem by participating in demand response,implementing energy saving measures,and adopting distributed energy resources like solar panels and electric *** study examines the difficulties and possibilities in India’s smart grid industry,highlighting the importance of cooperation among stakeholders to build a strong,effective,and environmentally friendly energy future.

关键词： Smart grid stakeholders smart grid technology market drivers

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Thermoelastic waves in a fractional-order initially stressed micropolar diffusive porous medium

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Journal of Ocean Engineering and Science 2021年第4期6卷 376-388页

作者： anand kumar Yadav Shishu Niketan Model Senior Secondary School Sector 22-DChandigarhIndia

The research article is the analysis of wave propagation in an initially stressed micropolar fractional-order derivative thermoelastic diffusion medium with *** governing equations in the context of generalized fractional-order derivative thermo-elasticity are formulated and the velocity equations are *** plane wave solution of these equations indicates the existence of six plane waves,namely coupled longitudinal displacement(cL),coupled thermal(cT),coupled mass diffusion(cMD),coupled longitudinal void volume fraction(cV),coupled transverse displacement(cT D),and coupled transverse micro-rotational(cT M)*** sets of coupled waves(cL),(cT),(cMD)and(cV)are found to be dis-persive,attenuating and influenced by the presence of thermal,diffusion and voids parameters in the *** speeds of coupled transverse displacement(cT D),and coupled transverse micro-rotational(cT M)waves are not affected by thermal,diffusion and void *** speeds of the plane waves,cL,cT,cMD,and cV are computed for a particular material and plotted against the thermal parameter,fre-quency,initial stress,diffusion and void parameters.

关键词： Micropolar Thermodiffusion Void Fractional-order thermoelasticity Initial stress Plane-wave

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Software design pattern mining using classification-based techniques

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Frontiers of Computer Science 2018年第5期12卷 908-922页

作者： Ashish kumar DWIVEDI anand TIRKEY Santanu kumar RATH Department of Computer Science and Engineering National Institute of Technology Rourkela 769008 India

Design patterns are often used in the development of object-oriented software. It offers reusable abstract information that is helpful in solving recurring design problems. Detecting design patterns is beneficial to the comprehension and maintenance of object-oriented software systems. Several pattern detection techniques based on static analysis often encounter problems when detecting design patterns for identical structures of patterns. In this study, we attempt to detect software design patterns by using software metrics and classification-based techniques. Our study is conducted in two phases： creation of metrics-oriented dataset and detection of software design patterns. The datasets are prepared by using software metrics for the learning of classifiers. Then, pattern detection is performed by using classification-based techniques. To evaluate the proposed method, experiments are conducted using three open source software programs, JHotDraw, QuickUML, and JUnit, and the results are analyzed.

关键词： design patterns design pattern mining machinelearning techniques object-oriented metrics

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Sliding mode controller design for frequency regulation in an interconnected power system

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Protection and Control of Modern Power Systems 2021年第1期6卷 77-88页

作者： anand kumar Md Nishat Anwar Shekhar kumar Department of Electrical Engineering National Institute of Technology PatnaPatnaBiharIndia

In this paper, a Sliding mode controller design method for frequency regulation in an interconnected power system is presented. A sliding surface having four parameters has been selected for the load frequency control (LFC) system model. In order to achieve an optimal result, the parameter of the controller is obtained by grey wolf optimization (GWO) and particle swarm optimization (PSO) techniques. The objective function for optimization has been considered as the integral of square of error of deviation in frequency and tie-line power exchange. The method has been validated through simulation of a single area as well as a multi-area power system. The performance of the Sliding mode controller has also been analyzed for parametric variation and random loading patterns. The performance of the proposed method is better than recently reported methods. The performance of the proposed Sliding mode controller via GWO has 88.91% improvement in peak value of frequency deviation over the method of Anwar and Pan in case study 1 and similar improvement has been observed over different case studies taken from the literature.

关键词： Load frequency control Sliding mode control(SMC) Grey wolf optimization Particle swarm optimization Multi-area power system

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Probing the compound effect of spatially varying intrinsic defects and doping on mechanical properties of hybrid graphene monolayers

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Journal of Materials Science & Technology 2020年第15期47卷 44-58页

作者： Kritesh kumar Gupta Tanmoy Mukhopadhyay aditya Roy Sudip Dey Department of Mechanical Engineering National Institute of Technology SilcharSilcharIndia Department of Aerospace Engineering Indian Institute of Technology KanpurKanpurIndia

Doping in pristine 2 D materials brings about the advantage of modulating wide range of mechanical properties ***,intrinsic defects(such as Stone-Wales and nanopore) in such hybrid materials are inevitable due to complex manu facturing and synthesis *** that,de fects and irregularities can be intentionally induced in a pristine nanostructure for multi-synchronous modulation of various multi-functional *** the case may be,in order to realistically analyse a doped graphene sheet,it is of utmost importance to investigate the compound effect of doping and defects in such 2 D *** we present a molecular dynamics based investigation for probing mechanical properties(such as Young’s modulus,post-elastic behaviour,failure strength and strain)of doped graphene(C14 and Si) coupling the effect of inevitable *** sensitivity of defect and doping are systematically analyzed considering different rational *** study reveals the effects of individual defects and doping along with their possible compounded influences on the failure stress,failure strain,Young’s modulus and constitutive relations beyond the elastic *** detailed mechanical characterization under the practically relevant compound effects would allow us to access the viability of adopting doped graphene in various multifunctional nanoelectromechanical devices and systems in a realistic situation.

关键词： Defect in graphene Doped graphene Defected 2D material Temperature-dependent mechanical properties Spatial sensitivity of defect and doping

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