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Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India

Journal of Rock Mechanics and Geotechnical engineering 2024年第8期16卷 2879-2893页

作者： Mukul Sharma Bhanwar Singh Choudhary Autar K.Raina Manoj Khandelwal Saurav Rukhiyar department of Mining engineering Indian Institute of Technology(ISM)Dhanbad826004India CSIR-Central institute of Mining and Fuel Research Nagpur Research Center(Mining Technology)Nagpur440006India institute of Innovation Science and SustainabilityFederation University AustraliaBallaratVIC3350Australia

Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading *** condition,known as hot-hole blasting,is dangerous due to the increased possibility of premature explosions in loaded ***,it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of ***,it will help achieve the desired fragment *** study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery *** on blast design,rock mass,and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational *** coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute error(MAE),mean square error(MSE),variance account for(VAF)and coefficient of efficiency in percentage(CE)were calculated to validate the *** indicates that the random forest algorithm(RFA)outperforms the artificial neural network(ANN),response surface method(RSM),and decision tree(DT).The values of R^(2),RMSE,MAE,MSE,VAF,and CE for RFA are 0.94,0.034,0.027,0.001,93.58,and 93.01,*** parametric sensitivity analyses(MPSAs)of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment *** analysis was finally used to define the best blast design variables to achieve optimum fragment size from *** optimum factor values for RFA of S/B,ld/B and ls/ld are 1.03,1.85 and 0.7,respectively.

关键词： Fiery seam Rock fragmentation Response Surface Method(RSM) Artificial Neural Network(ANN) Random Forest Algorithm(RFA) Multiple Parametric Sensitivity Analysis (MPSA)

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Typhoon-and pollution-driven enhancement of reactive bromine in the mid-latitude marine boundary layer

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National science Review 2024年第4期11卷 93-101页

作者： Shanshan Wang Qinyi Li Ruifeng Zhang Anoop Sharad Mahajan Swaleha Inamdar Nuria Benavent Sanbao Zhang Ruibin Xue Jian Zhu Chenji Jin Yan Zhang Xiao Fu Alba Badia Rafael P.Fernandez Carlos A.Cuevas Tao Wang Bin Zhou Alfonso Saiz-Lopez Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3) Department of Environmental Science and Engineering Fudan University institute of Eco-Chongming(IEC) department of Atmospheric Chemistry and Climate Institute of Physical Chemistry Blas CabreraCSIC department of Civil and Environmental engineering The Hong Kong Polytechnic University Environment Research institute Shandong University Centre for Climate Change Research Indian Institute of Tropical MeteorologyMinistry of Earth Sciences department of Chemistry University of Colorado Boulder institute of Environment and Ecology Tsinghua Shenzhen International Graduate SchoolTsinghua University Sostenipra Research Group Institute of Environmental Science and Technology(ICTA)Universitat Autonoma de Barcelona(UAB) institute for Interdisciplinary science (ICB) National Research Council (CONICET)

Tropospheric reactive bromine is important for atmospheric chemistry,regional air pollution,and global *** studies have reported measurements of atmospheric reactive bromine species in different environments,and proposed their main sources,***-salt aerosol（SSA）,oceanic biogenic activity,polar snow/ice,and *** and other strong cyclonic activities（***） induce abrupt changes in different earth system processes,causing widespread destructive ***,the role of typhoons in regulating reactive bromine abundance and sources remains ***,we report field observations of bromine oxide（BrO）,a critical indicator of reactive bromine,on the Huaniao Island（HNI）in the East China Sea in July *** observed high levels of BrO below 500 m with a daytime average of9.7±4.2 pptv and a peak value of ～26 pptv under the influence of a *** field measurements,supported by model simulations,suggest that the typhoon-induced drastic increase in wind speed amplifies the emission of SSA,significantly enhancing the activation of reactive bromine from SSA *** also detected enhanced BrO mixing ratios under high NOxconditions（ppbv level） suggesting a potential pollution-induced mechanism of bromine release from *** elevated levels of atmospheric bromine noticeably increase ozone destruction by as much as ～40% across the East China *** the high frequency of cyclonic activity in the northern hemisphere,reactive bromine chemistry is expected to play a more important role than previously thought in affecting coastal air quality and atmospheric oxidation *** suggest that models need to consider the hitherto overlooked typhoon-and pollution-mediated increase in reactive bromine levels when assessing the synergic effects of cyclonic activities on the earth system.

关键词： reactive bromine atmospheric chemistry marine boundary layer atmospheric oxidation capacity marine emission

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Multiplexed fluorescence and scatter detection with single cell resolution using on-chip fiber optics for droplet microfluidic applications

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Microsystems & Nanoengineering 2024年第2期10卷 207-218页

作者： Preksha Gupta Ambili Mohan Apurv Mishra Atindra Nair Neeladri Chowdhury Dhanush Balekai Kavyashree Rai Anil Prabhakar Taslimarif Saiyed Discovery Innovation Accelerator Centre for Cellular and Molecular PlatformsBellary RoadBengaluru560065KarnatakaIndia department of Electrical engineering Indian Institute of Technology MadrasChennai600036Tamil NaduIndia

Droplet microfluidics has emerged as a critical component of several high-throughput single-cell analysis techniques in biomedical research and *** significant progress in the development of individual assays,multiparametric optical sensing of droplets and their encapsulated contents has been *** current approaches,most commonly involving microscopy-based high-speed imaging of droplets,are technically complex and require expensive instrumentation,limiting their widespread *** address these limitations,we developed the OptiDrop platform;this platform is a novel optofluidic setup that leverages the principles of flow *** platform enables on-chip detection of the scatter and multiple fluorescence signals from the microfluidic droplets and their contents using optical *** highly customizable on-chip optical fiber-based signal detection system enables simplified,miniaturized,low-cost,multiparametric sensing of optical signals with high sensitivity and single-cell resolution within each *** demonstrate the ability of the OptiDrop platform,we conducted a differential expression analysis of the major histocompatibility complex(MHC)protein in response to IFNγ*** results showed the platform’s ability to sensitively detect cell surface biomarkers using fluorescently labeled ***,the OptiDrop platform combines the versatility of flow cytometry with the power of droplet microfluidics to provide wide-ranging,scalable optical sensing solutions for research and diagnostics.

关键词： scatter enable resolution

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Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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Computer Modeling in engineering & sciences 2024年第2期138卷 1981-2004页

作者： Shaik Mahaboob Basha Victor Hugo Cde Albuquerque Samia Allaoua Chelloug Mohamed Abd Elaziz Shaik Hashmitha Mohisin Suhail Parvaze Pathan department of Electronics and Communication engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India department of Teleinformatics engineering Federal University of CearáFortaleza60455-970Brazil Information Technology department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer science and engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates department of Electrical and Computer engineering Lebanese American UniversityByblos13-5053Lebanon department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India department of Veterinary Clinical sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

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Hopf bifurcation in a delayed prey-predator model with prey refuge involving fear effect

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International Journal of Biomathematics 2024年第5期17卷 1-32页

作者： Ankit Parwaliya Anuraj Singh Ajay Kumar department of Applied sciences ABV-Indian Institute of Information Technology and ManagementGwalior 474015India

This work investigates a prey-predator model featuring a Holling-type II functional response,in which the fear effect of predation on the prey species,as well as prey refuge,are ***,the model assumes that the growth rate of the prey population decreases as a result of the fear of ***,the detection of the predator by the prey species is subject to a delay known as the fear response delay,which is incorporated into the *** paper establishes the preliminary conditions for the solution of the delayed model,including positivity,boundedness and *** paper discusses the existence and stability of equilibrium points in the *** particular,the paper considers the discrete delay as a bifurcation parameter,demonstrating that the system undergoes Hopf bifurcation at a critical value of the delay *** direction and stability of periodic solutions are determined using central manifold and normal form ***,the global stability of the model is established at axial and positive equilibrium *** extensive numerical simulation is presented to validate the analytical findings,including the continuation of the equilibrium branch for positive equilibrium points.

关键词： Hopf bifurcation fear effect prey refuge periodic solutions time delay branch off

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Deep learning models for tuberculosis detection and infected region visualization in chest X-ray images

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Intelligent Medicine 2024年第2期4卷 104-113页

作者： Vinayak Sharma Nillmani Sachin Kumar Gupta Kaushal Kumar Shukla School of Electronics and Communication engineering Shri Mata Vaishno Devi University Jammu and KashmirIndia School of Biomedical engineering Indian Institute of TechnologyBanaras Hindu UniversityVaranasiIndia department of Computer science and engineering Indian Institute of TechnologyBanaras Hindu UniversityVaranasiIndia

Objective Tuberculosis(TB)is among the most frequent causes of infectious-disease-related *** being treatable by antibiotics,tuberculosis often goes misdiagnosed and untreated,especially in rural and low-resource *** X-rays are frequently used to aid diagnosis;however,this presents additional challenges because of the possibility of abnormal radiological appearance and a lack of radiologists in areas where the infection is most *** deep-learning-based imaging techniques for computer-aided diagnosis has the potential to enable accurate diagnoses and lessen the burden on medical *** the present work,we aimed to develop deep-learning-based segmentation and classification models for accurate and precise detection of tuberculosis in chest X-ray images,with visualization of infection using gradient-weighted class activation mapping(Grad-CAM)*** First,we trained the UNet segmentation model using 704 chest X-ray radiographs taken from the Montgomery County and Shenzhen Hospital ***,we implemented the trained UNet model on 1,400 tuberculosis and control chest X-ray scans to segment the lung *** images were taken from the National institute of Allergy and Infectious Diseases(NIAID)TB portal program ***,we applied the deep learning Xception model to classify the segmented lung region into tuberculosis and normal *** further investigated the visualization capabilities of the model using Grad-CAM to view tuberculosis abnormalities in chest X-rays and discuss them from radiological *** For segmentation by the UNet model,we achieved accuracy,Jaccard index,Dice coefficient,and area under the curve(AUC)values of 96.35%,90.38%,94.88%,and 0.99,*** classification by the Xception model,we achieved classification accuracy,precision,recall,F1-score,and AUC values of 99.29%,99.30%,99.29%,99.29%,and 0.999,*** Grad-CAM heatmap images from the tuberculos

关键词： Tuberculosis Artificial intelligence Deep learning Segmentation Classification Chest X-ray

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Mechanism of Universal Quantum Computation in the Brain

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Journal of Applied Mathematics and Physics 2024年第2期12卷 468-474页

作者： Aman Chawla Salvatore Domenic Morgera department of Computer science and engineering Indian Institute of Technology Delhi India department of Electrical engineering University of South Florida Tampa USA

In this paper, the authors extend [1] and provide more details of how the brain may act like a quantum computer. In particular, positing the difference between voltages on two axons as the environment for ions undergoing spatial superposition, we argue that evolution in the presence of metric perturbations will differ from that in the absence of these waves. This differential state evolution will then encode the information being processed by the tract due to the interaction of the quantum state of the ions at the nodes with the “controlling’ potential. Upon decoherence, which is equal to a measurement, the final spatial state of the ions is decided and it also gets reset by the next impulse initiation time. Under synchronization, several tracts undergo such processes in synchrony and therefore the picture of a quantum computing circuit is complete. Under this model, based on the number of axons in the corpus callosum alone, we estimate that upwards of 50 million quantum states might be prepared and evolved every second in this white matter tract, far greater processing than any present quantum computer can accomplish.

关键词： Axons Quantum computation Metric perturbation Decoherence Time-coded information

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Characterization and Propagation of Historical and Projected Droughts in the Umatilla River Basin, Oregon, USA

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Advances in Atmospheric sciences 2024年第2期41卷 247-262,I0020-I0028页

作者： Sudip GAUTAM Alok SAMANTARAY Meghna BABBAR-SEBENS Meenu RAMADAS School of Civil and Construction engineering Oregon State UniversityCorvallisOR 97331USA School of Infrastructure Indian Institute of TechnologyBhubaneswarOdisha 752050India

Climate change is expected to have long-term impacts on drought and wildfire risks in Oregon as summers continue to become warmer and drier. This paper investigates the projected changes in drought characteristics and drought propagation in the Umatilla River Basin in northeastern Oregon for mid-century(2030–2059) and late-century(2070–2099) climate scenarios. Drought characteristics for projected climates were determined using downscaled CMIP5 climate datasets from ten climate models and Soil and Water Assessment Tool to simulate effects on hydrologic processes. Short-term(three months) drought characteristics(frequency, duration, and severity) were analyzed using four drought indices, including the Standardized Precipitation Index(SPI-3), Standardized Precipitation-Evapotranspiration Index(SPEI-3), Standardized Streamflow Index(SSI-3), and the Standardized Soil Moisture Index(SSMI-3). Results indicate that short-term meteorological droughts are projected to become more prevalent, with up to a 20% increase in the frequency of SPI-3drought events. Short-term hydrological droughts are projected to become more frequent(average increase of 11% in frequency of SSI-3 drought events), more severe, and longer in duration(average increase of 8% for short-term droughts).Similarly, short-term agricultural droughts are projected to become more frequent(average increase of 28% in frequency of SSMI-3 drought events) but slightly shorter in duration(average decrease of 4%) in the future. Historically, drought propagation time from meteorological to hydrological drought is shorter than from meteorological to agricultural drought in most sub-basins. For the projected climate scenarios, the decrease in drought propagation time will likely stress the timing and capacity of water supply in the basin for irrigation and other uses.

关键词： Umatilla drought SPI SPEI SSI SSMI

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Maximizing Solar Potential Using the Differential Grey Wolf Algorithm for PV System Optimization

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Energy engineering 2024年第8期121卷 2129-2142页

作者： Ezhilmathi Nagarathinam Buvana Devaraju Karthiyayini Jayamoorthy Padmavathi Radhakrishnan Santhana Lakshmi ChandraMohan Vijayakumar Perumal Karthikeyan Balakrishnan department of Electrical and Electronics engineering Pandian Saraswathiyadav Engineering CollegeSivagangaiTamil Nadu630561India department of Electrical and Electronics engineering Sri Balaji Chockalingam Engineering CollegeArniTamil Nadu632317India department of Information science and engineering New Horizon College of EngineeringBangalore560103India department of Electrical and Electronics engineering Rajalakshmi Engineering CollegeChennaiTamil Nadu602105India department of Electrical and Electronics engineering Sona College of TechnologySalemTamil Nadu636005India School of Electronics engineering Vellore Institute of TechnologyChennaiTamil Nadu600127India department of Electrical and Electronics engineering Sri Krishna College of Engineering and TechnologyCoimbatoreTamil Nadu641008India

Maximum Power Point Tracking(MPPT)is crucial for maximizing the energy output of photovoltaic(PV)systems by continuously adjusting the operating point of the panels to track the point of maximum power production under changing environmental *** work proposes the design of an MPPT system for solar PV installations using the Differential Grey Wolf Optimizer(DGWO).It dynamically adjusts the parameters of the MPPT controller,specifically the duty cycle of the SEPIC converter,to efficiently track the Maximum Power Point(MPP).The proposed system aims to enhance the energy harvesting capability of solar PV systems by optimizing their performance under varying solar irradiance,temperature and shading *** results demonstrate the effectiveness of the DGWO-based MPPT system in maximizing the power output of solar PV installations compared to conventional MPPT *** research contributes to the development of advanced MPPT techniques for improving the efficiency and reliability of solar energy systems.

关键词： DGWO SEPIC converter MPPT PV module

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Axonal Conduction Velocity: A Computer Study

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Journal of Applied Mathematics and Physics 2024年第1期12卷 60-71页

作者： Arthur D. Snider Aman Chawla Salvatore D. Morgera department of Electrical engineering University of South Florida Tampa USA department of Computer science and engineering Indian Institute of Technology New Delhi India

This paper derives rigorous statements concerning the propagation velocity of action potentials in axons. The authors use the Green’s function approach to approximate the action potential and find a relation between ... 详细信息

关键词： Neuron Axon Action Potential Conduction Velocity Internode

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