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Surviving the odds: From perception to survival of fungal phytopathogens under host-generated oxidative burst

Plant Communications 2021年第3期2卷 38-54页

作者： yeshveer singh Athira Mohandas Nair Praveen Kumar Verma Plant Immunity Laboratory National Institute of Plant Genome ResearchAruna Asaf Ali MargNew Delhi 110067India School of Life Sciences Jawaharlal Nehru UniversityNew Delhi 110067India

Fungal phytopathogens pose a serious threat to global crop *** a handful of strategies are available to combat these fungal infections,and the increasing incidence of fungicide resistance is making the situation ***,the molecular understanding of plant–fungus interactions remains a primary focus of plant *** of the hallmarks of host–pathogen interactions is the overproduction of reactive oxygen species(ROS)as a plant defense mechanism,collectively termed the oxidative *** general,high accumulation of ROS restricts the growth of pathogenic organisms by causing localized cell death around the site of *** survive the oxidative burst and achieve successful host colonization,fungal phytopathogens employ intricate mechanisms for ROS perception,ROS neutralization,and protection from ROS-mediated ***,these countermeasures maintain the physiological redox homeostasis that is essential for cell *** addition to intracellular antioxidant systems,phytopathogenic fungi also deploy interesting effector-mediated mechanisms for extracellular ROS *** aspect of plant–pathogen interactions is significantly under-studied and provides enormous scope for future *** adaptive responses,broadly categorized into“escape”and“exploitation”mechanisms,are poorly *** this review,we discuss the oxidative stress response of filamentous fungi,their perception signaling,and recent insights that provide a comprehensive understanding of the distinct survival mechanisms of fungal pathogens in response to the host-generated oxidative burst.

关键词： reactive oxygen species(ROS) oxidative stress response fungal effectors stress signaling plant-pathogen interactions

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The dynamic effects of solar eclipses of October 25,2022,and October 14,2023,on GPS-derived total electron content

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Geodesy and Geodynamics 2025年第1期16卷 75-86页

作者： Vishal Chauhan Vishakha Rakesh singh Shishupal singh Vikram singh Om Prakash singh Department of Physics Graphic Era Hill University Department of Petroleum Engineering Graphic Era (Deemed to be University) Department of Physics St.John's College Department of Applied Sciences & Humanities Institute of Engineering & Technology

This study analyzes total electron content(TEC) variations during two solar eclipse events that occurred on October 25, 2022, and October 14, 2023. The solar eclipse of October 25, 2022, was a partial solar eclipse, while the eclipse of October 14, 2023, was an annular solar eclipse. For this study, the data of eight International GNSS Service(IGS) stations from different eclipse coverage zones are used to analyze TEC variations. It is found that the stations located in the maximum eclipse cover zone exhibited notable decreases in TEC values. The minimum variation of about 11.76% in TEC values is observed at the station situating in about 20 percent eclipse cover zone, while it varies from 22% to 38% at the stations falling in about 60 percent eclipse cover zone. The highest variation in TEC values of about 44% is found at the stations in about 80 percent eclipse cover zone. The time of occurrence of maximum depletion in TEC values at each station is in line with their longitudinal sequence. Atmospheric gravity waves(AGWs) are also observed by performing wavelet analysis on TEC data. The global TEC maps visualize and confirm observed TEC variations, providing spatial and temporal insights into the ionospheric response. This analysis highlights the influence of station location and eclipse coverage on the magnitude and spatial distribution of TEC variations.

关键词： Solar eclipse Ionosphere GPS TEC AGW

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Effect of Eu-Er substitution on structural,optical,dielectric,and electrical properties of Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19) hexaferrite

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Journal of Rare Earths 2025年第1期43卷 115-123,I0005页

作者： Jayashri Mahapatro Sher singh Meena Sadhana Agrawal Department of Physics National Institute of Technology RaipurRaipur492010India Solid State Physics Division Bhabha Atomic Research CentreMumbai400085MSIndia

The present work reports the structural,optical,dielectric,and electrical properties of Eu-Er substituted M-type Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19)(x=0.0.05,0.1,0.15,and 0.2)hexaferrites synthesized by sol-gel combustion *** hexagonal structure of the Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19) samples was confirmed from X-ray diffraction(XRD)*** values of lattice parameters of the Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19)samples are increased as compared to Ba_(0.5)Sr_(0.5)Fe_(12)O_(19) *** increase in the value of lattice parameters is attributed to the substitution of larger cations(Eu^(3+)and Er^(3+))in place of smaller cations(Fe^(3+)ions).The crystallite sizes of the Ba0.5Sr0.5EuxErxFe12-2x019 samples also increase due to the substitution of larger *** force constants(K_o and K_t)increases with increasing Eu-Er *** octahedral cluster shifts towards the higher wavenumber side whereas the tetrahedral cluster shifts towards the lower wavenumber side due to Eu-Er substitution in the Fourier transform infrared(FTIR)*** photoluminescence(PL)emission spectra for the Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19) samples are observed at 365 *** dielectric dispersion in the Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19) samples can be understood by Koop's theory and Maxwell-Wagner type of inte rfacial *** Jonscher's power law and the co rrelated barrier hopping(CBH)model,the frequency and temperature-dependent be haviour of ac conductivity of Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19) samples are *** temperature-dependent behaviour of the dc conductivity of the Ba_(0.5)Sr_(0.5)Eu_(x)Er_(x)Fe_(12-2x)O_(19) samples is explained by the variable range hopping(VRH)*** Motto temperature of the sample varies from 4.55×10^(9) to 2.31×10^(8) *** estimated maximum barrier height(WM)of the compound varies from 0.6603 to 0.1199 *** temperature coefficient and activation energy

关键词： Sol-gel process Porosity Dielectric properties Ferrites Rare earths

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Synergistic effects of constituents in rare earth-based composites:Enhanced structural,electrical and magnetic properties for water splitting applications

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Journal of Rare Earths 2025年第1期43卷 105-114,I0005页

作者： Chitralekha S.Shankar A.P.singh Functional Materials Research Laboratory Department of PhysicsARSD CollegeUniversity of Delhi1021India Department of Physics Multanimal Modi CollegeCh.Charan Singh UniversityMeerutU.PIndia

Rare earth-based Bi_(0.85)La_(0.15)FeO_(3)(BLFO)and NdMnO_(3)(NMO)particles were synthesised using the solidstate route,and their roles affecting structural,electrical,magnetic properties along with hydroelectric application in different concentrations i.e.,(1-x)BLFO:xNMO(where x=0,0.10,0.20,0.30 and 1.0)ceramics composites were investigated.X-ray diffraction analyses confirm the pure-phase formation of BLFO:NMO composites,featuring micrometer-scale crystallite *** transform infrared(FT-IR)spectra of BLFO:NMO composites reveal peak shifts with rising NMO content,indicating composite *** composites exhibit robust Maxwell-Wagner polarization and a pronounced composition-dependent *** addition of NMO to BLFO results in a rise in dielectric permittivity at lower frequencies,confirming relaxor behavior and indicating success in achieving the transition *** spectroscopy facilitates a clearer understanding of how charge carriers contribute to these composites and the impact of grain/grain *** saturation magnetization maximum value(i.e.,0.807 emu/g)was attained in *** coercivity decreases with the addition of NMO in *** results suggest the composite's enhanced suitability for microelectronics and hydropower cells,showing improved hydroelectric cell performance with increased NMO in BLFO,highlighting a notable ion diffusion mechanism.

关键词： Composites X-ray diffraction Relative permittivity Hydroelectric cell Rare earths

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Exploring the role of N-acetyltransferases in diseases:a focus on N-acetyltransferase 9 in neurodegeneration

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Neural Regeneration Research 2025年第10期20卷 2862-2871页

作者： Prajakta Deshpande Anuradha Venkatakrishnan Chimata Amit singh Department of Biology University of DaytonDaytonOHUSA Premedical Program University of DaytonDaytonOHUSA Center for Tissue Regeneration and Engineering at Dayton(TREND) University of DaytonDaytonOHUSA Integrative Science and Engineering Center University of DaytonDaytonOHUSA Center for Genomic Advocacy(TCGA) Indiana State UniversityTerre HauteINUSA

Acetyltransferases,required to transfer an acetyl group on protein are highly conserved proteins that play a crucial role in development and *** acetylation is a common post-translational modification pivotal to basic cellular *** to 80%-90%of proteins are acetylated during translation,which is an irreversible process that affects protein structure,function,life,and *** this review,we have discussed the various N-acetyltransferases present in humans,their function,and how they might play a role in ***,we have focused on N-acetyltransferase 9 and its role in microtubule *** have shed light on how N-acetyltransferase 9 and acetylation of proteins can potentially play a role in neurodegenerative *** have specifically discussed the N-acetyltransferase 9-acetylation independent function and regulation of c-Jun N-terminal kinase signaling and microtubule stability during development and neurodegeneration.

关键词： acetyl-coenzyme A Alzheimer’s disease animal models cell death drosophila eye human disease c-Jun N-terminal kinase signaling N-Acetyltransferases N-acetyltransferase 9 neurodegeneration

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Fibrinogen’s potential role in connecting cerebrovascular abnormalities with glymphatic dysfunction in Alzheimer’s disease

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Neural Regeneration Research 2025年第1期20卷 203-204页

作者： Vishal singh Arnab Choudhury Hyung Jin Ahn Department of Pharmacology Physiology and NeurosciencesRutgers-New Jersey Medical SchoolNewarkNJUSA Brain Health Institute Rutgers UniversityPiscatawayNJUSA

Alzheimer’s disease(AD)stands out as the primary manifestation of age-related dementia,portraying a chronic neurodegenerative disorder distinguished by the accumulation of fibrillar amyloid-β(Aβ)plaques and neurofibrillary tangles of hyperphosphorylated ***,from a clinical standpoint,AD presents itself as a complex condition with a spectrum of dysfunctions rather than a singular pathological *** often-overlooked aspect of the disease is the presence of extensive cerebrovascular abnormalities,given that the majority of AD patients experience altered cerebral blood flow,damaged vasculature,increased microinfarcts and *** models of AD further support this observation,showing cerebrovascular dysfunction such as impaired cerebral blood flow and altered cerebrovascular reactivity(Tataryn et al.,2021;Gareau et al.,2023).

关键词： cerebrovascular dysfunction Alzheimer

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Electrocardiogram Signal Denoising Using Optimized Adaptive Hybrid Filter with Empirical Wavelet Transform

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Journal of Shanghai Jiaotong University (Science) 2025年第1期30卷 66-80页

作者： Balasubramanian, S. Naruka, Mahaveer singh Tewari, Gaurav Department of Electronics and Communication Engineering Maharishi University of Information Technology Maharishi Vidya Mandir Lucknow226013 India Department of Electronics and Communication Engineering IEC College of Engineering and Technology Greater Noida201310 India Department of Electrical Communication Engineering School of Information and Communication Technology Gautam Buddha University Greater Noida201310 India

Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades. The electrocardiogram (ECG) signal is a comprehensive non-invasive method for determining cardiac health. Various health practitioners use the ECG signal to ascertain critical information about the human heart. In this article, swarm intelligence approaches are used in the biomedical signal processing sector to enhance adaptive hybrid filters and empirical wavelet transforms (EWTs). At first, the white Gaussian noise is added to the input ECG signal and then applied to the EWT. The ECG signals are denoised by the proposed adaptive hybrid filter. The honey badge optimization (HBO) algorithm is utilized to optimize the EWT window function and adaptive hybrid filter weight parameters. The proposed approach is simulated by MATLAB 2018a using the MIT-BIH dataset with white Gaussian, electromyogram and electrode motion artifact noises. A comparison of the HBO approach with recursive least square-based adaptive filter, multichannel least means square, and discrete wavelet transform methods has been done in order to show the efficiency of the proposed adaptive hybrid filter. The experimental results show that the HBO approach supported by EWT and adaptive hybrid filter can be employed efficiently for cardiovascular signal denoising. © Shanghai Jiao Tong University 2023.

关键词： Least squares approximations

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Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

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Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

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Impact of nonextensivity on the transport coefficients of strongly interacting QCD matter

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Chinese Physics C 2025年第02期 93-109页

作者： Dhananjay singh Arvind Kumar Department of Physics Dr.B R Ambedkar National Institute of Technology Jalandhar

Tsallis nonextensive statistics is applied to study the transport coefficients of strongly interacting matter within the Polyakov chiral SU（3） quark mean field model（PCQMF）.Nonextensivity is introduced within the PCQMF model through a dimensionless parameter q to examine the viscous properties,such as shear viscosity（η）and bulk viscosity（ζb）,and conductive properties,such as electrical conductivity(σel) and thermal conductivity（κ）.Additionally,some key thermodynamic quantities relevant to the transport coefficients,such as the speed of sound(csq2) and specific heat at constant volume(evq),are *** temperature dependence of the transport coefficients is explored through a kinetic theory approach with the relaxation time *** results are compared to those of the extensive case where q approaches *** nonextensive q parameter is found to have a significant effect on all transport *** find that the nonextensive behaviour of the medium enhances specific shear viscosity η/sq,as well as conductive coefficients σel/T and κ/*** contrast,the normalized bulk viscosity ζb/sqis found to decrease as the nonextensivity of the medium *** also studied the transport coefficients for finite values of chemical *** magnitudes of η,σel,and κ increase at lower temperatures,while ζbis found to decrease for systems with non-zero chemical potential.

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