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Non-Uniform Pion Tetrahedron Aether and Electron Tetrahedron Model

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Journal of High Energy Physics, Gravitation and Cosmology 2024年第2期10卷 810-824页

作者： rami Rom Independent Researcher Zikhron-Yaakov Israel

We propose that the QCD vacuum pion tetrahedron condensate density vary in space and drops to extremely low values in the Kennan, Barger and Cowie (KBC) void in analogy to earth’s atmospheric density drop with elevation from earth. We propose a formula for the gravitation acceleration based on the non-uniform pion tetrahedron condensate. Gravity may be due to the underlying microscopic attraction between quarks and antiquarks, which are part of the vacuum pion tetrahedron condensate. We propose an electron tetrahedron model, where electrons are comprised of tetraquark tetrahedrons, and . The quarks determine the negative electron charge and the or quarks determine the electron two spin states. The electron tetrahedron may perform a high frequency quark exchange reactions with the pion tetrahedron condensate by tunneling through the condensation gap creating a delocalized electron cloud with a fixed spin. The pion tetrahedron may act as a QCD glue bonding electron pairs in atoms and molecules and protons to neutrons in the nuclei. Conservation of valence quarks and antiquarks is proposed.

关键词： Standard Model (SM) QCD Vacuum Condensate Electric Dipole Moment (EDM) KBC Void Antimatter MOND Theory Aether

The Pionic Deuterium and the Pion Tetrahedron Vacuum Polarization

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Journal of High Energy Physics, Gravitation and Cosmology 2024年第1期10卷 329-345页

作者： rami Rom Zikhron-Ya’akov Israel

A double-well potential model is proposed for the pionic deuterium that enables to calculate the energy split, the potential barrier height and estimate the pion tetrahedron edge length. We propose that pion tetrahedrons, πTd = ud~dũ, play a central role in the Yukawa interaction by enabling quark exchange reactions between protons and neutrons by tunneling through a potential barrier. A vacuum polarization Feynman diagram is proposed for the πTd having chains of fermion loops for the two valence quarks and anti-quarks connected by gluons. With a higher order vacuum polarization diagram, the d and u quark loops are interleaved and the chiral symmetry is broken dynamically. The proposed πTd vacuum polarization integral does not diverge in both the IR and UV limits and vanishes in the limit of an infinite pion tetrahedron condensate. We propose a new Delbruck scattering Feynman diagram that includes d and u quark and anti-quark interleaved loops. We further propose that conversion of gravitons to photons may occur via quark and anti-quark loops that describe the pion tetrahedrons dynamics in the vacuum and may also transfer gravitational waves.

关键词： Pionic Deuterium (πD) Yukawa Interaction QCD Vacuum Double-Well Potential Chiral Perturbation Theory Vacuum Polarization Gravitational Waves

基于嵌入式网格的裂缝性致密油储层压裂生产一体化数值模拟方法

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计算物理 2024年

作者：徐世乾郭建春 Younis M.rami 卢聪 Texas A&M University Harold Vance Department of Petroleum Engineering College Station 西南石油大学油气藏地质及开发工程国家重点实验室

有效的一体化模拟裂缝性致密油储层压裂生产过程是评价压裂设计的关键之一。为此，基于嵌入式网格的基质裂缝全域空间流固耦合数值模拟方法，进一步考虑天然裂缝影响下裂缝动态扩展、低速非线性渗流、基质与裂缝应力敏感，实现了裂缝性... 详细信息

有效的一体化模拟裂缝性致密油储层压裂生产过程是评价压裂设计的关键之一。为此，基于嵌入式网格的基质裂缝全域空间流固耦合数值模拟方法，进一步考虑天然裂缝影响下裂缝动态扩展、低速非线性渗流、基质与裂缝应力敏感，实现了裂缝性致密油储层压裂生产一体化多机理模拟。进而分析了天然裂缝、非线性渗流对裂缝扩展及生产动态的一体化影响规律。研究结果表明：模型可以在生产过程中任意时刻模拟压裂，为重复压裂、加密井的设计分析提供了有效工具。当基质岩石的抗拉强度由10.2 MPa降到2.3 MPa时，破碎带逐渐增大，滤失作用增加，导致主裂缝长度降低8%-9%，但可以增加累产油量17.5%至61.1%，影响作用显著且主要影响早期的日产油量。与启动压力梯度模型相比，低速非线性渗流可以更好地预测致密油生产动态。该方法为裂缝性致密油储层压裂生产一体化的动态预测、规律分析、工艺优化提供了高效工具。

关键词：致密油裂缝性储层流固耦合压裂生产一体化嵌入式网格

Application of near-infrared spectroscopy for fast germplasm analysis and classification in multi-environment using intact-seed peanut(Arachis hypogaea L.)

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Oil Crop Science 2024年第2期9卷 132-141页

作者： Fentanesh Chekole Kassie Gilles Chaix Hermine Bille Ngalle Maguette Seye Coura Fall Hodo-Abalo Tossim Aissatou Sambou Olivier Gibert Fabrice Davrieux Joseph Martin Bell Jean-Francois rami Daniel Fonceka Joel Romaric Nguepjop Department of Plant Biology and Physiology Faculty of SciencesUniversity of Yaounde IYaoundeP.O.Box 337Cameroon Department of Plant Science College of AgricultureWolaita Sodo UniversitySodoP.O.Box 138Ethiopia CIRAD UMR AGAP InstitutMontpellierFrance AGAP Institut Univ MontpellierCIRADINRAEInstitut AgroMontpellierFrance ChemHouse Research Group MontpellierFrance Centre D’Etudes Regional Pour L’Amelioration de L’Adaptation a La Secheresse(CERAAS/ISRA) Route de KhomboleThiesBP 3320Senegal Dispositif de Recherche et de Formation en Partenariat Innovation et Amelioration Varietale en Afrique de L’Ouest(IAVAO)CERAASRoute de KhomboleThiesBP 3320Senegal CIRAD UMR QUALISUDSaint PierreFrance

Peanut is a worldwide oilseed crop and the need to assess germplasm in a non-destructive manner is important for seed nutritional *** this study,Near Infrared Spectroscopy(NIRS)was applied to rapidly assess germplasm variability from whole seed of 699 samples,field-collected and assembled in four genetic and environmentbased sets:one set of 300 varieties of a core-collection and three sets of 133 genotypes of an interspecific population,evaluated in three environments in a large spatial scale of two countries,Mbalmayo and Bafia in Cameroon and Nioro in Senegal,under rainfed *** elemental spectra were gathered on six subsets of seeds of each sample,after three rotation scans,with a spectral resolution of 16 cm-1over the spectral range of867 nm to 2530 *** were then processed by principal component analysis(PCA)coupled with Partial least squares-discriminant analysis(PLS-DA).As results,a huge variability was found between varieties and genotypes for all NIR wavelength within and between *** magnitude of genetic variation was particularly observed at 11 relevant wavelengths such as 1723 nm,usually related to oil content and fatty acid *** yielded the most chemical attributes in three significant PCs(i.e.,eigenvalues>10),which together captured 93%of the total variation,revealing genetic and environment structure of varieties and genotypes into four clusters,corresponding to the four samples *** pattern of genetic variability of the interspecific population covers,remarkably half of spectrum of the core-collection,turning out to be the ***,a PLS-DA model was developed and a strong accuracy of 99.6%was achieved for the four sets,aiming to classify each seed sample according to environment *** confusion matrix achieved for the two sets of Bafia and Nioro showed 100%of instances classified correctly with 100%at both sensitivity and specificity,confirming that their seed quality was different f

关键词： Groundnut Oilseed Near infrared spectroscopy Germplasm analysis Environment Nutritional Breeding

Machine Learning Approaches to Detect DoS and Their Effect on WSNs Lifetime

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Computers, Materials & Continua 2022年第3期70卷 4921-4946页

作者： Raniyah Wazirali rami Ahmad College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia The School of Information Technology Sebha UniversitySebha71Libya

Energy and security remain the main two challenges in Wireless Sensor Networks(WSNs).Therefore,protecting these WSN networks from Denial of Service(DoS)and Distributed DoS(DDoS)is one of the WSN networks security *** packet deep scan systems that rely on open field inspection in transport layer security packets and the open field encryption trend are making machine learning-based systems the only viable choice for these types of *** paper contributes to the evaluation of the use machine learning algorithms in WSN nodes traffic and their effect on WSN network life *** examined the performance metrics of different machine learning classification categories such asK-Nearest Neighbour(KNN),Logistic Regression(LR),Support Vector Machine(SVM),Gboost,Decision Tree(DT),Na飗e Bayes,Long Short Term Memory(LSTM),and Multi-Layer Perceptron(MLP)on aWSN-dataset in different *** test results proved that the statistical and logical classification categories performed the best on numeric statistical datasets,and the Gboost algorithm showed the best performance compared to different algorithms on average of all performance *** performance metrics used in these validations were accuracy,F1-score,False Positive Ratio(FPR),False Negative Ratio(FNR),and the training execution ***,the test results showed the Gboost algorithm got 99.6%,98.8%,0.4%0.13%in accuracy,F1-score,FPR,and FNR,*** training execution time,it obtained 1.41 s for the average of all training time execution *** addition,this paper demonstrated that for the numeric statistical data type,the best results are in the size of the dataset ranging from3000 to 6000 records and the percentage between categories is not less than 50%for each category with the other ***,this paper investigated the effect of Gboost on the WSN lifetime,which resulted in a 32%reduction compared to other Gboost-free scenarios.

关键词： WSN intrusion detection machine learning DoS attack WSN security WSN lifetime

Inhibition of autophagy rescues HT22 hippocampal neurons from erastin-induced ferroptosis

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Neural Regeneration Research 2023年第7期18卷 1548-1552页

作者： Nora Hanke Abdelhaq rami Institut für Experimentelle Neurobiologie(Anatomie Ⅱ) Klinikum der Johann Wolfgang von Goethe-UniversitätTheodor-Stern-Kai 760590 Frankfurt/MainGermany

Ferroptosis is a regulated form of cell death which is considered an oxidative iron-dependent *** lipid hydroperoxidase glutathione peroxidase 4 prevents the iron(Fe2+)-dependent formation of toxic lipid reactive oxygen *** emerging evidence indicates that inhibition of glutathione peroxidase 4 as a hallmark of ferroptosis in many cancer cell lines,the involvement of this biochemical pathway in neuronal death remains largely ***,we investigate,first whether the ferroptosis key players are involved in the neuronal cell death induced by *** second objective was to examine whether there is a cross talk between ferroptosis and *** third main was to address neuron response to erastin,with a special focus on ferritin and nuclear receptor coactivator 4-mediated *** test this in neurons,erastin(0.5-8μM)was applied to hippocampal HT22 neurons for 16 *** addition,cells were cultured with the autophagy inhibitor,3-methyladenin(10 mM)and/or ferroptosis inhibitors,ferrostatin 1(10-20μM)or deferoxamine(10-200μM)before exposure to *** this study,we demonstrated by immunofluorescence and western blot analysis,that erastin downregulates dramatically the expression of glutathione peroxidase 4,the sodium-independent cystine-glutamate antiporter and nuclear receptor coactivator *** protein levels of ferritin and mitochondrial ferritin in HT22 hippocampal neurons did not remarkably change following erastin *** addition,we demonstrated that not only the ferroptosis inhibitor,ferrostatin1/deferoxamine abrogated the ferroptotic cell death induced by erastin in hippocampal HT22 neurons,but also the potent autophagy inhibitor,*** conclude that(1)erastin-induced ferroptosis in hippocampal HT22 neurons,despite reduced nuclear receptor coactivator 4 levels,(2)that either nuclear receptor coactivator 4-mediated ferritinophagy does not occur or is of secondary importance in this model,(3)that ferroptos

关键词： erastin ferritin ferritinophagy ferroptosis glutathione peroxidase 4 HT22 neurons nuclear receptor coactivator 4

Hybrid Feature Extractions and CNN for Enhanced Periocular Identification During Covid-19

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Computer Systems Science & Engineering 2022年第4期41卷 305-320页

作者： Raniyah Wazirali rami Ahmed College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia The School of Information Technology Sebha UniversitySebha71Libya

The global pandemic of novel coronavirus that started in 2019 has ser-iously affected daily lives and placed everyone in a panic *** coronavirus led to the adoption of social distancing and people avoiding unneces-sary physical contact with each *** present situation advocates the require-ment of a contactless biometric system that could be used in future authentication systems which makesﬁngerprint-based person identiﬁcation ***-lar biometric is the solution because it does not require physical contact and is able to identify people wearing face ***,the periocular biometric region is a small area,and extraction of the required feature is the point of *** paper has proposed adopted multiple features and emphasis on the periocular *** the proposed approach,combination of local binary pattern(LBP),color histogram and features in frequency domain have been used with deep learning algorithms for classiﬁ***,we extract three types of fea-tures for the classiﬁcation of periocular regions for *** LBP represents the textual features of the iris while the color histogram represents the frequencies of pixel values in the RGB *** order to extract the frequency domain fea-tures,the wavelet transformation is *** learning from these features,a convolutional neural network(CNN)becomes able to discriminate the features and can provide better recognition *** proposed approach achieved the highest accuracy rates with the lowest false person identiﬁcation.

关键词： Person identiﬁcation convolutional neural network local binary pattern periocular region Covid-19

An Optimal Method for High-Resolution Population Geo-Spatial Data

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Computers, Materials & Continua 2022年第11期73卷 2801-2820页

作者： rami Sameer Ahmad Al Kloub Department of Disaster Management Al-Balqa Applied UniversityPrince Al-Hussien Bin Abdullah II Academy for Civil ProtectionJordan

China' Mainland has a poor distribution of meteorological *** models’estimation accuracy for creating high-resolution surfaces of meteorological data is restricted for air temperature,and low for relative humidity and wind speed(few studies reported).This study compared the typical generalized additive model(GAM)and autoencoder-based residual neural network(hereafter,residual network for short)in terms of predicting three meteorological parameters,namely air temperature,relative humidity,and wind speed,using data from 824 monitoring stations across China’s mainland in *** performance of the two models was assessed using a 10-fold cross-validation *** air temperature models employ basic variables such as latitude,longitude,elevation,and the day of the *** relative humidity models employ air temperature and ozone concentration as covariates,while the wind speed models use wind speed coarse-resolution reanalysis data as covariates,in addition to the fundamental *** coordinates represent spatial variation,while the time index of the day captures time variation in our spatiotemporal *** comparison to GAM,the residual network considerably improved prediction accuracy:on average,the coefficient of variation(CV)R2 of the three meteorological parameters rose by 0.21,CV root-mean square(RMSE)fell by 37%,and the relative humidity model improved the *** accuracy of relative humidity models was considerably improved once the monthly index was included,demonstrating that varied amounts of temporal variables are crucial for relative humidity *** also spoke about the benefits and drawbacks of using coarse resolution reanalysis data and closest neighbor values as *** comparison to classic GAMs,this study indicates that the residual network model may considerably increase the accuracy of national high spatial(1 km)and temporal(daily)resolution meteorological *** findings have implications for high-resoluti

关键词： Machine learning remote sensing geography disaster management geo-spatial analysis

Machine Learning Based Analysis of Real-Time Geographical of RS Spatio-Temporal Data

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Computers, Materials & Continua 2022年第6期71卷 5151-5165页

作者： rami Sameer Ahmad Al Kloub Department of Disaster Management Al-Balqa Applied UniversityPrince Al-Hussien Bin Abdullah II Academy for Civil ProtectionJordan

Flood disasters can be reliablymonitored using remote sensing photos with great spatiotemporal ***,satellite revisit periods and extreme weather limit the use of high spatial resolution *** a result,this research provides a method for combining Landsat and MODIS pictures to produce high spatiotemporal imagery for flood disaster *** the spatial and temporal adaptive reflectance fusion model(STARFM),the spatial and temporal reflectance unmixingmodel(STRUM),and three prominent algorithms of flexible spatiotemporal data fusion(FSDAF),Landsat fusion images are created by fusing MODIS and Landsat ***,to extract flood information,utilize a support vector machine(SVM)to classify the fusion *** the accuracy of your *** results suggest that the three spatio-temporal fusion algorithms may be used to effectively monitor floods,with FSDAF’s fusion results outperforming STARFM and STRUM in both study *** overall flood classification accuracy of the three STARFM,STRUM,and FSDAF algorithms in the Gwydir research region is 0.89,0.90,and 0.91,respectively,with Kappa coefficients of 0.63,0.64,and *** flood classification accuracy of the three fusion algorithms in the New Orleans research region is 0.90,0.89,and 0.91,with Kappa values of 0.77,0.76,and 0.81,*** spatio-temporal fusion technique can be used to successfully monitor floods,according to this study.

关键词： Support vector machine remote sensing fusion model geo-spatial analysis mapping