Normalization Coefficients Research Articles

Analytic continuation of differential cross-sections as a way to determine asymptotic normalization coefficients. Application to the 16O(d,p)17O reaction

Asymptotic normalization coefficients (ANC) are important nuclear characteristics. This paper discusses a method for determining ANC values from experimental data on differential cross-sections of nuclear transfer reactions. The method is based on the use of the analytic continuation of these cross-sections to the pole point of the reaction amplitude with respect to the variable [Formula: see text], where [Formula: see text] is the center-of-mass scattering angle. The method under consideration is used to determine the ANC for the channel [Formula: see text]O(1/2[Formula: see text]; 0.871[Formula: see text]MeV) [Formula: see text]O(0[Formula: see text]; 0[Formula: see text]MeV) [Formula: see text] from the data on the [Formula: see text]O(0[Formula: see text]; 0[Formula: see text]MeV)[Formula: see text]O (1/2[Formula: see text]; 0.871[Formula: see text]MeV) reaction. When determining the ANC, the corrections caused by the Coulomb interaction in the initial, final and intermediate states of the reaction were taken into account. It is shown that these corrections have a great impact on the extracted ANC value.

Asymptotic Normalization Coefficient Investigation of the 17O(d, p) Transfer for Astrophysical Application to the 17O(n, α)14C Reaction at Low Energies

Indirect methods have proven to be a complementary approach for extending our knowledge of nuclear structure and low-energy cross sections. Among these, the neutron-induced reaction cross sections appear to be of particular interest since their role both for unstable and stable beams. In view of this, we report here the combined study of the 17O(n, α)14C reaction accomplished by the Trojan Horse Method (THM) and the asymptotic normalization coefficient (ANC) method. The low-lying 8038, 8125, 8213, and 8282 keV resonances in 18O are studied, and their Γ n are derived. A comparison with recent direct data and recent THM experimental data is presented. The independent ANC investigation corroborates our previous THM results, confirms the consistence of the two indirect investigations, and shows new frontiers for neutron-induced reactions with radioactive ion beams. Moreover, we examined the impact of adopting the newly recommended 17O(n, α)14C reaction rate on asymptotic giant branch stars' nucleosynthesis. Our findings reveal significant variations (≳10%) in the production of the neutron-rich heavy isotopes sensitive to neutron density, underlining the neutron-poisoning effect of 17O on the s-process.

Effects of temperature on Two-point statistical characteristics in turbulent jets

Abstract large eddy simulations are carried out for jets at Mach number 0.9, temperature ratio 2.0 and 3.4. Simulations are validated by comparing with experiments from literature. Two-point correlation- and coherence- functions are analyzed. Results show that the increment of jet temperature affects the decay rate of correlation functions. The correlation functions are analyzed both in space and time by employed a normalization method. The normalization coefficient is found changing with the temperature. Compared to spatial normalization coefficients, the time normalization coefficient is found more sensitive to the temperature. The coherence function is found asymmetric in the upstream and downstream of the reference point. The present attempt to construct an empirical model to normalize the coherence function, so as to provide reference for the study of acoustic field.

Electron diffraction structure analysis of the amorphous polytetrafluoroethylene film

A thin amorphous film of fluoroplast (polytetrafluoroethylene) was obtained and studied by the electron diffraction structure analysis methods. The previously developed method of constructing the radial distribution function of atoms by the electron diffraction patterns from amorphous structures is applied, based on the determination of the normalization coefficient by varying the thermal parameter. The possibility of applying and necessary adaptations of this technique for the studied polytetrafluoroethylene samples are shown, taking into account its not quite usual amorphous structure due to the rigid spiral conformation of polymer chains …–CF2–…, which does not allow us to speak about the complete absence of the long-range order of the arrangement of atoms along the direction of the spiral axis. The measurements were carried out using the developed registration system on the electron diffraction camera EMR-102.

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ANC and SF of bound states in 15N→14C+p, 16O→15N+p, 19F→18O+p, 32S→31P+p

Asymptotic normalization coefficients (ANCs) and spectroscopic factors (SFs) for proton binding in the ground states of the [Formula: see text]N, [Formula: see text]O, [Formula: see text]F and [Formula: see text]S nuclei were extracted from an analysis of available literature data on the (3He[Formula: see text]) and ([Formula: see text]) reactions. Modified DWBA and ADWA analyses showed that the proton transfer process is more peripheral in (3He,d) reactions and therefore more reliable for determining the ANCs. As a result of the comparative analysis of peripheral (3He,d) and nonperipheral ([Formula: see text]) reactions, the uncertainties in the extracted values of SFs were reduced. The data obtained are to be used in calculating astrophysical S-factors for radiative proton capture.

Reservoir temperature prediction based on characterization of water chemistry data—case study of western Anatolia, Turkey

Reservoir temperature estimation is crucial for geothermal studies, but traditional methods are complex and uncertain. To address this, we collected 83 sets of water chemistry and reservoir temperature data and applied four machine learning algorithms. These models considered various input factors and underwent data preprocessing steps like null value imputation, normalization, and Pearson coefficient calculation. Cross-validation addressed data volume issues, and performance metrics were used for model evaluation. The results revealed that our machine learning models outperformed traditional fluid geothermometers. All machine learning models surpassed traditional methods. The XGBoost model, based on the F-3 combination, demonstrated the best prediction accuracy with an R2 of 0.9732, while the Bayesian ridge regression model using the F-4 combination had the lowest performance with an R2 of 0.8302. This study highlights the potential of machine learning for accurate reservoir temperature prediction, offering geothermal professionals a reliable tool for model selection and advancing our understanding of geothermal resources.

Calculation of the Cross Sections for Neutron Scattering on the 9Be Nucleus Using Ab Initio Calculated Asymptotic Normalization Coefficients and Decay Widths

Calculation of the Cross Sections for Neutron Scattering on the 9Be Nucleus Using Ab Initio Calculated Asymptotic Normalization Coefficients and Decay Widths

Comparative study of alpha scattering from various nuclei at 130 MeV: Microscopic potentials and coupled channel calculations

The angular distributions of the elastic and inelastic scattering cross sections of alpha projectiles on different heavy ion target nuclei including 12C, 16O, 24Mg, 28Si and 40Ca at energy of 130 MeV have been studied using two different microscopic real potentials generated by the energy density functional (EDF) theory, and single folding cluster model as well as phenomenological Woods-Saxon potentials. A new parameterization was considered for the first time by EDF and to make the normalization coefficient tend to unity, it is necessary to consider correction to the calculated real potential. Coupled channel calculations for various low-lying states were performed, and the best fit values for the deformation length with the above models were extracted by fitting the inelastic scattering cross section and compared to previous work values. The total reaction cross section, as well as the real and imaginary volume integrals, have been studied.

LIRRN: Location-Independent Relative Radiometric Normalization of Bitemporal Remote-Sensing Images.

Relative radiometric normalization (RRN) is a critical pre-processing step that enables accurate comparisons of multitemporal remote-sensing (RS) images through unsupervised change detection. Although existing RRN methods generally have promising results in most cases, their effectiveness depends on specific conditions, especially in scenarios with land cover/land use (LULC) in image pairs in different locations. These methods often overlook these complexities, potentially introducing biases to RRN results, mainly because of the use of spatially aligned pseudo-invariant features (PIFs) for modeling. To address this, we introduce a location-independent RRN (LIRRN) method in this study that can automatically identify non-spatially matched PIFs based on brightness characteristics. Additionally, as a fast and coregistration-free model, LIRRN complements keypoint-based RRN for more accurate results in applications where coregistration is crucial. The LIRRN process starts with segmenting reference and subject images into dark, gray, and bright zones using the multi-Otsu threshold technique. PIFs are then efficiently extracted from each zone using nearest-distance-based image content matching without any spatial constraints. These PIFs construct a linear model during subject-image calibration on a band-by-band basis. The performance evaluation involved tests on five registered/unregistered bitemporal satellite images, comparing results from three conventional methods: histogram matching (HM), blockwise KAZE, and keypoint-based RRN algorithms. Experimental results consistently demonstrated LIRRN's superior performance, particularly in handling unregistered datasets. LIRRN also exhibited faster execution times than blockwise KAZE and keypoint-based approaches while yielding results comparable to those of HM in estimating normalization coefficients. Combining LIRRN and keypoint-based RRN models resulted in even more accurate and reliable results, albeit with a slight lengthening of the computational time. To investigate and further develop LIRRN, its code, and some sample datasets are available at link in Data Availability Statement.

Optimizing the fuzzy PI controller for quadruple tank system using multi-objective Jaya algorithm

This article proposes the Jaya optimization algorithm for the multi-objective optimization of parameters for a Fuzzy Proportional-Integral (Fuzzy PI) controller, referred to as MOJaya. The purpose is to control the water level of a quadruple-tank system (QTS). The controlled plant is a nonlinear and uncertain Multiple-Input Multiple-Output (MIMO) system, which is affected by various factors such as parameter uncertainties, external disturbances, and significant time delays. These factors have a considerable impact on the stability of the control system. The parameters of the fuzzy controller and the normalization coefficients of the Fuzzy PI controller are optimized offline using the multi-objective Jaya optimization (MOJaya) algorithm. To demonstrate the effectiveness of the proposed algorithm, it was compared with the Fuzzy PI and PI-MOJaya algorithms. The simulation results indicate that the proposed algorithm outperforms the other algorithms in terms of control quality.

Analysis of astrophysical 26Mg(n,γ)27Mg reaction via the asymptotic normalization coefficient method

The [Formula: see text] reaction plays a crucial role in the process of nucleosynthesis in stars. It occurs primarily in massive stars during their late evolutionary stages or during explosive events like supernovae. This paper focuses on investigating discrepancies in the ANC values of the [Formula: see text] reaction by analyzing experimental angular distributions of [Formula: see text] using the DWBA, ADWA and CDCC methods for both ground and first excited states. We then use a mirror nucleus procedure to extract information on the ANCs of the ground state [Formula: see text] reaction. The Hauser–Feshbach formalism of the statistical Compound Nucleus (CN) model was applied in this study to perform a compound-nucleus analysis of the [Formula: see text] reaction. The [Formula: see text] reaction has almost fulfilled the condition of peripherality, which is necessary for understanding the magnitude of the direct reaction contribution. ANCs for the [Formula: see text] virtual decay system were obtained. Moreover, according to charge symmetry of mirror nuclei, the square of proton ANC for a [Formula: see text] is determined and comparison between the values of the presented ANCs.

Exotic B-Series and S-Series: Algebraic Structures and Order Conditions for Invariant Measure Sampling

AbstractB-Series and generalizations are a powerful tool for the analysis of numerical integrators. An extension named exotic aromatic B-Series was introduced to study the order conditions for sampling the invariant measure of ergodic SDEs. Introducing a new symmetry normalization coefficient, we analyze the algebraic structures related to exotic B-Series and S-Series. Precisely, we prove the relationship between the Grossman–Larson algebras over exotic and grafted forests and the corresponding duals to the Connes–Kreimer coalgebras and use it to study the natural composition laws on exotic S-Series. Applying this algebraic framework to the derivation of order conditions for a class of stochastic Runge–Kutta methods, we present a multiplicative property that ensures some order conditions to be satisfied automatically.

Design and Application of Intelligent Library Intelligence Authentication System Based on Information Entropy Early Warning Models

Abstract Identifying the authenticity of library intelligence has consistently posed a significant challenge in intelligence management. This paper aims to optimize the D-S evidence theory to address the issues of uncertainty, imprecision, and high conflict in library intelligence evidence fusion. To achieve this, DSmT is employed to extend the D-S evidence theory by eliminating the process of assigning conflicting information with normalization coefficients. Then, through the fuzzy information pseudo-feature analysis method, the library intelligent intelligence information entropy feature quantity is extracted, and semantic feature matching is used to construct the library intelligent intelligence true and false information recognition system. Finally, the recognition performance of the system is examined using a dataset to analyze the intelligence authenticity recognition of mis-spliced bacterial colony genomic data from a biological experiment that has been entered into the library intelligence database. Finally, it was found that the average recognition rate of this paper's system in the four classical datasets is 96.57%, which is higher than the 89.61% and 90.02% of the two evidence fusion classification schemes. The results of this paper's algorithm for high-conflict evidence are 0.9506, 0.0558, and 0.0097, reflecting the accuracy of the evidence support results. Finally, 35 colony genome splicing error intelligence were identified, of which 32 were genuine errors, with a precision rate of 91% and a recall rate of 94%. The library intelligence authenticity recognition system designed in this paper has excellent performance and provides an effective path and usable algorithmic model for library intelligence authentication.

Asymptotic normalization coefficient for the study of the mirror nuclei 7Li and 7Be

We present a theoretical study of the nuclear structure of the mirror nuclei 7Li and 7Be by using the asymptotic normalization coefficient (ANC) method through the transfer reactions 6Li(d,p)7Li and 6Li(3He,d)7Be. For these reactions, the elastic scattering and the transfer angular distributions were calculated considering cluster structures for the residual nucleus and the transfer particle. With the use of the Fresco code, we found the optical model parameters which reproduce the experimental data for the elastic and the transfer angular distributions and we got the ANC for the single particle model and the spectroscopic factor on the ground and the first excited states of each nuclei. This methodology allows to calculate the nuclear ANC which describes the peripheral behavior of both nuclei on their bound states.

Shedding light on 17O(n,α)14C reaction at astrophysical energies with Trojan Horse Method and Asymptotic Normalization Coefficient

Shedding light on ¹⁷O(n,α)¹⁴C reaction at astrophysical energies with Trojan Horse Method and Asymptotic Normalization Coefficient

Virtual platform for computer simulation of radionuclide imaging in nuclear cardiology: Comparison with clinical data

BACKGROUND: In radionuclide imaging, in vivo human clinical studies are limited because of radiation exposure and ethical concerns; therefore, mathematical modeling and in silico computer simulations based on digital models are becoming increasingly important. In the English-language literature, this approach is called “virtual clinical trials.” AIMS: This study aimed to develop software tools for the simulation of radionuclide visualization of myocardial perfusion by single-photon emission computed tomography combined with computed tomography using 99mTc-MIBI as the radiopharmaceutical and perform studies aimed at improving the accuracy of single-photon emission computed tomography. MATERIALS AND METHODS: A software package “Virtual platform for simulations of single-photon emission computed tomography combined with computed tomography method in nuclear cardiology” was developed using digital patient models, a scanner, and assessment of the state of the myocardium using digital images of the left ventricle in the form of a “polar map.” Verification of the software package was performed by comparison with clinical data obtained at the National Medical Research Center of Cardiology Named After Academician E.I. Chazov (Moscow). Simulation computer tests were performed, in which the accuracy of assessing the state of the myocardium was assessed, depending on the approach to normalizing the polar map and corrective factors in the reconstruction algorithm. RESULTS: The results of the simulation tests revealed that the assessment of left ventricular myocardial perfusion significantly depended on the method of normalizing the polar map and considered corrective factors in the reconstruction algorithm. The most accurate estimates were obtained by calculating the normalization coefficient from the average value of activity in the normal zone of the myocardium. The common approach to pixel normalization with maximum intensity can lead to errors. The results of the virtual trials were fully consistent with clinical observations. CONCLUSIONS: The transition from relative normalized values of activity in the myocardium to absolute quantitative estimates may eliminate existing limitations and uncertainties and is the main condition for improving the diagnostic accuracy of single-photon emission computed tomography combined with computed tomography in nuclear cardiology.

Fast Local Laplacian Filter Based on Modified Laplacian through Bilateral Filter for Coronary Angiography Medical Imaging Enhancement

Contrast enhancement techniques serve the purpose of diminishing image noise and increasing the contrast of relevant structures. In the context of medical images, where the differentiation between normal and abnormal tissues can be quite subtle, precise interpretation might become challenging when noise levels are relatively elevated. The Fast Local Laplacian Filter (FLLF) is proposed to deliver a more precise interpretation and present a clearer image to the observer; this is achieved through the reduction of noise levels. In this study, the FLLF strengthened images through its unique contrast enhancement capabilities while preserving important image details. It achieved this by adapting to the image’s characteristics and selectively enhancing areas with low contrast, thereby improving the overall visual quality. Additionally, the FLLF excels in edge preservation, ensuring that fine details are retained and that edges remain sharp. Several performance metrics were employed to assess the effectiveness of the proposed technique. These metrics included Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Normalization Coefficient (NC), and Correlation Coefficient. The results indicated that the proposed technique achieved a PSNR of 40.12, an MSE of 8.6982, an RMSE of 2.9492, an NC of 1.0893, and a Correlation Coefficient of 0.9999. The analysis highlights the superior performance of the proposed method when contrast enhancement is applied, especially when compared to existing techniques. This approach results in high-quality images with minimal information loss, ultimately aiding medical experts in making more accurate diagnoses.

Evaluation Method for Reverse Recovery Characteristics of Thyristors Based on Charge Measurement

The change of operation mode of the HVDC project causes a change of the external characteristic of the converter valve, and the reverse recovery characteristic of the thyristor inside the converter valve changes accordingly. Therefore, the reverse recovery charge measurement values of thyristors under different operating conditions cannot be directly compared, and the status of thyristors cannot be evaluated online. Therefore, a method of measuring the reverse recovery charge of series thyristor based on the turn-off voltage is presented in this paper. Then, the operation mode of the HVDC project is analyzed, and the external characteristics of the converter valve under different operation modes are discussed. Secondly, the external factors that affect the reverse recovery characteristics of thyristors are analyzed essentially, and the relationship between the external factors and the external characteristics of the converter valve is discussed. A reverse recovery charge model considering external factors is established, and a method to reduce the error is proposed. Finally, the reverse-recovery charge normalization coefficient is derived for the normalization of the measured values in different working conditions. Based on the charge online measurement method and the normalization method proposed in this paper, the reverse-recovery characteristic evaluation method of the thyristor is proposed, and the evaluation steps are introduced.

Determination of the astrophysical factor of the 3He(α,γ)7Be down to zero energy using the asymptotic normalization coefficient method

The observation of neutrinos emitted in the p − p chain and in the CNO cycle can be employed to test the Standard Solar Model. The 3He(α,γ)7Be reaction is the first reaction of the 2nd and 3rd branch of the p − p chain, so the indetermination of its cross section significantly affects the predicted 7Be and 8B neutrino fluxes. Notwithstanding its relevance and the great deal of experimental and theoretical papers, information of the reaction cross section at energies of the core of the Sun (15 keV - 30 keV) is sparse and additional experimental work is necessary to attain the target (~ 3%) accuracy. The precise understanding of the external capture component to the 3He(α,γ)7Be reaction cross section is pivotal for the theoretical assessment of the reaction mechanism. In this work, the indirect measurement of this external capture component using the Asymptotic Normalization Coefficient (ANC) technique is discussed. To extract the ANC, the angular distributions of deuterons yielded in the 6Li(3He,d)7Be α-transfer reaction were detected with high precision at E3He =3.0 MeV and 5.0 MeV. The ANCs were then deduced from the juxtaposition of DWBA and CC calculations with the experimental angular distributions and the zero energy astrophysical S-factor for 3He(α,γ)7Be reaction was calculated to equal 0.534 ± 0.025 keVb. Both our experimental and theoretical approaches were tested through the analysis of the 6Li(p,γ)7Be astrophysical factor, with further interesting astrophysical implications.