Parameter Beta Research Articles

Comparison of LEMI, LEMII and LEMIII to prediction of cell survival fraction of HTB140 cell line with GEANT4 and SURVIVAL code in proton therapy

The aim of this paper is to present the comparison of three models of Local Effect Model (LEMI, LEMII, LEMIII) with penetration depth of proton in a typical Spread-Out Bragg Peak (SOBP) for cell Survival Fraction (CSF) of HTB140 cell line.To evaluate the CSF, two tools, GEANT4 code and SURVIVAL code, were used. The dose and Linear Energy Transfer (LET) output of GEANT4 were used as input of SURVIVAL code for calculation of CSF parameters (alpha and beta) using three versions of LEM (LEMI, LEMII, and LEMIII). By using the Linear-Quadratic (LQ) model and output of survival code, the curve of CSF was predicted for HTB140 cell line and reasonable agreement with experimental data of CATANA (Centro di AdroTerapia ed Applicazioni Nucleari Avanzate) center was achieved. At 2 Gy, by moving from proximal to distal end of SOBP, the CSF of LEMI decreased from 0.94 to 0.92 and then increased to 0.97 at distal declining edge but LEMII and LEM III increased from 0.89 to 0.96 and 0.9 to 0.96 (proximal and distal declining edge) respectively.This is the first study to compare LEMI, LEMII, and LEMIII models for CSF curve of proton with penetration depth and was coupled both GEANT4 and SURVIVAL code to predict the CSF parameter. According to results, the prediction of the LEMII and LEMIII were in better agreement with experimental results as compared to the LEMI model.

Constraining the Lorentz-violating bumblebee vector field with big bang nucleosynthesis and gravitational baryogenesis

By assuming the cosmological principle i.e., an isotropic and homogeneous universe, we consider the cosmology of a vector-tensor theory of gravitation known as the bumblebee model. In this model a single Lorentz-violating timelike vector field with a nonzero vacuum expectation value (VEV) couples to the Ricci tensor and scalar, as well. Taking the ansatz B(t)sim t^beta for the time evolution of the vector field, where beta is a free parameter, we derive the relevant dynamic equations of the Universe. In particular, by employing observational data coming from the Big Bang Nucleosynthesis (BBN) and the matter–antimatter asymmetry in the baryogenesis era, we impose some constraints on the VEV of the bumblebee timelike vector field i.e., xi b^2, and the exponent parameter beta . The former and the latter limit the size of Lorentz violation, and the rate of the time evolution of the background Lorentz-violating bumblebee field, respectively.

Quantum gravity constraints on fine structure constant from GUP in braneworlds

The Generalized Uncertainty Principle (GUP) has been discussed in the thick braneworld scenario. By considering Rydberg atoms in this background, we show that the spacetime geometry affects Maxwell equations inducing an effective dielectric constant on the space. In its turn, the corrected Coulomb potential by the gravitational interaction yields a deviation on the 3-dimensional Bohr radius. Then, we compute the corrections on the fine structure constant owing to the GUP in higher-dimensional spacetime. We also found constraints for the deformation parameter beta and D-dimensional Planck length l_{D} by comparing the predicted deviations with the recent empirical data of the fine structure constant. We compute the intermediate length scale, which in principle may be larger than the Planck length scale. It is conjectured that below such scale Quantum Gravity effects should take place.

Deep Learning Jaringan Saraf Tiruan Untuk Pemecahan Masalah Deteksi Penyakit Daun Apel

Diseases on apple leaves are becoming a major issue for apple growers since they can cause the crop to fail. Due to the diversity of diseases that can affect apple leaves, it can be challenging for farmers to determine the cause of leaf damage. The purpose of this research is to evaluate a convolutional neural network (CNN) method for its potential use in solving the problem of apple leaf disease identification. Four types of illness are dealt with: normal, multi-illness, rusty, and scabby. Many methods, such as data preparation and a preset VGG-16 artificial neural network (CNN) architecture, are recommended for use in the deep artificial neural network processing method. The most precise outcomes occurred when the beta parameter value was set to 2 = 0.999 at Ephoch to 85/100 with an accuracy of 0.7582, and when the epsilon parameter value was set to 1e-07 at Ephoch to 32/100 with an accuracy of 0.7582 with the best accuracy.

Generalized Morse Wavelets parameter selection and transfer learning for pavement transverse cracking detection

Monitoring road surface anomalies is crucial to avoid potential harm to pedestrians, vehicles, and vehicle users. These factors have motivated the development of systems that employ signal processing and machine learning algorithms to detect these irregularities automatically by sensing the vehicle’s vibration. The wavelet transform (WT) has been frequently used for signal representation and feature extraction to solve signal classification problems. However, selecting a mother wavelet to perform the WT is challenging due to the need for methods that help to validate the time–frequency representation. Furthermore, machine learning algorithms require a sizeable sample size to train them, and setting their parameters is considered a time-consuming task. This paper proposes to compute the Continuous Wavelet Transform (CWT) through Generalized Morse Wavelets (GMWs) on vehicle’s vertical acceleration data for pavement transverse cracking detection. The parameters gamma and beta of the GMWs and the CWT’s voices per octave (VPO) were selected based on two metrics, the Heisenberg area and the Average Reconstruction Mean Squared Error. The scalogram generated through the CWT and GMWs was used to fine-tune pre-trained convolutional neural networks (CNNs) through transfer learning, such as GoogLeNet, SqueezeNet, and ResNet18. The proposed methodology set 1 VPO for the CWT, while the parameters gamma and beta of GMWs were set as 3 and 1.3333, respectively. The 5-fold cross-validation results of fine-tuning the CNNs showed that SqueezeNet provided a higher average validation sensitivity (84.3290 ± 5.5704) than GoogLeNet and ResNet18; however, the average validation specificity of SqueezeNet (92.7061 ± 7.2403) was lower.

Wall stabilization of high-beta anisotropic plasmas in an axisymmetric mirror trap

The stabilization of the ‘rigid’ flute and ballooning modes both with and without the effect of additional MHD anchors in an axisymmetric mirror trap, with the help of a perfectly conducting lateral wall, is studied using a model pressure distribution of a plasma with a steep-angle neutral beam injection at the magnetic field minimum. The calculations were performed for an anisotropic plasma in a model that simulates the pressure distribution during the injection of beams of fast neutral atoms into the magnetic field minimum. It is assumed that the lateral wall is an axisymmetric shell surrounding the plasma that follows the shape of the magnetic field line and is placed at a certain distance to the plasma border. It has been found that for the effective stabilization of the modes by the lateral wall only the parameter beta (β, ratio of plasma pressure to the magnetic field pressure) must exceed some critical value β crit. When combined with the conducting end plates imitating the MHD end stabilizers, there are two critical beta values and two stability zones and that can merge, making the entire range of allowable beta values stable. The dependence of the critical betas on the degree of plasma anisotropy, the mirror ratio, and the width of the vacuum gap between the plasma and the lateral wall is studied. In contrast to the previous studies focusing on a plasma model with a sharp boundary, we calculated the stability zones for a number of diffuse radial pressure profiles and several axial magnetic field profiles.

Improved rough approximations based on variable J-containment neighborhoods

Classic generalized rough set model in neighborhood systems provides a more general framework for depicting approximations, while it may meet the non-reflexive situations. Some scholars put forward different neighborhoods, such as adhesion neighborhoods (briefly, P_{j}-neighborhoods), containment neighborhoods (briefly, C_{j}-neighborhoods), and E_{j}-neighborhoods. However, not all of them are reflexive. Moreover, the granularity of P_{j}-neighborhoods and C_{j}-neighborhoods are too fine, and that of E_{j}-neighborhoods too coarse. To solve the problem, we aim to design a novel construction approach of neighborhoods, called variable j-containment neighborhoods (briefly, V_{j}^{beta }-neighborhoods), which satisfies the reflexivity and the granularity so flexible that the neighborhood space can adjust the granularity to meet the needs of problems. We generalize three kinds of rough approximations in V_{j}^{beta }-neighborhood spaces and discuss their properties. What’s more, we analyze the topology structures relying on V_{j}^{beta }-neighborhood spaces and compare our proposed approach with the existing approaches. By selecting the appropriate parameter beta, our neighborhood system is more flexible in adjusting the granularity to fit problem requirements. And illustrative examples demonstrate the advantages of the proposed rough set model to attribute reduction in incomplete information systems.

Fast analysis of gross alpha with a new plastic scintillation resin.

Radionuclides analysis is a complex task, with high time and economic costs. In decommissioning activities and environmental monitoring, it is very evident, in which, to obtain an appropriate information, it is necessary to perform as many analyses as possible. The number of these analyses can be reduced using screening gross alpha or gross beta parameters. However, the currently used methods cannot give an answer as fast as it would be desired and, moreover, more than 50% of the results reported in the interlaboratory exercises fall outside the acceptance range. This work presents the development of a new material and method to gross alpha activity determination using a plastic scintillation resin (PSresin) in drinking and river water samples. A specific procedure was developed involving a new PSresin (using bis-(3-trimethylsilyl-1-propyl)-methanediphosphonic acid as an extractant) that is selective for all actinides, radium and polonium. Quantitative retention and 100% detection efficiencies were obtained at pH 2 with nitric acid. PSA value of 135 was used for α/β discrimination. Eu was used to determine or estimate retention in sample analyses. The method developed can measure, in less than 5h from the reception of the sample, the gross alpha parameter with quantification errors comparable or even lower to those obtained with conventional methods.

Plenty of hyperbolicity on a class of linear homogeneous jerk differential equations

We consider 3times 3 partially hyperbolic linear differential systems over an ergodic flow X^t and derived from the linear homogeneous differential equation dddot{x}(t)+beta (X^t(t))dot{x}(X^t(t))+gamma (t) x(t)=0. Assuming that the partial hyperbolic decomposition E^soplus E^coplus E^u is proper and displays a zero Lyapunov exponent along the central direction E^c we prove that some C^0 perturbation of the parameters beta (t) and gamma (t) can be done in order to obtain non-zero Lyapunov exponents and so a chaotic behaviour of the solution.

A Risk-Return Analysis of SBI Mutual Fund

The aim of this study is to analyse the financial performance of SBI equity fund using statistical parameters (Standard Deviation, Beta, and Correlation Coefficient) and ratio analysis (Sharpe Ratio, Treynor Ratio). The study collected five years of data from SBI mutual fund house and focused on providing insights into the financial performance of selected mutual fund schemes. The findings of the study suggest that all SBI mutual funds have yielded more returns than bank fixed deposits.. Notably, the SBI Small Cap fund has been identified as the most volatile fund with the highest returns, while the SBI PSU fund has been found to be less volatile but with lower returns. The research findings could help investors understand the financial performance of mutual fund schemes better, enabling them to make informed investment decisions based on their risk profiles Key Words: Mutual fund, financial performance, risk return analysis

Limit theorems for moment processes of beta Dyson’s Brownian motions and beta Laguerre processes

In the regime where the parameter beta is proportional to the reciprocal of the system size, it is known that the empirical distribution of Gaussian beta ensembles (respectively, beta Laguerre ensembles) converges weakly to a probability measure of associated Hermite polynomials (respectively, associated Laguerre polynomials), almost surely. Gaussian fluctuations around the limit have been known as well. This paper aims to study a dynamical version of those results. More precisely, we study beta Dyson’s Brownian motions and beta Laguerre processes and establish law of large numbers (LLNs) and central limit theorems (CLTs) for their moment processes in the same regime.

BETA TRANSFORMATION OF THE LINDLEY POISSON DISTRIBUTION FOR OVER-DISPERSED COUNT DATA

A new distribution for over-dispersed count data is proposed, and its properties are studied. This is a two-parameter distribution which is obtained by introducing an additional parameter beta into the Poisson-Lindley distribution. The goodness-of-fit of this distribution is compared with other distributions that have been proposed to model overdispersion. Two illustrative examples are presented to show the flexibility of the model.

SOFIA Observations of 30 Doradus. II. Magnetic Fields and Large-scale Gas Kinematics

The heart of the Large Magellanic Cloud, 30 Doradus, is a complex region with a clear core-halo structure. Feedback from the stellar cluster R136 has been shown to be the main source of energy creating multiple parsec-scale expanding-shells in the outer region, and carving a nebula core in the proximity of the ionization source. We present the morphology and strength of the magnetic fields (B-fields) of 30 Doradus inferred from the far-infrared polarimetric observations by SOFIA/HAWC+ at 89, 154, and 214 μm. The B-field morphology is complex, showing bending structures around R136. In addition, we use high spectral and angular resolution [C ii] observations from SOFIA/GREAT and CO(2-1) from APEX. The kinematic structure of the region correlates with the B-field morphology and shows evidence of multiple expanding-shells. Our B-field strength maps, estimated using the Davis–Chandrasekhar–Fermi method and structure-function, show variations across the cloud within a maximum of 600, 450, and 350 μG at 89, 154, and 214 μm, respectively. We estimated that the majority of the 30 Doradus clouds are subcritical and sub-Alfvénic. The probability distribution function of the gas density shows that the turbulence is mainly compressively driven, while the plasma beta parameter indicates supersonic turbulence. We show that the B-field is sufficient to hold the cloud structure integrity under feedback from R136. We suggest that supersonic compressive turbulence enables the local gravitational collapse and triggers a new generation of stars to form. The velocity gradient technique using [C ii] and CO(2-1) is likely to confirm these suggestions.

The Chemistry, Recrystallization and Thermal Expansion of Brannerite from Akchatau, Kazakhstan

Numerous studies expose the potential of brannerite to become a good matrix, concentrating fission products and actinides. Minerals can complement the data collected from the synthetic materials and offer an advantage of a long-time exposure to radiation. Natural metamict brannerite from Akchatau, Kazakhstan, and its annealed sample were studied by EPMA, Raman spectroscopy, TGA, DSC, XRD and HTXRD. The radioactivity of pristine and annealed samples of brannerite was measured. Brannerite from Akchatau is characterized by the absence of significant amounts of REE and yttrium. The studied brannerite regains its structure at a temperature ~650 °C, revealed by the HTXRD and DSC. HTXRD was also performed on the annealed recrystallized brannerite. The thermal expansion for brannerite has been determined for the first time. The brannerite structure expands anisotropically with temperature increase. All the thermal expansion coefficients are positive except for αβ. The decreasing beta parameter indicates a "shear structural deformation". The angle between the 1st axis of the tensor and the crystallographic a axis decreases with the increase of the temperature. The structure expands mostly in the α11 direction, approaching the bisector of the β angle. Brannerite has a low CTE at room temperature-αv = 16 × 10-6 °C-1, which increases up to 39.4 × 10-6 °C-1 at 1100 °C. In general, the thermal stability of brannerite is comparable to that of the other perspective oxide radioactive waste-immobilizing matrices (e.g., Ln2Zr2O7, CePO4, CaTiO3, CaZrTi2O7). The calculated thermal expansion of brannerite and the understanding of its underlying crystal chemical mechanisms may contribute to the behavior prediction of the material (both metamict and crystalline) at high temperatures.

The aperiodic firehose instability of counter-beaming electrons in space plasmas

Context.Recent studies have revealed new unstable regimes of the counter-beaming electrons specific to hot and dilute plasmas from astrophysical scenarios: an aperiodic firehose-like instability is induced for highly oblique angles of propagation relative to the magnetic field, resembling the fast growing and aperiodic mode triggered by the temperature anisotropyT∥ > T⊥(where ∥, ⊥ denote directions relative to the magnetic field).Aims.The counter-beaming electron firehose instability is investigated here for space plasma conditions, which include not only a specific plasma parameterization but, in particular, the influence of an embedding background plasma of electrons and ions (protons).Methods.We applied fundamental plasma kinetic theory to prescribe the unstable regimes, characterize the wave-number dispersion of the growth rates, and differentiate from the regimes of interplay with other instabilities. We also used numerical particle-in-cell (PIC) simulations to confirm the instability of these aperiodic modes, and their effects on the relaxation of counter-beaming electrons.Results.Linear theory predicts a systematic inhibition of the (counter-)beaming electron firehose instability (BEFI) by reduction of the growth rates and the range of unstable wave-number with increasing relative density of the background electrons. To obtain finite and reasonably high values of the growth rate, the (relative) beam speed does not need to be very high (just comparable to the thermal speed), but the (counter-)beams must be dense enough, with a relative density of at least 15%–20% of the total density. Quantified in terms of the beam speed and the beta parameter, the plasma parametric conditions favorable to this instability are also markedly reduced under the influence of background electrons. Numerical simulations confirm not only that BEFI can be excited in the presence of background electrons, but also the inhibiting effect of this population, especially when this latter is cooler. In the regimes of transition to electrostatic (ES) instabilities, BEFI is still robust enough to develop as a secondary instability, after the relaxation of beams under a quick interaction with ES fluctuations.Conclusions.To the features presented in previous studies, we can add that BEFI resembles the properties of solar wind firehose heat-flux instability triggered along the magnetic field by the anti-sunward electron strahl. However, BEFI is driven by a double (counter-beaming) electron strahl, and develops at highly oblique angles, which makes it potentially effective in the regularization and relaxation of the electron counter-beams observed in expanding coronal loops (with closed magnetic field topology) and in interplanetary shocks.

What if beta is not stable? Applying the Kalman filter to risk estimates of top US companies over the long time horizon

The main objective of this paper is to examine the Kalman approach to estimate the time-varying CAPM beta on the US stock market over the long time horizon of thirty-one years. We investigate the beta estimates on the basis of three specifications: random walk (RW), mean-reverting process (MR), and random coefficient of the beta parameter (RC) for companies listed on NYSE and NASDAQ in the period 1990–2021. We examine the prognostic power of beta estimates and ranked the results according to criteria of forecast accuracy. In terms of the adopted criteria, the estimation of the beta parameter assuming its variability in time proved to be better than the OLS, LAD and ROLS methods of the Sharpe model. We can conclude that the Kalman filter approach with the assumption of a random coefficient (RC) or mean-reversion (MR) for the CAPM beta parameter gives the best results.

Digitalization of Distribution Transformer Failure Probability Using Weibull Approach towards Digital Transformation of Power Distribution Systems

Digitalization of the failure-probability modeling of crucial components in power-distribution systems is important for improving risk and reliability analysis for system-maintenance and asset-management practices. This paper aims to implement a Python programming-based Weibull approach for digitalization of distribution-transformer (DT) failures, considering a regional section of DTs in Sri Lanka as a case study. A comprehensive analysis for DT-failure data for six years has been utilized to derive a Weibull distribution analysis for DTs. The interpretation of the resulting beta and alpha parameters of the Weibull analysis for different categories of DTs in the selected region is also presented. The resulting data can be uploaded to computerized maintenance-management systems (CMMS), to adopt conclusions or resolutions reached by the asset and maintenance managers. Ultimately, failure-probability modeling is beneficial for decision-making processes for higher management aiming for the digital transformation of power-distribution systems.

The Sizes of Spine Curvatures of Children That Practice Selected Sports.

(1) Background: The aim of this study was to evaluate the shape of the spine curves in the cervical, thoracic and lumbar sections of children that practice selected sports. (2) Methods: The body posture of the examined children was assessed using the digital photography method, i.e., the Moiré method. Selected parameters characterizing the curvature of the spine (the Alpha, Beta and Gamma angles, the size of kyphosis in the thoracic spine and the size of lordosis in the lumbar spine) were analyzed. (3) Results: The study of the body posture using the Moiré method allowed for the assessment of the angles that determine the size of the spine's curvature. The analysis of differences among the groups included in the study (football, swimming, biathlon/taekwondo, volleyball) was carried out on the basis of one-dimensional models that take into account the distributions of individual parameters. On the basis of the Alpha, Beta and Gamma angles, it was possible to calculate the size of kyphosis in the thoracic section and the size of lordosis in the lumbar spine. There was a statistically significant difference in the size of the Alpha, Beta and Gamma parameters among the groups. (4) Conclusions: Most of the respondents had the correct body posture in the sagittal plane, regardless of the type of sport they practiced. Our results did not allow us to unequivocally state whether practicing various sports and having different training loads resulting from these sports have a negative or positive effect on the size of the anterior-posterior curvatures of the spine.

Analysis of COVID-19 and cancer data using new half-logistic generated family of distributions

We focus on a specific sub-model of the proposed family that we call the new half logistic-Fréchet. This sub-model stems from a new generalisation of the half-logistic distribution which we call the new half-logistic-G. The novelty of proposing this new family is that it does not include any additional parameters and instead relies on the baseline parameter. Standard statistical formulas are used to show the forms of the density and failure rate functions, ordinary and incomplete moments with generating functions, and random variate generation. The maximum likelihood estimation procedure is used to estimate the set of parameters. We conduct a simulation analysis to ensure that our calculations are converging with lower mean square error and biases. We use three real-life data sets to equate our model to well-established existing models. The proposed model outperforms the well-established four parameters beta Fréchet and exponentiated generalized Fréchet for some real life results, with three parameters such as half-logistic Fréchet, exponentiated Fréchet, Zografos–Balakrishnan gamma Fréchet, Topp–Leonne Fréchet, and Marshall–Olkin Fréchet and two-parameter classical Fréchet distribution.

ETHEREUM CRYPTOCURRENCY PRICE MOVEMENT PREDICTION SYSTEM USING TRIPLE EXPONENTIAL SMOOTHING METHOD

An innovation that was sparked is an alternative currency to replace conventional currency, namely digital currency that is secured using a cryptographic method called Cryptocurrency. However, cryptocurrency prices cannot be controlled, causing massive fluctuations. Cryptocurrency price changes are very stable due to several factors such as speculation from users and the nature of the follow-up from new to one of the causes. The cause of this bandwagon is due to extreme price increases in a short time, even within a day the price of Crypto can experience a difference of millions of rupiah for each increase and decrease. To answer this question, we need a software that can predict the Rupiah exchange rate. By using the Triple Exponential Smoothing prediction method. In implementing Triple Exponential Smoothing, historical data is needed which will later be processed to produce prediction results, for that we need parameters that can be used as historical data counters, in this study used parameters 0.40 as parameters Xt and S't and 0.60 as Beta parameters. In the process, starting from calculating the first to third smoothing, ensuring Constants, Slopes, and Parabolics, to completing the process by producing Forecasting, the results of the measurement of the margin error level with a margin of error of 0.94638% using data for the final 2021 period, which is between November - December on the Triple Exponential implementation simulation and on the implementation into the system that has been developed is 3.7249% using data from May 2022 to June 2022