bluuebunny/crossref_metadata_2025 huggingface dataset:
Statistical calculation of beta radiotherapy dose using I-131: analysis and simulation method.
Authors: Ahmad Muntaser S. , Mohammad Hjouj
Published: February 2024

Radioiodine-131 (I-131) treats hyperthyroidism and differentiated thyroid carcinoma. In I-131, beta radiation (β−) is utilized for treatment and gamma radiation (γ) is used for diagnostic. This research sought to determine if a patient would be treated by establishing an equation for beta-thyroid cell interaction. The prospective study included 35 thyroid cancer patients receiving I-131 treatment. Beta and gamma readings were taken at different distances and sent to the statistical shop to find the coefficients of change on which the beta reaction depends and the equation that depends on it to find the beta range involved in healing. The strongest equation was R square (98.1%). To measure beta at 1 m, use the equation with a 99% association between variables and independent variables, and improve with ANOVA with a p-value of 0.00 0.05. The equation is: β_1m= -123.893+(0.947*δ) +(0.123*ε) -(0.002*π) -(2.11*Log Gamma). The discrepancy between true beta readings (mean = 1040) and the equation (mean = 1087, p-value = 0.411) is more than 0.05. That indicates the values are same. The equation that measures beta during iodine therapy has been achieved, which is the first step to improved thyroid cancer treatment.
An advanced approach to reconstruct CT images from limited-angle projections, reducing radiation dose and tube load.
Authors: BaniOdeh Doaa , Hjouj Mohammad
Published: February 2024

The process of reconstructing CT scan images from limited angle projections is critical and requires strict adherence to the ALARA principle. This principle is designed to minimize radiation exposure while maintaining image quality. Our study utilized filter back-projection (FBP) and algebraic iterative reconstruction (IR) algorithms to reconstruct brain CT images from 200 projection lines and a 100 × 100 matrix size. By combining the results of a MATLAB function with the insights of a radiologist, we can produce high-quality images that decrease radiation dose and tube load. Our findings reveal that the algebraic method is superior to the filter back-projection in preserving image quality when utilizing limited-angle projections.
A Developed Multi-Level Deep Learning Model for Network Slicing Classification in 5G Network
Authors: Hamza Hawraa S. , Ebady Manaa Mehdi
Published: February 2024

5G is considered as a key contributor and infrastructure supplier in the communication technology industry, capable of supporting a wide range of services such as virtual reality, driverless automobiles, e-health, and a variety of intelligent applications. Network slicing is designed to support the diversity of services applications with increased performance and flexibility needs by dividing the physical network into many logical networks. Service classification allows 5G service providers to accurately select the network slices for each service. We propose a Network Slicing classifier that uses a Multi-level Deep learning Model. First, we created a dataset of 5G network slicing that contain attributes connected with various network services. Next, we performed a multi-level model that consist of a set of Machine learning and deep learning model (such as deep Neural Network, Random Forest and Decision Tree) as a first level followed by next level that which is represent Attentive Interpretable Tabular Learning model. The outcomes of the experiment showed that the proposed model was able to exceed the normal models with high performance results.
QESRL: Exploring Selfish Reinforcement Learning for Repeated Quantum Games
Authors: Silva Agustin , Gustavo Zabaleta Omar , Miguel Arizmendi Constancio
Published: February 2024

A novel unified learning algorithm that seamlessly applies to both classical and quantum non-zero sum games is presented. Building upon the exploring selfish reinforcement learning (ESRL) framework previously proposed in the context of classical games, we extend this approach to handle quantum games with imperfect information. A comparison is made between performance and fairness among agents learning using plain QRL vs. QESRL. The latter enables agents to explore and learn periodic policy strategies in quantum games, leveraging the quantization of games to uncover fairer results. By addressing the challenges posed by the expanded strategy space in quantum games, we test the algorithm’s scalability by increasing the number of agents. Empirical evidence is provided to showcase its performance and to compare classical and quantum game scenarios. The proposed learning algorithm represents a significant step towards understanding the convergence and optimality of strategies in non-zero sum games across classical and quantum settings, bringing us closer to harnessing the potential of independent reinforcement learning and quantum computing in game theory applications.
Design of unbiased reduced order filter for stochastic systems with sampled measurements
Authors: Kamenshchikov Mikhail
Published: February 2024

The problem of synthesizing reduced order filter, that forms an unbiased estimate of linear functional from an unknown phase vector of a continuous time stochastic system with sampled measurements and additive noises, is considered in this work. The H
2 norm of the weighted transfer function from input noises to estimation error is used as a performance criterion. The method for reduced order filter design is based on the expression of the explicit dependence of performance criterion on unknown parameters in the canonical basis and the application of the non-convex optimization technique. Numerical simulations are performed to illustrate the proposed approach.
A Discrete Odd Lindley Half-Logistic Distribution with Applications
Authors: Shamlan D , Baaqeel H , Fayomi A
Published: February 2024

In the reality, the most of lifetime data is discrete in nature, despite it is known that this data is continuous. As a consequence, the tendency to convert the continuous lifetime distributions to its discrete counterpart has raised. The nature of the most lifetime data in real life is discrete, thus, many of researchers interested to convert. This article aims to introduce a new one-parameter discrete distribution, namely Discrete Odd Lindley Half-Logistic (DOLiHL) distribution. The DOLiHL distribution is derived by discretizing the analogue continuous distribution, using a survival discretization technique. An intensive study of this distribution is provided, including characteristic functions and statistical properties. Moreover, the unknown parameter is estimated using different methods of estimation namely, the maximum likelihood method, method of moments, least squares method and Cramer-von Mises minimum distance estimation method. A simulation study is conducted to examine the distribution’s behavior and compare between the estimation methods at different sample sizes. To evaluate the efficiency of this distribution against other competitive distributions, an implementation on real data in different fields is performed. In conclude, the DOLiHL distribution has assured its efficiency of fitting in lifetime and count data from various fields in real life.
Arithmetic modeling of k-ary n-cubes and toroidal k-ary grids
Authors: Roig Pedro J. , Alcaraz Salvador , Gilly Katja , Bernad Cristina , Juiz Carlos
Published: February 2024

The use of toroidal topologies offers many advantages in the computing field when it comes to both pattern spotting and path finding strategies. The former is covered by de Bruijn shapes, which permit to uniquely locate a single pattern throughout the shape. However, the latter is mainly carried out by k-ary n-cubes, which label node identifiers in a sequential order according to rows, columns, layers, and so on. This scheme facilitates the movement among nodes by just applying arithmetic operations, such as integer divisions and arithmetic modulo n. On the othe hand, toroidal k-ary grids are an alternative available in some specific cases, where determined patterns appear in all dimensions of each node, thus allowing to use those patterns to dictate paths to move among nodes. In this paper, the arithmetic bases of both path finding strategies have been presented and some pseudocode algorithms have been designed.
Numerical study of the “two components” model and background effects in muonic hydrogen experiments
Authors: Danev P , Tonchev H , Boradjiev I , Stoilov M
Published: February 2024

In this study, we explore the X-ray time spectra of muonic oxygen in various H
2 + O
2 gaseous mixtures by means of numerical simulations based on a sophisticated kineticrate equations model. Our primary focus is on the “two components” hypothesis, which was put forward to account for the experimentally observed two successive exponential behaviors in the radiation time-distribution. To ensure an accurate representation of the physical processes in the experiments, we incorporate precise transition rate coefficients for the elastic and inelastic scattering between the muonic hydrogen atoms and other gas constituents, in our simulation code. Specifically, a crucial aspect in our approach is the utilization of the energy dependence of the muon transfer rate to oxygen, recently extracted from experimental data by the FAMU collaboration. The accurate knowledge of such muonic oxygen X-ray time spectra is vital for cutting-edge experiments like FAMU, where the hyperfine splitting in muonic hydrogen atoms is to be determined with high accuracy, as this time spectra serves as a significant part of the background for the desired signal.
A high order method for oscillatory delay differential equations
Authors: Luca Liliana , Ricciardello Angela , Ruggieri Marianna
Published: February 2024

This paper addresses the oscillatory properties of a class of second-order neutral delay differential equations (NDDEs) and introduces a numerical scheme based on a fourth-order predictor-corrector multistep method for solving NDDEs of this type. An example in the family of oscillatory equations has been integrated by using the proposed numerical scheme. Results confirm the theoretical assumptions.
Random Fourier Surrogate for simulation calibration
Authors: Mahyub M , Souza LS , Batalo B , Yamazaki K
Published: February 2024

In this paper we propose Random Fourier Surrogate (RFS) as a method for simulation calibration. Computer simulations are actively used in various fields to model and analyze complex real-world phenomena, enabling practitioners to explore situations inaccessible by other means. To create a simulation that accurately reflects the desired real-world scenario requires calibrating the simulation parameters, a non-trivial process that requires domain expertise and iterative trial-and-error. The model-bridge paradigm has been proposed to automatize this process, where a more computationally efficient surrogate model is used in lieu of the real simulation, and a bridge model is used to map the noninterpretable surrogate parameters to calibrated simulation parameters, which are physically interpretable. Recently an efficient solution called tangent slope-intercept (TSI) descriptors has been proposed, where tangent lines of a principal curve are used to represent the simulation in low dimensionality. However, we find that it has two key problems: it is prone to overfitting and is sensitive to initialization. We address these issues using Random Fourier Features to construct a surrogate model, thereby reducing calibration time by avoiding complex computations, while retaining high accuracy. We evaluate the effectiveness of our method with different experiments on synthetic signal simulations and physical simulations of turbulent flow dynamics.
Multiscaled inviscid Taylor-Green vortex flow for examining energy conservation error in incompressible flows
Authors: Gong Xuanyou , Suzuki Hiroki , Kouchi Toshinori
Published: February 2024

This study investigates kinetic energy conservation errors in incompressible flows using multiplexed inviscid Taylor-Green vortices. Fourth-order precision Runge-Kutta methods, specifically five- and six-step methods, were employed and an inviscid two-dimensional periodic flow field was used as a test case. This method allows the energy conservation error to be suppressed to a very low level. Recent previous studies have dealt with turbulence generation using a multi-scale turbulence grid. In this study, the Taylor-Green vortex of the analytical solution is multiplexed to generate a flow field with a number of wavenumbers. Visualisation results of the initial field and the energy distribution over time were obtained. It was observed that the errors in the time evolution of the fluid energy were extremely small, and that the errors actually increased with time. However, the influence of the time step range was limited and the analytical and numerical solutions were in general agreement. As a result, it was confirmed that the inviscid Taylor-Green vortex is effective in examining the energy conservation error for incompressible flows.
Simulation of the Knudsen Pump by means of Quasi Gasdynamic Equation System
Authors: Kudryashova T A , Polyakov S V , Shilnikov E V
Published: February 2024

The use of miniature micropumps based on the effect of thermal gas sliding along the walls with an applied temperature gradient (Knudsen pump) is very relevant when creating modern miniature devices. Currently, algorithmically complex methods such as DSMC are usually used to simulate gas flows in such pumps. Progress in the development of algorithms based on a quasi-gasdynamic system of equations, pushed the authors to apply such algorithm to modeling the flow of a binary gas mixture gases in one variant of a micropump. The equations of the QGD system are conservation laws with additional dissipative terms. These terms contain a coefficient determined by the characteristic time between particles collisions. In this paper, the problem of flow in a rectangular Knudsen pump is solved based on this algorithm for a gas mixture in a single-fluid approximation. Different variants of the composition of the gas mixture are considered. The Knudsen numbers for which it is possible to describe gas flows by the QGD system correspond to flows of dense or moderately rarefied gases. Calculations for not too large Knudsen numbers demonstrated a good agreement with the results obtained by the DSMC method which is much more complex and expensive.
Non-linear response of kinetic energy in an inviscid Taylor-Green flow obtained by OpenFOAM-LES with respect to time increments
Authors: Ono Akira , Suzuki Hiroki , Kouchi Toshinori
Published: February 2024

This study investigates the conservation error of kinetic energy with respect to time increment using OpenFOAM LES. The energy conservation error is verified using an inviscid Taylor-Green vortex and the effect on energy conservation is checked by varying the time increment by a factor of 30. Differences in the response of turbulent energy conservation between large and small time increments are also verified. Higher order accuracy for time increments is expected when the kinetic energy conservation accuracy is high, however the actual behaviour in OpenFOAM needs to be investigated: as the implicit time integration method is used in OpenFOAM, a non-linear response is expected. As a result, it is evident that kinetic energy is not fully conserved in the inviscid flow of OpenFOAM. The kinetic energy distribution is similar for different time increments, with a different relationship between the conservation error observed in the range of large and small time increments.
Experimental validation on a calibration position of a hot-wire anemometer for measuring multi-scale grid-generated turbulence
Authors: Yamaguchi Hiroto , Suzuki Hiroki , Kouchi Toshinori
Published: February 2024

This study aims to experimentally examine conditions that should be satisfied by a calibration position of a constant-temperature hot-wire anemometer. Specifically, this study addresses an appropriate measurement point when this calibration is performed downstream of a turbulent field generated by a multi-scale turbulence grid. The hot-wire measurement in this study is based on an I-type probe with a standard 5 μm tungsten wire. The hot-wire anemometer in this study is small and can be attached to a probe support. In this study, uncertainty in the calibration curve of the hot-wire measurement is first checked. Here, Pitot tube velocimetry to obtain the calibration curves is carried out using two bell-type micro-differential pressure gauges. Then, the characteristics of the obtained velocity fluctuations and turbulence will be examined. Based on this relative velocity fluctuation RMS value, the effects of the obtained streamwise velocity fluctuation on output voltage are obtained by asymptotically expanding a calibration curve. Using these results, the intensity of the free-stream turbulence, which has a negligible effect on output voltage giving a calibration curve, is clarified.
On stable and quasi-chaotic regimes in a one-dimensional unimodal mapping obtained by modeling the dynamics of a biological population
Authors: Polyanovsky V O , Kamenev I G
Published: February 2024

The paper considers the properties of the difference equation describing the dynamics of the animal population, obtained earlier in the framework of studies of tundra communities. We have considered a special case in which the model is represented by a one-parameter difference equation that defines a one-dimensional unimodal mapping of a segment into itself, similar to the well-known triangular (tent) mapping, supplemented by a region with a constant value. A change in the mapping parameter generates a bifurcation scenario, in which stability zones arise, characterized by orbits of a constant period, interspersed with zones with more complicated, “quasi-chaotic” regimes. Based on the properties of the n-iterated triangular mapping, a necessary and sufficient condition for the localization of cyclic orbits in the considered type of unimodal mappings is formulated, which makes it possible to identify stability regions for any given period n. On the basis of this condition an algorithm for detecting stability zones is proposed. The main subject of the study is the fractal properties of the set, which is the complement of the obtained set of stability regions to the entire domain of mapping definition. The dynamics of the DH
(n) value is obtained, the limit of which at n → ∞ is equal to the fractal dimension dH
. It is shown that in the studied range of n (2 ≤ n ≤ 22), the DH
(n) < 0.9, which suggest that dH
< 1. If so, then according to the definition of a fractal set, its topological dimension is dT
= 0, which means that the complement of the set of stability regions consists of isolated points.
Equivalent Radius for Well Inflow Calculations at Different Regimes in Reservoir Flow Simulations
Authors: Zhaglova Anna E , Ibragimov Akif I , Indrupskiy Ilya M , Zakirov Ernest S , Anikeev Daniil P
Published: February 2024

A problem of well representation in numerical simulation of fluid flows in porous media is considered. When modelling hydrocarbon reservoirs, underground gas storages and other natural porous media, there’s a large typical difference in scales of wells (about 10 cm) and inter-well distances (from hundreds to thousands meters), so wells aren’t resolved on the grid as explicit boundaries in large-scale reservoir simulations. Instead, wells are represented by sources/sinks. The problem is that the average pressure in a grid block containing the well (well block pressure, WBP) isn’t equal to the well pressure (bottomhole pressure, BHP). D. Peaceman showed that WBP can be interpreted as the pressure at equivalent radius inside the well grid block. He derived the classical formula for the equivalent radius for steady-state (SS) Darcy flow. Though Peaceman showed it could be used for pseudo steady-state (PSS) flow as well, his derivation for PSS was not accurate. In this paper we compute the equivalent radius for PSS and boundary dominated (BD) regimes of Darcy flow and examine the impact of flow regime and distance to external boundary (or inter-well distance) on it. The results are important for accurate well representation in numerical flow simulations of underground reservoirs.
Justification of Urgent Brain CT scans at Palestinian Government Hospitals
Authors: Nazzal Anas , Ahmad Muntaser S. , Mohammad Hjouj
Published: February 2024

CT In cases of mild brain injury emergencies, CT scans can be valuable. However, misuse can result in radiation exposure and increased costs. This study examines CT scan utilization in Palestinian government hospitals, using a comprehensive multi-hospital analytical approach. It involved 66 emergency doctors and residents from Darwish Nazzal, Al Hussein, and Palestine Medical Complex. Findings indicate disparities in CT scan ordering practices among emergency physicians. Only 33.3% adhere to recommended guidelines, while 10.6% request scans for non-medical reasons. A lack of awareness regarding radiation exposure is seen in 39.4% of clinicians. Moreover, there are variations in image interpretation and ordering practices between morning and night shifts. Cost concerns are expressed by 68.2% of doctors, and 14.5% of CT scans were unjustified, often due to vague requests. This study underscores the importance of educating clinicians on radiation risks and promoting adherence to current CT scan criteria. Local guidelines and checklists are needed to justify CT scans, and physicians should participate in seminars on radiation doses and maximum allowable levels to reduce unnecessary scans. The hiring of night-shift radiologists in public hospitals is also recommended to enhance patient records and reduce costs.
Electro-mechanical analogy for Prabhakar-like fractional viscoelasticity
Authors: Colombaro Ivano , Arnone Giuseppe
Published: February 2024

The aim of this paper is to set up a formal equivalence between a mechanical system and an electrical one. Specifically, we consider the Maxwell-Prabhakar linear viscoelastic model, based on Prabhakar fractional operators. Therefore, we find the analogous expression for the electric current due to a step potential. The expression for the resulting electric current depends on the variable characterizing the viscoelastic model and its behaviour is then discussed with the support of some interesting plots.
Evaluation of location-data based features using Gaussian mixture models for age group estimation
Authors: Kakimoto Yohei , Omae Yuto
Published: February 2024

Several studies have estimated the demographics and behavioral patterns of users of mobile devices, such as smartphones, using a variety of information obtained from such devices. However, most studies have estimated unknown demographics by correlating the geographical information of users with their mobile device usage histories and social networks. In such cases, significant costs are incurred in preprocessing the data before building an estimation model. Therefore, in this study, we verified whether user demographics can be estimated using only location data obtained from mobile devices. We constructed a machine-learning model that classifies user age groups into two classes, young and elderly, based on the input features generated from location information using a Gaussian-mixture model. By measuring the classification performance of the constructed model, we confirmed that location information contained the information necessary for user attribute estimation. Experimental results confirmed that the classification model constructed based on location information exhibited high classification accuracy for the two classes of equally sampled age groups. These findings indicate that location data contain the necessary information for estimating user demographics.
SIMBAD: a simplified emission-concentration model for a computationally efficient assessment of energy policies impact on air quality
Authors: Paolo Costa Matteo , De Angelis Elena , Pirovano Guido
Published: February 2024

The reconstruction of airborne pollutant concentration fields based on emission reduction scenarios is a complex task. Simulations with chemistry and transport models (CTM) are computationally expensive and not suited for iterative optimisation that could require the evaluation of a great number of scenarios. To address this, data-driven surrogate models have been used to approximate the relationship between emission and ambient air concentrations. In this study, a different approach is presented. SIMBAD is a simplified model based on CAMx (Comprehensive Air Quality Model with Extensions) and the Direct Decoupled Method (DDM) algorithm that estimates concentration changes due to variations in emission fields. SIMBAD was validated by comparing PM10 and NO2 concentrations with CAMx simulations implementing the same emission variations. The testing scenarios involved different emission reductions and precursor species to assess SIMBAD’s performance in both simple and complex cases. The model’s performance in reproducing the non-linear nature of atmospheric processes was satisfactory, showing an average Root Mean Square Error (RMSE) always lower than 0.2 μg/m3 and a normalised bias below 2%. Slightly lower accuracy was found in more complex scenarios involving multiple pollutants and sectors modified simultaneously. Overall, SIMBAD proved to be an efficient and accurate tool for evaluating the impacts of energy policies on air quality, providing valuable insights for policymakers and researchers alike.
CFD simulation of double-pass solar dryer with air return
Authors: Droguy Y N , Koffi P E , Sissoko A , Andji J , Soro Y , Gbaha P
Published: February 2024

An indirect solar dryer was designed and manufactured in Yamoussoukro, Côte d’Ivoire. It is equipped with three parameters including two air intake ports, a fan and a removable hot air recovery system. Vacuum CFD simulations were performed in order to observe the influence of these parameters on the effectiveness of the device. The fan switched off speeds of 9 m/s and made the air distribution uniform in the drying cabin. The natural convection operation made it possible to reach 62°C in the drying chamber compared to 55°C for the forced convection operation. The unique opening of the low air intake port in operation accentuates the temperature variations in the cabin compartments with differences of + 5°C from one level to another. The hot air return system has a positive impact on temperature trends because it allows values of 65°C to be reached inside the chamber, ideal for drying agri-food products. However, this recovery reduces the air velocity in the cabin, which is a disadvantage for the performance during products. This problem could be solved by increasing the fan power.
Features of numerical modeling electrical coalescence in a droplet-layer system using the arbitrary Lagrangian-Eulerian method
Authors: Elagin I A , Yagodin G S , Chirkov V A
Published: February 2024

The electrocoalescence of a water drop at the water-oil interface was numerically analyzed using the finite element method by solving a set of equations including hydrodynamics and electrostatics. The simulation was performed using COMSOL Multiphysics software, the interface movement was implemented using an arbitrary Lagrangian-Eulerian method (also called the moving-mesh method). The influence of the initial distance from the drop to the layer, as well as the size of the entire domain on the outcome of the process was studied. The electrical coalescence and non-coalescence of a single uncharged droplet with a layer under the action of the DC field were calculated in a wide range of electric field strength. The created computer model makes it possible to calculate the voltage dependence of the detached droplet volume and charge. Also, it can help to determine features of non-coalescence, including the stretching of the droplet along the interelectrode gap and spraying.
Numerical modeling of interaction of turbulent flow with trash screen in open channels
Authors: Kokkiligadda Gangadhar , Dhar Anirban , Reddy Hanmaiahgari Prashanth
Published: February 2024

Trash screens are widely employed at the entrance of hydraulic structures, water intakes, and pumping stations to trap flowing debris that could exasperate downstream troubles. The characteristics of the vertical trash screen flow are measured using a Three-Dimensional Acoustic Doppler Velocimetry instrument for different flow conditions. The governing equations of the flow are numerically solved using k–ω SST, k–ϵ STD, k–ϵ RNG, and Reynolds Stress Model (RSM) and Large Eddy Simulations (LES). ANSYS-Fluent is used for these numerical simulations. The free surface of the vertical trash screen flow is computed by the volume of fluid method. The Grid Convergence Index is used to analyze the impact of the chosen grid structure on the numerical results. Experimental measurements of the velocity field and free surface profiles are compared with the numerical results of 3D simulations for validation. This study aims to identify the behavior of flow through screens in more detail through experimental and numerical simulations. The computed flow profiles considering all five cases agree well with the measured profile, whereas streamwise velocity in most portions of the flow, the k-ω SST outperforms the other models, and the RSM turbulence model is the second most effective.
A spatial classification applied to convectional reaction-diffusion boundary problems basing on a geometrical polymorphism of biological objects
Authors: Nartsissov Y. R.
Published: February 2024

Convectional reaction-diffusion is a common physical process which forms a background for existence of all biological objects. Along with the fluid flows it provides a supplying/removing of chemical compounds in a living system. In mathematical modelling PDE border problems are usually used for decryption of such kind phenomena. In the present study the classification of mathematical problems is developed on the base of the general geometrical properties of the considering living objects. Moreover, the uniform/non-uniform and the homogenic/non-homogenic structure of the boundaries and the internal area are taken into consideration. The type of classified models is determined by the structure of both an outer boundary and the inner space of the contemplated objects (i.e. their homogeneity/heterogeneity, H/H Classification). Furthermore, several dimensionless metrics are also introduced to estimate geometrical features influence the spatial-time distributions of chemical compound concentrations. The proposed classification can be applied to any kind of biological systems to consider a spatial polymorphism and its influence on the metabolic gradients.
Predicting the Type of Narrow Bipolar Pulse: A Machine Learning Approach
Authors: Thabrew K.A.S. , Vayanganie A. , Fernando M. , Gunasekara L. , Abeywardhana R.
Published: February 2024

Narrow Bipolar Pulses (NBP) depicts the electric field (E-Field) changes due to a Compact Intra-cloud Discharge (CID) and are of two types namely Positive NBP (PNBP) and Negative NBP (NNBP). In this study, 437 NBPs were statistically investigated using a dataset collected in Sri Lanka in 2013, 2015, 2016 and 2017. Seven independent variables (Pulse Duration (PD), Rise Time (RT), Slow Front Duration (SFD), Zero Crossing Time (ZCT), Full Width at Half Maximum (FWHM) and Ratio between the Initial and Overshoot Peak Amplitudes (RIOPA)) and one dependent variable (Type of NBP) were analyzed. Two machine learning classification models, the Random Forest (RF) model and the Binary Logistic Regression (BLR) model, were used to predict the dependent variable based on the independent variables. Two models were compared in terms accuracy (ACC), sensitivity (SE), specificity (SP), AUC (Area Under the Curve)-ROC (Receiver Operator Characteristic) curve and kappa statistic. RF model scored the highest in terms of ACC (0.91), specificity (0.94), Kappa statistics (0.82) and AUC (0.98). In conclusion, RF model had the best performance in predicting the type of NBP hence can be used as a suitable automated method to classify the type of NBP.
Optimizing gas production with innovative approach to evaporative halite precipitation and liquid loading management
Authors: Al Siyabi R , Ganat T , Al-Hadrami H
Published: February 2024

The article discusses two issues that affect the productivity of gas wells: halite precipitation and liquid loading. Halite precipitation occurs when salt crystals form in the well, while liquid loading happens when liquids build up in the well, reducing gas production. Accurate prediction of these issues is essential to mitigate them effectively. While liquid loading can be managing by reducing the size of tubing, halite precipitation is more challenging to predict and manage. The existing approaches have not sufficiently validated, and the current halite management measures are not cost-effective. The article reports on a study that aims to develop a model using halite envelope to predict the onset of halite precipitation in a gas field in Oman. The study simulated halite envelopes for thirty different gas wells known to have experienced halite precipitation problems. The results showed that there is significant variation in the size and shape of halite envelopes in different wells, making it infeasible to construct a single envelope for the entire field. However, grouping halite envelopes based on inflow resistance and constructing a model for each group proved to be a powerful tool for halite prediction. The study also investigated the use of velocity string (VS) technology as a new approach to managing halite precipitation. The study simulated halite envelopes for a few wells with different sizes of VS installed, estimating the timing of halite precipitation reoccurrence. The results showed that the effectiveness of VS as a halite remedial technique depends mainly on the rock quality and the time of installation. Additionally, the study assessed the impact of installing VS on liquid loading and the synergy between halite management and de-liquefaction by using VS. The results showed that the synergy between halite management and de-liquefaction using VS depends mainly on rock quality and the size of the installed VS.
On the τ-p Transform and Seismic Data
Authors: Hjouj Fawaz
Published: February 2024

In this work, an improved algebraic reconstruction for Radon transform of seismic type is proposed. Namely, the τ-p transform. The discrete formulations of this reconstruction problem are accomplished via the standard square function on the 2-D region [0,1]×[0,1], since its transform is known exactly. The interior-point algorithm approach with some MATLAB optimization functions is used for solving the system and recovering the image. The new algorithm produces accurate reconstructed images and is suitable for the case of limitation on the number of available projections.
Role of shift constant in Energy Shifted SAV for Hamiltonian Systems
Authors: Zama F , Ducceschi M , Bilbao S
Published: February 2024

In recent years, considerable work has been devoted to the design of energy-stable numerical methods, a class of geometrical integration technique in which the discrete energy or pseudo-energy remains conserved. This property finds practical applications in systems for which the energy is bounded from below since the growth of the solutions is then itself bounded, yielding a form of stability. Such a property may be further exploited to transform the energy overall into a quadratic form, representing the core of recent numerical techniques such as the invariant energy quadratization (IEQ) and the scalar auxiliary variable (SAV) approaches. These methods have been applied to a large class of problems due to their remarkable efficiency. Yet, several aspects of such techniques have seen little investigation. In this work, the role of the “shift” constant in the expression of the potential energy in Hamiltonian systems is investigated. This is a positive gauge constant that may be used to augment the expression of the energy. Since Hamilton’s equations are given in terms of gradients of the Hamiltonian, such a constant has no influence on the resulting dynamics in the continuous system. However, empirical evidence has suggested that the convergence properties of the associated SAV approaches are affected by the magnitude of the shift factor. In this work, the behaviour of the relative global error of SAV schemes in the cases of the harmonic and Duffing oscillators is numerically investigated. The results reveal an optimal shift factor that increases the convergence rate. Using the optimal shift factor, the proposed method displays variable order accuracy ranging from second to twelfth order.
Structure Preserving Schemes for Coupled Nonlinear Schrödinger Equation
Authors: Akkoyunlu Canan , Şaylan Pelin
Published: February 2024

The numerical solution of CNLS equations are studied for periodic wave solutions. We use the first order partitioned average vector field method, the second order partitioned average vector field composition method and plus method. The nonlinear implicit schemes preserve the energy and the momentum. The results show that the methods are successful to get approximation.
Magnetoconductance from spin-charge inter-conversion in two-terminal molecular nanojunctions with strong spin-orbit coupling electrodes.
Authors: Dednam W. , Lombardi E. B. , Zotti Linda A. , García-Blázquez M. A. , Palacios J. J.
Published: February 2024

Spin-charge inter-conversion mediated by spin-orbit coupling can lead to finite magnetoconductance in two-terminal molecular nanojunctions under non-equilibrium conditions. Here, we demonstrate how such a finite magnetoconductance can emerge in model two-terminal molecular nanojunctions by means of density functional theory based transport calculations with spin-orbit coupling in a first-order perturbation approximation. The junctions are built from the two chiral partners of an idealized helical molecule and tungsten or gold electrodes with two layers of magnetic nickel at the interface of the drain electrodes. Using Au source electrodes and a low applied bias of 0.1 V, we find percentage relative magnetoconductance values in excess of the lower bound reported in recent low-temperature, low-bias, experiments. The left-handed molecule is seen to exhibit greater magnetoconductance than its right-handed chiral partner for both Au and W source electrodes, thus demonstrating that our calculations can also exhibit enantioselectivity.
Method SPH for numerical solution of filtering problems: including capillary forces in fluid flow simulation
Authors: Bashurov V , Zhigalov V
Published: February 2024

This paper explores the theory of filtration within porous media, focusing on multicomponent mixtures’ dynamics and their numerical modeling. Key equations governing filtration, including Darcy’s law and mass conservation, are introduced. The concept of smoothed particle hydrodynamics (SPH) is presented as a powerful numerical technique for approximating these equations. SPH’s integral interpolation approach accommodates complex fluid-solid interactions and is applied to one-dimensional and two-dimensional test cases. Results demonstrate SPH’s effectiveness in capturing intricate dynamics and aligning with traditional methodologies. This study contributes to understanding fluid dynamics in porous media and underscores SPH’s potential for accurate simulations in diverse applications, from hydrocarbon reservoirs to environmental systems. The first section in your paper.
A Finite Element Approach for Forearm Neuromodulation: Impact of Electrode Size on the Current Density
Authors: Salkim Enver
Published: February 2024

Electrical impedance myography is a transcutaneous neuromodulation method for assessing muscle conditions through the application of a high-frequency, low-intensity current to the muscle region of interest (ROI). It has been shown that the mechanisms underpinning these findings are controversial as studies showed that the current reaching the target structure may not be enough to activate tissue due to various factors. It has been shown that anatomical properties as well as non-anatomical factors including electrode shape and size, inter-electrode distance may affect the outcome. This study was conducted to investigate the impact of the different sizes of the electrodes on the current density of the ROI. It may not be feasible to investigate these parameters impact on the outcome using experimental procedures. Alternatively, the computational methos have been used as a tool to study electrical stimulation of bio-computational models. The neuromodulators can be designed and developed using such advanced methods. This study investigates the impact of the electrode size on the current distributions. The fundamental anatomical layers of the human forearm were generated based on standard dimensions using concentric shapes. A sinusoidal bipolar current pulse was applied on the different sizes of electrodes to simulate current distribution within the associated anatomical layers. It was shown that the electrode size has a significant impact on the induced current density of the target anatomical layer.
Overcoming challenges in deep inspect of vpn and proxy by deep learning
Authors: Radchenko V D , Alekseenko A , Rusnak A , Fomin S I
Published: February 2024

The rapid growth of proxying and VPN techniques has presented formidable challenges for internet operators in classifying network traffic. These methods not only hinder effective traffic policing and resource restriction but also introduce complexities by allowing VPNs to masquerade under application protocols. Furthermore, the increasing popularity of applications like Voice over IP (VoIP) and peer-to-peer (P2P) technologies further exacerbates the difficulty in controlling and classifying such traffic. Conventional techniques like Server Name Indication (SNI) analysis are witnessing diminishing effectiveness over time. Network providers now face the critical task of acquiring detailed knowledge about the specific applications and protocols utilised by their customers, enabling them to accurately allocate resources and ensure robust traffic management in this challenging landscape.
Conscious Model of Particle Physics: The Grand Theory Unifying Local and Non-Local Realities
Authors: Samarawickrama Mahendra
Published: February 2024

The randomness in quantum mechanics is due to missing consciousness. By introducing consciousness, the complex dynamics in reality become causal, deterministic and unpredictable but not random. The reality behaves in a way the awareness is preserved, which causes the integrity of the experience. This behaviour complies with the Principle of Least Action. We introduce the consciousness particle aka primion to the Standard Model of particle physics to explore the implication of consciousness on reality. As per the Conscious Model of particle physics, quantum entanglement shares parameters in consciousness, adhering to non-local reality. An observation collapses of entangled wave function violates the integrity in consciousness and transforms the non-local reality to local. By incorporating consciousness, it is possible to understand reality as causal and deterministic, yet unpredictable but not random. The Conscious Model of particle physics unifies causation, relativity, and quantum mechanics and establishes a grand theory of understanding reality. Further, this research established that consciousness is an independent fundamental dimension that preserves integrity in awareness of non-local reality. This new dimension facilitates quantum entanglement to establish non-local awareness beyond the experience of five sensors or materialism. The wisdom of non-local awareness is beyond the imagination, the experience of five sensors, computation or analysis. It exists at the non-local consciousness dimension rather than our experiences, perceptions and knowledge in local space-time dimensions. Similar to our five sensors (touch, sight, hearing, smell and taste), which are developed to observe and measure local reality in space-time, the Mind emerges to be aware of both local and non-local realities through consciousness.
Effect on a QKD Chain Going Through a Generic Pauli Channel Together with a Correction Based on the 3-qubit Code
Authors: Morales-Alvarado Carlos , Raúl Morazán-Luz José , Navarro-Carrillo María , Pabon-Barbery Mateo , Delgado Francisco
Published: February 2024

Quantum cryptography is an emergent area in quantum technologies to set secure communication. BB84 protocol is a procedure to exchange a secure key to encode communication in the form of a chain of quantum bits. In this work, we model the non-ideal transmission of such a key through a parametric family of noisy channels: Pauli channels (including Bit-flipping and Dephasing noises). Assuming that Quantum Key Distribution is performed under such protocol, we analyse the fidelity of the transmission and the probability distribution for the imperfect outcomes. The analysis also includes the application of the quantum error correction algorithm: the 3-qubit code. Finally, we add the presence of an eavesdropper getting his conditional success rate to become unnoticed. The agreement in the basis selection between the transmitter and receiver is assumed as under a tentative reconciliation procedure. Outcomes show just positive effects on the transmission between sender and receiver, but a mild improvement for the success probability for the eavesdropper.
Numerical simulation of water jet load induced by spherical bubble collapse under underwater explosion
Authors: Yu J , Zhang X P , Sheng Z X , Hao Y , Shen C , Chen J P , Zhang J
Published: February 2024

In this study, a numerical method combining the HLLC solver and FV-WENO scheme is proposed to accurately simulate the behavior of multiphase compressible fluids and investigate the formation process of water jets. The HLLC solver approximates the conservation equations of the fluid by using numerical fluxes from the approximate Riemann problem, while the FV-WENO scheme improves the accuracy of the numerical solution by employing the weighted essentially non-oscillatory (WENO) reconstruction method. The combination of these methods allows for a more accurate simulation of the behavior of multiphase compressible fluids, leading to an accurate depiction of the formation process of water jets. By simulating the interaction between underwater shock waves from explosions and single or multiple spherical bubbles, we study the generation, development, and collapse of water jets during the bubble collapse process. By revealing the characteristics of the load during the formation of water jets and the interaction mechanisms between bubbles, our study provides support for further research on water jet phenomena. The formation process of water jets is of great significance for understanding the propagation of underwater shock waves and structural damage. Through this study, we delve into the mechanism of water jet formation, providing a new perspective on the propagation of underwater shock waves and structural damage. Our research results demonstrate that the application of the HLLC solver and FVWENO scheme in water jet simulation effectively improves the accuracy and precision of the numerical solution.
Boltzmann Equation and Knudsen Group - Boundary Shape and Boundary Conditions
Authors: Löbus Jörg-Uwe
Published: February 2024

A Boltzmann type equation is considered where both, the physical and the velocity space, are bounded. It is assumed that the boundary conditions consist of a reflective as well as a diffusive component. Existence of positive bounds from below and above has been proved. It has been demonstrated that under conditions on the shape of the boundary, the underlying Knudsen type transport semigroup can be embedded in a not necessarily positive group for time t ∈ ℝ. As a consequence, the Boltzmann type equation considered has a unique global solution for time t ∈ [τ
0, ∞) for some τ
0 < 0. The time τ
0 does not depend on the initial value at time 0. It can be arbitrarily small depending on the intensity of the collisions.