Search results for: diffusion%20equation

Authors: Balakrishna Shetty

Abstract:

Introduction: Stem Cell Imaging is a challenging field since the advent of Stem Cell treatment in humans. Series of research on tagging and tracking the stem cells has not been very effective. The present study is an effort by the authors to track the stem cells injected into calf muscles by Magnetic Resonance Diffusion Weighted Imaging. Materials and methods: Stem Cell injection deep into the calf muscles of patients with peripheral vascular disease is one of the recent treatment modalities followed in our institution. 5 patients who underwent deep intramuscular injection of stem cells as treatment were included for this study. Pre and two hours Post injection MRI of bilateral calf regions was done using 1.5 T Philips Achieva, 16 channel system using 16 channel torso coils. Axial STIR, Axial Diffusion weighted images with b=0 and b=1000 values with back ground suppression (DWIBS sequence of Philips MR Imaging Systems) were obtained at 5 mm interval covering the entire calf. The invert images were obtained for better visualization. 120ml of autologous bone marrow derived stem cells were processed and enriched under c-GMP conditions and reduced to 40ml solution containing mixture of above stem cells. Approximately 40 to 50 injections, each containing 0.75ml of processed stem cells, was injected with marked grids over the calf region. Around 40 injections, each of 1ml normal saline, is injected into contralateral leg as control. Results: Significant Diffusion hyper intensity is noted at the site of injected stem cells. No hyper intensity noted before the injection and also in the control side where saline was injected conclusion: This is one of the earliest studies in literature showing diffusion hyper intensity in intramuscularly injected stem cells. The advantages and deficiencies in this study will be discussed during the presentation.

Keywords: stem cells, imaging, DWI, peripheral vascular disease

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Authors: Lingge Tan, Hongpeng Xu, Jieun Yang, Maarten Hornikx

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Acoustic diffusers are important components in enhancing the quality of room acoustics. This paper provides a type of modular diffuser based on the Sierpinski Triangle of the plane and combines it with fractal theory to expand the effective frequency range. In numerical calculations and full-scale model experiments, the effect of fractal design elements on normal-incidence diffusion coefficients is examined. It is demonstrated the reasonable times of iteration of modules is three, and the coverage density is 58.4% in the design frequency from 125Hz to 4kHz.

Keywords: acoustic diffuser, fractal, Sierpinski-triangle, diffusion coefficient

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Authors: Fadi Eleiwi, Taous Meriem Laleg-Kirati

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This paper presents a complete dynamic modeling of a membrane distillation process. The model contains two consistent dynamic models. A 2D advection-diffusion equation for modeling the whole process and a modified heat equation for modeling the membrane itself. The complete model describes the temperature diffusion phenomenon across the feed, membrane, permeate containers and boundary layers of the membrane. It gives an online and complete temperature profile for each point in the domain. It explains heat conduction and convection mechanisms that take place inside the process in terms of mathematical parameters, and justify process behavior during transient and steady state phases. The process is monitored for any sudden change in the performance at any instance of time. In addition, it assists maintaining production rates as desired, and gives recommendations during membrane fabrication stages. System performance and parameters can be optimized and controlled using this complete dynamic model. Evolution of membrane boundary temperature with time, vapor mass transfer along the process, and temperature difference between membrane boundary layers are depicted and included. Simulations were performed over the complete model with real membrane specifications. The plots show consistency between 2D advection-diffusion model and the expected behavior of the systems as well as literature. Evolution of heat inside the membrane starting from transient response till reaching steady state response for fixed and varying times is illustrated.

Keywords: membrane distillation, dynamical modeling, advection-diffusion equation, thermal equilibrium, heat equation

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Authors: D. Gueribiz, F. Jacquemin, S. Fréour

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During their service life, composite materials are submitted to humid environments. The moisture absorbed by their matrix polymer induced internal stresses which can lead to multi-scale damage and may reduce the lifetime of composite structures. The estimation of internal stresses is based at a first on realistic evaluation of the diffusive behavior of composite materials. Generally, the modeling and simulation of the diffusive behavior of composite materials are extensively investigated through decoupled models based on the assumption of Fickien behavior. For these approaches, the concentration and the deformation (or stresses), the two state variables of the problem considered are governed by independent equations which are solved separately. In this study, a model coupling diffusive behavior with stresses state for a polymer matrix composite reinforced with impermeable fibers is proposed, the investigation of diffusive behavior is based on a more general thermodynamic approach which introduces a dependence of diffusive behavior on internal stresses state. The coupled diffusive behavior modeling was established in first for homogeneous and isotropic matrix and it is, thereafter, extended to impermeable unidirectional composites.

Keywords: composites materials, moisture diffusion, effective moisture diffusivity, coupled moisture diffusion

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Authors: Abdul Hadi Bin Abdol Rahim, Alhassan Salami Tijani

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Hydrogen produced by means of polymer electrolyte membrane electrolyzer (PEME) is one of the most promising methods due to clean and renewable energy source. In the process, some energy loss due to mass transfer through a PEM is caused by diffusion, electro-osmotic drag, and the pressure difference between the cathode channel and anode channel. In PEME water molecules and ionic particles transferred between the electrodes from anode to cathode, Extensive mixing of the hydrogen and oxygen at anode channel due to gases cross-over must be avoided. In recent times the consciousness of safety issue in high pressure PEME where the oxygen mix with hydrogen at anode channel could create, explosive conditions have generated a lot of concern. In this paper, the steady state and simulation analysis of gases crossover in PEME on the temperature and pressure effect are presented. The simulations have been analysis in MATLAB based on the well-known Fick’s Law of molecular diffusion. The simulation results indicated that as temperature increases, there is a significant decrease in operating voltage.

Keywords: diffusion, gases crosover, steady state, Fick’s law

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Authors: Sibashish Baksi, Ujjaini Sarkar, Sudeshna Saha

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In the present study, hydrolysis of Pinus roxburghi wood powder was carried out with Viscozyme, and kinetics of the hydrolysis has been investigated. Finely ground sawdust is submerged into 2% aqueous peroxide solution (pH=11.5) and pretreated through autoclaving, probe sonication, and alkaline peroxide pretreatment. Afterward, the pretreated material is subjected to hydrolysis. A chain of experiments was executed with delignified biomass (50 g/l) and varying enzyme concentrations (24.2–60.5 g/l). In the present study, 14.32 g/l of glucose, along with 7.35 g/l of xylose, have been recovered with a viscozyme concentration of 48.8 g/l and the same condition was treated as optimum condition. Additionally, thermal deactivation of viscozyme has been investigated and found to be gradually decreasing with escalated enzyme loading from 48.4 g/l (dissociation constant= 0.05 h⁻¹) to 60.5 g/l (dissociation constant= 0.02 h⁻¹). The hydrolysis reaction is a pseudo first-order reaction, and therefore, the rate of the hydrolysis can be expressed as a fractal-like kinetic equation that communicates between the product concentration and hydrolytic time t. It is seen that the value of rate constant (K) increases from 0.008 to 0.017 with augmented enzyme concentration from 24.2 g/l to 60.5 g/l. Greater value of K is associated with stronger enzyme binding capacity of the substrate mass. However, escalated concentration of supplied enzyme ensures improved interaction with more substrate molecules resulting in an enhanced de-polymerization of the polymeric sugar chains per unit time which eventually modifies the physiochemical structure of biomass. All fractal dimensions are in between 0 and 1. Lower the value of fractal dimension, more easily the biomass get hydrolyzed. It can be seen that with increased enzyme concentration from 24.2 g/l to 48.4 g/l, the values of fractal dimension go down from 0.1 to 0.044. This indicates that the presence of more enzyme molecules can more easily hydrolyze the substrate. However, an increased value has been observed with a further increment of enzyme concentration to 60.5g/l because of diffusional limitation. It is evident that the hydrolysis reaction system is a heterogeneous organization, and the product formation rate depends strongly on the enzyme diffusion resistances caused by the rate-limiting structures of the substrate-enzyme complex. Value of the rate constant increases from 1.061 to 2.610 with escalated enzyme concentration from 24.2 to 48.4 g/l. As the rate constant is proportional to Fick’s diffusion coefficient, it can be assumed that with a higher concentration of enzyme, a larger amount of enzyme mass dM diffuses into the substrate through the surface dF per unit time dt. Therefore, a higher rate constant value is associated with a faster diffusion of enzyme into the substrate. Regression analysis of time curves with various enzyme concentrations shows that diffusion resistant constant increases from 0.3 to 0.51 for the first two enzyme concentrations and again decreases with enzyme concentration of 60.5 g/l. During diffusion in a differential scale, the enzyme also experiences a greater resistance during diffusion of larger dM through dF in dt.

Keywords: viscozyme, glucose, fractal kinetics, thermal deactivation

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Authors: Moataz Medhat, Essam Khalil, Hatem Haridy

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The present study investigates the flame structure of turbulent diffusion flame of synthesis fuel in a 300 KW swirl-stabilized burner. The three-dimensional model adopts a realizable k-ε turbulent scheme interacting with two-dimensional PDF combustion scheme by applying flamelet concept. The study reveals more characteristics on turbulent diffusion flame of synthesis fuel when changing the inlet air swirl number and the burner quarl angle. Moreover, it concerns with studying the effect of flue gas recirculation and staging with taking radiation effect into consideration. The comparison with natural gas was investigated. The study showed two zones of recirculation, the primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. The results revealed an increase in temperature in the external recirculation zone as a result of increasing the swirl number of the inlet air stream. Also, it was found that recirculating part of the combustion products decreases pollutants formation especially nitrogen monoxide. The predicted results showed a great agreement when compared with the experiments.

Keywords: gas turbine, syngas, analysis, recirculation

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Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Sally Salah El Menshawy, Ghada M. Ahmed GabAllah, Doaa Khedr M. Khedr

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Background: Our study aims to detect the diagnostic role of DTI in the differentiation of salivary glands benign and malignant lesions. Results: Our study included 50 patients (25males and 25 females) divided into 4 groups (benign lesions n=20, malignant tumors n=13, post-operative changes n=10 and normal n=7). 28 patients were with parotid gland lesions, 4 patients were with submandibular gland lesions and only 1 case with sublingual gland affection. The mean fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of malignant salivary gland tumors (n = 13) (0.380±0.082 and 0.877±0.234× 10⁻³ mm² s⁻¹) were significantly different (P<0.001) than that of benign tumors (n = 20) (0.147±0.03 and 1.47±0.605 × 10⁻³ mm² s⁻¹), respectively. The mean FA and ADC of post-operative changes (n = 10) were (0.211±0.069 and 1.63±0.20× 10⁻³ mm² s⁻¹) while that of normal glands (n =7) was (0.251±0.034and 1.54±0.29× 10⁻³ mm² s⁻¹), respectively. Using ADC to differentiate malignant lesions from benign lesions has an (AUC) of 0.810, with an accuracy of 69.7%. ADC used to differentiate malignant lesions from post-operative changes has (AUC) of 1.0, and an accuracy of 95.7%. FA used to discriminate malignant from benign lesions has (AUC) of 1.0, and an accuracy of 93.9%. FA used to differentiate malignant from post-operative changes has (AUC) of 0.923, and an accuracy of 95.7%. Combined FA and ADC used to differentiate malignant from benign lesions has (AUC) of 1.0, and an accuracy of 100%. Combined FA and ADC used to differentiate malignant from post-operative changes has (AUC) of 1.0, and an accuracy of 100%. Conclusion: Combined FA and ADC can differentiate malignant tumors from benign salivary gland lesions.

Keywords: diffusion tensor imaging, MRI, salivary gland, tumors

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Authors: Mohammad Ghiasvand, Babak Khorsandi, Morteza Kolahdoozan

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Under the influence of waves, oil in the sea is subject to vertical scattering in the water column. Scientists' knowledge of how oil is dispersed in the water column is one of the lowest levels of knowledge among other processes affecting oil in the marine environment, which highlights the need for research and study in this field. Therefore, this study investigates the distribution of oil in the water column in a turbulent environment with zero velocity characteristics. Lack of laboratory results to analyze the distribution of petroleum pollutants in deep water for information Phenomenon physics on the one hand and using them to calibrate numerical models on the other hand led to the development of laboratory models in research. According to the aim of the present study, which is to investigate the distribution of oil in homogeneous and isotropic turbulence caused by the oscillating Grid, after reaching the ideal conditions, the crude oil flow was poured onto the water surface and oil was distributed in deep water due to turbulence was investigated. In this study, all experimental processes have been implemented and used for the first time in Iran, and the study of oil diffusion in the water column was considered one of the key aspects of pollutant diffusion in the oscillating Grid environment. Finally, the required oscillation velocities were taken at depths of 10, 15, 20, and 25 cm from the water surface and used in the analysis of oil diffusion due to turbulence parameters. The results showed that with the characteristics of the present system in two static modes and network motion with a frequency of 0.8 Hz, the results of oil diffusion in the four mentioned depths at a frequency of 0.8 Hz compared to the static mode from top to bottom at 26.18, 57 31.5, 37.5 and 50% more. Also, after 2.5 minutes of the oil spill at a frequency of 0.8 Hz, oil distribution at the mentioned depths increased by 49, 61.5, 85, and 146.1%, respectively, compared to the base (static) state.

Keywords: homogeneous and isotropic turbulence, oil distribution, oscillating grid, oil spill

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Authors: Radka Pernicova

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Chloride resistance in Ultra High Performance Concrete (UHPC) is determined in this paper. This work deals with the one dimension chloride transport, which can be potentially dangerous particularly for the durability of concrete structures. Risk of reinforcement corrosion due to exposure to the concrete surface to direct the action of chloride ions (mainly in the form de-icing salts or groundwater) is dangerously increases. The measured data are investigated depending on the depth of penetration of chloride ions into the concrete structure. Comparative measurements with normal strength concrete are done as well. The experimental results showed that UHCP have improved resistance of chlorides penetration than NSC and also chloride diffusion depth is significantly lower in UHCP.

Keywords: chloride, one dimensional diffusion, transport, salinity, UHPC

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.

Keywords: Integral differential equations, , L-stable methods, pricing European options, Jump–diffusion model

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Authors: M. Abdoos, A. Amadeh, M. Adabi

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In recent decades, the use of titanium and its alloys due to their high mechanical properties, light weight and their corrosion resistance has increased in military and industry applications. However, the poor surface properties can limit their widely usage. Many researches were carried out to improve their surface properties. The most effective technique is based on solid-state diffusion of elements that can form intermetallic compounds with the substrate. In the present work, inter-diffusion of nickel and titanium and formation of Ni-Ti intermetallic compounds in nickel-coated Ti-6Al-4V alloy have been studied. Initially, nickel was electrodeposited on the alloy using Watts bath at a current density of 20 mA/cm2 for 1 hour. The coated specimens were then heat treated in a tubular furnace under argon atmosphere at different temperatures near Ti β-transus to maximize the diffusion rate for various durations in order to improve the surface properties of the Ti-6Al-4V alloy. The effect of temperature and time on the thickness of diffusion layer and characteristics of intermetallic phases was studied by means of scanning electron microscope (SEM) equipped with energy dispersive X-ray spectrometer (EDS) and microhardness test. The results showed that a multilayer structure was formed after heat treatment: an outer layer of remaining nickel, an area of intermetallic layers with different compositions and solid solution of Ni-Ti. Three intermetallic layers was detected by EDS analysis, namely an outer layer with about 75 at.% Ni (Ni3Ti), an intermediate layer with 50 at.% Ni (NiTi) and finally an inner layer with 36 at.% Ni (NiTi2). It was also observed that the increase in time or temperature led to the formation of thicker intermetallic layers. Meanwhile, the microhardness of heat treated samples increased with formation of Ni-Ti intermetallics; however, its value depended on heat treatment parameters.

Keywords: heat treatment, microhardness, Ni coating, Ti-6Al-4V

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Authors: Ilija Plecas, Dalibor Arbutina

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The leaching rate of 60Co from spent mix bead (anion and cation) exchange resins in a cement-bentonite matrix has been studied. Transport phenomena involved in the leaching of a radioactive material from a cement-bentonite matrix are investigated using three methods based on theoretical equations. These are: the diffusion equation for a plane source, an equation for diffusion coupled to a first order equation and an empirical method employing a polynomial equation. The results presented in this paper are from a 25-year mortar and concrete testing project that will influence the design choices for radioactive waste packaging for a future Serbian radioactive waste disposal center.

Keywords: cement, concrete, immobilization, leaching, permeability, radioactivity, waste

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Authors: Judith Stein, Elfriede Friedmann

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The injection of a drug into the vitreous body for the treatment of retinal diseases like wet aged-related macular degeneration (AMD) is the most common medical intervention worldwide. We develop mathematical models for drug transport in the vitreous body of a human eye to analyse the impact of different rheological models of the vitreous on drug distribution. In addition to the convection diffusion equation characterizing the drug spreading, we use porous media modeling for the healthy vitreous with a dense collagen network and include the steady permeating flow of the aqueous humor described by Darcy's law driven by a pressure drop. Additionally, the vitreous body in a healthy human eye behaves like a viscoelastic gel through the collagen fibers suspended in the network of hyaluronic acid and acts as a drug depot for the treatment of retinal diseases. In a completely liquefied vitreous, we couple the drug diffusion with the classical Navier-Stokes flow equations. We prove the global existence and uniqueness of the weak solution of the developed initial-boundary value problem describing the drug distribution in the healthy vitreous considering the permeating aqueous humor flow in the realistic three-dimensional setting. In particular, for the drug diffusion equation, results from the literature are extended from homogeneous Dirichlet boundary conditions to our mixed boundary conditions that describe the eye with the Galerkin's method using Cauchy-Schwarz inequality and trace theorem. Because there is only a small effective drug concentration range and higher concentrations may be toxic, the ability to model the drug transport could improve the therapy by considering patient individual differences and give a better understanding of the physiological and pathological processes in the vitreous.

Keywords: coupled PDE systems, drug diffusion, mixed boundary conditions, vitreous body

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Authors: N. Chahmana, I. Zerroual

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The aim of our work is the contribution to the improvement of the performances of the positive plate of the lead acid battery. For that, we synthesized two varieties of PbO2 used in industry, alpha and beta PbO2 by electrochemical way starting from the not formed industrial plates. We studied the kinetics of reduction of the alpha varieties and PbO2 beta on electrode with microcavity in sulphuric medium. The electrochemical study of the powders of α and β-PbO2 was made by cyclic voltamperometry with sweeping of potential by using a traditional assembly with three electrodes. Values of the coefficient of diffusion of the proton in α and β-PbO2 are respectively equal to 0.498*10-8cm2 /s and 0.793*10-8 cm2 /s. During the cycling of the two varieties of PbO2, we obtain a clear increase in the capacity.

Keywords: lead accumulator, α and β - PbO2, synthesis, kinetics, cyclic voltametry, coefficient of diffusion

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Authors: Alexander Norbach

Abstract:

The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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Authors: Kayode Oshinubi, Brice Kammegne, Jacques Demongeot

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The use of mathematical tools like Partial Differential Equations and Ordinary Differential Equations have become very important to predict the evolution of a viral disease in a population in order to take preventive and curative measures. In December 2019, a novel variety of Coronavirus (SARS-CoV-2) was identified in Wuhan, Hubei Province, China causing a severe and potentially fatal respiratory syndrome, i.e., COVID-19. Since then, it has become a pandemic declared by World Health Organization (WHO) on March 11, 2020 which has spread around the globe. A reaction-diffusion system is a mathematical model that describes the evolution of a phenomenon subjected to two processes: a reaction process in which different substances are transformed, and a diffusion process that causes a distribution in space. This article provides a mathematical study of the Susceptible, Exposed, Infected, Recovered, and Vaccinated population model of the COVID-19 pandemic by the bias of reaction-diffusion equations. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined using the Lyapunov function are considered and the endemic equilibrium point exists and is stable if it satisfies Routh–Hurwitz criteria. Also, adequate conditions for the existence and uniqueness of the solution of the model have been proved. We showed the spatial distribution of the model compartments when the basic reproduction rate $\mathcal{R}_0 < 1$ and $\mathcal{R}_0 > 1$ and sensitivity analysis is performed in order to determine the most sensitive parameters in the proposed model. We demonstrate the model's effectiveness by performing numerical simulations. We investigate the impact of vaccination and the significance of spatial distribution parameters in the spread of COVID-19. The findings indicate that reducing contact with an infected person and increasing the proportion of susceptible people who receive high-efficacy vaccination will lessen the burden of COVID-19 in the population. To the public health policymakers, we offered a better understanding of the COVID-19 management.

Keywords: COVID-19, SEIRV epidemic model, reaction-diffusion equation, basic reproduction number, vaccination, spatial distribution

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Authors: Mounir Kehal

Abstract:

The post-globalization epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behavior has come to provide the competitive and comparative edge. Enterprises have turned to explicit - and even conceptualizing on tacit - knowledge management to elaborate a systematic approach to develop and sustain the intellectual capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualized. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper, we present an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Kianoosh Samimi, Siham Kamali-Bernard, Ali Akbar Maghsoudi

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This paper aims to contribute to the characterization and the understanding of fresh state, compressive strength and chloride penetration tendency of high strength self-compacting concretes (HSSCCs) where Portland cement type II is partially substituted by 10% and 15% of natural pumice and zeolite. First, five concrete mixtures with a control mixture without any pozzolan are prepared and tested in both fresh and hardened states. Then, resistance to chloride penetration for all formulation is investigated in non-steady state and steady state by measurement of chloride penetration and diffusion coefficient. In non-steady state, the correlation between initial current and chloride penetration with diffusion coefficient is studied. Moreover, the relationship between diffusion coefficient in non-steady state and electrical resistivity is determined. The concentration of free chloride ions is also measured in steady state. Finally, chloride penetration for all formulation is studied in immersion and tidal condition. The result shows that, the resistance to chloride penetration for HSSCC in immersion and tidal condition increases by incorporating pumice and zeolite. However, concrete with zeolite displays a better resistance. This paper shows that the HSSCC with 15% pumice and 10% zeolite is suitable in fresh, hardened, and durability characteristics.

Keywords: Chloride penetration, immersion, pumice, HSSCC, tidal, zeolite

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Authors: Yohanes Chekol Malede

Abstract:

σ-phase has negative effects on the corrosion responses and the mechanical properties of steels. The growth of σ-phase in the austenite matrix of AISI 347H FG steel was simulated using DICTRA software using CALPHAD method. The simulation work included the influence of both volume diffusion and grain boundary diffusion. The simulation results showed a good agreement with the experimental findings. The simulation results revealed a Cr-depleted and a Ni-enriched σ-phase/austenite interface. Effects of temperature, grain size, and composition of alloying elements on the growth kinetics of σ-phase were assessed. The simulated results were fitted to the JMAK equation and a good correlation was obtained.

Keywords: AISI 347H FG austenitic steel, CALPHAD, sigma phase, microstructure evolution

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Authors: Mounir Kehal, Adel Al Araifi

Abstract:

The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Afshin Zohdi, Selçuk Özdemir, Mustafa Aksoy

Abstract:

Tungsten carbide-cobalt (WC-Co) is a widely utilized material for cold forming dies, including those employed in fastener production. In this study, we investigated the effectiveness of the pack boriding method in improving the surface properties of WC-Co cold forging dies. The boriding process involved embedding WC-Co samples, along with a steel control sample, within a chamber made of H13 tool steel. A boriding powder mixture was introduced into the chamber, which was then sealed using a paste. Subsequently, the samples were subjected to a temperature of 700°C for 5 hours in a furnace. Microstructural analysis, including cross-sectional examination and scanning electron microscopy (SEM), confirmed successful boron diffusion and its presence on the surface of the borided samples. The microhardness of the borided layer was significantly increased (3980 HV1) compared to the unborided sample (1320 HV3), indicating enhanced hardness. The borided layer exhibited an acceptable thickness of 45 microns, with a diffusion coefficient of 1.125 × 10-7 mm²/s, signifying a moderate diffusion rate. Energy-dispersive X-ray spectroscopy (EDS) mapping revealed an increase in boron content, desirable for the intended purpose, while an undesired increase in oxygen content was observed. Furthermore, the pin-on-disk wear test demonstrated a reduction in friction coefficient, indicating improved mechanical and tribological properties of the surface. The successful implementation of the pack boriding process highlights its potential for enhancing the performance of WC-Co cold forging dies.

Keywords: WC-Co, cold forging dies, pack boriding, surface hardness, wear resistance, microhardness, diffusion coefficient, scanning electron microscopy, energy-dispersive X-ray spectroscopy

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Authors: Wangxu Xia

Abstract:

BACKGROUND BI-RADS 4 lesions raise the possibility of malignancy that warrant further clinical and radiologic work-up. This study aimed to evaluate the predictive performance of diffusion-weighted imaging(DWI) and microcalcifications on mammography for predicting malignancy of BI-RADS 4 lesions. In addition, the predictive performance of DWI combined with microcalcifications was alsocompared with the Kaiser score. METHODS During January 2021 and June 2023, 144 patients with 178 BI-RADS 4 lesions underwent conventional MRI, DWI, and mammography were included. The lesions were dichotomized intobenign or malignant according to the pathological results from core needle biopsy or surgical mastectomy. DWI was performed with a b value of 0 and 800s/mm2 and analyzed using theapparent diffusion coefficient, and a Kaiser score > 4 was considered to suggest malignancy. Thediagnostic performances for various diagnostic tests were evaluated with the receiver-operatingcharacteristic (ROC) curve. RESULTS The area under the curve (AUC) for DWI was significantly higher than that of the of mammography (0.86 vs 0.71, P<0.001), but was comparable with that of the Kaiser score (0.86 vs 0.84, P=0.58). However, the AUC for DWI combined with mammography was significantly highthan that of the Kaiser score (0.93 vs 0.84, P=0.007). The sensitivity for discriminating malignant from benign BI-RADS 4 lesions was highest at 89% for Kaiser score, but the highest specificity of 83% can be achieved with DWI combined with mammography. CONCLUSION DWI combined with microcalcifications on mammography could discriminate malignant BI-RADS4 lesions from benign ones with a high AUC and specificity. However, Kaiser score had a better sensitivity for discrimination.

Keywords: MRI, DWI, mammography, breast disease

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Authors: Reinhold Kosfeld, Andreas Gohs

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In the reduction of CO₂ emissions, the transition to environmentally friendly transport modes has a high significance. In Germany, the climate protection programme 2030 includes various measures for promoting electromobility. Although electric cars at present hold a market share of just over one percent, its stock more than doubled in the past two years. Special measures like tax incentives and a buyer’s premium have been put in place to promote the shift towards electric cars and boost their diffusion. Knowledge of the future expansion of electric cars is required for planning purposes and adaptation measures. With a view of these objectives, we particularly investigate the effect of spatial spillovers on forecasting performance. For this purpose, time series econometrics and panel econometric models are designed for pure electric cars and hybrid cars for Germany. Regional forecasting models with spatial interactions are consistently estimated by using spatial econometric techniques. Regional data on the stocks of electric cars and their determinants at the district level (NUTS 3 regions) are available from the Federal Motor Transport Authority (Kraftfahrt-Bundesamt) for the period 2017 - 2019. A comparative examination of aggregated regional and national predictions provides quantitative information on accuracy gains by allowing for spatial spillovers in forecasting electric mobility.

Keywords: electric mobility, forecasting market diffusion, regional panel data model, spatial interaction

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Authors: Mnasri Faiza, El Ganaoui Mohammed, Khelifa Mourad, Gabsi Slimane

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The main objective of this paper is to describe the hydrothermal behavior through porous material of construction due to temperature gradient. The construction proposed a bi-layer structure which composed of two different materials. The first is a bio-sourced panel named IBS-AKU (inertia system building), the second is the Neopor material. This system (IBS-AKU Neopor) is developed by a Belgium company (Isohabitat). The study suggests a multi-layer structure of the IBS-AKU panel in one dimension. A numerical method was proposed afterwards, by using the finite element method and a refined mesh area to strong gradients. The evolution of temperature fields and the moisture content has been processed.

Keywords: heat transfer, moisture diffusion, porous media, composite IBS-AKU, simulation

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

Abstract:

The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: Himanshu Singh, Rishi Kant, Shantanu Bhattacharya

Abstract:

This paper adopts a top-down approach for mathematical modeling to predict the size reduction from micro to nano-scale through persistent etching. The process is simulated using a finite difference approach. Previously, various researchers have simulated the etching process for 1-D and 2-D substrates. It consists of two processes: 1) Convection-Diffusion in the etchant domain; 2) Chemical reaction at the surface of the particle. Since the process requires analysis along moving boundary, partial differential equations involved cannot be solved using conventional methods. In 1-D, this problem is very similar to Stefan's problem of moving ice-water boundary. A fixed grid method using finite volume method is very popular for modelling of etching on a one and two dimensional substrate. Other popular approaches include moving grid method and level set method. In this method, finite difference method was used to discretize the spherical diffusion equation. Due to symmetrical distribution of etchant, the angular terms in the equation can be neglected. Concentration is assumed to be constant at the outer boundary. At the particle boundary, the concentration of the etchant is assumed to be zero since the rate of reaction is much faster than rate of diffusion. The rate of reaction is proportional to the velocity of the moving boundary of the particle. Modelling of the above reaction was carried out using Matlab. The initial particle size was taken to be 50 microns. The density, molecular weight and diffusion coefficient of the substrate were taken as 2.1 gm/cm3, 60 and 10-5 cm2/s respectively. The etch-rate was found to decline initially and it gradually became constant at 0.02µ/s (1.2µ/min). The concentration profile was plotted along with space at different time intervals. Initially, a sudden drop is observed at the particle boundary due to high-etch rate. This change becomes more gradual with time due to declination of etch rate.

Keywords: particle size reduction, micromixer, FDM modelling, wet etching

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Authors: Ji-Hyok Kim, Il-Gyong Paek, Yong-Jun Kim

Abstract:

We propose a numerical model based on drift-diffusion theory and lattice Boltzmann method (LBM) to analyze the electro-hydrodynamic behavior in low-pressure direct current (DC) glow discharge plasmas. We apply the drift-diffusion theory for 4-species and employ the standard lattice Boltzmann model (SLBM) for the electron, the finite difference-lattice Boltzmann model (FD-LBM) for heavy particles, and the finite difference model (FDM) for the electric potential, respectively. Our results are compared with those of other methods, and emphasize the necessity of a two-dimensional analysis for glow discharge.

Keywords: glow discharge, lattice Boltzmann method, numerical analysis, plasma simulation, electro-hydrodynamic

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Authors: E. Obreque-Slier, F. Orellana-Rodríguez, R. López-Solís

Abstract:

Phenolic compounds are secondary metabolites present in some foods, such as wine. Polyphenols comprise two main groups: flavonoids (anthocyanins, flavanols, and flavonols) and non-flavonoids (stilbenes and phenolic acids). Phenolic acids are low molecular weight non flavonoid compounds that are usually grouped into benzoic (gallic, vanillinic and protocatechuic acids) and cinnamic acids (ferulic, p-coumaric and caffeic acids). Likewise, tannic acid is an important polyphenol constituted mainly by gallic acid. Phenolic compounds are responsible for important properties in foods and drinks, such as color, aroma, bitterness, and astringency. Astringency is a drying, roughing, and sometimes puckering sensation that is experienced on the various oral surfaces during or immediately after tasting foods. Astringency perception has been associated with interactions between flavanols present in some foods and salivary proteins. Despite the quantitative relevance of phenolic acids in food and beverages, there is no information about its effect on salivary proteins and consequently on the sensation of astringency. The objective of this study was assessed the interaction of several phenolic acids (gallic, vanillinic, protocatechuic, ferulic, p-coumaric and caffeic acids) with saliva. Tannic acid was used as control. Thus, solutions of each phenolic acids (5 mg/mL) were mixed with human saliva (1:1 v/v). After incubation for 5 min at room temperature, 15-μL aliquots of the mixtures were dotted on a cellulose membrane and allowed to diffuse. The dry membrane was fixed in 50 g/L trichloroacetic acid, rinsed in 800 mL/L ethanol and stained for protein with Coomassie blue for 20 min, destained with several rinses of 73 g/L acetic acid and dried under a heat lamp. Both diffusion area and stain intensity of the protein spots were semiqualitative estimates for protein-tannin interaction (diffusion test). The rest of the whole saliva-phenol solution mixtures of the diffusion assay were centrifuged and fifteen-μL aliquots of each supernatant were dotted on a cellulose membrane, allowed to diffuse and processed for protein staining, as indicated above. In this latter assay, reduced protein staining was taken as indicative of protein precipitation (precipitation test). The diffusion of the salivary protein was restricted by the presence of each phenolic acids (anti-diffusive effect), while tannic acid did not alter diffusion of the salivary protein. By contrast, phenolic acids did not provoke precipitation of the salivary protein, while tannic acid produced precipitation of salivary proteins. In addition, binary mixtures (mixtures of two components) of various phenolic acids with gallic acid provoked a restriction of saliva. Similar effect was observed by the corresponding individual phenolic acids. Contrary, binary mixtures of phenolic acid with tannic acid, as well tannic acid alone, did not affect the diffusion of the saliva but they provoked an evident precipitation. In summary, phenolic acids showed a relevant interaction with the salivary proteins, thus suggesting that these wine compounds can also contribute to the sensation of astringency.

Keywords: astringency, polyphenols, tannins, tannin-protein interaction

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