Search results for: particle packing model

Authors: Zainab A. Bu Sinnah, David I. Graham

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The Lattice Boltzmann Method has been developed and used to simulate both steady and unsteady fluid flow problems such as turbulent flows, multiphase flow and flows in the vascular system. As an example, the study of blood flow and its properties can give a greater understanding of atherosclerosis and the flow parameters which influence this phenomenon. The blood flow in the vascular system is driven by a pulsating pressure gradient which is produced by the heart. As a very simple model of this, we simulate plane channel flow under periodic forcing. This pulsatile flow is essentially the standard Poiseuille flow except that the flow is driven by the periodic forcing term. Moment boundary conditions, where various moments of the particle distribution function are specified, are applied at solid walls. We used a second-order single relaxation time model and investigated grid convergence using two distinct approaches. In the first approach, we fixed both Reynolds and Womersley numbers and varied relaxation time with grid size. In the second approach, we fixed the Womersley number and relaxation time. The expected second-order convergence was obtained for the second approach. For the first approach, however, the numerical method converged, but not necessarily to the appropriate analytical result. An explanation is given for these observations.

Keywords: Lattice Boltzmann method, single relaxation time, pulsatile flow, moment based boundary condition

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Authors: Jui-Ching Chou

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Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.

Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model

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Authors: Umar Saeed

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Peptidyl-prolyl cis/trans isomerases Par14 and Par17 in humans play crucial roles in diverse cellular processes, including protein folding, chromatin remodeling, DNA binding, ribosome biogenesis, and cell cycle progression. However, the effects of Par14 and Par17 on viral replication have been explored to a limited extent. We first time discovered their influential roles in promoting Hepatitis B Virus replication. In this study, we observed that in the presence of HBx, either Par14 or Par17 could upregulate HBV replication. However, in the absence of HBx, neither Par14 nor Par17 had any effect on replication. Their mechanism of action involves binding to specific motifs within HBc and HBx proteins. Notably, they target the conserved 133Arg-Pro134 (RP) motif of HBc and the 19RP20-28RP29 motifs of HBx. This interaction is fundamental for the stability of HBx, core particles, and HBc. Par14 and Par17 exhibit versatility by binding both outside and inside core particles, thereby facilitating core particle assembly through their participation in HBc dimer-dimer interactions. NAGE and immunoblotting analyses unveiled the binding of Par14/Par17 to core particles. Co-immunoprecipitation experiments further demonstrated the interaction of Par14/Par17 with core particle assembly-defective and dimer-positive HBc-Y132A. It's essential to emphasize that R133 is the key residue in the HBc RP motif that governs their interaction with Par14/Par17. Chromatin immunoprecipitation conducted on HBV-infected cells elucidated the participation of residues S19 and E46/D74 in Par14 and S44 and E71/D99 in Par17 in the recruitment of 133RP134 motif-containing HBc into cccDNA. Depleting PIN4 in liver cell lines results in a significant reduction in cccDNA levels, pgRNA, sgRNAs, HBc, core particle assembly, and HBV DNA synthesis. Notably, parvulin inhibitors like juglone and PiB have proven to be effective in substantially reducing HBV replication. These inhibitors weaken the interaction between HBV core particles and Par14/Par17, underscoring the dynamic nature of this interaction. It's also worth noting that specific Par14/Par17 inhibitors hold promise as potential therapeutic options for chronic hepatitis B.

Keywords: Par14Par17, HBx, HBc, cccDNA, HBV

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Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: Esam Jassim

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Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health. This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption. This study highlights the behavior of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. The influence of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two sub-bituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ration of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3. A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modeled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution. Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7. As an alkaline-earth element, calcium is considered the fundamental element responsible for boiler deficiency since it is the major player in the mechanism of ash slagging process. The mechanism of particle size distribution and mineral species of ash particles are presented using CCSEM and size-segregated ash characteristics. Conclusions are drawn from the analysis of pulverized coal ash generated from a utility-scale boiler.

Keywords: coal combustion, inorganic element, calcium evolution, fluid dynamics

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Authors: M. R. S. Nasuha, K. Azman, H. Azhan, S. A. Senawi, A. Mardhiah

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Studies on Samarium doped glasses possess lot of interest due to their potential applications for high-density optical memory, optical communication device, the design of laser and color display etc. Sm3+ doped borotellurite glasses of the system (70-x) TeO2-20B2O3-10ZnO-xSm2O3 (where x = 0.0, 0.5, 1.0, 1.5, 2.0 and 2.5 mol%) have been prepared using melt-quenching method. Their physical properties such as density, molar volume and oxygen packing density as well as the optical measurements by mean of their absorption and emission characteristic have been carried out at room temperature using UV/VIS and photoluminescence spectrophotometer. The results of physical properties are found to vary with respect to Sm3+ ions content. Meanwhile, three strong absorption peaks are observed and are well resolved in the ultra violet and visible regions due to transitions between the ground state and various excited state of Sm3+ ions. Thus, the photoluminescence spectra exhibit four emission bands from the initial state, which correspond to the 4G5/2 → 6H5/2, 4G5/2 → 6H7/2, 4G5/2 → 6H9/2 and 4G5/2 → 6H11/2 fluorescence transitions at 562 nm, 599 nm, 645 nm and 706 nm respectively.

Keywords: absorption, borotellurite, down-conversion, emission

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Authors: George B. Abaka-Wood, Massimiliano Zanin, Jonas Addai-Mensah, William Skinner

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The versatility of froth flotation has made it vital in the beneficiation of rare earth elements minerals from either high or low-grade ores. There has been a significant increase in the quantity of iron oxide silicate-rich tailings generated from the extraction of primary commodities such as copper and gold in Australia, which have been identified to contain very low-grade rare earth oxides (≤ 1%). There is a vast knowledge gap in the beneficiation of rare earth oxides from such tailings. The aim of this research is to investigate the feasibility of using fatty acids as collectors for the flotation recovery and upgrade of rare earth oxides from selected iron-oxide silicate-rich tailings. Two forms of fatty acid collectors (oleic acid and sodium oleate) were tested in this investigation. Flotation tests were carried out using a 1.2 L Denver D-12 cell. The effects of pulp pH, fatty acid dosage, particle size distribution (-150 +75 µm, -75 +38 µm and -38 µm) and conventional depressants (sodium silicate and starch) dosage on flotation recovery of rare earth oxides were investigated. A comparison of the flotation results indicated that sodium oleate was the more efficient fatty acid for rare earth oxides flotation at all the pulp pH investigated. The flotation performance was found to be particle size-dependent. Both sodium silicate and starch were unselective in decreasing the recovery of iron oxides and silicate minerals, respectively with the corresponding decrease in rare earth oxides recovery. Generally, iron oxides and silicate minerals formed the substantial fraction of the flotation concentrates obtained, both in the absence and presence of depressants, resulting in a generally low rare earth oxides upgrade, even though rare earth oxides recoveries were high. The flotation tests carried out on the tailings sample suggest the feasibility of rare earth oxides recovery using fatty acids, although particle size distribution and minerals liberation are key limiting factors in achieving selective rare earth oxides upgrade.

Keywords: depressants, flotation, oleic acid, sodium oleate

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

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Authors: R. N. Astya, E. S. Nugraha, S. P. Nurheni, Hoerudin

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Vitamin A deficiency remains to be among the major malnutrition problems in Indonesia. Vitamin A is a fat-soluble vitamin which renders it difficult to be fortified in water-based foods and beverages. Furthermore, its low solubility and stability in aqueous system may limit its bioaccessibility in the gastrointestinal tract. Nanoemulsification of vitamin A may solve these problems. The objective of this study was to investigate bioaccessibility of vitamin A (retinyl palmitate/RP) nanoemulsion as influenced by two types of carrier oil (Virgin Coconut Oil/VCO and corn oil/CO) and surfactant concentrations (polysorbate 20/Tween 20 3% and 6%). Oil in water (o/w) nanoemulsions of vitamin A was produced through a combination of high shear-high pressure homogenization technique. The results showed that RP-VCO nanoemulsions were 121.62 nm (3%) and 115.40 (6%) nm in particle size, whereas RP-CO nanoemulsions were 154.72 nm (3%) and 134.00 nm (6%) in particle size. As for VCO nanoemulsions, the bioaccessibility of vitamin A was shown to be 89.84% and 55.32%, respectively. On the other hand, CO nanoemulsions produced vitamin A bioaccessibility of 53.66% and 44.85%, respectively. In general, VCO nanoemulsions showed better bioaccessibility of vitamin A than CO nanoemulsions. In this study, RP-VCO nanoemulsion with 3% Tween 20 had the highest ζ-potential value (-26.5 mV) and produced the highest bioaccessibility of vitamin A (89.84%, P<0.05). Additionally, the vitamin A nanoemulsion was stable even for after a week of freeze and thaw treatment. Following the freeze and thaw treatment, the vitamin A nanoemulsion showed good stability without aggregation and separation. These results would be useful for designing effective vitamin A delivery systems for food and beverage applications.

Keywords: bioaccessibility, carrier oil, surfactant, vitamin A nanoemulsion

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Authors: Marzia Hoque Tania, Oishy Roy, ASW Kurny, Fahmida Gulshan

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This paper presents results of the investigation on the characterization of silica sand of northern region of Bangladesh on the basis of material composition, particle shape, and size, density, transportation, crystallinity, etc. before and after upgradation. The raw sand samples collected from Nilphamari and Lalmonirhat district were studied and compared for the prospect silica as a high valued commodity rather than heavy minerals. The raw sand particles were colorful in appearance with varying particle size distribution. Scanning Electron Microscopy (SEM) showed uniformity in grain size and mineralogical composition. X-ray fluorescence (XRF) analysis indicated the silica content of the as-received sample to be 75%. Thermogravimetric and Differential Thermal Analysis (DTA) did not detect the presence of any organic material. These tests revealed the sample to be alpha-quartz. Samples were washed with organic and inorganic acid with a combination of varying rotation speed, concentration, solid-liquid ratio. Experiments showed the silica content could be enhanced to more than 85% by washing with 15% sulphuric acid in room temperature. Beneficiation can be improved in further work considering the effect of varying temperature or advanced technology.

Keywords: beneficiation, characterization, commercial grade sand, glass sand, silica, upgradation

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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Authors: Adji Achmad Rinaldo Fernandes

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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

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Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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Authors: Dileep Maarisetty, Janaki Komandur, Saroj S. Baral

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In the current work, photocatalytic degradation of phenol was carried both in UV and visible light to find the slowest step that is limiting the rate of photo-degradation process. Characterization such as XRD, SEM, FT-IR, TEM, XPS, UV-DRS, PL, BET, UPS, ESR and zeta potential experiments were conducted to assess the credibility of catalysts in boosting the photocatalytic activity. To explore the synergy, TiO₂ was doped with graphene and alumina. The orbital hybridization with alumina doping (mediated by graphene) resulted in higher electron transfer from the conduction band of TiO₂ to alumina surface where oxygen reduction reactions (ORR) occur. Besides, the doping of alumina and graphene introduced defects into Ti lattice and helped in improving the adsorptive properties of modified photo-catalyst. Results showed that these defects promoted the oxygen reduction reactions (ORR) on the catalyst’s surface. ORR activity aims at producing reactive oxygen species (ROS). These ROS species oxidizes the phenol molecules which is adsorbed on the surface of photo-catalysts, thereby driving the photocatalytic reactions. Since mass transfer is considered as rate limiting step, various mathematical models were applied to the experimental data to probe the best fit. By varying the parameters, it was found that intra-particle diffusion was the slowest step in the degradation process. Lagergren model gave the best R² values indicating the nature of rate kinetics. Similarly, different adsorption isotherms were employed and realized that Langmuir isotherm suits the best with tremendous increase in uptake capacity (mg/g) of TiO₂-rGO-Al₂O₃ as compared undoped TiO₂. This further assisted in higher adsorption of phenol molecules. The results obtained from experimental, kinetic modelling and adsorption isotherms; it is concluded that apart from changes in surface, optoelectronic and morphological properties that enhanced the photocatalytic activity, the intra-particle diffusion within the catalyst’s pores serve as rate-limiting step in deciding the fate of photo-catalytic degradation of phenol.

Keywords: ORR, phenol degradation, photo-catalyst, rate kinetics

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Authors: Phanindra Prasad Thummala, Umran Tezcan Un, Ahmet Ozan Celik

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Removal of CO₂ by MEA (monoethanolamine) in structured packing columns depends highly on the gas-liquid interfacial area and film thickness (liquid load). CFD (computational fluid dynamics) is used to find the interfacial area, film thickness and their impact on mass transfer in gas-liquid flow effectively in any column geometry. In general modeling approaches used in CFD derive mass transfer parameters from standard correlations based on penetration or surface renewal theories. In order to avoid the effect of assumptions involved in deriving the correlations and model the mass transfer based solely on fluid properties, state of art approaches like one fluid formulation is useful. In this work, the one fluid formulation was implemented and evaluated for modeling the physical mass transfer of CO₂ by N₂O analogy in OpenFOAM CFD software. N₂O analogy avoids the effect of chemical reactions on absorption and allows studying the amount of CO₂ physical mass transfer possible in a given geometry. The computational domain in the current study was a flat plate with gas and liquid flowing in the countercurrent direction. The effect of operating parameters such as flow rate, the concentration of MEA and angle of inclination on the physical mass transfer is studied in detail. Liquid side mass transfer coefficients obtained by simulations are compared to the correlations available in the literature and it was found that the one fluid formulation was effectively capturing the effects of interface surface instabilities on mass transfer coefficient with higher accuracy. The high mesh refinement near the interface region was found as a limiting reason for utilizing this approach on large-scale simulations. Overall, the one fluid formulation is found more promising for CFD studies involving the CO₂ mass transfer.

Keywords: one fluid formulation, CO₂ absorption, liquid mass transfer coefficient, OpenFOAM, N₂O analogy

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Authors: Yi-Xuan Huang, Kung-Ming Chung, Ping-Han Chung

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Pressure sensitive paint (PSP), which relies on the oxygen quenching of a luminescent molecule, is an optical technique used in wind-tunnel models. A full-field pressure pattern with low aerodynamic interference can be obtained, and it is becoming an alternative to pressure measurements using pressure taps. In this study, a polymer-ceramic PSP was used, using toluene as a solvent. The porous particle and polymer were silica gel (SiO₂) and RTV-118 (3g:7g), respectively. The compound was sprayed onto the model surface using a spray gun. The absorption and emission spectra for Ru(dpp) as a luminophore were respectively 441-467 nm and 597 nm. A Revox SLG-55 light source with a short-pass filter (550 nm) and a 14-bit CCD camera with a long-pass (600 nm) filter were used to illuminate PSP and to capture images. This study determines surface pressure patterns for a forebody of an AGARD B model in a compressible flow. Since there is no experimental data for surface pressure distributions available, numerical simulation is conducted using ANSYS Fluent. The lift and drag coefficients are calculated and in comparison with the data in the open literature. The experiments were conducted using a transonic wind tunnel at the Aerospace Science and Research Center, National Cheng Kung University. The freestream Mach numbers were 0.83, and the angle of attack ranged from -4 to 8 degree. Deviation between PSP and numerical simulation is within 5%. However, the effect of the setup of the light source should be taken into account to address the relative error.

Keywords: pressure sensitive paint, forebody, surface pressure, compressible flow

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Authors: M. Jerold, V. Sivasubramanian

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This study reports the removal of Malachite Green (MG) from simulated wastewater by using marine macro algae Ulva lactuca. Batch biosorption experiments were carried out to determine the biosorption capacity. The biosorption capacity was found to be maximum at pH 10. The effect of various other operation parameters such as biosorbent dosage, initial dye concentration, contact time and agitation was also investigated. The equilibrium attained at 120 min with 0.1 g/L of biosorbent. The isotherm experimental data fitted well with Langmuir Model with R² value of 0.994. The maximum Langmuir biosorption capacity was found to be 76.92 mg/g. Further, Langmuir separation factor RL value was found to be 0.004. Therefore, the adsorption is favorable. The biosorption kinetics of MG was found to follow pseudo second-order kinetic model. The mechanistic study revealed that the biosorption of malachite onto Ulva lactuca was controlled by film diffusion. The solute transfer in a solid-liquid adsorption process is characterized by the film diffusion and/or particle diffusion. Thermodynamic study shows ΔG° is negative indicates the feasibility and spontaneous nature for the biosorption of malachite green. The biosorbent was characterized using Scanning Electron Microscopy, Fourier Transform Infrared Spectroscopy, and elemental analysis (CHNS: Carbon, Hydrogen, Nitrogen, Sulphur). This study showed that Ulva lactuca can be used as promising biosorbent for the removal of MG from wastewater.

Keywords: biosorption, Ulva lactuca, wastewater, malachite green, isotherm, kinetics

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Chun-Lang Chang, Chun-Kai Liu

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In this study, the patients that have undergone total knee replacement surgery from the 2010 National Health Insurance database were adopted as the study participants. The important factors were screened and selected through literature collection and interviews with physicians. Through the Cross Entropy Method (CE), Genetic Algorithm Logistic Regression (GALR), and Particle Swarm Optimization (PSO), the weights of the factors were obtained. In addition, the weights of the respective algorithms, coupled with the Excel VBA were adopted to construct the Case Based Reasoning (CBR) system. The results through statistical tests show that the GALR and PSO produced no significant differences, and the accuracy of both models were above 97%. Moreover, the area under the curve of ROC for these two models also exceeded 0.87. This study shall serve as a reference for medical staff as an assistance for clinical assessment of infections in order to effectively enhance medical service quality and efficiency, avoid unnecessary medical waste, and substantially contribute to resource allocations in medical institutions.

Keywords: Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization, Total Knee Replacement Surgery

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Authors: Tamer El-Messery, Beraat Ozcelik

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This study aimed to produce functional yogurt supplemented with microencapsulated krill oil as a source of omega 3, which is known, to maintain the normal brain function, reduce the risk of cancer, and preventing cardiovascular disease. Krill oil was mixed with black cumin oil (1:1) in order to increase its oxidative stability. β-caroteine (10 mg/100 ml) was used as a standard antioxidant. Maltodextrin (MD) was mixed with whey protein concentrate (WPC) and gum Arabic (GA) at the ratio of 8:2:0.5 ratios and used for microencapsulation of single or mixed oils. The microcapsules were dried by freeze and spray drying in order to maximize encapsulation efficiency and minimize lipid oxidation. The feed emulsions used for particle production were characterized for stability, viscosity and particle size, zeta potential, and oxidative stability. The oxidative stability for mixed krill oil and black cumin oil was the highest. The highest encapsulation efficiency was obtained using spray drying, which also showed the highest oxidative stability. The addition of encapsulated krill and black cumin oils (1:1) powder in yogurt manufacture reduced slightly effects on the development of acidity, textural parameters, and water holding capacity of yogurt as compared to control.

Keywords: Krill oil, black cumin oil, micro-encapsulation, oxidative stability, functional yogurt

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Harish K. Chandrawanshi, Mithun S. Rajput, Neelima Choure, Purnima Dey Sarkar, Shailesh Jain

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The present research study aimed to fabricate and evaluate biodegradable nanoparticles of aromatase inhibitor letrozole, intended for breast cancer therapy. Letrozole loaded poly(D,L-lactide-co-glycolide acid) nanoparticles were prepared by solvent evaporation method using dichlorometane as solvent (oil phase) and polyvinyl alcohol (PVA) as aqueous phase. Prepared nanoparticles were characterized by particle size, infrared spectra, drug loading efficiency, drug entrapment efficiency and in vitro release and also evaluated for in vivo anticancer activity. The high speed homogenizer was used to produce stable nanoparticles of mean size range 198.35 ± 0.04 nm with high entrapment efficiency (69.86 ± 2.78%). Percentage of drug and homogenization speed significantly influenced the particle size, entrapment efficiency and release (p<0.05). The nanoparticles show significant in vivo anticancer activity against Ehrlich ascites carcinoma in mice. The significant system sustained the release of letrozole drug effectively and further investigation could exhibit its potential usefulness in breast cancer therapy.

Keywords: breast cancer/therapy, letrozole, nanoparticles, PLGA

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Authors: Chun-Yu Chen, Kua-Rong Wu, Yu-Cheng Chen, Perng-Jy Tsai

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Cooking fumes are known containing polycyclic aromatic hydrocarbons (PAHs) and aldehydes, and some of them have been proven carcinogenic or possibly carcinogenic to humans. Considering their chronic health effects, long-term exposure data is required for assessing cooking workers’ lifetime health risks. Previous exposure assessment studies, due to both time and cost constraints, mostly were based on the cross-sectional data. Therefore, establishing a long-term exposure data has become an important issue for conducting health risk assessment for cooking workers. An approach was proposed in this study. Here, the generation rates of both PAHs and aldehydes from a cooking process were determined by placing a sampling train exactly under the under the exhaust fan under the both the total enclosure condition and normal operating condition, respectively. Subtracting the concentration collected by the former (representing the total emitted concentration) from that of the latter (representing the hood collected concentration), the fugitive emitted concentration was determined. The above data was further converted to determine the generation rates based on the flow rates specified for the exhaust fan. The determinations of the above generation rates were conducted in a testing chamber with a selected cooking process (deep-frying chicken nuggets under 3 L peanut oil at 200°C). The sampling train installed under the exhaust fan consisted respectively an IOM inhalable sampler with a glass fiber filter for collecting particle-phase PAHs, followed by a XAD-2 tube for gas-phase PAHs. The above was also used to sample aldehydes, however, installed with a filter pre-coated with DNPH, and followed by a 2,4-DNPH-cartridge for collecting particle-phase and gas-phase aldehydes, respectively. PAHs and aldehydes samples were analyzed by GC/MS-MS (Agilent 7890B), and HPLC-UV (HITACHI L-7100), respectively. The obtained generation rates of both PAHs and aldehydes were applied to the near-field/ far-field exposure model to estimate the exposures of cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration). For validating purposes, both PAHs and aldehydes samplings were conducted simultaneously using the same sampling train at both near-field and far-field sites of the testing chamber. The sampling results, together with the use of the mixed-effect model, were used to calibrate the estimated near-field/ far-field exposures. In the present study, the obtained emission rates were further converted to emission factor of both PAHs and aldehydes according to the amount of food oil consumed. Applying the long-term food oil consumption records, the emission rates for both PAHs and aldehydes were determined, and the long-term exposure databanks for cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration) were then determined. Results show that the proposed approach was adequate to determine the generation rates of both PAHs and aldehydes under various fan exhaust flow rate conditions. The estimated near-field/ far-field exposures, though were significantly different from that obtained from the field, can be calibrated using the mixed effect model. Finally, the established long-term data bank could provide a useful basis for conducting long-term exposure assessments for cooking workers exposed to PAHs and aldehydes.

Keywords: aldehydes, cooking oil fumes, long-term exposure assessment, modeling, polycyclic aromatic hydrocarbons (PAHs)

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Authors: Nabil Saad, David Morgan, Manish Gupta

Abstract:

Visibility has become a key component of air quality and is regulated in many areas by environmental laws such as the EPA Clean Air Act and Regional Haze Rule. Typically, visibility is calculated by estimating the optical absorption and scattering of both gases and aerosols. A major component of the aerosols’ climatic effect is due to their scattering and absorption of solar radiation, which are governed by their optical and physical properties. However, the accurate assessment of this effect on global warming, climate change, and air quality is made difficult due to uncertainties in the calculation of single scattering albedo (SSA). Experimental complications arise in the determination of the single scattering albedo of an aerosol particle since it requires the simultaneous measurement of both scattering and extinction. In fact, aerosol optical absorption, in particular, is a difficult measurement to perform, and it’s often associated with large uncertainties when using filter methods or difference methods. In this presentation, we demonstrate the use of a new open-path Optical Extinction Analyzer (OEA) in conjunction with a nephelometer and two particle sizers, emphasizing the benefits that co-employment of the OEA offers to derive the complex refractive index of aerosols and their single scattering albedo parameter. Various use cases, data reproducibility, and instrument calibration will also be presented to highlight the value proposition of this novel Open-Path OEA.

Keywords: aerosols, extinction, visibility, albedo

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: S. Lekhavat, U. Srimongkoluk, P. Ratanachamnong, G. Laungsopapun

Abstract:

Quercetin was encapsulated with whey protein and high methoxyl pectin by spray drying technique. Feed solution, consisting of 0.1875 0.125 and 0.0625 % w/w quercetin, respectively, was prepared and then sprays at outlet temperature of 70, 80 and 90 °C. Quercetin contents either in feed solution or in spray dried powder were determined by HPLC technique. Physicochemical properties such as viscosity and total soluble solid of feed solution as well as moisture content and water activity of spray dried powder were examined. Particle morphology was imaged using scanning electron microscope. The results showed that feed solution has total soluble solid and viscosity in range of 1.73-5.60 ºBrix and 2.58-8.15 cP, in that order. After spray drying, the moisture content and water activity value of powder are in range of 0.58-2.72 % and 0.18-0.31, respectively. Quercetin content in dried sample increased along with outlet drying temperature but decreased when total soluble solid increased. It was shown that particles are likely to shrivel when spray drying at high temperature. The suggested conditions for encapsulation of quercetin are feed solution with 0.0625 % (w/w) quercetin and spray drying at drying outlet temperature of 90°C.

Keywords: drying temperature, particle morphology, spray drying, quercetin

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Authors: Tokuei Sako

Abstract:

The ground and low-lying singly-excited states of He and He-like atomic ions have been studied by the Full Configuration Interaction (FCI) method focusing on the angular correlation between two electrons in the studied systems. The two-electron angle density distribution obtained by integrating the square-modulus of the FCI wave function over the coordinates other than the interelectronic angle shows a distinct trend between the singlet-triplet pair of states for different values of the nuclear charge Zn. Further, both of these singlet and triplet distributions tend to show an increasingly stronger dependence on the interelectronic angle as Zn increases, in contrast to the well-known fact that the correlation energy approaches towards zero for increasing Zn. This controversial observation has been rationalized on the basis of the recently introduced concept of so-called conjugate Fermi holes.

Keywords: He-like systems, angular correlation, configuration interaction wave function, conjugate Fermi hole

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Authors: Sophie Herr, Antoine Leybros, Yves Barre, Sergey Nikitenko, Rachel Pflieger

Abstract:

The proportion of soil contaminated by a wide range of pollutants (heavy metals, PCBs, pesticides, etc.) of anthropogenic origin is constantly increasing, and it is becoming urgent to address this issue. Among remediation methods, soil washing is an effective, relatively fast, and widely used process. This study assesses its coupling with ultrasound: indeed, sonication induces the formation of cavitation bubbles in solution that enhance local mass transfer through agitation and particle erosion. The removal of target toxic elements Ni(II) and Zn(II) from vermiculite clay has been studied under 20 kHz ultrasound and silent conditions. Several acids were tested, and HCl was chosen as the solvent. The effects of solid/liquid ratio and particle size were investigated. Metal repartition in the clay has been followed by Tessier's sequential extraction procedure. The results showed that more metal elements bound to the challenging residual phase were desorbed with 20 kHz ultrasound than in silent conditions. This supports the promising application of ultrasound for heavy metal desorption in difficult conditions. Further experiments were performed at high-frequency US (362 kHz), and it was shown that fragmentation of the vermiculite particles is then limited, while positive effects of US in the decontamination are kept.

Keywords: desorption, heavy metals, ultrasound, vermiculite

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

Abstract:

Achieving precise radiotherapy through carbon therapy necessitates the accurate monitoring of radiation dose distribution within the patient's body. This process is pivotal for targeted tumor treatment, minimizing harm to healthy tissues, and enhancing overall treatment effectiveness while reducing the risk of side effects. In our investigation, we adopted a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo (MC) simulations. Initially, Geant4 simulations were employed to extract the initial positions of secondary particles generated during interactions between carbon ions and water, including protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we explored the relationship between the carbon ion beam and these secondary particles. Interaction vertex imaging (IVI) proves valuable for monitoring dose distribution during carbon therapy, providing information about secondary particle locations and abundances, particularly protons. The IVI method relies on charged particles produced during ion fragmentation to gather range information by reconstructing particle trajectories back to their point of origin, known as the vertex. In the context of carbon ion therapy, our simulation results indicated a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the unique elongated geometry of the target, hindering the straightforward transmission of forward-generated protons. Consequently, the limited protons that did emerge predominantly originated from points close to the target entrance. Fragment (protons) trajectories were approximated as straight lines, and a beam back-projection algorithm, utilizing interaction positions recorded in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitor secondary proton doses, interaction vertex imaging

Procedia PDF Downloads 78