Search results for: particle filtering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1960

Search results for: particle filtering

1390 Thermal Energy Storage Based on Molten Salts Containing Nano-Particles: Dispersion Stability and Thermal Conductivity Using Multi-Scale Computational Modelling

Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

Abstract:

New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

Procedia PDF Downloads 175
1389 Experimental Investigation of the Aeroacoustics Field for a Rectangular Jet Impinging on a Slotted Plate: Stereoscopic Particle Image Velocimetry Measurement before and after the Plate

Authors: Nour Eldin Afyouni, Hassan Assoum, Kamel Abed-Meraim, Anas Sakout

Abstract:

The acoustic of an impinging jet holds significant importance in the engineering field. In HVAC systems, the jet impingement, in some cases, generates noise that destroys acoustic comfort. This paper presents an experimental study of a rectangular air jet impinging on a slotted plate to investigate the correlation between sound emission and turbulence dynamics. The experiment was conducted with an impact ratio L/H = 4 and a Reynolds number Re = 4700. The survey shows that coherent structures within the impinging jet are responsible for self-sustaining tone production. To achieve this, a specific experimental setup consisting of two simultaneous Stereoscopic Particle Image Velocimetry (S-PIV) measurements was developed to track vortical structures both before and after the plate, in addition to acoustic measurements. The results reveal a significant correlation between acoustic waves and the passage of coherent structures. Variations in the arrangement of vortical structures between the upstream and downstream sides of the plate were observed. This analysis of flow dynamics can enhance our understanding of slot noise.

Keywords: impinging jet, coherent structures, SPIV, aeroacoustics

Procedia PDF Downloads 68
1388 A New Approach of Preprocessing with SVM Optimization Based on PSO for Bearing Fault Diagnosis

Authors: Tawfik Thelaidjia, Salah Chenikher

Abstract:

Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

Procedia PDF Downloads 419
1387 Characterization of Coal Fly Ash with Potential Use in the Manufacture Geopolymers to Solidify/Stabilize Heavy Metal Ions

Authors: P. M. Fonseca Alfonso, E. A. Murillo Ruiz, M. Diaz Lagos

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Understanding the physicochemical properties and mineralogy of fly ash from a particular source is essential for to protect the environment and considering its possible applications, specifically, in the production of geopolymeric materials that solidify/stabilize heavy metals ions. The results of the characterization of three fly ash samples are shown in this paper. The samples were produced in the TERMOPAIPA IV thermal power plant in the State of Boyaca, Colombia. The particle size distribution, chemical composition, mineralogy, and molecular structure of three samples were analyzed using laser diffraction, X-ray fluorescence, inductively coupled plasma mass spectrometry, X-ray diffraction, and infrared spectroscopy respectively. The particle size distribution of the three samples probably ranges from 0.128 to 211 μm. Approximately 59 elements have been identified in the three samples. It is noticeable that the ashes are made up of aluminum and silicon compounds. Besides, the iron phase in low content was also found. According to the results found in this study, the fly ash samples type F has a great potential to be used as raw material for the manufacture of geopolymers with potential use in the stabilization/solidification of heavy metals; mainly due to the presence of amorphous aluminosilicates typical of this type of ash, which react effectively with alkali-activator.

Keywords: fly ash, geopolymers, molecular structure, physicochemical properties.

Procedia PDF Downloads 103
1386 Solid Lipid Nanoparticles of Levamisole Hydrochloride

Authors: Surendra Agrawal, Pravina Gurjar, Supriya Bhide, Ram Gaud

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Levamisole hydrochloride is a prominent anticancer drug in the treatment of colon cancer but resulted in toxic effects due poor bioavailability and poor cellular uptake by tumor cells. Levamisole is an unstable drug. Incorporation of this molecule in solid lipids may minimize their exposure to the aqueous environment and partly immobilize the drug molecules within the lipid matrix-both of which may protect the encapsulated drugs against degradation. The objectives of the study were to enhance bioavailability by sustaining drug release and to reduce the toxicities associated with the therapy. Solubility of the drug was determined in different lipids to select the components of Solid Lipid Nanoparticles (SLN). Pseudoternary phase diagrams were created using aqueous titration method. Formulations were subjected to particle size and stability evaluation to select the final test formulations which were characterized for average particle size, zeta potential, and in-vitro drug release and percentage transmittance to optimize the final formulation. SLN of Levamisole hydrochloride was prepared by Nanoprecipitation method. Glyceryl behenate (Compritol 888 ATO) was used as core comprising of Tween 80 as surfactant and Lecithin as co-surfactant in (1:1) ratio. Entrapment efficiency (EE) was found to be 45.89%. Particle size was found in the range of 100-600 nm. Zeta potential of the formulation was -17.0 mV revealing the stability of the product. In-vitro release study showed that 66 % drug released in 24 hours in pH 7.2 which represent that formulation can give controlled action at the intestinal environment. In pH 5.0 it showed 64% release indicating that it can even release drug in acidic environment of tumor cells. In conclusion, results revealed SLN to be a promising approach to sustain the drug release so as to increase bioavailability and cellular uptake of the drug with reduction in toxic effects as dose has been reduced with controlled delivery.

Keywords: SLN, nanoparticulate delivery of levamisole, pharmacy, pharmaceutical sciences

Procedia PDF Downloads 420
1385 A Semantic E-Learning and E-Assessment System of Learners

Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

Abstract:

The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

Procedia PDF Downloads 315
1384 Influence of Microparticles in the Contact Region of Quartz Sand Grains: A Micro-Mechanical Experimental Study

Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

Abstract:

The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

Procedia PDF Downloads 180
1383 Least-Square Support Vector Machine for Characterization of Clusters of Microcalcifications

Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

Abstract:

Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

Procedia PDF Downloads 342
1382 Protein-Enrichment of Oilseed Meals by Triboelectrostatic Separation

Authors: Javier Perez-Vaquero, Katryn Junker, Volker Lammers, Petra Foerst

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There is increasing importance to accelerate the transition to sustainable food systems by including environmentally friendly technologies. Our work focuses on protein enrichment and fractionation of agricultural side streams by dry triboelectrostatic separation technology. Materials are fed in particulate form into a system dispersed in a highly turbulent gas stream, whereby the high collision rate of particles against surfaces and other particles greatly enhances the electrostatic charge build-up over the particle surface. A subsequent step takes the charged particles to a delimited zone in the system where there is a highly uniform, intense electric field applied. Because the charge polarity acquired by a particle is influenced by its chemical composition, morphology, and structure, the protein-rich and fiber-rich particles of the starting material get opposite charge polarities, thus following different paths as they move through the region where the electric field is present. The output is two material fractions, which differ in their respective protein content. One is a fiber-rich, low-protein fraction, while the other is a high-protein, low-fiber composition. Prior to testing, materials undergo a milling process, and some samples are stored under controlled humidity conditions. In this way, the influence of both particle size and humidity content was established. We used two oilseed meals: lupine and rapeseed. In addition to a lab-scale separator to perform the experiments, the triboelectric separation process could be successfully scaled up to a mid-scale belt separator, increasing the mass feed from g/sec to kg/hour. The triboelectrostatic separation technology opens a huge potential for the exploitation of so far underutilized alternative protein sources. Agricultural side-streams from cereal and oil production, which are generated in high volumes by the industries, can further be valorized by this process.

Keywords: bench-scale processing, dry separation, protein-enrichment, triboelectrostatic separation

Procedia PDF Downloads 172
1381 Scale Effects on the Wake Airflow of a Heavy Truck

Authors: Aude Pérard Lecomte, Georges Fokoua, Amine Mehel, Anne Tanière

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Air quality in urban areas is deteriorated by pollution, mainly due to the constant increase of the traffic of different types of ground vehicles. In particular, particulate matter pollution with important concentrations in urban areas can cause serious health issues. Characterizing and understanding particle dynamics is therefore essential to establish recommendations to improve air quality in urban areas. To analyze the effects of turbulence on particulate pollutants dispersion, the first step is to focus on the single-phase flow structure and turbulence characteristics in the wake of a heavy truck model. To achieve this, Computational Fluid Dynamics (CFD) simulations were conducted with the aim of modeling the wake airflow of a full- and reduced-scale heavy truck. The Reynolds Average Navier-Stokes (RANS) approach with the Reynolds Stress Model (RSM)as the turbulence model closure was used. The simulations highlight the apparition of a large vortex coming from the under trailer. This vortex belongs to the recirculation region, located in the near-wake of the heavy truck. These vortical structures are expected to have a strong influence on particle dynamics that are emitted by the truck.

Keywords: CDF, heavy truck, recirculation region, reduced scale

Procedia PDF Downloads 201
1380 A Two-Stage Airport Ground Movement Speed Profile Design Methodology Using Particle Swarm Optimization

Authors: Zhang Tianci, Ding Meng, Zuo Hongfu, Zeng Lina, Sun Zejun

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Automation of airport operations can greatly improve ground movement efficiency. In this paper, we study the speed profile design problem for advanced airport ground movement control and guidance. The problem is constrained by the surface four-dimensional trajectory generated in taxi planning. A decomposed approach of two stages is presented to solve this problem efficiently. In the first stage, speeds are allocated at control points which ensure smooth speed profiles can be found later. In the second stage, detailed speed profiles of each taxi interval are generated according to the allocated control point speeds with the objective of minimizing the overall fuel consumption. We present a swarm intelligence based algorithm for the first-stage problem and a discrete variable driven enumeration method for the second-stage problem since it only has a small set of discrete variables. Experimental results demonstrate the presented methodology performs well on real world speed profile design problems.

Keywords: airport ground movement, fuel consumption, particle swarm optimization, smoothness, speed profile design

Procedia PDF Downloads 567
1379 Studies on Organic and Inorganic Micro/Nano Particle Reinforced Epoxy Composites

Authors: Daniel Karthik, Vijay Baheti, Jiri Militky, Sundaramurthy Palanisamy

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Fibre based nano particles are presently considered as one of the potential filler materials for the improvement of mechanical and physical properties of polymer composites. Due to high matrix-filler interfacial area there will be uniform and homogeneous dispersion of nanoparticles. In micro/nano filler reinforced composites, resin material is usually tailored by organic or inorganic nanoparticles to have improved matrix properties. The objective of this study was to compare the potential of reinforcement of different organic and inorganic micro/nano fillers in epoxy composites. Industrial and agricultural waste of fibres like Agave Americana, cornhusk, jute, basalt, carbon, glass and fly ash was utilized to prepare micro/nano particles. Micro/nano particles were obtained using high energy planetary ball milling process in dry condition. Milling time and ball size were kept constant throughout the ball milling process. Composites were fabricated by hand lay method. Particle loading was kept constant to 3% wt. for all composites. In present study, loading of fillers was selected as 3 wt. % for all composites. Dynamic mechanical properties of the nanocomposite films were performed in three-point bending mode with gauge length and sample width of 50 mm and 10 mm respectively. The samples were subjected to an oscillating frequency of 1 Hz, 5 Hz and 10 Hz and 100 % oscillating amplitude in the temperature ranges of 30°C to 150°C at the heating rate of 3°C/min. Damping was found to be higher with the jute composites. Amongst organic fillers lowest damping factor was observed with Agave Americana particles, this means that Agave americana fibre particles have betters interface adhesion with epoxy resin. Basalt, fly ash and glass particles have almost similar damping factors confirming better interface adhesion with epoxy.

Keywords: ball milling, damping factor, matrix-filler interface, particle reinforcements

Procedia PDF Downloads 255
1378 A Comparative Study on the Thermophysical and Lubricity Characteristics of Multiwall Carbon Nanotube/Oil and Nanoclay/Oil Nanofluids

Authors: H. Singh, H. Bhowmick

Abstract:

Now-a-days, particle based lubricants have been widely used to enhance the lubrication performance. Use of tailor made micro/nanofluids can reduce the friction losses and dissipate heat in a better way. Use of Carbon Nanotubes (CNTs) has gained interests because of its structure that can endure much better in a system mechanically or thermally in comparison to any other additive in oil. On the other hand, nanoclays have been characterized mechanically and tribologically for the use of clay/polymer composite, and they have been gaining huge interest. Hence it is interesting to be investigated the effect of nanoclays as additive in oil. Thermophysical characteristics of lubricant play a predominant role in defining the friction and wear characteristics of lubricated contacts. However, very limited studies have been carried out to correlate the thermophysical properties of nanolubricants with their lubricity characteristics. Besides, most of the lubricant formulations till dates are found to be optimized for steel/steel contacts. In the present study, Multiwall Carbon Nanotube (MWCNT) and nanoclay are used as particle additives in mineral oil to develop nanofluids of various concentrations. The prepared lubricants are tested for their rheological, thermal and lubricity characteristics under aluminium-steel contacts. From the thermophysical investigation, it is observed that nanoclay particles significantly improve the viscosity of lubricant with an insignificant improvement in thermal conductivity. On the other hand, MWCNT particles moderately increase the viscosity but significantly increase the thermal conductivity of the base oil. Frictional responses of the nanofluids are characterized using a Pin-on-Disc tribometer which reveal some interesting facts. The findings from this study will greatly aid in formulating the particle based lubricants for cutting fluid in metal forming industries as well as fully developed nanolubricants for aluminium and Aluminium Metal Matrix Composite (AMMC) tribocontact for the use in the automotive and their allied industries.

Keywords: MWCNT, Multiwall Carbon Nanotube, nanoclay, nanolubricant, rheology, thermal conductivity

Procedia PDF Downloads 120
1377 Effect of Helical Flow on Separation Delay in the Aortic Arch for Different Mechanical Heart Valve Prostheses by Time-Resolved Particle Image Velocimetry

Authors: Qianhui Li, Christoph H. Bruecker

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Atherosclerotic plaques are typically found where flow separation and variations of shear stress occur. Although helical flow patterns and flow separations have been recorded in the aorta, their relation has not been clearly clarified and especially in the condition of artificial heart valve prostheses. Therefore, an experimental study is performed to investigate the hemodynamic performance of different mechanical heart valves (MHVs), i.e. the SJM Regent bileaflet mechanical heart valve (BMHV) and the Lapeyre-Triflo FURTIVA trileaflet mechanical heart valve (TMHV), in a transparent model of the human aorta under a physiological pulsatile right-hand helical flow condition. A typical systolic flow profile is applied in the pulse-duplicator to generate a physiological pulsatile flow which thereafter flows past an axial turbine blade structure to imitate the right-hand helical flow induced in the left ventricle. High-speed particle image velocimetry (PIV) measurements are used to map the flow evolution. A circular open orifice nozzle inserted in the valve plane as the reference configuration initially replaces the valve under investigation to understand the hemodynamic effects of the entered helical flow structure on the flow evolution in the aortic arch. Flow field analysis of the open orifice nozzle configuration illuminates the helical flow effectively delays the flow separation at the inner radius wall of the aortic arch. The comparison of the flow evolution for different MHVs shows that the BMHV works like a flow straightener which re-configures the helical flow pattern into three parallel jets (two side-orifice jets and the central orifice jet) while the TMHV preserves the helical flow structure and therefore prevent the flow separation at the inner radius wall of the aortic arch. Therefore the TMHV is of better hemodynamic performance and reduces the pressure loss.

Keywords: flow separation, helical aortic flow, mechanical heart valve, particle image velocimetry

Procedia PDF Downloads 158
1376 Development of a Microfluidic Device for Low-Volume Sample Lysis

Authors: Abbas Ali Husseini, Ali Mohammad Yazdani, Fatemeh Ghadiri, Alper Şişman

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We developed a microchip device that uses surface acoustic waves for rapid lysis of low level of cell samples. The device incorporates sharp-edge glass microparticles for improved performance. We optimized the lysis conditions for high efficiency and evaluated the device's feasibility for point-of-care applications. The microchip contains a 13-finger pair interdigital transducer with a 30-degree focused angle. It generates high-intensity acoustic beams that converge 6 mm away. The microchip operates at a frequency of 16 MHz, exciting Rayleigh waves with a 250 µm wavelength on the LiNbO3 substrate. Cell lysis occurs when Candida albicans cells and glass particles are placed within the focal area. The high-intensity surface acoustic waves induce centrifugal forces on the cells and glass particles, resulting in cell lysis through lateral forces from the sharp-edge glass particles. We conducted 42 pilot cell lysis experiments to optimize the surface acoustic wave-induced streaming. We varied electrical power, droplet volume, glass particle size, concentration, and lysis time. A regression machine-learning model determined the impact of each parameter on lysis efficiency. Based on these findings, we predicted optimal conditions: electrical signal of 2.5 W, sample volume of 20 µl, glass particle size below 10 µm, concentration of 0.2 µg, and a 5-minute lysis period. Downstream analysis successfully amplified a DNA target fragment directly from the lysate. The study presents an efficient microchip-based cell lysis method employing acoustic streaming and microparticle collisions within microdroplets. Integration of a surface acoustic wave-based lysis chip with an isothermal amplification method enables swift point-of-care applications.

Keywords: cell lysis, surface acoustic wave, micro-glass particle, droplet

Procedia PDF Downloads 64
1375 Human Par14 and Par17 Isomerases Bind Hepatitis B Virus Components Inside and Out

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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1374 Methaheuristic Bat Algorithm in Training of Feed-Forward Neural Network for Stock Price Prediction

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

Procedia PDF Downloads 528
1373 A Clustering-Based Approach for Weblog Data Cleaning

Authors: Amine Ganibardi, Cherif Arab Ali

Abstract:

This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

Procedia PDF Downloads 161
1372 Flotation of Rare Earth Oxides from Iron-Oxide Silicate Rich Tailings Using Fatty Acids

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

Abstract:

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

Procedia PDF Downloads 171
1371 Bioaccessibility of Vitamin A Nanoemulsion: Influence of Carrier Oil and Surfactant Concentration

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

Abstract:

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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1370 Characterization and Comparative Analysis of North Bengal Sand

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

Abstract:

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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1369 A Dissipative Particle Dynamics Study of a Capsule in Microfluidic Intracellular Delivery System

Authors: Nishanthi N. S., Srikanth Vedantam

Abstract:

Intracellular delivery of materials has always proved to be a challenge in research and therapeutic applications. Usually, vector-based methods, such as liposomes and polymeric materials, and physical methods, such as electroporation and sonoporation have been used for introducing nucleic acids or proteins. Reliance on exogenous materials, toxicity, off-target effects was the short-comings of these methods. Microinjection was an alternative process which addressed the above drawbacks. However, its low throughput had hindered its adoption widely. Mechanical deformation of cells by squeezing them through constriction channel can cause the temporary development of pores that would facilitate non-targeted diffusion of materials. Advantages of this method include high efficiency in intracellular delivery, a wide choice of materials, improved viability and high throughput. This cell squeezing process can be studied deeper by employing simple models and efficient computational procedures. In our current work, we present a finite sized dissipative particle dynamics (FDPD) model to simulate the dynamics of the cell flowing through a constricted channel. The cell is modeled as a capsule with FDPD particles connected through a spring network to represent the membrane. The total energy of the capsule is associated with linear and radial springs in addition to constraint of the fixed area. By performing detailed simulations, we studied the strain on the membrane of the capsule for channels with varying constriction heights. The strain on the capsule membrane was found to be similar though the constriction heights vary. When strain on the membrane was correlated to the development of pores, we found higher porosity in capsule flowing in wider channel. This is due to localization of strain to a smaller region in the narrow constriction channel. But the residence time of the capsule increased as the channel constriction narrowed indicating that strain for an increased time will cause less cell viability.

Keywords: capsule, cell squeezing, dissipative particle dynamics, intracellular delivery, microfluidics, numerical simulations

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1368 Improve Closed Loop Performance and Control Signal Using Evolutionary Algorithms Based PID Controller

Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

Abstract:

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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1367 Intelligent Control of Doubly Fed Induction Generator Wind Turbine for Smart Grid

Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

Abstract:

Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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1366 A Hybrid Feature Selection Algorithm with Neural Network for Software Fault Prediction

Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

Abstract:

Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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1365 A Study on the Assessment of Prosthetic Infection after Total Knee Replacement Surgery

Authors: Chun-Lang Chang, Chun-Kai Liu

Abstract:

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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1364 Improving Oxidative Stability of Encapsulated Krill and Black Cumin Oils and its Application in Functional Yogurt

Authors: Tamer El-Messery, Beraat Ozcelik

Abstract:

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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1363 Design and Characterization of Aromatase Inhibitor Loaded Nanoparticles for the Treatment of Breast Cancer

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

Abstract:

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

Procedia PDF Downloads 559
1362 Evaluation of Nanoparticle Application to Control Formation Damage in Porous Media: Laboratory and Mathematical Modelling

Authors: Gabriel Malgaresi, Sara Borazjani, Hadi Madani, Pavel Bedrikovetsky

Abstract:

Suspension-Colloidal flow in porous media occurs in numerous engineering fields, such as industrial water treatment, the disposal of industrial wastes into aquifers with the propagation of contaminants and low salinity water injection into petroleum reservoirs. The main effects are particle mobilization and captured by the porous rock, which can cause pore plugging and permeability reduction which is known as formation damage. Various factors such as fluid salinity, pH, temperature, and rock properties affect particle detachment. Formation damage is unfavorable specifically near injection and production wells. One way to control formation damage is pre-treatment of the rock with nanoparticles. Adsorption of nanoparticles on fines and rock surfaces alters zeta-potential of the surfaces and enhances the attachment force between the rock and fine particles. The main objective of this study is to develop a two-stage mathematical model for (1) flow and adsorption of nanoparticles on the rock in the pre-treatment stage and (2) fines migration and permeability reduction during the water production after the pre-treatment. The model accounts for adsorption and desorption of nanoparticles, fines migration, and kinetics of particle capture. The system of equations allows for the exact solution. The non-self-similar wave-interaction problem was solved by the Method of Characteristics. The analytical model is new in two ways: First, it accounts for the specific boundary and initial condition describing the injection of nanoparticle and production from the pre-treated porous media; second, it contains the effect of nanoparticle sorption hysteresis. The derived analytical model contains explicit formulae for the concentration fronts along with pressure drop. The solution is used to determine the optimal injection concentration of nanoparticle to avoid formation damage. The mathematical model was validated via an innovative laboratory program. The laboratory study includes two sets of core-flood experiments: (1) production of water without nanoparticle pre-treatment; (2) pre-treatment of a similar core with nanoparticles followed by water production. Positively-charged Alumina nanoparticles with the average particle size of 100 nm were used for the rock pre-treatment. The core was saturated with the nanoparticles and then flushed with low salinity water; pressure drop across the core and the outlet fine concentration was monitored and used for model validation. The results of the analytical modeling showed a significant reduction in the fine outlet concentration and formation damage. This observation was in great agreement with the results of core-flood data. The exact solution accurately describes fines particle breakthroughs and evaluates the positive effect of nanoparticles in formation damage. We show that the adsorbed concentration of nanoparticle highly affects the permeability of the porous media. For the laboratory case presented, the reduction of permeability after 1 PVI production in the pre-treated scenario is 50% lower than the reference case. The main outcome of this study is to provide a validated mathematical model to evaluate the effect of nanoparticles on formation damage.

Keywords: nano-particles, formation damage, permeability, fines migration

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1361 Visibility Measurements Using a Novel Open-Path Optical Extinction Analyzer

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

Procedia PDF Downloads 78