Search results for: wavelet particle decomposition

Authors: Reginald Umunakwe, Obinna Chibuzor Okoye, Uzoma Samuel Nwigwe, Damilare John Olaleye, Akinlabi Oyetunji

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The potential for the development of PPS-AlMMCs as light weight material for industrial applications was investigated. Periwinkle shells were milled and the density of the particles determined. Particulate periwinkle shell of particle size 75µm was used to reinforce aluminium 6063 alloy at 10wt% filler loading using two-step stir casting technique. The composite materials were stirred for five minutes in a semi-solid state and the stirring time varied as 3, 6 and 9 minutes at above the liquidus temperature. A specimen was also produced with pre-heated filler. The effect of variation in stirring time and reinforcement pre-heating on the porosity of the composite materials was investigated. The results of the analysis show that a composition of reinforcement pre-heating and stirring for 3 minutes produced a composite material with the lowest porosity of 1.05%.

Keywords: composites, periwinkle shell, two-step casting, porosity

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Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

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We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

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Authors: Roman Marsalek

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Preparation of nano-particles of cerium oxide and adsorption of bovine serum albumine on them were studied. Particle size distribution and influence of pH on zeta potential of prepared CeO2 were determined. Average size of prepared cerium oxide nano-particles was 9 nm. The simultaneous measurements of the bovine serum albumine adsorption and zeta potential determination of the (adsorption) suspensions were carried out. The adsorption isotherms were found to be of typical Langmuir type; values of the bovine serum albumin adsorption capacities were calculated. Increasing of pH led to decrease of zeta potential and decrease of adsorption capacity of cerium oxide nano-particles. The maximum adsorption capacity was found for strongly acid suspension (am=118 mg/g). The samples of nanoceria with positive zeta potential adsorbed more bovine serum albumine on the other hand, the samples with negative zeta potential showed little or no protein adsorption. Surface charge or better say zeta potential of CeO2 nano-particles plays the key role in adsorption of proteins on such type of materials.

Keywords: adsorption, BSA, cerium oxide nanoparticles, zeta potential, albumin

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Authors: Sergio A. Bernal-Chavez, Sergio Alcalá-Alcalá, Doris A. Cerecedo-Mercado, Adriana Ganem-Rondero

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The prevalence of people with chronic wounds has increased dramatically by many factors including smoking, obesity and chronic diseases, such as diabetes, that can slow the healing process and increase the risk of becoming chronic. Because of this situation, the improvement of chronic wound treatments is a necessity, which has led to the scientific community to focus on improving the effectiveness of current therapies and the development of new treatments. The wound formation is a physiological complex process, which is characterized by an inflammatory stage with the presence of proinflammatory cells that create a proteolytic microenvironment during the healing process, which includes the degradation of important growth factors and cytokines. This decrease of growth factors and cytokines provides an interesting strategy for wound healing if they are administered externally. The use of nanometric drug delivery systems, such as polymer nanoparticles (NP), also offers an interesting alternative around dermal systems. An interesting strategy would be to propose a formulation based on a thermosensitive hydrogel loaded with polymeric nanoparticles that allows the inclusion and application of a platelet lysate (PL) on damaged skin, with the aim of promoting wound healing. In this work, NP were prepared by a double emulsion-solvent evaporation technique, using polylactic-co-glycolic acid (PLGA) as biodegradable polymer. Firstly, an aqueous solution of PL was emulsified into a PLGA organic solution, previously prepared in dichloromethane (DCM). Then, this disperse system (W/O) was poured into a polyvinyl alcohol (PVA) solution to get the double emulsion (W/O/W), finally the DCM was evaporated by magnetic stirring resulting in the NP formation containing PL. Once the NP were obtained, these systems were characterized by morphology, particle size, Z-potential, encapsulation efficiency (%EE), physical stability, infrared spectrum, calorimetric studies (DSC) and in vitro release profile. The optimized nanoparticles were included in a thermosensitive gel formulation of Pluronic® F-127. The gel was prepared by the cold method at 4 °C and 20% of polymer concentration. Viscosity, sol-gel phase transition, time of no flow solid-gel at wound temperature, changes in particle size by temperature-effect using dynamic light scattering (DLS), occlusive effect, gel degradation, infrared spectrum and micellar point by DSC were evaluated in all gel formulations. PLGA NP of 267 ± 10.5 nm and Z-potential of -29.1 ± 1 mV were obtained. TEM micrographs verified the size of NP and evidenced their spherical shape. The %EE for the system was around 99%. Thermograms and in infrared spectra mark the presence of PL in NP. The systems did not show significant changes in the parameters mentioned above, during the stability studies. Regarding the gel formulation, the transition sol-gel occurred at 28 °C with a time of no flow solid-gel of 7 min at 33°C (common wound temperature). Calorimetric, DLS and infrared studies corroborated the physical properties of a thermosensitive gel, such as the micellar point. In conclusion, the thermosensitive gel described in this work, contains therapeutic amounts of PL and fulfills the technological properties to be used in damaged skin, with potential application in wound healing and tissue regeneration.

Keywords: growth factors, polymeric nanoparticles, thermosensitive hydrogels, tissue regeneration

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Mauricio Cruz, Andrés Díaz García, Martha Isabel Gómez, Juan Carlos Serrato Bermúdez

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The disadvantages of using natural substrates in SSF processes have been well recognized and mainly are associated to gradual decomposition of the substrate, formation of agglomerates and decrease of porosity bed generating limitations in the mass and heat transfer. Additionally, in several cases, materials with a high agricultural value such as sour milk, beets, rice, beans and corn have been used. Thus, the use of economic inert supports (natural or synthetic) in combination with a nutrient suspension for the production of biocontrol microorganisms is a good alternative in SSF processes, but requires further studies in the fields of modeling and optimization. Therefore, the aim of this work is to compare the performance of two inert supports, a synthetic (polyurethane foam) and a natural one (rice husk), identifying the factors that have the major effects on the productivity of T. asperellum Th204 and the maximum specific growth rate in a PROPHYTA L05® fixed bed bioreactor. For this, the six factors C:N ratio, temperature, inoculation rate, bed height, air moisture content and airflow were evaluated using a fractional design. The factors C:N and air flow were identified as significant on the productivity (expressed as conidia/dry substrate•h). The polyurethane foam showed higher maximum specific growth rate (0.1631 h-1) and productivities of 3.89 x107 conidia/dry substrate•h compared to rice husk (2.83x106) and natural substrate based on rice (8.87x106) used as control. Finally, a quadratic model was generated and validated, obtaining productivities higher than 3.0x107 conidia/dry substrate•h with air flow at 0.9 m3/h and C:N ratio at 18.1.

Keywords: bioprocess, scale up, fractional design, C:N ratio, air flow

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Authors: Arjun G. Koppad

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The study was conducted in Joida taluk of Uttara Kannada district, Karnataka, India, to assess the land use land cover (LULC) and forest aboveground biomass using L band SAR data. The study area covered has dense, moderately dense, and sparse forests. The sampled area was 0.01 percent of the forest area with 30 sampling plots which were selected randomly. The point center quadrate (PCQ) method was used to select the tree and collected the tree growth parameters viz., tree height, diameter at breast height (DBH), and diameter at the tree base. The tree crown density was measured with a densitometer. Each sample plot biomass was estimated using the standard formula. In this study, the LULC classification was done using Freeman-Durden, Yamaghuchi and Pauli polarimetric decompositions. It was observed that the Freeman-Durden decomposition showed better LULC classification with an accuracy of 88 percent. An attempt was made to estimate the aboveground biomass using SAR backscatter. The ALOS-2 PALSAR-2 L-band data (HH, HV, VV &VH) fully polarimetric quad-pol SAR data was used. SAR backscatter-based regression model was implemented to retrieve forest aboveground biomass of the study area. Cross-polarization (HV) has shown a good correlation with forest above-ground biomass. The Multi Linear Regression analysis was done to estimate aboveground biomass of the natural forest areas of the Joida taluk. The different polarizations (HH &HV, VV &HH, HV & VH, VV&VH) combination of HH and HV polarization shows a good correlation with field and predicted biomass. The RMSE and value for HH & HV and HH & VV were 78 t/ha and 0.861, 81 t/ha and 0.853, respectively. Hence the model can be recommended for estimating AGB for the dense, moderately dense, and sparse forest.

Keywords: forest, biomass, LULC, back scatter, SAR, regression

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Authors: Sasan Mohammadi

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Due to our passion for coffee, we use 16 billion throwaway coffee cups yearly. Coffee lovers throughout the globe have discovered the hard way that their paper cups are not recyclable, despite what coffee businesses have repeatedly assured them [1] A disposable, single-use coffee cup comprises a paper and polyethylene layer. Polyethylene is a typical material used to fill a coffee cup's inside to keep its structure and provide water and heat resistance. In addition, the polyethylene layer prevents recycling since it is difficult to separate the plastic liner from the paper layer [2]. In addition, owing to the plastic membrane lining many of these cups, they cannot be recycled and may take up to 30 years to biodegrade [3]. Most of researcher try to separate plastic part ,but it is not economical and easy.For this purposes,it is not yet happen. In our research we don't separate plastic, just we make a homogeneous pulp with cold water.then fix it in mold and dry it,after completely drying cycle we heated the product in 100 degree of centigrade this cause a sintering effect by plastic particle between paper fibers.This method increase 30 percent the strength of product.This product has a good sound proof and thermal isolation. This means we can use it as insulator.with low density we can control the the density by percentage of air solved in pulp.

Keywords: recycling, disposable coffee cup, insolator, low density

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Authors: K. Noah, F.-S. Lien

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In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.

Keywords: compressible lattice Boltzmann method, multiple relaxation times, large eddy simulation, turbulent jet flows

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Dipali Nagaonkar, Mahendra Rai

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Chitosan, a carbohydrate polymer at nanoscale level has gained considerable momentum in drug delivery applications due to its inherent biocompatibility and non-toxicity. However, conventional synthetic strategies for chitosan nanoparticles mainly rely upon physicochemical techniques, which often yield chitosan microparticles. Hence, there is an emergent need for development of controlled synthetic protocols for chitosan nanoparticles within the nanometer range. In this context, we report the green synthesis of size controlled chitosan nanoparticles by using Pongamia pinnata (L.) leaf extract. Nanoparticle tracking analysis confirmed formation of nanoparticles with mean particle size of 85 nm. The stability of chitosan nanoparticles was investigated by zetasizer analysis, which revealed positive surface charged nanoparticles with zeta potential 20.1 mV. The green synthesized chitosan nanoparticles were further explored for encapsulation and controlled release of antioxidant biomolecule, quercetin. The resulting drug loaded chitosan nanoparticles showed drug entrapment efficiency of 93.50% with drug-loading capacity of 42.44%. The cumulative in vitro drug release up to 15 hrs was achieved suggesting towards efficacy of green synthesized chitosan nanoparticles for drug delivery applications.

Keywords: Chitosan nanoparticles, green synthesis, Pongamia pinnata, quercetin

Procedia PDF Downloads 563

Authors: B. Voucko, M. Benkovic, N. Cukelj, S. Drakula, D. Novotni, S. Balbino, D. Curic

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Oxidative stress is considered as one of the causes leading to metabolic disorders in humans. Therefore, the ability of antioxidants to inhibit free radical production is their primary role in the human organism. Antioxidants originating from cereals, especially flavonoids and polyphenols, are mostly bound and indigestible. Micronization damages the cell wall which consecutively results in bioactive material to be more accessible in vivo. In order to ensure complete fragmentation, micronization is often combined with high temperatures (e.g., for bran 200°C) which can lead to degradation of bioactive compounds. The innovative non-thermal technology of cryo-milling is an ultra-fine micronization method that uses liquid nitrogen (LN2) at a temperature of 195°C to freeze and cool the sample during milling. Freezing at such low temperatures causes the material to become brittle which ensures the generation of fine particles while preserving the bioactive content of the material. The aim of this research was to determine if production of ultra-fine material with cryo-milling will result in the augmentation of available bioactive compounds of buckwheat and pumpkin seed cake. For that reason, buckwheat and pumpkin seed cake were ground in a ball mill (CryoMill, Retch, Germany) with and without the use of LN2 for 8 minutes, in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm) at an oscillation frequency of 30 Hz. The cryo-milled samples were cooled with LN2 for 2 minutes prior to milling, followed by the first cycle of milling (4 minutes), intermediary cooling (2 minutes), and finally the second cycle of milling (further 4 minutes). A continuous process of milling was applied to the samples ground without freezing with LN2. Particle size distribution was determined using the Scirocco 2000 dry dispersion unit (Malvern Instruments, UK). Antioxidant activity was determined by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) test and ferric reducing antioxidant power (FRAP) assay, while the total phenol content was determined using the Folin Ciocalteu method, using the ultraviolet-visible spectrophotometer (Specord 50 Plus, Germany). The content of the free phenolic acids, rutin in buckwheat, tyrosol in pumpkin seed cake, was determined with an HPLC-PDA method (Agilent 1200 series, Germany). Cryo-milling resulted in 11 times smaller size of buckwheat particles, and 3 times smaller size of pumpkin seed particles than milling without the use of LN2, but also, a lower uniformity of the particle size distribution. Lack of freezing during milling of pumpkin seed cake caused a formation of agglomerates due to its high-fat content (21 %). Cryo-milling caused augmentation of buckwheat flour antioxidant activity measured by DPPH test (23,9%) and an increase in available rutin content (14,5%). Also, it resulted in an augmentation of the total phenol content (36,9%) and available tyrosol content (12,5%) of pumpkin seed cake. Antioxidant activity measured with the FRAP test, as well as the content of phenolic acids remained unchanged independent of the milling process. The results of this study showed the potential of cryo-milling for complete raw material utilization in the food industry, as well as a tool for extraction of aimed bioactive components.

Keywords: bioactive, ball-mill, buckwheat, cryo-milling, pumpkin seed cake

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Authors: D. Deepak, N. Yagnesh Sharma

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Abrasive Water Jet (AWJ) machining is a relatively new nontraditional machine tool used in machining of fiber reinforced composite. The quality of machined surface depends on jet exit kinetic energy which depends on various operating and material parameters. In the present work the effect abrasive parameters such as its size, concentration and type on jet kinetic energy is investigated using computational fluid dynamics (CFD). In addition, the effect of these parameters on wall shear stress developed inside the nozzle is also investigated. It is found that for the same operating parameters, increase in the abrasive volume fraction (concentration) results in significant decrease in the wall shear stress as well as the jet exit kinetic energy. Increase in the abrasive particle size results in marginal decrease in the jet exit kinetic energy. Numerical simulation also indicates that garnet abrasives produce better jet exit kinetic energy than aluminium oxide and silicon carbide.

Keywords: abrasive water jet machining, jet kinetic energy, operating pressure, wall shear stress, Garnet abrasive

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Authors: A. Abdikian

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Propagation of nonlinear acoustic wave in dense electron-positron (e-p) plasmas in the presence of an external magnetic field and stationary ions (to neutralize the plasma background) is studied. By means of the quantum hydrodynamics model and applying the reductive perturbation method, the Zakharov-Kuznetsov equation is derived. Using the bifurcation theory of planar dynamical systems, the compressive structure of electrostatic solitary wave and periodic travelling waves is found. The numerical results show how the ion density ratio, the ion cyclotron frequency, and the direction cosines of the wave vector affect the nonlinear electrostatic travelling waves. The obtained results may be useful to better understand the obliquely nonlinear electrostatic travelling wave of small amplitude localized structures in dense magnetized quantum e-p plasmas and may be applicable to study the particle and energy transport mechanism in compact stars such as the interior of massive white dwarfs etc.

Keywords: bifurcation theory, phase portrait, magnetized electron-positron plasma, the Zakharov-Kuznetsov equation

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Authors: Yung-Chih Kuo, I-Hsuan Lee

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Solid lipid nanoparticles (SLNs) conjugated with aprotinin (Apr) and melanotransferrin antibody (Anti-MTf) were used to carry doxorubicin (Dox) across the blood–brain barrier (BBB) for glioblastoma multiforme (GBM) chemotherapy. Dox-entrapped SLNs with grafted Apr and Anti-MTf (Apr-Anti-MTf-Dox-SLNs) were applied to a cultured monolayer comprising human brain-microvascular endothelial cells (HBMECs) with regulation of human astrocyte (HAs) and to a proliferated colony of U87MG cells. Based on the average particle diameter, zeta potential, entrapping efficiency of Dox, and grafting efficiency of Apr and Anti-MTf, we found that 40% (w/w) 1,2-dipalmitoyl-sn-glycero-3-phosphocholine in lipids were appropriate for fabricating Apr-Anti-MTf-Dox-SLNs. In addition, Apr-Anti-MTf-Dox-SLNs could prevent Dox from fast dissolution and did not induce a serious cytotoxicity to HBMECs and HAs when compared with free Dox. Moreover, the treatments with Apr-Anti-MTf-Dox-SLNs enhanced the ability of Dox to infuse the BBB and to inhibit the growth of GBM. The current Apr-Anti-MTf-Dox-SLNs can be a promising pharmacotherapeutic preparation to penetrate the BBB for malignant brain tumor treatment.

Keywords: solid lipid nanoparticle, glioblastoma multiforme, blood–brain barrier, doxorubicin

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Jackson Niyongabo

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This study addresses a notable gap in the existing literature on the relationship between energy consumption, economic growth, and CO₂ emissions, particularly within the African context. While numerous studies have explored these dynamics globally and regionally across various development levels, few have delved into the nuances of regions and income levels specific to African countries. Furthermore, the evaluation of the interplay between green growth policies, green energy technologies, and their impact on environmental quality has been underexplored. This research aims to fill these gaps by conducting a comprehensive analysis of the transition from conventional economic growth and energy consumption to a paradigm of green growth coupled with green energy utilization across the African continent from 1980 to 2018. The study is structured into three main parts: an empirical examination of the long-term effects of energy intensity, renewable energy consumption, and economic growth on CO₂ emissions across diverse African regions and income levels; an estimation of the long-term impact of green growth and green energy use on CO₂ emissions for countries implementing green policies within Africa, as well as at regional and global levels; and a comparative analysis of the impact of green growth policies on environmental degradation before and after implementation. Employing advanced econometric methods and panel estimators, the study utilizes a testing framework, panel unit tests, and various estimators to derive meaningful insights. The anticipated results and conclusions will be elucidated through causality tests, impulse response, and variance decomposition analyses, contributing valuable knowledge to the discourse on sustainable development in the African context.

Keywords: economic growth, green growth, energy consumption, CO₂ emissions, econometric models, green energy

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Authors: B. Makhlouf, O. Bouchhida, M. Nibouche, K. Laidi

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A variety of methods for selective harmonics elimination pulse width modulation have been developed, the most frequently used for real-time implementation based on look-up tables method. To address real-time requirements based in modified carrier signal is proposed in the presented work, with a general formulation to real-time harmonics control/elimination in switched inverters. Firstly, the proposed method has been demonstrated for a single value of the modulation index. However, in reality, this parameter is variable as a consequence of the voltage (amplitude) variability. In this context, a simple interpolation method for calculating the modified sine carrier signal is proposed. The method allows a continuous adjustment in both amplitude and frequency of the fundamental. To assess the performance of the proposed method, software simulations and hardware experiments have been carried out in the case of a single-phase inverter. Obtained results are very satisfactory.

Keywords: harmonic elimination, Particle Swarm Optimisation (PSO), polynomial interpolation, pulse width modulation, real-time harmonics control, voltage inverter

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Authors: Xiaodong Gao, Pingchuan Dong, Qichao Gao

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There has been lots of published work focused on asphaltene deposited on the smooth pipe under steady conditions, while particle deposition on the blockage wellbores under transient conditions has not been well elucidated. This work attempts to predict the deposition rate of asphaltene particles in blockage tube through CFD simulation. The Euler-Lagrange equation has been applied during the flow of crude oil and asphaltene particles. The net gravitational force, virtual mass, pressure gradient, saffman lift, and drag forces are incorporated in the simulations process. Validation of CFD simulation results is compared to the benchmark experiments from the previous literature. Furthermore, the effect of blockage location, blockage length, and blockage thickness on deposition rate are also analyzed. The simulation results indicate that the maximum deposition rate of asphaltene occurs in the blocked tube section, and the greater the deposition thickness, the greater the deposition rate. Moreover, the deposition amount and maximum deposition rate along the length of the tube have the same trend. Results of this study are in the ability to better understand the deposition of asphaltene particles in production and help achieve to deal with the asphaltene challenges.

Keywords: asphaltene deposition rate, blockage length, blockage thickness, blockage diameter, transient condition

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Authors: Yassets Egaña, Patricio Núñez, Juan C. Rios, Ivan Balic, Alex Manquez, Yarela Flores, Maria C. Gatica, Sergio Diez De Medina, Rocio Tijaro-Rojas

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Globally, humans produce millions of tons of waste per year. An important percentage of this waste is plastic, which frequently ends up in landfills and oceans. During the last decades, the greatest plastics production in history have been made, a few amount of this plastic is recycled, the rest ending up as plastic pollution in soils and seas. Plastic pollution is disastrous for the environment, affecting essential species, quality of consumption water, and some economic activities such as tourism, in different parts of the world. Due to its durability and decomposition on micro-plastics, animals and humans are accumulating a variety of plastic components without having clear their effects on human health, economy, and wildlife. In dry regions as the Atacama Desert, up to 95% of the water consumption comes from underground reservoirs, therefore preventing the soil pollution is an urgent need. This contribution focused on isolating, genotyping and optimizing microorganisms that use plastic waste as the only source of food to construct a batch-type bioreactor able to degrade in a faster way the plastic waste before it gets the desert soils and groundwater consumed by people living in this areas. Preliminary results, under laboratory conditions, has shown an improved degradation of polyethylene when three species of bacteria and three of fungi act on a selected plastic material. These microorganisms have been inoculated in dry soils, initially lacking organic matter, under environmental conditions in the laboratory. Our team designed and constructed a prototype using the natural conditions of the region and the best experimental results.

Keywords: biological breakdown, plastic bags, prototype, desert regions

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Authors: J. O. Akinyele, R. W. Salim, K. O. Oikelome, O. T. Olateju

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Rice Husk (RH) is the major byproduct in the processing of paddy rice. The management of this waste has become a big challenge to some of the rice producers, some of these wastes are left in open dumps while some are burn in the open space, and these two actions have been contributing to environmental pollution. This study evaluates an alternative waste management of this agricultural product for use as a civil engineering material. The RH was burn in a controlled environment to form Rice Husk Ash (RHA). The RHA was mix with lateritic clay at 0, 2, 4, 6, 8, and 10% proportion by weight. Chemical test was conducted on the open burn and controlled burn RHA with the lateritic clay. Physical test such as particle size distribution, Atterberg limits test, and density test were carried out on the mix material. The chemical composition obtained for the RHA showed that the total percentage compositions of Fe2O3, SiO2 and Al2O3 were found to be above 70% (class “F” pozzolan) which qualifies it as a very good pozzolan. The coefficient of uniformity (Cu) was 8 and coefficient of curvature (Cc) was 2 for the soil sample. The Plasticity Index (PI) for the 0, 2, 4, 6, 8. 10% was 21.0, 18.8, 16.7, 14.4, 12.4 and 10.7 respectively. The work concluded that RHA can be effectively used in hydraulic barriers and as a stabilizing agent in soil stabilization.

Keywords: rice husk ash, pozzolans, paddy rice, lateritic clay

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Authors: Rui Sun, Tamer M. Ismail, Xiaohan Ren, M. Abd El-Salam

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Incineration of municipal solid waste (MSW) is one of the key scopes in the global clean energy strategy. A computational fluid dynamics (CFD) model was established. In order to reveal these features of the combustion process in a fixed porous bed of MSW. Transporting equations and process rate equations of the waste bed were modeled and set up to describe the incineration process, according to the local thermal conditions and waste property characters. Gas phase turbulence was modeled using k-ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The heterogeneous reaction rates were determined using Arrhenius eddy dissipation and the Arrhenius-diffusion reaction rates. The effects of primary air flow rate and temperature in the burning process of simulated MSW are investigated experimentally and numerically. The simulation results in bed are accordant with experimental data well. The model provides detailed information on burning processes in the fixed bed, which is otherwise very difficult to obtain by conventional experimental techniques.

Keywords: computational fluid dynamics (CFD) model, waste incineration, municipal solid waste (MSW), fixed bed, primary air

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Authors: Luanna B. Prevost, Kelli Carter, Margaurete Romero, Kirsti Martinez

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Writing is an essential scientific practice, yet, in several countries, the increasing university science class-size limits the use of written assessments. Written assessments allow students to demonstrate their learning in their own words and permit the faculty to evaluate students’ understanding. However, the time and resources required to grade written assessments prohibit their use in large-enrollment science courses. This study examined the use of machine learning algorithms to automatically analyze student writing and provide timely feedback to the faculty about students' writing in biology. Written responses to questions about matter and energy transformation were collected from large-enrollment undergraduate introductory biology classrooms. Responses were analyzed using the LightSide text mining and classification software. Cohen’s Kappa was used to measure agreement between the LightSide models and human raters. Predictive models achieved agreement with human coding of 0.7 Cohen’s Kappa or greater. Models captured that when writing about matter-energy transformation at the ecosystem level, students focused on primarily on the concepts of heat loss, recycling of matter, and conservation of matter and energy. Models were also produced to capture writing about processes such as decomposition and biochemical cycling. The models created in this study can be used to provide automatic feedback about students understanding of these concepts to biology faculty who desire to use formative written assessments in larger enrollment biology classes, but do not have the time or personnel for manual grading.

Keywords: machine learning, written assessment, biology education, text mining

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Authors: Ravi Gujjula, Chinna Eranna, Narasimha Mangadoddy

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Hydrodynamic study of gas and solid flow in an internally circulating fluidized bed with draft tube is made in this paper using high speed camera and pressure probes for the laboratory ICFB test rig 3.0 m X 2.7 m column having a draft tube located in the center of ICFB. Experiments were conducted using different sized sand particles with varying particle size distribution. At each experimental run the standard pressure-flow curves for both draft tube and annular region beds measured and the same time downward particles velocity in the annular bed region were also measured. The effect of superficial gas velocity, static bed height (40, 50 & 60 cm) and the draft tube gap height (10.5 & 14.5 cm) on pressure drop profiles, solid circulation pattern, and gas bypassing dynamics for the ICFB investigated extensively. The mechanism of governing solid recirculation and the pressure losses in an ICFB has been eluded based on gas and solid dynamics obtained from the experimental data. 3D ICFB CFD simulation runs conducted and extracted data validated with ICFB experimental data.

Keywords: icfb, cfd, pressure drop, solids recirculation, bed height, draft tube

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Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

Procedia PDF Downloads 357

Authors: Azeem Ur Rehman, Asma Tayyaba

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This article deals with the promotional effects of CeO2 on PtPd/CeO2-OMC electro catalysts. The synthesized catalysts are characterized using different physico chemical techniques and evaluated in a formic acid oxidation fuel cell. N2 adsorption/desorption analysis shows that CeO2 modification increases the surface area of OMC from 1005 m2/g to 1119 m2/g. SEM, XRD and TEM analysis reveal that the presence of CeO2 enhances the active metal(s) dispersion on the CeO2-OMC surface. The average particle size of the dispersed metal decreases with the increase of Pt/Pd ratio on CeO2-OMC support. Cyclic voltametry measurement of Pd/CeO2-OMC gives 12 % higher anodic current activity with 83 mV negative shift of the peak potential as compared to unmodified Pd/OMC. In bimetallic catalysts, the addition of Pt improves the activity and stability of the catalysts significantly. Among the bimetallic samples, Pd3Pt1/CeO2-OMC displays superior current density (74.6 mA/cm2), which is 28.3 times higher than that of Pt/CeO2-OMC. It also shows higher stability in extended period of runs with least indication of CO poisoning effects.

Keywords: CeO2, ordered mesoporous carbon (OMC), electro catalyst, formic acid fuel cell

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Authors: Amandeep Kaur, N. S. Atri, Munruchi Kaur

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Herbivorous dung is a special substrate for the growth of fungi. Fungi growing thereon are known as coprophilous. These fungi are amongst the most abundant taxa in the ecosystem, which regulate the decomposition of dung organic matter, nutrient dynamics and maintenance of ecological balance on the earth. The coprophilous fungi represent a diverse group of saprobes, including taxa from most major fungal groups belonging to Zygomycota, Ascomycota and Basidiomycota. The present work, however, has been focused on the basidiomycetous coprophilous mushrooms belonging to the order Agaricales. The research work includes the results of eco-taxonomic studies of coprophilous mushrooms in Punjab, India, on the basis of a survey of dung localities of the state. The mushrooms were collected growing as saprobes on dung of various domesticated and wild herbivorous animals in pastures, grasslands, zoos, and on dung heaps in villages, etc. The present study observed the frequency of distribution of coprophilous mushrooms in different taxonomic categories in different regions of the state in various seasons on different dung types along with their growing habit. The paper also discusses their economic utility as edible, inedible, poisonous, medicinal and hallucinogenic species. The study has shown that animal dung is a good niche for the growth of mushrooms. However, the natural habitats with dung deposits are getting destroyed because of different developmental activities. Livestock in agriculture-based societies like Punjab state in India should be managed in a manner that favors their grazing in the wild places and thereby the growth of coprophilous mushrooms so that a significant role in ecological balance on the earth is established.

Keywords: herbivorous dung, psychoactive, seasonal availability, taxo-ecology

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Authors: Mahmoud Samkan

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In this paper, the design and assessment of new coordination between Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method are proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one.

Keywords: SVC, PSSs, multimachine power system, coordinated design, bacteria swarm optimization, statistical assessment

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Authors: Julia DeVoy, Olivia Berlin

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The United States exports over 1.6 billion pounds of post-consumer textiles every year, primarily to countries in the Global South. These textiles make their way to landfills and open-air dumps where they decompose, contaminating water systems and releasing harmful greenhouse gases. Through this inequitable system of waste disposal, countries with less political and economic power are coerced into accepting the environmental and health consequences of over-consumption in the Global North. Thus, the global trade of post-consumer textile waste represents a serious issue of environmental justice and a public health hazard. Our research located, characterizes, and quantifies the environmental and human health risks that occur when post-consumer textiles are left to decompose in landfills and open-air dumps in the Global South. In our work, we make use of United Nations International Trade Statistics data to map the global distribution of post-consumer textiles exported from the United States. Next, we present our landfill simulating reactor designed to measure toxicity of leachate resulting from the decomposition of textiles in developing countries and to quantify the related greenhouse gas emissions. This design makes use of low-cost and sustainable materials to promote frugal innovation and make landfill reactors more accessible. Finally, we describe how the data generated from these tools can be leveraged to inform individual consumer behaviors, local policies around textile waste disposal, and global advocacy efforts to mitigate the environmental harms caused by textile waste.

Keywords: sustainability, textile design, public health, built environment

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Authors: M. Mana, M. S. Ouali, L. C. de Menorval

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A spent bleaching earth from an edible oil refinery has been treated by impregnation with a normal sodium hydroxide solution followed by mild thermal treatment (100°C). The obtained material (TSBE) was washed, dried and characterized by X-ray diffraction, FTIR, SEM, BET, and thermal analysis. The clay structure was not apparently affected by the treatment and the impregnated organic matter was quantitatively removed. We have investigated the comparative sorption of safranine and methylene blue on this material, the spent bleaching earth (SBE) and the virgin bleaching earth (VBE). The kinetic results fit the pseudo second order kinetic model and the Weber & Morris, intra-particle diffusion model. The pH had no effect on the sorption efficiency. The sorption isotherms followed the Langmuir model for various sorbent concentrations with good values of determination coefficient. A linear relationship was found between the calculated maximum removal capacity and the solid/solution ratio. A comparison between the results obtained with this material and those of the literature highlighted the low cost and the good removal capacity of the treated spent bleaching earth.

Keywords: basic dyes, isotherms, sorption, spent bleaching earth

Procedia PDF Downloads 234