Search results for: experimental imaging

Authors: Djamel Remache, Serge Dos Santos, Michael Cliez, Michel Gratton, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan

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Skin tissue is an inhomogeneous and anisotropic material. Uniaxial tensile testing is one of the primary testing techniques for the mechanical characterization of skin at large scales. In order to predict the mechanical behavior of materials, the direct or inverse analytical approaches are often used. However, in case of an inhomogeneous and anisotropic material as skin tissue, analytical approaches are not able to provide solutions. The numerical simulation is thus necessary. In this work, the uniaxial tensile test and the FEM (finite element method) based inverse method were used to identify the anisotropic mechanical properties of porcine skin tissue. The uniaxial tensile experiments were performed using Instron 8800 tensile machine®. The uniaxial tensile test was simulated with FEM, and then the inverse optimization approach (or the inverse calibration) was used for the identification of mechanical properties of the samples. Experimentally results were compared to finite element solutions. The results showed that the finite element model predictions of the mechanical behavior of the tested skin samples were well correlated with experimental results.

Keywords: mechanical skin tissue behavior, uniaxial tensile test, finite element analysis, inverse optimization approach

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Authors: Sajida Saqira, Anthony Chariton, Grant C. Hose

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The Anthropocene has seen dramatic environmental changes which are affecting every ecosystem on earth. Freshwater ecosystems are particularly vulnerable as they are at risk from the many activities that go on and contaminants that are released in catchments. They are thus subject to many stressors simultaneously. Freshwater ecosystems respond to stress at all levels of biological organization, from subcellular to community structure and ecosystem functioning. The aim of this study was to examine the resistance and resilience of freshwater ecosystems to multiple stressors. Here we explored the individual and combined effects of copper as a chemical stressor and common carp (Cyprinus carpio) as a biological stressor on the health, functioning, and recovery of outdoor experimental pond ecosystems in a long-term, controlled, factorial experiment. Primary productivity, decomposition, and water and sediment quality were analysed at regular intervals for one year to understand the health and functioning of the ecosystems. Changes to benthic biota were quantified using DNA-based and traditional microscopy-based counts of invertebrates. Carp were added to the ponds to copper contaminated sediments (with controls) to explore the combined effects of copper and carp and removed after six months to explore the resilience and recovery of the system. The outcomes of this study will advance our understanding of the impacts of multiple stressors on freshwater ecosystems, and the resilience of these systems to copper and C. carpio, which are both globally significant stressors in freshwater systems.

Keywords: carp, copper, ecosystem health, freshwater ecosystem, multiple stressors

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

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

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

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Mohammad Al-Dawoody

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This study aims at exploring if priming is affected by gender in Modern Standard Arabic and if it is restricted solely to subjects with no specific language impairment (SLI). The sample in this study consists of 74 subjects, between the ages of 11;1 and 11;10, distributed into (a) 2 SLI experimental groups of 38 subjects divided into two gender groups of 18 females and 20 males and (b) 2 non-SLI control groups of 36 subjects divided into two gender groups of 17 females and 19 males. Employing a mixed research design, the researcher conducted this study within the framework of the relevance theory (RT) whose main assumption is that human beings are endowed with a biological ability to magnify the relevance of the incoming stimuli. Each of the four groups was given two different priming stimuli: audio-visual priming (T1) and syntactic priming (T2). The results showed that the priming effect was sheer distinct among SLI participants especially when retrieving typical responses (TR) in T1 and T2 with slight superiority of males over females. The results also revealed that non-SLI females showed stronger original response (OR) priming in T1 than males and that non-SLI males in T2 excelled in OR priming than females. Furthermore, the results suggested that the audio-visual priming has a stronger effect on SLI females than non-SLI females and that syntactic priming seems to have the same effect on the two groups (non-SLI and SLI females). The conclusion is that the priming effect varies according to gender and is not confined merely to non-SLI subjects.

Keywords: specific language impairment, relevance theory, audio-visual priming, syntactic priming, modern standard Arabic

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Authors: M. Jerold, V. Sivasubramanian

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

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

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Authors: Mahmood Al Ramahi, G. Keszthelyi-Szabo, S. Beszedes

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Hydrothermal carbonization (HTC) is a thermochemical reaction that utilizes saturated water and vapor pressure to convert waste biomass to C-rich products This work evaluated the effect of HTC as a pre- and post-treatment technique to anaerobic digestion (AD) of dairy sludge, as information in this field is still in its infancy, with many research and methodological gaps. HTC effect was evaluated based on energy recovery, nutrients transformation, and sludge biodegradability. The first treatment approach was executed by applying hydrothermal carbonization (HTC) under a range of temperatures, prior to mesophilic anaerobic digestion (AD) of dairy sludge. Results suggested an optimal pretreatment temperature at 210 °C for 30 min. HTC pretreatment increased methane yield and chemical oxygen demand removal. The theoretical model based on Boyle’s equation had a very close match with the experimental results. On the other hand, applying HTC subsequent to AD increased total energy production, as additional energy yield was obtained by the solid fuel (hydrochar) beside the produced biogas. Furthermore, hydrothermal carbonization of AD digestate generated liquid products (HTC digestate) with improved chemical characteristics suggesting their use as liquid fertilizers.

Keywords: hydrothermal carbonization, anaerobic digestion, energy balance, sludge biodegradability, biogas

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Authors: Hamed Hosseinkazemi, Esmaeil Biazar

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For tissue engineering of bone, anatomical and operational reconstructions of damaged tissue seem to be vital. This is done via reconstruction of bone and appropriate biological joint with bone tissues of damaged areas. In this study the condition of biodegradable bed Nanofibrous PHBV and USSC cells were used to accelerate bone repair of damaged area. Hollow nanofabrication scaffold of damageable life was designed as PHBV by electrospinning and via determining the best factors such as the kind and amount of solvent, specific volume and rate. The separation of osseous tissue infiltration and evaluating its nature by flow cytometrocical analysis was done. Animal test including USSC as well as PHBV condition in the damaged bone was done in the rat. After 8 weeks the implanted area was analyzed using CT scan and was sent to histopathology ward. Finally, the rate and quality of reconstruction were determined after H and E coloring. Histomorphic analysis indicated a statistically significant difference between the experimental group of PHBV, USSC+PHBV and control group. Besides, the histopathologic analysis showed that bone reconstruction rate was high in the area containing USSC and PHBV, compared with area having PHBV and control group and consequently the reconstruction quality of bones and the relationship between the new bone tissues and surrounding bone tissues were high too. Using PHBR scaffold and USSC together could be useful in the amending of wide range of bone lesion.

Keywords: bone lesion, nanofibrous PHBV, stem cells, umbilical cord blood

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Authors: Gina Zavaleta-Espejo, Segundo R. Jáuregui-Rosas, Fanny V. Samanamud-Moreno, José Saldaña Jiménez, Anibal Felix-Quintero, Víctor Montero-Del Aguila, Elsi Mejía-Uriarte

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Vicugnapacos "alpaca" fabrics are considered special for their finesse, and the garments in the textile market are very luxurious. It has many special characteristics such as antiallergic, soft, hygroscopic, among others. In this sense, the research aimed to evaluate the antimicrobial activity of alpaca fabrics functionalized with silver nanoparticles on the bacteria Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 25923. For the functionalization of the fabrics, AgNO3 and different concentrations of trisodium citrate (TSC) 2, 6, and 10 mg. Tissue characterization was performed using Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The determination of the antimicrobial activity of the alpaca tissues was made by the Kirby-Bauer method with alpaca tissue discs functionalized with silver nanoparticles, an experimental design was made in completely randomized blocks with three treatments and a negative control with three repetitions. The results showed that inhibition halos were formed for both bacteria, therefore, the functionalized tissues have a high antimicrobial activity, whose mechanism of action is attributed to the free radicals (ROS) generated by the nanoparticles that cause oxidative damage to the bacteria. proteins and lipids of the bacterial cell wall.

Keywords: antimicrobial, animal fibers, fabrics, functionalization, trisodium citrate

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Authors: Mekdes Lulu

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This study assessed the effect of the interactions of biochar (BC), farmyard manure (FYM) and lime on soil chemical properties and on different wheat attributes in Southern Ethiopia. The experimental design was a randomized complete block in three replications. The site significantly (p ≤ 0.05) influenced soil and wheat attributes. Biochar showed a large significant effect (p ≤ 0.05) on soil organic carbon, cation exchange capacity, and exchangeable potassium (K), while lime showed a substantially significant (p ≤ 0.05) effect on exchangeable Calcium (Ca) and acidity. Farmyard manure (10 tonnes ha−1 ) had a significant effect on soil total nitrogen (TN). Biochar and lime showed a large significant effect on soil pH and available phosphorus (P) depending on the site. All amendments showed a significant (p ≤ 0.001) effect on most wheat attributes, but the highest effect was from BC. Biochar produced highly significant (p ≤ 0.001) effects on plant height, total number of tillers and productive tillers, number of seeds per spike, aboveground biomass, grain yield, and P and K content in wheat grain and straw. We accredited the greater effect of BC on wheat attributes to its influence on soil chemical properties. We recommend long-term studies on the impact of BC alone or in combination with FYM on acid soil types.

Keywords: grain yield, soil amendments, soil nutrients, soil organic carbon, Triticum aestivum

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Authors: Ermelinda Bloise, Giuseppe Mele

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In recent years, Cashew Nut Shell Liquid (CNSL) has received great attention from researchers because it is an abundant waste material from the agri-food industry that fits perfectly into the idea of reusing waste from renewable resources for the production of new functional materials. The different components of this waste showed a certain chemical versatility and, above all, various biological activities. Take advantage of their surface-active capacity in particular conditions, various amphiphilic nanostructures have been prepared through sustainable chemical processes using cardanol (CA) and anacardic acid (AA) as two main components of the CNSL. In-batch solvent-free method has been developed to obtain new versatile green nanovesicles capable of effectively incorporating and stabilizing both hydrophobic and hydrophilic bioactive molecules. Furthermore, these nanosystems have shown antioxidant and cytotoxic properties and, in vitroinvestigations, established that they efficiently taken-up some human cells. With the idea of meeting the principles of green chemistry, even more, some improvements of the synthetic procedure have been implemented in terms of milder temperature and pH conditions, producing one-component nanovesicles, in which the AA and CA-derivatives are the sole building block of the green nanosystems. Finally, a new experimental approach has been carried out by a microfluidic route, with the advantage to operate at continuous flows, with a reduced amount of reagents, waste, and at lower temperatures, ensuring the achievement of size-monodisperse amphiphilic nanostructures that do not need further purification steps.

Keywords: bioactive nanosystems, bio-based renewables, cashew oil, green nanoformulations

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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Authors: Opeyemi Atiba-Oyewo, Taile Y. Leswfi, Maurice S. Onyango, Christian Wolkersdorfer

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This paper describes the preparation of surface modified montmorillonite using hexadecyltrimethylammonium bromide (HDTMA-Br) for the removal of vanadium from mine water. The adsorbent before and after adsorption was characterised by Fourier transform infra-red (FT-IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM), while the amount of vanadium adsorbed was determined by ICP-OES. The batch adsorption method was employed using vanadium concentrations in solution ranging from 50 to 320 mg/L and vanadium tailings seepage water from a South African mine. Also, solution pH, temperature and sorbent mass were varied. Results show that the adsorption capacity was affected by solution pH, temperature, sorbent mass and the initial concentration. Electrical conductivity of the mine water before and after adsorption was measured to estimate the total dissolved solids in the mine water. Equilibrium isotherm results revealed that vanadium sorption follows the Freundlich isotherm, indicating that the surface of the sorbent was heterogeneous. The pseudo-second order kinetic model gave the best fit to the kinetic experimental data compared to the first order and Elovich models. The results of this study may be used to predict the uptake efficiency of South Africa montmorillonite in view of its application for the removal of vanadium from mine water. However, the choice of this adsorbent for the uptake of vanadium or other contaminants will depend on the composition of the effluent to be treated.

Keywords: adsorption, vanadium, modified montmorillonite, equilibrium, kinetics, mine water

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Authors: Amin Jabbari

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The state of the art in major 3D printing technologies, such as powder-based and slurry based, has led researchers to investigate the ability to fabricate bone scaffolds for bone tissue engineering using biomaterials. In addition, 3D printing technology can simulate mechanical and biological surface properties and print with high precision complex internal and external structures that match their functional properties. Polymer matrix composites reinforced with particulate bioceramics, hydrogels reinforced with particulate bioceramics, polymers coated with bioceramics, and non-porous bioceramics are among the materials that can be investigated for bone scaffold printing. Furthermore, it was shown that the introduction of high-density micropores into the sparingly dissolvable CSiMg10 and dissolvable CSiMg4 shell layer inevitably leads to a nearly 30% reduction in compressive strength, but such micropores can easily influence the ion release behavior of the scaffolds. Also, biocompatibility tests such as cytotoxicity, hemocompatibility and genotoxicity were tested on printed parts. The printed part was tested in vitro, and after 24-26 h for cytotoxicity, and 4h for hemocompatibility test, the CSiMg4@CSiMg10-p scaffolds were found to have significantly higher osteogenic capability than the other scaffolds of implantation. Overall, these experimental studies demonstrate that 3D printed, additively-manufactured bioceramic calcium (Ca)-silicate scaffolds with appropriate pore dimensions are promising to guide new bone ingrowth.

Keywords: AM, 3D printed implants, bioceramic, tissue engineering

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Authors: Sharon Li, Zhonghang Xia

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Post-database search is an essential phase in peptide identification using tandem mass spectrometry (MS/MS) to refine peptide-spectrum matches (PSMs) produced by database search engines. These engines frequently face difficulty differentiating between correct and incorrect peptide assignments. Despite advances in statistical and machine learning methods aimed at improving the accuracy of peptide identification, challenges remain in selecting critical features for these models. In this study, two machine learning models—a random forest tree and a support vector machine—were applied to three datasets to enhance PSMs. SHAP values were utilized to determine the significance of each feature within the models. The experimental results indicate that the random forest model consistently outperformed the SVM across all datasets. Further analysis of SHAP values revealed that the importance of features varies depending on the dataset, indicating that a feature's role in model predictions can differ significantly. This variability in feature selection can lead to substantial differences in model performance, with false discovery rate (FDR) differences exceeding 50% between different feature combinations. Through SHAP value analysis, the most effective feature combinations were identified, significantly enhancing model performance.

Keywords: peptide identification, SHAP value, feature selection, random forest tree, support vector machine

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Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo

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Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.

Keywords: model, shale gas, concentration, organic compounds

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Authors: Asad Islam, Khalid Parvez

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Compressor fans in modern aircraft engines are of considerate importance, as they provide majority of thrust required by the aircraft. Their challenging environment is frequently subjected to non-uniform inflow conditions. These conditions could be either due to the flight operating requirements such as take-off and landing, wake interference from aircraft fuselage or cross-flow wind conditions. So, in highly maneuverable flights regimes of fighter aircrafts affects the overall performance of an engine. Since the flow in compressor of an aircraft application is highly sensitive because of adverse pressure gradient due to different flow orientations of the aircraft. Therefore, it is prone to unstable operations. This paper presents the study that focuses on axial compressor response to inlet flow orientations for the range of angles as 0 to 15 degrees. For this purpose, NASA Rotor-37 was taken and CFD mesh was developed. The compressor characteristics map was generated for the design conditions of pressure ratio of 2.106 with the rotor operating at rotational velocity of 17188.7 rpm using CFD simulating environment of ANSYS-CFX®. The grid study was done to see the effects of mesh upon computational solution. Then, the mesh giving the best results, (when validated with the available experimental NASA’s results); was used for further distortion analysis. The flow in the inlet nozzle was given angle orientations ranging from 0 to 15 degrees. The CFD results are analyzed and discussed with respect to stall margin and flow separations due to induced distortions.

Keywords: axial compressor, distortions, angle, CFD, ANSYS-CFX®, bladegen®

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Authors: Tayyaba Ghani, Mazhar Mehmood, Mohammad Mujahid

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TiO₂ nanotubes are receiving immense attraction in the field of dye-sensitized solar cells due to their well-defined nanostructures, efficient electron transport and large surface area as compared to other one dimensional structures. In the present work, we have investigated the influence of temperature on the morphology of anodically produced self-organized Titanium oxide nanotubes (TiNTs). TiNTs are synthesized by two-step anodization method in an ethylene glycol based electrolytes containing ammonium fluoride. Experiments are performed at constant anodization voltage for two hours. An investigation by the SEM images reveals that if the temperature is kept constant during the anodizing experiment, variation in the average tube diameter is significantly reduced. However, if the temperature is not controlled then due to the exothermic nature of reactions for the formation of TiNTs, the temperature of electrolyte keep on increasing. This variation in electrolyte bath temperature introduced strong variations in tube diameter (20 nm to 160 nm) along the length of tubes. Current profiles, recorded during the anodization experiment, predict the effect of constant and varying experimental temperatures as well. In both cases, XRD results show the complete anatase crystal structure of nanotube upon annealing at 450 °C. Present work highlights the importance of constant temperature during the anodization experiments in order to develop an ordered array of nanotubes with a uniform tube diameter.

Keywords: anodization, ordering, temperature, TiO₂ nanotubes

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Authors: Joseph Amponsah

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This research proposes an equation to predict and determine the momentum source equation term after factoring in the radial friction between the fluid and the blades and the impeller's propulsive power. This research aims to look at how CFD software can be used to predict the effect of flows in nuclear reactor stirred tanks through a momentum source equation and the concentration distribution of tracers that have been introduced in reactor tanks. The estimated findings, including the dimensionless concentration curves, power, and pumping numbers, dimensionless velocity profiles, and mixing times 4, were contrasted with results from tests in stirred containers. The investigation was carried out in Part I for vessels that were agitated by one impeller on a central shaft. The two types of impellers employed were an ordinary Rushton turbine and a 6-bladed 45° pitched blade turbine. The simulations made use of numerous reference frame techniques and the common k-e turbulence model. The impact of the grid type was also examined; unstructured, structured, and unique user-defined grids were looked at. The CFD model was used to simulate the flow field within the Rushton turbine nuclear reactor stirred tank. This method was validated using experimental data that were available close to the impeller tip and in the bulk area. Additionally, analyses of the computational efficiency and time using MRF and SM were done.

Keywords: Ansys fluent, momentum equation, CFD, prediction

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Authors: Xin Zhao. Xuerong Zheng. Andrey L. Rogach

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Using single metal atoms has been considered an efficient way to develop new HER and OER catalysts. MXenes, a class of two-dimensional materials, have attracted tremendous interest as promising substrates for single-atom metal catalysts. However, there is still a lack of systematic investigations on the interaction mechanisms between various MXenes substrates and single atoms. Besides, due to the poor interaction between metal atoms and substrates resulting in low loading and stability, dual-atom MXenes-based catalysts have not been successfully synthesized. We summarized the electrocatalytic enhancement mechanism of three MXenes-based single-atom catalysts through experimental and theoretical results demonstrating the stronger hybridization between Co 3d and surface-terminated O 2p orbitals, optimizing the electronic structure of Co single atoms in the composite. This, in turn, lowers the OER and HER energy barriers and accelerates the catalytic kinetics in the case of the Co@V2CTx composite. The poor interaction between single atoms and substrates can be improved by a surface modification to synthesize dual-atom catalysts. The synergistic electronic structure enhances the stability and electrocatalytic activity of the catalyst. Our study provides guidelines for designing single-atom and dual-atom MXene-based electrocatalysts and sheds light on the origins of the catalytic activity of single-atoms on MXene substrates.

Keywords: dual-atom catalyst, single-atom catalyst, MXene substrates, water splitting

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Authors: S. Girish, N. Ajay

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Permeation properties have been widely used to quantify durability characteristics of concrete for assessing long term performance and sustainability. The processes of deterioration in concrete are mediated largely by water. There is a strong interest in finding a better way of assessing the material properties of concrete in terms of durability. Water sorptivity is a useful single material property which can be one of the measures of durability useful in service life planning and prediction, especially in severe environmental conditions. This paper presents the results of the comparative study of sorptivity of Self-Compacting Concrete (SCC) with conventionally vibrated concrete. SCC is a new, special type of concrete mixture, characterized by high resistance to segregation that can flow through intricate geometrical configuration in the presence of reinforcement, under its own mass, without vibration and compaction. SCC mixes were developed for the paste contents of 0.38, 0.41 and 0.43 with fly ash as the filler for different cement contents ranging from 300 to 450 kg/m3. The study shows better performance by SCC in terms of capillary absorption. The sorptivity value decreased as the volume of paste increased. The use of higher paste content in SCC can make the concrete robust with better densification of the micro-structure, improving the durability and making the concrete more sustainable with improved long term performance. The sorptivity based on secondary absorption can be effectively used as a durability index to predict the time duration required for the ingress of water to penetrate the concrete, which has practical significance.

Keywords: self-compacting concrete, service life prediction, sorptivity, volume of paste

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

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Authors: Gargi Ghoshal, Ashay Jain

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Microencapsulation of β-carotene was optimized by complex coacervation technique using casein/gum tragacanth (CAS/GT) coating as a function of pH, initial protein to polysaccharide mixing ratio (Pr:Ps), total biopolymer concentration, core material load, zeta potential, and ionic strength. This study was aimed to understand the influence of experimental parameters on the coacervation kinetics, the coacervate yield, and entrapment efficiency. At a Pr:Ps = 2:1, an optimum pH of complex coacervation was found 4.35, at which the intensity of electrostatic interaction was maximum. At these ratios of coating, the phase separation occurred the fastest and the final coacervate yield and entrapment efficiency was the highest. Varying the Pr: Ps shifted the value of optimum pH. This incident was due to the level of charge compensation of the CAS/GT complexes. Finally, electrostatic interaction and formation of coacervates between CAS and GT were confirmed by Fourier transform infra-red (FTIR) spectra. The size and surface properties of coacervates were studied using scanning electron microscopy (SEM). The resultant formulation (β-carotene loaded microcapsules) was evaluated for in vitro release study and antioxidant activity. Stability of encapsulated β-carotene was also evaluated under three levels of temperature (5, 25 and 40 °C) for 3 months. Encapsulation strongly increased the stability of micronutrients. Our results advocate potential of microcapsules as a novel carrier for the safeguard and sustained release of micronutrient.

Keywords: β-carotene, casein, complex coacervation, controlled release, gum tragacanth, microcapsules

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Authors: Gregory Sullivan

Abstract:

The evolution of global warming has escalated the number and complexity of forest fires around the world. As an example, the United States and Brazil combined generated more than 30,000 forest fires last year. The impact to our environment, structures and individuals is incalculable. The world has learned to try to take this in stride, trying multiple ways to contain fires. Some countries are trying to use cameras in limited areas. There are discussions of using hundreds of low earth orbit satellites and linking them together, and, interfacing them through ground networks. These are all truly noble attempts to defeat the forest fire phenomenon. But there is a better, simpler answer. A bigger piece of the solutions puzzle is to see the fires while they are small, soon after initiation. The approach is to see the fires while they are very small and report their location (latitude and longitude) to local first responders. This is done by placing a sensor at geostationary orbit (GEO: 26,000 miles above the earth). By placing this small satellite in GEO, we can “stare” at the earth, and sense temperature changes. We do not “see” fires, but “measure” temperature changes. This has already been demonstrated on an experimental scale. Fires were seen at close to initiation, and info forwarded to first responders. it were the first to identify the fires 7 out of 8 times. The goal is to have a small independent satellite at GEO orbit focused only on forest fire initiation. Thus, with one small satellite, focused only on forest fire initiation, we hope to greatly decrease the impact to persons, property and the environment.

Keywords: space detection, wildfire early warning, demonstration wildfire detection and action from space, space detection to first responders

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Authors: Aurelien Boutin

Abstract:

In optical systems such as Variable Optical Delay Lines, where a collimated beam has to go back and forth, corner cubes are used in order to keep the reflected beam parallel to the incoming beam. However, the reflected beam can be laterally shifted, which will lead to losses. In this paper, we report on a patented optical design that allows keeping the reflected beam with the exact same position and direction whatever the displacement of the corner cube leading to zero losses. After explaining how the optical design works and theoretically allows to compensate for any defects in the translation of the corner cube, we will present the results of experimental comparisons between a standard layout (i.e., only corner cubes) and our optical layout. To compare both optical layouts, we used a fiber-to-fiber coupling setup. It consists of a couple of lights from one fiber to the other, thanks to two lenses. The ensemble [fiber+lense] is fixed and called a collimator so that the light is coupled from one collimator to another. Each collimator was precisely made in order to have a precise working distance. In the experiment, we measured and compared the Insertion Losses (IL) variations between both collimators with the distance between them (i.e., natural Gaussian beam coupling losses) and between both collimators in the different optical layouts tested, with the same optical length propagation. We will show that the IL variations of our setup are less than 0.05dB with respect to the IL variations of collimators alone.

Keywords: free-space optics, variable optical delay lines, optical cavity, auto-alignment

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Authors: Michele C. Mesomo, Madeline de Souza Correa, Roberta L. Kruger, Luis R. S. Kanda, Marcos L. Corazza

Abstract:

Natural extracts of plants have been used for many years for different purposes and recently they have been screened for their potential use as alternative remedies and food preservatives. Inflorescences of M. paradisiaca L., also known as the heart of the banana, have great economic interest due to its fruit. All parts of the banana are used for many different purposes, including use in folk medicine. The use of extraction via supercritical technology has grown in recent years, though it is still necessary to obtain experimental information for the construction of industrial plants. This work reports the extraction of Musa paradisiaca L. using compressed propane as solvent. The effects of the supercritical extraction conditions, pressure and temperature on the yield were evaluated. The raw material, inflorescences banana, was dried at 313.15 K and milled. The particle size used for the packaging of the extraction cell was 12 mesh (23.5%), 16 mesh (23.5%), 32 mesh (34.5%), 48 mesh (18.5%). The extractions were performed in a laboratory scale unit at pressures of 3.0 MPa, 6.5 MPa and 10.0 MPa and at 308.15 K, 323.15 K and 338.15 K. The operating conditions tested achieved a maximum yield of 2.94 wt% for the CO2 extraction at 10.0 MPa and 338.15 K, higher pressure and temperature. The lower yield, 2.29 wt%, was obtained in the condition of lower pressure and higher temperature. Temperature presented significant and positive effect on the extraction yield with supercritical CO2, while pressure had no effect on the yield. The overall extraction curves showed typical behavior obtained for the supercritical extraction procedure and and reached a constant extraction rate of about 80 to 100 min. The largest amount of extract was obtained at the beginning of the process, within 10 to 60 min.

Keywords: banana, natural products, supercritical extraction, temperature

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Authors: Clement Leroy, Guillaume Boitel

Abstract:

This paper presents a comparative benchmarking review of a steady and transient three-dimensional (3D) flow computations in centrifugal pump using commercial (AnsysCFX) and open source (OpenFOAM) computational fluid dynamics (CFD) software. In centrifugal rotor-dynamic pump, the fluid enters in the impeller along to the rotating axis to be accelerated in order to increase the pressure, flowing radially outward into another stage, vaned diffuser or volute casing, from where it finally exits into a downstream pipe. Simulations are carried out at the best efficiency point (BEP) and part load, for single-phase flow with several turbulence models. The results are compared with overall performance report from experimental data. The use of CFD technology in industry is still limited by the high computational costs, and even more by the high cost of commercial CFD software and high-performance computing (HPC) licenses. The main objectives of the present study are to define OpenFOAM methodology for high-quality 3D steady and transient turbomachinery CFD simulation to conduct a thorough time-accurate performance analysis. On the other hand a detailed comparisons between computational methods, features on latest Ansys release 18 and OpenFOAM is investigated to assess the accuracy and industrial applications of those solvers. Finally an automated connected workflow (IoT) for turbine blade applications is presented.

Keywords: benchmarking, CFX, internet of things, openFOAM, time-accurate, turbomachinery

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Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

Abstract:

Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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Authors: Sila Uzkul, Ayse Dilek Ogreti̇r Ozceli̇k

Abstract:

Sexual development, which starts from fertilization, gainssocial, cultural and psychological dimensions with birth and becomes a lifelongpart of human life. Inorderforchildrentogrowup as healthyindividuals, alldevelopmentalareasneedto be supportedcorrectly, but when it comestosexualdevelopmentandeducation, studiesshowthateducatorsandparentsareinsufficient in terms of information on this subject, andtheyareworried, inadequate In, In restless, In uncomfortableandexcited in In terms In of communication. With this research, it is aimedtoincreasetheknowledgelevel of the parents, theirpositiveattitudetowardssexualeducation, positivecommunicationduringsexualeducationandawareness of sexualabusebyprovidingsexualeducationtotheparents of childrenreceivingpre-schooleducation. The study group of this research, which was designed in quantitativeresearchtype, experimental design, and Solomon four-group model, will be composed of parents of childrenattendingpre-schooleducationinstitutions. In the preparation of the Preschool SexEducation Program to be applied to parents, primaryandsecondarydatasourceswill be used, literaturereviewandarchivescanningmethodswill be used. In the content of the program, theeight main topics (our body, sexuality, emotions, relationships, health, norms, reproductionandrights) thatthe World HealthOrganizationstatesshould be addressed in sexualeducation how toteachthesesubjectstotheirchildren, how toanswerquestionsfromthechild, childsexualdevelopmentandsexualabusetopicswill be included. Theparentsexualeducation program is plannedto be held online (byzoom) for about 45 minutesonce a weekfor 11 weeks. Data will be collectedusingtheSexualCommunicationScale, theSexualEducationAttitudeScale, the sexual Development Knowledge Level andtheAbuse Information/AttitudeScaleforParents. Demographic information of the the parents will be collectedwiththePersonal Information Form to be preparedbytheresearchers. Appropriatestatisticalmethodswill be used in theanalysis of thedata. Studyfindingswill be given in an oral presentation.

Keywords: preschool, sexual development, sexuality education, sexual communication, early childhood, parents' sex education

Procedia PDF Downloads 172