Search results for: geothermal gradient anomalies

Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

Procedia PDF Downloads 144

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

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

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

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Authors: Ayesha Asma, Aqsa Arooj

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It is an essential need in this era of Science and Technology to investigate some unique and appropriate materials for optoelectronic applications. Here, we deliberated, for the first time, the structural, optoelectronic, mechanical, vibrational, and thermo dynamical properties of hexagonal structure selenium-based ternary chalcogenides AScSe₂ (A= K, Cs) by using Perdew-Burke-Ernzerhof Generalized-Gradient-Approximation (PBE-GGA). The lattice angles for these materials are found as α=β=90o and γ=120o. KScSe₂ optimized with lattice parameters a=b=4.3 (Å), c=7.81 (Å) whereas CsScSe₂ got relaxed at a=b=4.43 (Å) and c=8.51 (Å). However, HSE06 functional has overestimated the lattice parameters to the extent that for KScSe₂ a=b=4.92 (Å), c=7.10 (Å), and CsScSe₂ a=b=5.15 (Å), c=7.09 (Å). The energy band gap of these materials calculated via PBE-GGA and HSE06 functionals confirms their semiconducting nature. Concerning Born’s criteria, these materials are mechanically stable ones. Moreover, the temperature dependence of thermodynamic potentials and specific heat at constant volume are also determined while using the harmonic approximation. The negative values of free energy ensure their thermodynamic stability. The vibrational modes are calculated by plotting the phonon dispersion and the vibrational density of states (VDOS), where infrared (IR) and Raman spectroscopy are used to characterize the vibrational modes. The various optical parameters are examined at a smearing value of 0.5eV. These parameters unveil that these materials are good absorbers of incident light in ultra-violet (UV) regions and may be utilized in photovoltaic applications.

Keywords: structural, optimized, vibrational, ultraviolet

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Authors: Ross Lee, Pritpal Singh, Andrew Jester

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As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, new battery technology is necessary for grid applications to curtail these risks. Biological cells, such as human neurons and electrolytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell, akin to the charging/discharging of a battery cell. This work serves as the first step to developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na⁺-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior similar to human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: battery, biomimetic, electrolytes, human neurons, ion-selective membranes, membrane potential

Procedia PDF Downloads 119

Authors: Ardiana Murtezani, Ilirijana Dallku, Teuta Osmani Vllasolli, Sabit Sllamniku

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Background: The use of foot orthoses are always indicated when there are alterations of the optimal biomechanics' position of the foot. Orthotics are very effective and very suitable for the majority of patients with pain due to overload which can be related to biomechanical disorders. Aim: To assess the frequency of patients requiring foot orthoses, type of orthoses and analysis of their disease leading to the use of foot orthoses. Material and Methods: Our study included 128 patients with various foot pathologies, treated at the outpatient department of the Ortho-Prosthetic Center of Kosovo (OPCK) in Prishtina. Prospective-descriptive clinical method was used during this study. Functional status of patients was examined, and the following parameters are noted: range of motion measurements for the affected joints/lower extremities, manual test for muscular strength below the knee and foot of the affected extremity, perimeter measurements of the lower extremities, measurements of lower extremities, foot length measurement, foot width measurements and size. In order to complete the measurements the following instruments are used: plantogram, pedogram, meter and cork shoe lift appliances. Results: The majority of subjects in this study are male (60.2% vs. 39.8%), and the dominant age group was 0-9 (47.7%), 61 subjects respectively. Most frequent foot disorders were: congenital disease 60.1%, trauma cases 13.3%, consequences from rheumatologic disease 12.5%, neurologic dysfunctions 11.7%, and the less frequented are the infectious cases 1.6%. Congenital anomalies were the most frequent cases, and from this group majority of cases suffered from pes planovalgus (37.5%), eqinovarus (15.6%) and discrepancies between extremities (6.3%). Furthermore, traumatic amputations (2.3%) and arthritis (0.8%). As far as neurologic disease, subjects with cerebral palsy are represented with (3.1%), peroneal nerve palsy (2.3%) and hemiparesis (1.6%). Infectious disease osteomyelitis sequels are represented with (1.6%). Conclusion: Based on our study results, we have concluded that the use of foot orthoses for patients suffering from rheumatoid arthritis and nonspecific arthropaty was effective treatment choice, leading to decrease of pain, less deformities and improves the quality of life.

Keywords: orthoses, epidemiological analysis, rheumatoid arthritis, rehabilitation

Procedia PDF Downloads 233

Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion

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Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.

Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law

Procedia PDF Downloads 154

Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

Procedia PDF Downloads 139

Authors: Ankur Dixit, Hiroaki Wagatsuma

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The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

Procedia PDF Downloads 175

Authors: Fadi Al-Badour, Nesar Merah, Abdelrahman Shuaib, Abdelaziz Bazoune

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In the current work, a Coupled Eulerian Lagrangian (CEL) model is developed to simulate the friction stir welding (FSW) process of dissimilar Aluminum alloys (Al 6061-T6 with Al 5083-O). The model predicts volumetric defects, material flow, developed temperatures, and stresses in addition to tool reaction loads. Simulation of welding phase is performed by employing a control volume approach, whereas the welding speed is defined as inflow and outflow over Eulerian domain boundaries. Only material softening due to inelastic heat generation is considered and material behavior is assumed to obey Johnson-Cook’s Model. The model was validated using published experimentally measured temperatures, at similar welding conditions, and by qualitative comparison of dissimilar weld microstructure. The FE results showed that most of developed temperatures were below melting and that the bulk of the deformed material in solid state. The temperature gradient on AL6061-T6 side was found to be less than that of Al 5083-O. Changing the position Al 6061-T6 from retreating (Ret.) side to advancing (Adv.) side led to a decrease in maximum process temperature and strain rate. This could be due to the higher resistance of Al 6061-T6 to flow as compared to Al 5083-O.

Keywords: friction stir welding, dissimilar metals, finite element modeling, coupled Eulerian Lagrangian Analysis

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Authors: Atena Naeimi, Mehri-Sadat Ekrami-Kakhki

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Fe3O4 is one of the important magnetic oxides with spinel structure; it has exhibited unique electric and magnetic properties based on the electron transfer between Fe2+ and Fe3+ in the octahedral sites. Fe3O4 have received considerable attention in various areas such as cancer therapy, drug targeting, enzyme immobilization catalysis, magnetic cell separation, magnetic refrigeration systems and super-paramagnetic materials. Fe3O4–ZnO nanostructures were synthesized via a surfactant-free ultrasonic reaction at room temperatures. The effect of various parameters such as temperature, time, and power on the size and morphology of the product was investigated. Alternating gradient force magnetometer shows that Fe3O4 nanoparticles exhibit super-paramagnetic behaviour at room temperature. For preparation of nanocomposite 1 g of Fe3O4 nanostructures were dispersed in 100 mL of distilled water. 0.25 g of Zn (NO3)2 and 20 mL of NH3 solution 1 M were then slowly added to the solution under ultrasonic irradiation. The product was centrifuged, washed with distilled water and dried in the air. The photocatalytic behaviour of Fe3O4–ZnO nanoparticles was evaluated using the degradation of a methyl orange aqueous solution under ultraviolet light irradiation. As time increased, more and more methyl orange was adsorbed on the nanoparticles catalyst, until the absorption peak vanish. The methyl orange concentration decreased rapidly with increasing UV-irradiation time.

Keywords: nanocomposite, ultrasonic, paramagnetic, photocatalytic

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Authors: A. Oukaira, A. Lakhssassi, O. Ettahri

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To make a good thermal management in an ABDM (Adapter Board Detector Module) card, we must first control temperature and its gradient from the first step in the design of integrated circuits ASIC of our complex system. In this paper, our main goal is to develop and validate the thermal stability in order to get an idea of the flow of heat around the ASIC in transient and thus address the thermal issues for integrated circuits at the ABDM card. However, we need heat sources simulations for ABDM card to establish its thermal mapping. This led us to perform simulations at each ASIC that will allow us to understand the thermal ABDM map and find real solutions for each one of our complex system that contains 36 ABDM map, taking into account the different layers around ASIC. To do a transient simulation under NISA, we had to build a function of power modulation in time TIMEAMP. The maximum power generated in the ASIC is 0.6 W. We divided the power uniformly in the volume of the ASIC. This power was applied for 5 seconds to visualize the evolution and distribution of heat around the ASIC. The DBC (Dirichlet Boundary conditions) method was applied around the ABDM at 25°C and just after these simulations in NISA tool we will validate them by COMSOL tool, wich is a numerical calculation software for a modular finite element for modeling a wide variety of physical phenomena characterizing a real problem. It will also be a design tool with its ability to handle 3D geometries for complex systems.

Keywords: ABDM, APD, thermal mapping, complex system

Procedia PDF Downloads 264

Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

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Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, chemometrics, molecular modeling, molecular descriptors, QSPR

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

Procedia PDF Downloads 88

Authors: Jeong Woo Kang, MiYoung Baek, Ki-Suk Kim, Kwang-Jick Lee, ByungJae So

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Introduction: A fast, easy and sensitive detection method was developed and validated by liquid chromatography tandem mass spectrometry for the determination of marbofloxacin in pig plasma which was further applied to study the pharmacokinetics of marbofloxacin. Materials and Methods: The plasma sample (500 μL) was mixed with 1.5 ml of 0.1% formic acid in MeCN to precipitate plasma proteins. After shaking for 20 min, The mixture was centrifuged at 5,000 × g for 30 min. It was dried under a nitrogen flow at 50℃. 500 μL aliquot of the sample was injected into the LC-MS/MS system. Chromatographic analysis was carried out mobile phase gradient consisting 0.1% formic acid in D.W. (A) and 0.1% formic acid in MeCN (B) with C18 reverse phase column. Mass spectrometry was performed using the positive ion mode and the selected ion monitoring (MRM). Results and Conclusions: The method validation was performed in the sample matrix. Good linearities (R2>0.999) were observed and the quantified average recoveries of marbofloxacin were 87 - 92% at level of 10 ng g-1 -100 ng g-1. The percent of coefficient of variation (CV) for the described method was less than 10 % over the range of concentrations studied. The limits of detection (LOD) and quantification (LOQ) were 2 and 5 ng g-1, respectively. This method has also been applied successfully to pharmacokinetic analysis of marbofloxacin after intravenous (IV), intramuscular (IM) and oral administration (PO). The mean peak plasma concentration (Cmax) was 2,597 ng g-1at 0.25 h, 2,587 ng g-1at 0.44 h and 2,355 ng g-1at 1.58 h for IV, IM and PO, respectively. The area under the plasma concentration-time curve (AUC0–t) was 24.8, 29.0 and 25.2 h μg/mL for IV, IM and PO, respectively. The elimination half-life (T1/2) was 8.6, 13.1 and 9.5 for IV, IM and PO, respectively. Bioavailability (F) of the marbofloxacin in pig was 117 and 101 % for IM and PO, respectively. Based on these result, marbofloxacin does not have any obstacles as therapeutics to develop the oral formulations such as tablets and capsules.

Keywords: marbofloxacin, LC-MS/MS, pharmacokinetics, chromatographic

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Authors: Wanhyun Cho, Seongchae Seo, Soonja Kang

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In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques.

Keywords: color image, contrast enhancement technique, variational approach, Euler-Lagrang equation, dynamic approximation method, EME measure

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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: Evln Ranga Charyulu, S. P. Venu Madhavarao, S. Udaya kumar, S. V. S. S. N. V. G. Krishna Murthy

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With the advent of new nanometer process technologies, it is possible to integrate billion transistors on a single substrate. When more and more functionality included there is the possibility of multi-million transistors switching simultaneously consuming more power and dissipating more power along with more leakage of current into the substrate of porous silicon or germanium material. These results in substrate heating and thermal noise generation coupled to signals of interest. The heating process is represented by coupled nonlinear partial differential equations in porous silicon and germanium. By identifying heat sources and heat fluxes may results in designing of ultra-low power circuits. The PDEs are solved by finite difference scheme assuming that boundary layer equations in porous silicon and germanium. Local heat fluxes along the vertical isothermal surface immersed in porous SI/Ge are considered. The parameters considered for optimization are thermal diffusivity, thermal expansion coefficient, thermal diffusion ratio, permeability, specific heat at constant temperatures, Rayleigh number, amplitude of wavy surface, mass expansion coefficient. The diffusion of heat was caused by the concentration gradient. Thermal physical properties are homogeneous and isotropic. By using L8, TAGUCHI method the parameters are optimized.

Keywords: heat transfer, pde, taguchi optimization, SI/Ge

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Authors: O. Afshar

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Unlike other renewable energy sources, tidal current energy is an extremely reliable, predictable and continuous energy source as the current pattern and speed can be predicted throughout the year. A key concern associated with tidal turbines is their long-term reliability when operating in the hostile marine environment. Bio-fouling changes the physical shape and roughness of turbine components, hence altering the overall turbine performance. This paper seeks to employ Computational Fluid Dynamics (CFD) method to quantify the effects of this problem based on the obtained flow field information. The simulation is carried out on a NACA 63-618 aerofoil. The Reynolds Averaged Navier-Stokes (RANS) equations with Shear Stress Transport (SST) turbulent model are used to simulate the flow around the model. Different levels of fouling are studied on 2D aerofoil surface with quantified fouling height and density. In terms of lift and drag coefficient results, numerical results show good agreement with the experiment which was carried out in wind tunnel. Numerical results of research indicate that an increase in fouling thickness causes an increase in drag coefficient and a reduction in lift coefficient. Moreover, pressure gradient gradually becomes adverse as height of fouling increases. In addition, result by turbulent kinetic energy contour reveals it increases with fouling height and it extends into wake due to flow separation.

Keywords: tidal energy, lift coefficient, drag coefficient, roughness

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Authors: Ahmad Lutfi, Nikolas Dhega

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The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

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Authors: Huda Aldossari

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Members of the Brassicaceae family, such as rocket species, have high concentrations of glucosinolates (GLSs). GSLs and isothiocyanates (ITCs), the product of GLSs hydrolysis, are the most influential compounds that affect flavour in rocket species. Aside from their contribution to the flavour, GSLs and ITCs are of particular interest due to their potential ability to inhibit the growth of human pathogenic bacteria such as E. coli O157. Quantitative and qualitative analysis of glucosinolate compounds in rocket extracts was obtained by Liquid Chromatography-Mass Spectrometry (LC–MS).Each individual component of non-volatile GLSs and ITCs was isolated by High-Performance Liquid Chromatography (HPLC) fractionation. The identity and purity of each fraction were confirmed using Ultra High-Performance Liquid Chromatography (UPLC). The separation of glucosinolates in the complex rocket extractions was performed by optimizing a HPLC fractionation method through changing the mobile phase composition, solvent gradient, and the flow rate. As a result, six glucosinolates compounds (Glucosativin, 4-Methoxyglucobrassicin, Glucotropaeolin GTP, Glucoiberin GIB, Diglucothiobenin, and Sinigrin) have been isolated, identified and quantified in the complex samples. This step aims to evaluate the antibacterial activity of glucosinolates and their enzymatic hydrolysis against bacterial growth of E.coli k12. Therefore, fractions from this study will be used to determine the most active compounds by investigating the efficacy of each component of GLSs and ITCs at inhibiting bacterial growth.

Keywords: rocket, glucosinolates, E.coli k12., HPLC fractionatio

Procedia PDF Downloads 98

Authors: Siraj Beyan Mohamed, Woldia University

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The study is accompanied in northern Ethiopian basement rocks, Finarwa area, and its surrounding areas, south eastern Tigray. From the field observations, the geology of the area haven been described and mapped based on mineral composition, texture, structure, and colour of both fresh and weather rocks. Inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectrometry (AAS) have conducted to analysis gold and base metal mineralization. The ore mineral under microscope are commonly base metal sulphides pyrrhotite, Chalcopyrite, pentilanditeoccurring in variable proportions. Galena, chalcopyrite, pyrite, and gold mineral are hosted in quartz vein. Pyrite occurs both in quartz vein and enclosing rocks as a primary mineral. The base metal sulfides occur as disseminated, vein filling, and replacement. Geochemical analyses result determination of the threshold of geochemical anomalies is directly related to the identification of mineralization information. From samples, stream sediment samples and the soil samples indicated that the most promising mineralization occur in the prospect area are gold(Au), copper (Cu), and zinc (Zn). This is also supported by the abundance of chalcopyrite and sphalerite in some highly altered samples. The stream sediment geochemical survey data shows relatively higher values for zinc compared to Pb and Cu. The moderate concentration of the base metals in some of the samples indicates availability base metal mineralization in the study area requiring further investigation. The rock and soil geochemistry shows the significant concentration of gold with maximum value of 0.33ppm and 0.97 ppm in the south western part of the study area. In Finarwa, artisanal gold mining has become an increasingly widespread economic activity of the local people undertaken by socially differentiated groups with a wide range of education levels and economic backgrounds incorporating a wide variety of ‘labour intensive activities without mechanisation.

Keywords: gold, base metal, anomaly, threshold

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Authors: Mohammad Bqoor, Mohammad Hamdan, Isam Janajreh, Sufian Abedrabbo

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This extensive theoretical study on a novel Ionized Gas Thermoelectric Generator (IG-TEG) system has shown the ability of continuous energy extracting from the thermal energy of ambient air around standard room temperature and even below. This system does not need a temperature gradient in order to work, unlike the other TEGs that use the Seebeck effect, and therefore this new system can be utilized in sustainable energy systems, as well as in green cooling solutions, by extracting energy instead of wasting energy in compressing the gas for cooling. This novel system was designed based on Static Ratchet Potential (SRP), which is known as a spatially asymmetric electric potential produced by an array of positive and negative electrodes. The ratchet potential produces an electrical current from the random Brownian Motion of charged particles that are driven by thermal energy. The key parameter of the system is particle transportation, and it was studied under the condition of flashing ratchet potentials utilizing several methods and examined experimentally, ensuring its functionality. In this study, a different approach is pursued to estimate particle transportation by evaluating the charged particle distribution and applying the other conditions of the SRP, and showing continued energy harvesting potency from the particles’ transportation. Ultimately, power levels of 10 Watt proved to be achievable from a 1 m long system tube of 10 cm radius.

Keywords: thermoelectric generator, ratchet potential, Brownian ratchet, energy harvesting, sustainable energy, green technology

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Rupamoni Thakur, Madhusmita Dehingia, Narayan C. Talukdar, Mojibur R. Khan

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The human gut is an extremely active fermentation site and is inhabited by diverse bacterial species. Consumption of alcoholic beverages has been shown to substantially modulate the human gut bacterial profile (GBP) of an individual. Assam, a major north-eastern state of India, is home to a number of tribal populations of which the tea-tribes form a major community. These tea-tribal communities are known to prepare and consume a locally-prepared alcoholic beverage from fermented jaggery, whose chemical composition is unknown. In this study, we demonstrate the effect of daily intake of the locally-prepared alcoholic beverage on the GBP of the tea-tribal communities and correlate it with the changes in the biochemical biomarkers of the population. The fecal bacterial diversity of 40 drinkers and 35 non-drinking healthy individuals were analyzed by polymerase chain reaction (PCR)–denaturing gradient gel electrophoresis (DGGE). The results suggested that the GBP was significantly modulated in the fermented-beverage consuming subjects. Significant difference was also observed in the serum biochemical parameters such as triglyceride, total cholesterol and the liver marker enzymes (ASAT/ALAT and GGT). Further studies to identify the GBP of drinkers vs non-drinkers through Next-generation Sequencing (NGS) analysis and to correlate the changes with the biochemical biomarkers of the population is underway.

Keywords: alcoholic beverage, gut bacterial profile, PCR-DGGE analysis, tea-tribes of India

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Authors: S. Ilahi, S. Almosni, F. Chouchene, M. Perrin, K. Zelazna, N. Yacoubi, R. Kudraweic, P. Rale, L. Lombez, J. F. Guillemoles, O. Durand, C. Cornet

Abstract:

Great efforts have been dedicated to obtain high quality of GaAsPN. The properties of GaAsPN have played a great part on the development of solar cells devices based in Si substrate. The incorporation of N in GaAsPN that having a band gap around of 1.7 eV is of special interest in view of growing in Si substrate. In fact, post-growth and rapid thermal annealing (RTA) could be an effective way to improve the quality of the layer. Then, the influence of growth conditions and post-growth annealing on optical and thermal parameters is considered. We have used Photothermal deflection spectroscopy PDS to investigate the impact of rapid thermal annealing on thermal and optical properties of GaAsPN. In fact, the principle of the PDS consists to illuminate the sample by a modulated monochromatic light beam. Then, the absorbed energy is converted into heat through the nonradiative recombination process. The generated thermal wave propagates into the sample and surrounding media creating a refractive-index gradient giving rise to the deflection of a laser probe beam skimming the sample surface. The incident light is assumed to be uniform, and only the sample absorbs the light. In conclusion, the results are promising revealing an improvement in absorption coefficient and thermal conductivity.

Keywords: GaAsPN absorber, photothermal defelction technique PDS, photonics on silicon, thermal conductivity

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Authors: Morteza Shayan Arani, Mohammadamin Esmailzadehazimi, Mohammadreza Moeini, Mohammad Toorani, Aouni A. Lakis

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This paper investigates the nonlinear response of thin, incompressible, hyperelastic cylindrical shells in the presence of a time-varying temperature field while considering initial geometric imperfections. The governing equations of motion are derived using an improved Donnell's shallow shell theory. The hyperelastic material is modeled using the Mooney-Rivlin model with two parameters, incorporating temperature-dependent terms. The Lagrangian method is applied to obtain the equation of motion. The resulting governing equation is addressed through the Lindstedt-Poincaré and Multiple Scale methods. The linear and nonlinear models presented in this study are verified against existing open literature, demonstrating the accuracy and reliability of the presented model. The study focuses on understanding the influence of temperature variations and geometrical imperfections on the natural frequency and amplitude-frequency response of the systems. Notably, the investigation reveals the coexistence of hardening and softening peaks in the amplitude-frequency response, which vary in magnitude depending on these parameters. Additionally, resonance peaks exhibit changes as a result of temperature and geometric imperfections.

Keywords: hyperelastic material, cylindrical shell, geometrical nonlinearity, material naolinearity, initial geometric imperfection, temperature gradient, hardening and softening

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Authors: Ming Ze Kao

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Static magnetic fields (SMF) are widely used in several medical applications, especially in diagnosis of tumors. However, biological effects of the SMFs on modulating cell physiology through the Lorentz force, which is highly frequency and magnitude dependent, remain to be elucidated. Specific patterns from SMFs of static MF, delivered by means of Halbach array magnets with a gradient increment of 6.857mT/mm from center to border, were found to have profound inhibitory effect on the growth rate of human cell line derived from Nasopharyngeal carcinoma patients. The SMFs, which were shown to be noncontact, selectively impact rapid dividing cells while quiescent cells stay intact. The phenomenon acts in two modes: the arrest of cell proliferation in the G2/M phase and destruction of cell mitosis in cell division. First mode is manifested by impacting the proper formation of mitotic spindle, whereas the second results in disintegration of the cancer cell. Both modes are demonstrated when SMF was applied for 24 hours to cancer cells, the results revealed that metaphase arrest during mitosis due to activation of DNA damage response (DDR), resulting in high expression of ATM-NBS1-CHEK signaling pathways and higher G2/M phase ratio compared with control group. Here, experimental data suggest that the SMFs cause activation of cell cycle checkpoints, which implies the MFs as a potential therapeutic modality as a sensitizer for radiotherapy or chemotherapy.

Keywords: static magnetic field, DNA damage response, Halbach array, magnetic therapy

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Authors: Neda Azimi, Masoud Rahimi, Faezeh Mohammadi

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Computational fluid dynamics (CFD) simulation was performed to investigate the effect of ferrofluid stimulation on hydrodynamic and mass transfer characteristics of two immiscible liquid phases in a Y-micromixer. The main purpose of this work was to develop a numerical model that is able to simulate hydrodynamic of the ferrofluid flow under magnetic field and determine its effect on mass transfer characteristics. A uniform external magnetic field was applied perpendicular to the flow direction. The volume of fluid (VOF) approach was used for simulating the multiphase flow of ferrofluid and two-immiscible liquid flows. The geometric reconstruction scheme (Geo-Reconstruct) based on piecewise linear interpolation (PLIC) was used for reconstruction of the interface in the VOF approach. The mass transfer rate was defined via an equation as a function of mass concentration gradient of the transported species and added into the phase interaction panel using the user-defined function (UDF). The magnetic field was solved numerically by Fluent MHD module based on solving the magnetic induction equation method. CFD results were validated by experimental data and good agreements have been achieved, which maximum relative error for extraction efficiency was about 7.52 %. It was showed that ferrofluid actuation by a magnetic field can be considered as an efficient mixing agent for liquid-liquid two-phase mass transfer in microdevices.

Keywords: CFD modeling, hydrodynamic, micromixer, ferrofluid, mixing

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Authors: Kobus-Cisowska Joanna, Flaczyk Ewa, Gramza-Michalowska Anna, Kmiecik Dominik, Przeor Monika, Marcinkowska Agata

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In recent years, proceed to the attractiveness of typical bakery products. Expanding the education and nutrition knowledge society will develop the production of functional foods, which has a positive impact on human health. Therefore, the aim of the present study was to evaluate the effect of the addition of white mulberry fruit on the content of biologically active compounds in the new designed functional bread premixes designed for selected disease: anemia, diabetes, obesity and cardiovascular disease. For flavonols and phenolic acids content UPLC was conducted, using an NovaPack C18 column and a gradient elution system. It was found that all attempts bread characterized by a high content of biologically active compounds: polyphenols, phenolic acids, and flavonoids. The highest total content of polyphenolic compounds found in the samples of bread for anemia, diabetes and cardiovascular disease both before and after storage. The analyzed sample differed in content of phenolic acids. The highest content of these compounds were found in samples of bread for anemia and diabetes. It was found that the analyzed sample contained phenolic acids that are derivatives of hydroxybenzoic and hydroxycinnamic acid. The new designed bread contained significant amounts of flavonols, of which the dominant was routine.

Keywords: mulberry, antioxidant, polyphenols, phenolic acids, flavonols

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Authors: S. Maleczek, K. Drabczyk, L. Bogdan, A. Iwan

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It is known that for industrial applications using solar panel constructed from silicon solar cells require high-efficiency performance. One of the main problems in solar panels is different mechanical and structural defects, causing the decrease of generated power. To analyse defects in solar cells, various techniques are used. However, the thermal imaging is fast and simple method for locating defects. The main goal of this work was to analyze defects in constructed flexible silicon photovoltaic modules via thermal imaging and electroluminescence method. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. Thermal behavior was observed using thermographic camera (VIGOcam v50, VIGO System S.A, Poland) using a DC conventional source. Electroluminescence was observed by Steinbeis Center Photovoltaics (Stuttgart, Germany) equipped with a camera, in which there is a Si-CCD, 16 Mpix detector Kodak KAF-16803type. The camera has a typical spectral response in the range 350 - 1100 nm with a maximum QE of 60 % at 550 nm. In our work commercial silicon solar cells with the size 156 × 156 mm were cut for nine parts (called single solar cells) and used to create photovoltaic modules with the size of 160 × 70 cm (containing about 80 single solar cells). Flexible silicon photovoltaic modules on polyamides or polyester fabric were constructed and investigated taking into consideration anomalies on the surface of modules. Thermal imaging provided evidence of visible voltage-activated conduction. In electro-luminescence images, two regions are noticeable: darker, where solar cell is inactive and brighter corresponding with correctly working photovoltaic cells. The electroluminescence method is non-destructive and gives greater resolution of images thereby allowing a more precise evaluation of microcracks of solar cell after lamination process. Our study showed good correlations between defects observed by thermal imaging and electroluminescence. Finally, we can conclude that the thermographic examination of large scale photovoltaic modules allows us the fast, simple and inexpensive localization of defects at the single solar cells and modules. Moreover, thermographic camera was also useful to detection electrical interconnection between single solar cells.

Keywords: electro-luminescence, flexible devices, silicon solar cells, thermal imaging

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