Search results for: trust-region method

Authors: Hossein Ghaedamini, Salman Farahbakhsh, Alireza Amirbeigi, Zahra Saghafi, Salman Daneshi, Alireza Ghaedamini

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Background: Assessing the challenges of clinical education of medical students is one of the most important and sensitive parts of medical education. The aim of this study was to investigate the views and experiences of Kerman medical students on the factors that facilitate and inhibit the quality of clinical education. Materials and Methods: This research was qualitative and used a phenomenological approach. The study population included medical interns of Kerman University of Medical Sciences in 1400. The method of data collection was in-depth interviews with participants. Data were encoded and analyzed by Claizey stepwise model. Results: First, about 540 primary codes were extracted in the form of two main themes (facilitators and inhibitors) and 10 sub-themes including providing motivational models and creating interest in interns, high scientific level of professors and the appropriate quality of their teaching, the use of technology in the clinical education process, delegating authority and freedom of action and more responsibilities to interns, inappropriate treatment of some officials, professors, assistants and department staff with their interns, inadequate educational programming, lack of necessary cooperation and providing inappropriate treatment by clinical training experts for interns, inadequate evaluation method in clinical training for interns, poor quality mornings, the unefficiency of grand rounds, the inappropriate way of evaluating clinical training for interns, the lack of suitable facilities and conditions with the position of a medical intern, and the hardwork of some departments were categorized. Conclusion: Clinical education is always mixed with special principles and subtleties, and special attention to facilitators and inhibitors in this process has an important role in improving its quality.

Keywords: clinical education, medical students, qualitative study, education

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Authors: Dina Kon Mushid, Kabutakapua Kakanda, Dibu Dave Mbako

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The failure of material usually involves elastoplastic deformation and fracturing. Continuum mechanics can effectively deal with plastic deformation by using a yield function and the flow rule. At the same time, it has some limitations in dealing with the fracture problem since it is a theory based on the continuous field hypothesis. The lattice model can simulate the fracture problem very well, but it is inadequate for dealing with plastic deformation. Based on the discretized virtual internal bond model (DVIB), this paper proposes a lattice model that can account for plasticity. DVIB is a lattice method that considers material to comprise bond cells. Each bond cell may have any geometry with a finite number of bonds. The two-body or multi-body potential can characterize the strain energy of a bond cell. The two-body potential leads to the fixed Poisson ratio, while the multi-body potential can overcome the limitation of the fixed Poisson ratio. In the present paper, the modified Stillinger-Weber (SW), a multi-body potential, is employed to characterize the bond cell energy. The SW potential is composed of two parts. One part is the two-body potential that describes the interatomic interactions between particles. Another is the three-body potential that represents the bond angle interactions between particles. Because the SW interaction can represent the bond stretch and bond angle contribution, the SW potential-based DVIB (SW-DVIB) can represent the various Poisson ratios. To embed the plasticity in the SW-DVIB, the plasticity is considered in the two-body part of the SW potential. It is done by reducing the bond stiffness to a lower level once the bond reaches the yielding point. While before the bond reaches the yielding point, the bond is elastic. When the bond deformation exceeds the yielding point, the bond stiffness is softened to a lower value. When unloaded, irreversible deformation occurs. With the bond length increasing to a critical value, termed the failure bond length, the bond fails. The critical failure bond length is related to the cell size and the macro fracture energy. By this means, the fracture energy is conserved so that the cell size sensitivity problem is relieved to a great extent. In addition, the plasticity and the fracture are also unified at the bond level. To make the DVIB able to simulate different Poisson ratios, the three-body part of the SW potential is kept elasto-brittle. The bond angle can bear the moment before the bond angle increment is smaller than a critical value. By this method, the SW-DVIB can simulate the plastic deformation and the fracturing process of material with various Poisson ratios. The elastoplastic SW-DVIB is used to simulate the plastic deformation of a material, the plastic fracturing process, and the tunnel plastic deformation. It has been shown that the current SW-DVIB method is straightforward in simulating both elastoplastic deformation and plastic fracture.

Keywords: lattice model, discretized virtual internal bond, elastoplastic deformation, fracture, modified stillinger-weber potential

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Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

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Authors: Joseph Bostick

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A method of decreasing the heating load of HVAC systems in a single-dwelling model of a multifamily building, by controlling movable insulation through the optimization of flux, time, surface incident solar radiation, and temperature thresholds. Simulations are completed using a co-simulation between EnergyPlus and MATLAB as an optimization tool to find optimal control thresholds. Optimization of the control thresholds leads to a significant decrease in total heating energy expenditure.

Keywords: energy plus, MATLAB, simulation, energy efficiency

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Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

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In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

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Authors: Chong Hu, Tiantian Wang, Zhe Li, Ourui Huang, Yichen Pan

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When the train is running in a high geothermal tunnel, changes in the temperature field will cause disturbances in the propagation and superposition of pressure waves in the tunnel, which in turn have an effect on the aerodynamic resistance of the train. The aim of this paper is to investigate the effect of the changes in the lengths of the high-temperature zone of the tunnel on the aerodynamic resistance of the train, clarifying the evolution mechanism of aerodynamic resistance of trains in tunnels with high ground temperatures. Firstly, moving model tests of trains passing through wall-heated tunnels were conducted to verify the reliability of the numerical method in this paper. Subsequently, based on the three-dimensional unsteady compressible RANS method and the standard k-ε two-equation turbulence model, the change laws of the average aerodynamic resistance under different high-temperature zone lengths were analyzed, and the influence of frictional resistance and pressure difference resistance on total resistance at different times was discussed. The results show that as the length of the high-temperature zone LH increases, the average aerodynamic resistance of a train running in a tunnel gradually decreases; when LH = 330 m, the aerodynamic resistance can be reduced by 5.7%. At the moment of maximum resistance, the total resistance, differential pressure resistance, and friction resistance all decrease gradually with the increase of LH and then remain basically unchanged. At the moment of the minimum value of resistance, with the increase of LH, the total resistance first increases and then slowly decreases; the differential pressure resistance first increases and then remains unchanged, while the friction resistance first remains unchanged and then gradually decreases, and the ratio of the differential pressure resistance to the total resistance gradually increases with the increase of LH. The results of this paper can provide guidance for scholars who need to investigate the mechanism of aerodynamic resistance change of trains in high geothermal environments, as well as provide a new way of thinking for resistance reduction in non-high geothermal tunnels.

Keywords: high-speed trains, aerodynamic resistance, high-ground temperature, tunnel

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Authors: Sara Najiazarpour, Mahsa Najiazarpour

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There are many problems in contracting projects and their performance. At each project stage and due to different reasons, these problems affect cost, time and overall project quality. Hence, in order to increase the efficiency and performance in all levels of the chain and with supply chain management approach, there will be a coordination from the beginning of a project (contractor selection) to the end of project (handover of project). Contractor selection is the foremost part of construction projects which in this multi-criteria decision-making, the best contractor is determined by expert judgment, different variables and their priorities. In this paper for selecting the best contractor, numerous criteria were collected by asking from adept experts and then among them, 16 criteria with highest frequency were considered for questionnaire. This questionnaire was distributed between experts. Cronbach's alpha coefficient was obtained as 72%. Then based on Borda's function 12 important criteria was selected which was categorized in four main criteria and related sub-criteria as follow: Environmental factors and physical equipment: procurement and materials (supplier), company's machines, contractor’s proposed cost estimate - financial capacity: bank turnover and company's assets, the income of tax declaration in last year, Ability to compensate for losses or delays - past performance- records and technical expertise: experts and key personnel, the past technical backgrounds and experiences, employer satisfaction of previous contracts, the number of similar projects was done - standards: rank and field of expertise which company is qualified for and its validity, availability and number of permitted projects done. Then with PROMTHEE method, the criteria were normalized and monitored, finally the best alternative was selected. In this research, qualitative criteria of each company is became a quantitative criteria. Finally, information of some companies was evaluated and the best contractor was selected based on all criteria and their priorities.

Keywords: contractor evaluation and selection, project development, supply chain management, PROMTHEE method

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Authors: Flóra Pomázi, Sándor Baranya, Zoltán Szalai

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A harmonized monitoring of the suspended sediment transport along such a large river as the world’s most international river, the Danube River, is a rather challenging task. The traditional monitoring method in Hungary is obsolete but using indirect measurement devices and techniques like optical backscatter sensors (OBS), laser diffraction or acoustic backscatter sensors (ABS) could provide a fast and efficient alternative option of direct methods. However, these methods are strongly sensitive to the particle characteristics (i.e. particle shape, particle size and mineral composition). The current method does not provide sufficient information about particle size distribution, mineral analysis is rarely done, and the shape of the suspended sediment particles have not been examined yet. The aims of the study are (1) to determine the particle characterisation of suspended sediment in the Danube River using advanced particle characterisation methods as laser diffraction and automated imaging, and (2) to perform a sensitivity analysis of the indirect methods in order to determine the impact of suspended particle characteristics. The particle size distribution is determined by laser diffraction. The particle shape and mineral composition analysis is done by the Morphologi G3ID image analyser. The investigated indirect measurement devices are the LISST-Portable|XR, the LISST-ABS (Sequoia Inc.) and the Rio Grande 1200 kHz ADCP (Teledyne Marine). The major findings of this study are (1) the statistical shape of the suspended sediment particle - this is the first research in this context, (2) the actualised particle size distribution – that can be compared to historical information, so that the morphological changes can be tracked, (3) the actual mineral composition of the suspended sediment in the Danube River, and (4) the reliability of the tested indirect methods has been increased – based on the results of the sensitivity analysis and the previous findings.

Keywords: advanced particle characterisation, automated imaging, indirect methods, laser diffraction, mineral composition, suspended sediment

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Authors: Akanksha Lohmore, Devanshu Arya, Preeti Kapur

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Rarely does the human mind look at the positive fallout of highly negative events. Positive psychology attempts to emphasize on the strengths and positives for human well-being. The present study examines the underpinning socio-cognitive factors of the protest movements regarding the gang rape case of December 16th, 2012 through the lens of positive psychology. A gamut of negative emotions came to the forum globally: of anger, shame, hatred, violence, death penalty for the perpetrators, amongst other equally strong. In relation to this incident, a number of questions can be raised. Can such a heinous crime have some positive inputs for contemporary society? What is it that has held people to protests for long even when they see faded lines of success in view? This paper explains the constant feeding of protests and continuation of movements by the robust model of Collective Hope by Snyder, a phenomenon unexplored by social psychologists. In this paper, mixed method approach was undertaken. Results confirmed the interaction of various socio-psychological factors that imitated the Snyders model of collective hope. Emergence of major themes was: Sense of Agency, Sense of Worthiness, Social Sharing and Common Grievances and Hope of Collective Efficacy. Statistical analysis (correlation and regression) showed significant relationship between media usage and occurrence of these themes among participants. Media-communication processes and educational theories for development of citizenship behavior can find implications from these results. Theory development as indicated by theorists working in the area of Social Psychology of Protests can be furthered by the direction of research.

Keywords: agency, collective, hope, positive psychology, protest, social media

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Authors: Carlos Riascos, Peter Thomson

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Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: N. Santatriniaina, J. Deseure, T. Q. Nguyen, H. Fontaine, C. Beitia, L. Rakotomanana

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Nowadays, with the increasing of the wafer's size and the decreasing of critical size of integrated circuit manufacturing in modern high-tech, microelectronics industry needs a maximum attention to challenge the contamination control. The move to 300 mm is accompanied by the use of Front Opening Unified Pods for wafer and his storage. In these pods an airborne cross contamination may occur between wafers and the pods. A predictive approach using modeling and computational methods is very powerful method to understand and qualify the AMCs cross contamination processes. This work investigates the required numerical tools which are employed in order to study the AMCs cross-contamination transfer phenomena between wafers and FOUPs. Numerical optimization and finite element formulation in transient analysis were established. Analytical solution of one dimensional problem was developed and the calibration process of physical constants was performed. The least square distance between the model (analytical 1D solution) and the experimental data are minimized. The behavior of the AMCs intransient analysis was determined. The model framework preserves the classical forms of the diffusion and convection-diffusion equations and yields to consistent form of the Fick's law. The adsorption process and the surface roughness effect were also traduced as a boundary condition using the switch condition Dirichlet to Neumann and the interface condition. The methodology is applied, first using the optimization methods with analytical solution to define physical constants, and second using finite element method including adsorption kinetic and the switch of Dirichlet to Neumann condition.

Keywords: AMCs, FOUP, cross-contamination, adsorption, diffusion, numerical analysis, wafers, Dirichlet to Neumann, finite elements methods, Fick’s law, optimization

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Authors: Simont Toussi

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Cameroon and the Central African Republic arebound by the provisions of many regional and international charters, which condemn the manipulation of information, obstacles to access reliable information, or the limitation of freedoms of expression and opinion. These two countries also have constitutional guarantees for free speech and access to true and liable information. However, they are yet to define specific policies and regulations for access to information, disinformation, or misinformation. Yet, certain countries’ laws and regulations related to information and communication technologies, to criminal procedures, to terrorism, or intelligence services contain provisions that rather hider human rights by condemning false information. Like many other African countries, Cameroon and the Central African Republic face a profound democratic regression, and governments use multiple methods to stifle online discourse and digital rights. Despite the increased uptake of digital tools for political participation, there is a lack of interactivity and adoption of these tools. This enables a scarcity of information and creates room for the spreading of disinformation in the public space, hamperingdemocracy and the respect for human rights. This research aims to analyse the adequacy of stakeholders’ responses to disinformation in Cameroon and the Central African Republic in periods of political contestation, such as elections and anti-government protests, to highlight the nature, perpetrators, strategies, and channels of disinformation, as well as its effects on democratic actors, including civil society, bloggers, government critics, activists, and other human rights defenders. The study follows a qualitative method with literature review, content analysis, andkey informant’sinterviews with stakeholders’ representatives, emphasized crowdsourcing as a data and information collecting method in the two countries.

Keywords: disinformation, democracy, political manipulation, social media, media, fake news, central Africa, cameroon, misinformation, free speech

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Authors: Bahieddine. Bouabdellah, Benameur. Amiri, Abdelkader.nouri

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Europium-doped gallium nitride (EuGaN) is a promising material for optoelectronic and thermoelectric devices. This study investigates its optical properties using density functional theory (DFT) with the FP-LAPW method and MBJ+U correction. The simulation substitutes a gallium atom with europium in a hexagonal GaN lattice (6% doping). Distinct absorption peaks are observed in the optical analysis. These results highlight EuGaN's potential for various applications and pave the way for further research on rare earth-doped materials.

Keywords: eugan, fp-lapw, dft, wien2k, mbj hubbard

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Authors: Stéphanie Pellerin, Bérengére Podvin, Luc Pastur

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In aerovehicles context, the flow around an Ahmed body profile is simulated using the velocity-vorticity formulation of the Navier-Stokes equations, associated to a penalization method for solids and Large Eddy Simulation for turbulence. The study focuses both on the ground influence on the flow and on the dissymetry of the wake, observed for a ground clearance greater than 10% of the body height H. Unsteady and mean flows are presented and analyzed. POD study completes the analysis and gives information on the most energetic structures of the flow.

Keywords: Ahmed body, bi-stability, LES, near wake

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Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

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Authors: Nureni Amoo, Sunday Aroge, Oluranti Akintola, Hakeem Olujide, Ibrahim Alabi

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This study investigated the optimum landfill site in Osogbo so as to identify suitable solid waste dumpsite for proper waste management in the capital city. Despite an increase in alternative techniques for disposing of waste, landfilling remains the primary means of waste disposal. These changes in attitudes in many parts of the world have been supported by changes in laws and policies regarding the environment and waste disposal. Selecting the most suitable site for landfill can avoid any ecological and socio-economic effects. The increase in industrial and economic development, along with the increase of population growth in Osogbo town, generates a tremendous amount of solid waste within the region. Factors such as the scarcity of land, the lifespan of the landfill, and environmental considerations warrant that the scientific and fundamental studies are carried out in determining the suitability of a landfill site. The analysis of spatial data and consideration of regulations and accepted criteria are part of the important elements in the site selection. This paper presents a multi-criteria decision-making method using geographic information system (GIS) with the integration of the fuzzy logic multi-criteria decision making (FMCDM) technique for landfill suitability site evaluation. By using the fuzzy logic method (classification of suitable areas in the range of 0 to 1 scale), the superposing of the information layers related to drainage, soil, land use/land cover, slope, land use, and geology maps were performed in the study. Based on the result obtained in this study, five (5) potential sites are suitable for the construction of a landfill are proposed, two of which belong to the most suitable zone, and the existing waste disposal site belonged to the unsuitable zone.

Keywords: fuzzy logic multi-criteria decision making, geographic information system, landfill, suitable site, waste disposal

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Authors: Yong Min You

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The study on the torque ripple of Permanent Magnet Synchronous Motors (PMSMs) has been rapidly progressed, which effects on the noise and vibration of the electric vehicle. There are several ways to reduce torque ripple, which are the increase in the number of slots and poles, the notch of the rotor and stator teeth, and the skew of the rotor and stator. However, the conventional methods have the disadvantage in terms of material cost and productivity. The demagnetization characteristic of PMSMs must be attained for electric vehicle application. Due to rare earth supply issue, the demand for Dy-free permanent magnet has been increasing, which can be applied to PMSMs for the electric vehicle. Dy-free permanent magnet has lower the coercivity; the demagnetization characteristic has become more significant. To improve the torque ripple as well as the demagnetization characteristics, which are significant parameters for electric vehicle application, an unequal air-gap model is proposed for a PMSM. A shape optimization is performed to optimize the design variables of an unequal air-gap model. Optimal design variables are the shape of an unequal air-gap and the angle between V-shape magnets. An optimization process is performed by Latin Hypercube Sampling (LHS), Kriging Method, and Genetic Algorithm (GA). Finite element analysis (FEA) is also utilized to analyze the torque and demagnetization characteristics. The torque ripple and the demagnetization temperature of the initial model of 45kW PMSM with unequal air-gap are 10 % and 146.8 degrees, respectively, which are reaching a critical level for electric vehicle application. Therefore, the unequal air-gap model is proposed, and then an optimization process is conducted. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 7.7 %. In addition, the demagnetization temperature of the optimized model was also increased by 1.8 % while maintaining the efficiency. From these results, a shape optimized unequal air-gap PMSM has shown the usefulness of an improvement in the torque ripple and demagnetization temperature for the electric vehicle.

Keywords: permanent magnet synchronous motor, optimal design, finite element method, torque ripple

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Authors: Tukeaban Hasanova, Jamila Imamalieva

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By the operational method, the problem on two-dimensional wave propagation in elastic medium excited by the round cylinder is solved. An analytical solution responding to instantaneous application of speed to the inclusion at its subsequent change is constructed. The two-dimensional problem on wave propagation in an elastic medium is considered.

Keywords: cylinder, inclusion, wave, elastic medium, speed

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Authors: Mahmoud Huleihel, George Abu-Aqil, Manal Suleiman, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman

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Urinary tract infections (UTIs) are considered to be the most common bacterial infections worldwide, which are caused mainly by Escherichia (E.) coli (about 80%). Klebsiella pneumoniae (about 10%) and Pseudomonas aeruginosa (about 6%). Although antibiotics are considered as the most effective treatment for bacterial infectious diseases, unfortunately, most of the bacteria already have developed resistance to the majority of the commonly available antibiotics. Therefore, it is crucial to identify the infecting bacteria and to determine its susceptibility to antibiotics for prescribing effective treatment. Classical methods are time consuming, require ~48 hours for determining bacterial susceptibility. Thus, it is highly urgent to develop a new method that can significantly reduce the time required for determining both infecting bacterium at the species level and diagnose its susceptibility to antibiotics. Fourier-Transform Infrared (FTIR) spectroscopy is well known as a sensitive and rapid method, which can detect minor molecular changes in bacterial genome associated with the development of resistance to antibiotics. The main goal of this study is to examine the potential of FTIR spectroscopy, in tandem with machine learning algorithms, to identify the infected bacteria at the species level and to determine E. coli susceptibility to different antibiotics directly from patients' urine in about 30minutes. For this goal, 1600 different E. coli isolates were isolated for different patients' urine sample, measured by FTIR, and analyzed using different machine learning algorithm like Random Forest, XGBoost, and CNN. We achieved 98% success in isolate level identification and 89% accuracy in susceptibility determination.

Keywords: urinary tract infections (UTIs), E. coli, Klebsiella pneumonia, Pseudomonas aeruginosa, bacterial, susceptibility to antibiotics, infrared microscopy, machine learning

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Authors: I. Ibrahim, A. Mann

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Phytochemical screening of crude Chrysanthlum Indicum revealed the presence of carbohydrates, flavonoids, saponins, tannins, alkanoids, steroidal nucleus and cardiac glycosides. The extract was evaluated against some pathogenic organisms by agar dilution method. The minimum inhibitory concentration and minimum bacteriocidal concentration (MBC) of the active extract of Chrysanthlum Indicum shows that its extract could be a potential source of antimicrobial agents.

Keywords: extract, phytochemicals, antimicrobial, antibacterial, Chrysanthlum indicum

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Authors: Karim Hrratha, Khaled Essalahb, Christophe Morellc, Henry Chermettec, Salima Boughdiria

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Among the carbon-carbon bond formation types, allylation of active methylene compounds with cyclic Baylis-Hillman (BH) alcohols is a reliable and widely used method. This reaction is a very attractive tool in organic synthesis of biological and biodiesel compounds. Thus, in view of an insistent and peremptory request for an efficient and straightly method for synthesizing the desired product, a thorough analysis of various aspects of the reaction processes is an important task. The product afforded by the reaction of active methylene with BH alcohols depends largely on the experimental conditions, notably on the catalyst properties. All experiments reported that catalysis is needed for this reaction type because of the poor ability of alcohol hydroxyl group to be as a suitable leaving group. Within the catalysts, several transition- metal based have been used such as palladium in the presence of acid or base and have been considered as reliable methods. Furthemore, acid catalysts such as BF3.OEt2, BiX3 (X= Cl, Br, I, (OTf)3), InCl3, Yb(OTf)3, FeCl3, p-TsOH and H-montmorillonite have been employed to activate the C-C bond formation through the alkylation of active methylene compounds. Interestingly a report of a smoothly process for the ability of 4-imethyaminopyridine(DMAP) to catalyze the allylation reaction of active methylene compounds with cyclic Baylis-Hillman (BH) alcohol appeared recently. However, the reaction mechanism remains ambiguous, since the C- allylation process leads to an unexpected product (noted P1), corresponding to a direct allylation instead of conjugate allylation, which involves the most electrophilic center according to the electron withdrawing group CO effect. The main objective of the present theoretical study is to better understand the role of the DMAP catalytic activity as well as the process leading to the end- product (P1) for the catalytic reaction of a cyclic BH alcohol with active methylene compounds. For that purpose, we have carried out computations of a set of active methylene compounds varying by R1 and R2 toward the same alcohol, and we have attempted to rationalize the mechanisms thanks to the acid–base approach, and conceptual DFT tools such as chemical potential, hardness, Fukui functions, electrophilicity index and dual descriptor, as these approaches have shown a good prediction of reactions products.The present work is then organized as follows: In a first part some computational details will be given, introducing the reactivity indexes used in the present work, then Section 3 is dedicated to the discussion of the prediction of the selectivity and regioselectivity. The paper ends with some concluding remarks. In this work, we have shown, through DFT method at the B3LYP/6-311++G(d,p) level of theory that: The allylation of active methylene compounds with cyclic BH alcohol is governed by orbital control character. Hence the end- product denoted P1 is generated by direct allylation.

Keywords: DFT calculation, gas phase pKa, theoretical mechanism, orbital control, charge control, Fukui function, transition state

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Authors: Dina Athariah, Desriani Desriani, Bugi Ratno Budiarto, Abinawanto Abinawanto, Dwi Wulandari

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Breast cancer is a regulated by many genes. Defect in PIK3CA gene especially at position of exon 9 (E542K and E545K), called hot spot mutation induce early transformation of breast cells. The early detection of breast cancer based on mutation profile of this hot spot region would be hampered by the existence of pseudogene, marked by its substitution mutation at base 1658 (E545A) and deletion at 1659 that have been previously proven in several cancers. To the best of the authors’ knowledge, until recently no studies have been reported about pseudogene phenomenon in breast cancer. Here, we reported PCR optimization to to obtain true exon 9 of PIK3CA gene from its pseudogene hence increasing the validity of data. Material and methods: two genomic DNA with Dev and En code were used in this experiment. Two pairs of primer were design for Standard PCR method. The size of PCR products for each primer is 200bp and 400bp. While other primer was designed for Nested-PCR followed with DNA sequencing method. For Nested-PCR, we optimized the annealing temperature in first and second run of PCR, and the PCR cycle for first run PCR (15x versus 25x). Result: standard PCR using both primer pairs designed is failed to detect the true PIK3CA gene, appearing a substitution mutation at 1658 and deletion at 1659 of PCR product in sequence chromatogram indicated pseudogene. Meanwhile, Nested-PCR with optimum condition (annealing temperature for the first round at 55oC, annealing temperatung for the second round at 60,7oC with 15x PCR cycles) and could detect the true PIK3CA gene. Dev sample were identified as WT while En sample contain one substitution mutation at position 545 of exon 9, indicating amino acid changing from E to K. For the conclusion, pseudogene also exists in breast cancer and the apllication of optimazed Nested-PCR in this study could detect the true exon 9 of PIK3CA gene.

Keywords: breast cancer, exon 9, hotspot mutation, PIK3CA, pseudogene

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Authors: Tahra ElObeid, Omnya Ahmed, Reem Al-Sharshani, Doaa Dalloul, Jannat Alnattei

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Background: Camelus dormedarius camels are also called ‘the Arabian camels’ and are present in the desert area of North Africa and the Middle East. Recently, camel’s milk has a great attention globally because of their proteins and peptides that have been reported to be beneficial for the health and in the management of many diseases. Objectives: This study was designed to investigate the antioxidant, antimicrobial activity and to evaluate the total phenolic content of camel’s milk proteins in Qatar. Methods: Fresh two camel’s milk samples from Omani breed and called Muhajer (camel’s milk A and B) were collected on the 1st of the December. Both samples were from the same location Al- Shahaniyah, Doha, Qatar, but from different local private farms and feeding system. Camel’s milk A and B were defatted by centrifugation and their proteins were extracted by acid and thermal precipitation. The antioxidant activity was determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. Total phenolic compound (TPC) was evaluated by Folin-Ciocalteu reagent (FCR). On the other hand, the antimicrobial activity against eight different type of pathogenic bacteria was evaluated by disc diffusion method and the zone of inhibition was measured. Results: The of the total phenolic content of whole milk in both camel’s milk A and B were significantly the highest among the protein extracts. The % of the DPPH radical inhibition of casein protein in both camel’s milk A and B were significantly the highest among the protein extracts. In this study, there were marked changes in the antibacterial activity in the different camel milk protein extracts. All extracts showed bacterial overgrowth. Conclusion: The antioxidant activity of the camel milk protein extracts correlated to their unique phenolic compounds and bioactive protein peptides. The antimicrobial activity was not detected perhaps due to the technique, the quality, or the extraction method. Overall, camel's milk exhibits a high antioxidant activity, which is responsible for many health benefits besides the nutritional values.

Keywords: camels milk, antioxidant content, antimicrobial activity, proteins, Qatar

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Authors: Ghazala Yasmeen, Zahid Yousaf

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Frequent social media use has significantly changed people's life and communication styles during the last two decades. Social media use has multiple dimensions, and there are nuanced relationships between it and how it affects different societal subgroups. With the increased popularity and rapid growth of social networking sites, people are experiencing potential social media addiction, which causes severe mental health problems. How social media is dramatically influencing the lives and mental health of its users, and particularly of the students, creating psychological issues, e.g., isolation, depression, and anxiety, will be the primary objective of this study. This research will address the problems confronted by many students who are regular social media users and can undergo mental distress. This study aims to explore how social media use can lead to isolation, depression, and anxiety. This research will also investigate the effects of cyber-bullying on social, emotional, and psychological wellbeing. For this purpose, the researcher will use the survey technique as a method of inquiry. Ryff's theory of Psychological wellbeing will be used as a theoretical framework to explore the association between social media addiction and psychological effects among users. For data collection, the researcher will use the quantitative research method through a survey questionnaire from three universities in Pakistan from the public and private sectors. This study will imply a two-stage random sampling technique. At first, the researcher will select 20% of students from universities. In the second stage, 20% of students using different social networking sites will be chosen, and draw a representative sample from these will be. The intended study will use questionnaires comprising two portions. The first section will consist of social media engagement by the students, following impacts on their mental health and reported attitude towards psychological wellbeing. This study will spotlight the considerations of parents, educationists, and policymakers to take measures against the devastating effects of cyber-crimes on young adults.

Keywords: anxiety, depression, isolation, social media, wellbeing

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Authors: Mattea Carmen Castrovilli, Antonella Cartoni

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Electrospray ionisation (ESI), a well-established technique widely used to produce ion beams of biomolecules in mass spectrometry (ESI-MS), can be used for ambient soft landing of enzymes on a specific substrate. In this work, we show how the ambient electrospray deposition (ESD) technique can be successfully exploited for manufacturing a promising, green-friendly electrochemical amperometric laccase-based biosensor with unprecedented reuse and storage performance. These biosensors have been manufactured by spraying a laccase solution of 2μg/μL at 20% of methanol on a commercial carbon screen printed electrode (C-SPE) using a custom ESD set-up. The laccase-based ESD biosensor has been tested against catechol compounds in the linear range 2-100 μM, with a limit of detection of 1.7 μM, without interference from cadmium, chrome, arsenic, and zinc and without any memory effects, but showing a matrix effect in lake and well water. The ESD biosensor shows enhanced performances compared to the ones fabricated with other immobilization methods, like drop-casting. Indeed, it retains 100% activity up to two months of storage at ambient conditions without any special care and working stability up to 63 measurements on the same electrode just prepared and 20 on a one-year-old electrode subjected to redeposition together with a 100% resistance to use of the same electrode in subsequent days. The ESD method is a one-step, environmentally friendly method that allows the deposition of the bio-recognition layer without using any additional chemicals. The promising results in terms of storage and working stability also obtained with the more fragile lactate oxidase enzyme suggest these improvements should be attributed to the ESD technique rather than to the bioreceptor, highlighting how the ESD could be useful in reducing pollution from disposable devices. Acknowledgment: The understanding at the molecular level of this promising biosensor by using different spectroscopies, microscopies and analytical techniques is the subject of our PRIN 2022 project ESILARANTE.

Keywords: reuse, storage performance, immobilization, electrospray deposition, biosensor, laccase, catechol detection, green chemistry

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Authors: M. Salama, K. Haggag, H. El-Sayed

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An environmentally and ecologically acceptable method for eradication of wool fabrics based on microwave irradiation (MWI) was described. The process would be a suitable alternative for mothproofing of wool using toxic degradative chemical or biological methods. The effect of microwave irradiation and exposure time on the extent of eradication of wool fabrics from moth larvae was monitored. The inherent properties of the MW-irradiated wool fabrics; viz. tensile properties, alkali solubility, and yellowing index, were not adversely altered.

Keywords: microwave, wool, fabric, moth, eradication, resistance

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Authors: Ziyi Zhou, Qiuxiao Chen, Shuang Wu

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Population diversification phenomena becomes quite common in villages located in China’s developed coastal area. Based on the analysis of the traditional rural society and its landscape characteristics, and in consideration of diversified landscape requirements due to the population diversification, with dual ideas of heritage and innovation, methods for rural landscape design were explored by taking Duxuao Village in Zhejiang Province of China as an example.

Keywords: rural landscape, population diversification, landscape design, urban management

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Authors: Sidra Pervez, Afsheen Aman, Shah Ali Ul Qader

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The importance of attaining an optimum performance of an enzyme is often a question of devising an effective method for its immobilization. Cross-linked enzyme aggregate (CLEAs) is a new approach for immobilization of enzymes using carrier free strategy. This method is exquisitely simple (involving precipitation of the enzyme from aqueous buffer followed by cross-linking of the resulting physical aggregates of enzyme molecules) and amenable to rapid optimization. Among many industrial enzymes, amyloglucosidase is an important amylolytic enzyme that hydrolyzes alpha (1→4) and alpha (1→6) glycosidic bonds in starch molecule and produce glucose as a sole end product. Glucose liberated by amyloglucosidase can be used for the production of ethanol and glucose syrups. Besides this amyloglucosidase can be widely used in various food and pharmaceuticals industries. For production of amyloglucosidase on commercial scale, filamentous fungi of genera Aspergillus are mostly used because they secrete large amount of enzymes extracellularly. The current investigation was based on isolation and identification of filamentous fungi from genus Aspergillus for the production of amyloglucosidase in submerged fermentation and optimization of cultivation parameters for starch saccharification. Natural isolates were identified as Aspergillus niger KIBGE-IB36, Aspergillus fumigatus KIBGE-IB33, Aspergillus flavus KIBGE-IB34 and Aspergillus terreus KIBGE-IB35 on taxonomical basis and 18S rDNA analysis and their sequence were submitted to GenBank. Among them, Aspergillus fumigatus KIBGE-IB33 was selected on the basis of maximum enzyme production. After optimization of fermentation conditions enzyme was immobilized on CLEA. Different parameters were optimized for maximum immobilization of amyloglucosidase. Data of enzyme stability (thermal and Storage) and reusability suggested the applicability of immobilized amyloglucosidase for continuous saccharification of starch in industrial processes.

Keywords: aspergillus, immobilization, industrial processes, starch saccharification

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

Procedia PDF Downloads 412