Search results for: digital surface model (DSM)

Authors: Amer Rghei

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The Sahara region potentially is one of the most attractive heritage areas in the world. Yet presently, the heritage of the Sahara is currently facing serious planning challenges of underdeveloped and neglected economic and physical potentials. Deterioration of heritage resources has been observed by the author during his several field tours for historic sites has discovered special heritage values such as in Ghadames which combines historic oasis, natural environment along with its exceptional urban fabric and architectural character. Despite the richness of Ghadames with historic significance, it is found that at the present time, Ghadames city, the UNESCO World Heritage site, is facing serious challenges including the abandonment by its tenants and inclusive negligence by its officials. The author believes that Ghadames can illustrate an excellent heritage example in North Africa with cultural pride and socio-economic opportunities that can contribute to overall economic development in the Sahara region. However, the paper deals with the case of Ghadames ‘The World Heritage Site’ in Libya and discusses the current challenges and possible planning for its heritage conservation strategy. The momentous resources in Ghadames with their historical, environmental, economic, social, cultural, and aesthetic values would benefit from a careful heritage planning and management program for its significant values. In this paper an attempt is made to investigate this issue seriously towards building a model of a strategy for heritage conservation planning for Ghadames is proposed.

Keywords: Ghadames, Oasis architecture, Sahara region, heritage environment

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Authors: John Mambambo

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Debates on the link between Bantu languages are often epitomized by animated theoretical critiques, including the language zoning and groupings. This evaluative, qualitative inquiry hovers above theoretical critiques to offer the sparsely studied ChiShona and isiXhosa code-switching nexus, a yawning gap in scholarship. Using interviews, questionnaires and observations, data germane to the study were collected from a purposively selected group of Shona speakers who had resided in Xhosa-speaking communities for not less than a year. Deploying Myers-Scotton’s Markedness theory, the paper gazes into the pragmatic linguistic affinity that is affirmed through the Shona-Xhosa code-switching in Cape Town. The assorted social variables motivating bilingual speakers to code-switch in Cape Town are also explored in this study. The study unveils that Shona speakers are motivated to code-switch by the linguistic affinity between ChiShona and isiXhosa. Other socio-political justifications also give an impetus to this phenomenon. The Matrix Language Frame Model affirms that ChiShona is the base while isiXhosa is the embedded language during code-switching. This paper is a momentous advancement of the extant literature on code-switching. It is a unique contribution to the nexus between ChiShona and isiXhosa languages, providing fresh insights into the discourse on African language comparison studies.

Keywords: code-switching, chishona, isiXhosa, bilingualism

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Authors: Zafer Cakmak, Birol Bulut, Cengiz Taskiran

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Technological advances, the world becoming smaller and increasing world population increase our interdependence with individuals that we maybe never meet face to face. It is impossible for the modern individuals to escape global developments and their impact. Furthermore, it is very unlikely for the global societies to turn back from the path they are in. These effects of globalization in fact encumber the humankind at a certain extend. We succumb to these responsibilities for we desire a better future, a habitable world and a more peaceful life. In the present study, global responsibility levels of the participants were measured and the significance of global reactions that individuals have to develop on global issues was reinterpreted under the light of the existing literature. The study was conducted with general survey model, one of the survey methodologies General survey models are surveys conducted on the whole universe or a group, sample or sampling taken from the universe to arrive at a conclusion about the universe, which includes a high number of elements. The study was conducted with data obtained from 350 pre-service teachers attending 2016 spring semester to determine 'Global Social Responsibility' levels of social studies pre-service teachers based on several variables. Collected data were analyzed using SPSS 21.0 software. T-test and ANOVA were utilized in the data analysis.

Keywords: social studies, globalization, global social responsibility, education

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: Handan Ertaş

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The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process. It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: organizational trust level, organizational justice perceptions, staff, Konya

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Inês Amorim Leitão, Loes van Shaick, António Dinis Ferreira, Violette Geissen

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Plastic pollution is a growing concern worldwide: plastics are commercialized in large quantities and it takes a long time for them to degrade. When in the environment, plastic is fragmented into microplastics (<5mm), which have been found in all environmental compartments at different locations. Microplastics contribute to the environmental pollution in water, air and soil and are linked to human health problems. The progressive increase of population living in cities led to the aggravation of the pollution problem worldwide, especially in urban environments. Urban areas represent a strong source of pollution, through the roads, industrial production, wastewater, landfills, etc. It is expected that pollutants such as microplastics are transported diffusely from the sources through different pathways such as wind and rain. Therefore, it is very complex to quantify, control and treat these pollutants, designated current problematic issues by the European Commission. Green areas are pointed out by experts as natural filters for contaminants in cities, through their capacity of retention by vegetation. These spaces have thus the capacity to control the load of pollutants transported. This study investigates the spatial distribution of microplastics in urban soils of different land uses, their transport through atmospheric deposition, wind erosion, runoff and streams, as well as their deposition in vegetation like grass and tree leaves in urban environment. Coimbra, a medium large city located in the central Portugal, is the case-study. All the soil, sediments, water and vegetation samples were collected in Coimbra and were later analyzed in the Wageningen University & Research laboratory. Microplastics were extracted through the density separation using Sodium Phosphate as solution (~1.4 g cm−3) and filtration methods, visualized under a stereo microscope and identified using the u-FTIR method. Microplastic particles were found in all the different samples. In terms of soils, higher concentrations of microplastics were found in green parks, followed by landfills and industrial places, and the lowest concentrations in forests and pasture land-uses. Atmospheric deposition and streams after rainfall events seems to represent the strongest pathways of microplastics. Tree leaves can retain microplastics on their surfaces. Small leaves such as needle leaves seem to present higher amounts of microplastics per leaf area than bigger leaves. Rainfall episodes seem to reduce the concentration of microplastics on leaves surface, which suggests the wash of microplastics down to lower levels of the tree or to the soil. When in soil, different types of microplastics could be transported to the atmosphere through wind erosion. Grass seems to present high concentrations of microplastics, and the enlargement of the grass cover leads to a reduction of the amount of microplastics in soil, but also of the microplastics moved from the ground to the atmosphere by wind erosion. This study proof that vegetation can help to control the transport and dispersion of microplastics. In order to control the entry and the concentration of microplastics in the environment, especially in cities, it is essential to defining and evaluating nature-based land-use scenarios, considering the role of green urban areas in filtering small particles.

Keywords: microplastics, cities, sources, pathways, vegetation

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Authors: Taylan Ozturk, Osama Maklad

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This study examines the aerodynamic and flow properties of a multi-element airfoil using computational fluid dynamics (CFD) research. This computational analysis aims to optimize slat design concerning lift-drag coefficients and to determine the ideal gap size between the main airfoil and the front flap. It examines the influence of varying angles of attack and the effects of varied Reynolds numbers. A NACA 2412 airfoil, equipped with custom-designed front and rear flaps, was modeled in SolidWorks and simulated in ANSYS Fluent utilizing the k-ω SST turbulence model. This study quantifies lift and drag coefficients, turbulent kinetic energy, and vorticity magnitude across various configurations. The results clearly indicate that the slat-optimized design geometry featuring a 4 mm gap provides the best performance regarding both lift and drag, with maximum efficiency achieved at a 4-degree angle of attack. Furthermore, the results indicate the initiation of stall conditions beyond 20 degrees and demonstrate how an increase in Reynolds numbers influences flow separation and turbulence patterns. In addition, the maximum L/D ratio which is 36.18 achieved. These findings enhance the comprehension of multi-element airfoil behavior, directly impacting aircraft design and operation, particularly in high-lift situations.

Keywords: multi-element airfoil, CFD simulation, aerodynamic characteristics, Reynolds number analysis

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Authors: Ching-Yuan Huang, Rhay-Hung Weng, Yi-Ting Chen

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Mentoring functions will improve new nurses' job performance, provide support with new nurses, and then reduce the turnover rate of them. This study explored the impact of transformational leadership and interpersonal interaction on mentoring functions. We employed a questionnaire survey to collect data and selected a sample of new nurses from three hospitals in Taiwan. A total of 306 valid surveys were obtained. Multiple regression model analysis was conducted to test the study hypothesis. Inspirational motivation, idealized influence, and individualized consideration had a positive influence on overall mentoring function, but intellectual stimulation had a positive influence on career development function only. Perceived similarity and interaction frequency also had positive influences on mentoring functions. When the shift overlap rate exceeded 80%, mentoring function experienced a negative result. The transformational leadership of mentors actually would improve the mentoring functions among new staff nurses. Perceived similarity and interaction frequency between mentees and mentors also had a positive influence on mentoring functions. Managers should enhance the transformational leadership of mentors by designing leadership training and motivation programs. Furthermore, nursing managers should promote the interaction between new staff nurses and their mentors, but the shift overlap rate should not exceed 80%.

Keywords: interpersonal interaction, mentoring function, mentor, new nurse, transformational leadership

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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Authors: Anu Vinod Ranade

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Aim: To evaluate and compare the effects of Vitamin C and Vitamin E on experimentally induced testicular torsion and detorsion in rats. Methods: Forty Male Wistar Albino rats were divided into five groups. Animals in the Group I underwent Sham operation, Group II consisted of animals that were subjected to torsion for three hours followed by detorsion for 24 hours without any treatment. While Group III, IV and V were orally pretreated with Vitamin C (40mg/kg.bw), vitamin E (100mg/kg.bw) and a combination of Vitamin C and vitamin E respectively for a period of 30 days. The testes of the experimental groups were manually rotated to 720° clockwise for three hours and counter rotated for 24 hours to induce ischemia and reperfusion. Sequential biopsies were performed and the testes were collected at the end of 24 hours of detrosion for morphological evaluation. Result: There was a significant decrease in the standard tubular diameter and the epithelial height of the seminiferous tubules in the untreated group when compared to Sham controls. The standard tubular diameter and seminiferous epithelial height showed near normal values when animals were pretreated with Vitamin C and Vitamin E individually or in combination. Conclusion: The results showed that pretreatment of with antioxidants vitamin E and vitamin C when administered prior to testicular torsion in rats significantly reduced the torsion and detorsion induced histopathlogical injury.

Keywords: vitamin C, vitamin E, standard tubular diameter, standard epithelial height, testicular torsion

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Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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Authors: Emad Heydarnia, Aref Sepasi, Nika Asefi, Sara Khakshournia, Javad Mohammadnejad

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Background: Despite breakthrough therapeutics in breast cancer, it is one of the main causes of mortality among women worldwide. Thus, drug therapies for treating breast cancer have recently been developed by scientists. Metformin and Sorafenib are well-known therapeutic in breast cancer. In the present study, we combined Sorafenib and PCL-sorafenib with metformin to improve drug absorption and promote therapeutic efficiency. Methods: The MCF-7 cells were treated with Metformin, Sorafenib, or PCL-sorafenib. The growth inhibitory effect of these drugs and cell viability were assessed using MTT and flow cytometry assays, respectively. The expression of targeted genes involved in cell proliferation, signaling, and the cell cycle was measured by Real-time PCR. Results: The results showed that MCF-7 cells treated with Metformin/Sorafenib and PCL-sorafenib/Metformin co-treatment contributed to 50% viability compared to untreated group. Moreover, PI and Annexin V staining tests showed that the cells viability for Metformin/Sorafenib and PCL-sorafenib/Metformin was 38% and 17%, respectively. Furthermore, Sorafenib/Metformin and PCL-sorafenib/Metformin leads to p53 gene expression increase by which they can increase ROS, thereby decreasing GPX4 gene expression. In addition, they affected the expression of BCL2, and BAX genes and altered the cell cycle. Conclusion: Together, the combination of PCL-sorafenib/Metformin and Sorafenib/Metformin increased Sorafenib absorption at lower doses and also leads to apoptosis and oxidative stress increases in MCF-7 cells.

Keywords: breast cancer, metformin, nanotechnology, sorafenib

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Authors: Oladipo Joseph Ajayi, Yakubu Muhammed, Caleb Galadima

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This study was conducted to examine the income diversification of smallholder farmers in Bosso Local Government area of Niger state, Nigeria. The specific objectives were to examine the socio-economic characteristics of the farmers, identify the sources of income among the farmers, determine the pattern of income diversification and evaluate the determinants of income diversification of farmers in the study area. A multi-stage sampling technique was used to select 94 respondents for the study. Primary data were used, and these were collected with aid of a well structured interview schedule. Descriptive statistics, diversity index, and Tobit regression model were employed to analyze the data. The mean age of the farmers was 44 years. The average household size was 8 members per household, and the average farming experience was 12 years. 21.27 percent did not have formal education. It was further found that 69.1 percent of the respondents had an income diversity index of 0.3-0.4. This indicated that their level of income diversification was moderately low. The determinants of income diversification in the study area were education, household size, marital status, and primary income. These variables were positively related to income diversification. The study revealed that diversification into various income sources has helped to increase household income to sustain the family demands even though their level of income diversification was low within the study area.

Keywords: diversification, income, households, smallholder farmers

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Authors: Alaa Al Hawari, Mohammad Khader, Wael El Hasan, Mahmoud Alijla, Ammar Manawi, Abdelbaki Benamour

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The production of aluminium alloys and ingots -starting from the processing of alumina to aluminium, and the final cast product- was studied using a Life Cycle Assessment (LCA) approach. The studied aluminium supply chain consisted of a carbon plant, a reduction plant, a casting plant, and a power plant. In the LCA model, the environmental loads of the different plants for the production of 1 ton of aluminium metal were investigated. The impact of the aluminium production was assessed in eight impact categories. The results showed that for all of the impact categories the power plant had the highest impact only in the cases of Human Toxicity Potential (HTP) the reduction plant had the highest impact and in the Marine Aquatic Eco-Toxicity Potential (MAETP) the carbon plant had the highest impact. Furthermore, the impact of the carbon plant and the reduction plant combined was almost the same as the impact of the power plant in the case of the Acidification Potential (AP). The carbon plant had a positive impact on the environment when it comes to the Eutrophication Potential (EP) due to the production of clean water in the process. The natural gas based power plant used in the case study had 8.4 times less negative impact on the environment when compared to the heavy fuel based power plant and 10.7 times less negative impact when compared to the hard coal based power plant.

Keywords: life cycle assessment, aluminium production, supply chain, ecological impacts

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Authors: N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, L. Gverdtsiteli

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Tbilisi, a large city of the South Caucasus, is a junction point connecting Asia and Europe, Russia and republics of the Asia Minor. Over the last years, its atmosphere has been experienced an increasing anthropogenic load. Numerical modeling method is used for study of Tbilisi atmospheric air pollution. By means of 3D non-linear non-steady numerical model a peculiarity of city atmosphere pollution is investigated during background western light air. Dust concentration spatial and time changes are determined. There are identified the zones of high, average and less pollution, dust accumulation areas, transfer directions etc. By numerical modeling, there is shown that the process of air pollution by the dust proceeds in four stages, and they depend on the intensity of motor traffic, the micro-relief of the city, and the location of city mains. In the interval of time 06:00-09:00 the intensive growth, 09:00-15:00 a constancy or weak decrease, 18:00-21:00 an increase, and from 21:00 to 06:00 a reduction of the dust concentrations take place. The highly polluted areas are located in the vicinity of the city center and at some peripherical territories of the city, where the maximum dust concentration at 9PM is equal to 2 maximum allowable concentrations. The similar investigations conducted in case of various meteorological situations will enable us to compile the map of background urban pollution and to elaborate practical measures for ambient air protection.

Keywords: air pollution, dust, numerical modeling, urban

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Authors: R. Jannat, N. S. Juyena, F. Y. Bari, M. N. Islam

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Understanding anatomy of female reproductive organs is very much important to identify any variation in disease condition. Therefore, this study was conducted to determine the morphometry of female reproductive tract in small ruminant using ultrasonography. The reproductive tracts of 2l does and 20 ewes were collected, and both gross and ultrasonographic image measurements were performed to study morphometry of cervix, body of uterus, horn of uterus and ovary. Water bath ultrasonography technique was used with trans-abdominal linear probe for image measurements. Results revealed significant (P<0.001) variation among gross and image measurements of cervix, body of uterus and ovaries in does whereas, significant (P<0.001) variation existed between gross and image measurements of ovaries diameter in ewes. Gross measurements were proportionately higher than image measurements in both species. The mean length and width were found higher in right ovaries than those of left ovaries. In addition, the diameter of right ovaries was higher than those of left ovaries in both species. Pearson's correlation revealed a positive relation between two measurements. Moreover, it was found that echogenicity varied with reproductive organs. This is a model study. This study may help to identify female reproductive structures by trans-abdominal ultrasonography.

Keywords: female reproductive tract, morphometry, small ruminants, ultrasonography

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Authors: Mehmet Salih Bayraktutan, Emre Tokmak

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Great Ararat Volcano is the highest peak in South Caucasus Volcanic Plateau. Uplifted by Quaternary basaltic pyroclastic and lava flows. Numerous volcanic cones formed along with the tensional fractures under N-S compressional geodynamic framework. Basaltic flows have fresh surface morphology give ages of 650-680 K years. Hyperstene andesites constitute a major mass of Greater Ararat gives ages of 450-490 K years. During the early eruption period, predominately pyroclastics, cinder, lapilly-ash volcanic bombs were extruded. Third-period eruptions dominantly basaltic lava flows. Andesitic domes aligned along with the NW-SE striking fractures. Hyalo basalt and hornblende basaltic lavas are the latest lava eruptions. Hyalo-basaltic eruptions occurred via parasitic cones distributed far from the center. Parasitic cones are most common at the foot of Mount covered by recent NW flowing basaltic lava. Some of the cones are distributed on a circular pattern. One of the most hazardous disasters recorded in Eastern Turkey was July 1840 Cehennem Canyon Flood. Volcanic activities seismically triggered resulted in melting of glacier cap, mixed with ash and pyroclastics, flowed down along the Valley. Mud rich Slush urged catastrophically northwards, crossed Ars River and damned Surmeli Basin, forming reservoir behind. Ararat volcanoes are located on NW-SE striking Agri Fault Zone. Right lateral extensional faults, along which a series of andesitic domes formed. Great Ararat, in general strato-type volcano. This huge structure, developed in two main parts with different topographic and morphological features. The large lower base covers a widespread area composed of predominantly pyroclastics, ignimbrites, aglomerates, thick pumice, perlite deposits. Approximately 1/3 of the Crest by height formed of this basement. And 2/3 of the upper part with a conic- shape composed of basaltic lava flows. The active tectonic structure consists of three different patterns. The first network is radially distributed fractures formed during the last stage of lava eruptions. The second group of active faults striking in NW direction, and continue in N30W strike, formes Igdir Fault Zone. The third set of faults, dipping in the northwest with 75-80 degrees, strikes NE- SW across the whole Mount, slicing Great Ararat into four segments. In the upper stage of Cehennem Canyon, this set cutting volcanic layers caused numerous Waterfalls, Rock Avalanches, Mud Flows along the canyon, threatens the Village of Yanidogan, at the apex of flood deposits. Great Ararat Region has high seismo-tectonic risk and by occurrence frequency and magnitude, which caused in history caused heavy disasters, at villages surrounding the Ararat Basement.

Keywords: Eastern Turkey, geohazard, great ararat volcano, seismo-tectonic features

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Authors: Qiao Mao

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There is a growing number of studies concerning STEM (Science, Technology, Engineering, and Mathematics) and STEAM (Science, Technology, Engineering, Arts, and Mathematics). However, the research is little on STEAM competitions from Arts' perspective. This study takes the annual PowerTech STEAM competition in Taiwan as an example. In this activity, students are asked to make wooden bionic mechanical beasts on the spot and participate in a model and speed competition. This study aims to explore how Arts influences STEM after it involves in the making of mechanical beasts. A case study method is adopted. Through expert sampling, five prize winners in the PowerTech Youth Science and Technology Creation Competition and their supervisors are taken as the research subjects. Relevant data which are collected, sorted out, analyzed and interpreted afterwards, derive from observations, interview and document analyses, etc. The results of the study show that in the PowerTech Youth Science and Technology Creation Competition, when Arts involves in STEM, (1) it has an impact on the athletic performance, balance, stability and symmetry of mechanical beasts; (2) students become more interested and more creative in making STEAM mechanical beasts, which can promote students' learning of STEM; (3) students encounter more difficulties and problems when making STEAM mechanical beasts, and need to have more systematic thinking and design thinking to solve problems.

Keywords: PowerTech, STEAM contest, mechanical beast, arts' role

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Authors: J. Joy, T. H. New, I. H. Ibrahim

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A computational study on bio-inspired NACA634-021 hydrofoils with leading-edge protuberances has been carried out to investigate their hydrodynamic flow control characteristics at a Reynolds number of 14,000 and different angles-of-attack. The numerical simulations were performed using ANSYS FLUENT and based on Reynolds-Averaged Navier-Stokes (RANS) solver mode incorporated with k-ω Shear Stress Transport (SST) turbulence model. The results obtained indicate varying flow phenomenon along the peaks and troughs over the span of the hydrofoils. Compared to the baseline hydrofoil with no leading-edge protuberances, the leading-edge modified hydrofoils tend to reduce flow separation extents along the peak regions. In contrast, there are increased flow separations in the trough regions of the hydrofoil with leading-edge protuberances. Interestingly, it was observed that dissimilar flow separation behaviour is produced along different peak- or trough-planes along the hydrofoil span, even though the troughs or peaks are physically similar at each interval for a particular hydrofoil. Significant interactions between adjacent flow structures produced by the leading-edge protuberances have also been observed. These flow interactions are believed to be responsible for the dissimilar flow separation behaviour along physically similar peak- or trough-planes.

Keywords: computational fluid dynamics, flow separation control, hydrofoils, leading-edge protuberances

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Authors: Kazuhisa Koda, Tsutomu Kobayashi

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Laura Island, which is located about 50 km away from downtown, is a source of water supply in Majuro atoll, which is the capital of the Republic of the Marshall Islands. Low and flat Majuro atoll has neither river nor lake. It is very important for Majuro atoll to ensure the conservation of its water resources. However, up-coning, which is the process of partial rising of the freshwater-saltwater boundary near the water-supply well, was caused by the excess pumping from it during the severe drought in 1998. Up-coning will make the water usage of the freshwater lens difficult. Thus, appropriate water usage is required to prevent up-coning in the freshwater lens because there is no other water source during drought. Numerical simulation of water usage applying SEAWAT model was conducted at the central part of Laura Island, including the water-supply well, which was affected by up-coning. The freshwater lens was created as a result of infiltration of consistent average rainfall. The lens shape was almost the same as the one in 1985. 0 of monthly rainfall and variable daily pump discharge were used to calculate the sustainable pump discharge from the water-supply well. Consequently, the total amount of pump discharge was increased as the daily pump discharge was increased, indicating that it needs more time to recover from up-coning. Thus, a pump standard to reduce the pump intensity is being proposed, which is based on numerical simulation concerning the occurrence of the up-coning phenomenon in Laura Island during the drought.

Keywords: freshwater lens, islands, numerical simulation, sustainable water use

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Authors: Tesfay Gebremichael Reda

Abstract:

Nanoparticle technology is fast progressing and is being employed in innumerable medical applications. At this time, the public's health is seriously threatened by the rise of bacterial strains resistant to several medications. Metal nanoparticles are a potential alternate approach for tackling this global concern, and this is the main focus of this study. The citrate precursor sol-gel synthesis method was used to synthesize the, Niₓ Co(₁-ₓ) Fe₂ O₄, (where x = 0.0:0.2:1.0) nanoparticle. XRD identified the development of the cubic crystal structure to have a preferential orientation along (311), and the average particle size was found to be 29-38 nm. The average crystallizes assessed with ImageJ software and origin 22 of the SEM are nearly identical to the XRD results. In the created NCF NPs, the FT-IR spectroscopy reveals structural examinations and the redistribution of cations between octahedral (505-428 cm-1) and tetrahedral (653-603 cm-1) locales. Finally, the decrease of coercive fields HC, 2384 Oe to 241.93 Oe replacement of Co²+ cation with Ni²+. Band gap energy rises as Ni concentration increases, which may be attributed to the fact that the ionic radii of Ni²+ ions are smaller than that of Co²+ ions, which results in a strong electrostatic interaction. On the contrary, except at x = 0.4, the dielectric constant decreases as the nickel concentration increases. According to the findings of this research work, nanoparticles composed of Ni₀.₄ Co₀.₄ Fe₂ O₄ have demonstrated a promising value against S. aureus and E. coli, and it suggests a proposed model for their potential use as a new source of antibacterial agents.

Keywords: antimicrobial, band gap, citrate precursor, dielectric, nanoparticle

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Micheal O. Alabi

Abstract:

Additive manufacturing (AM) is the official industry standard term (ASTM F2792) for all applications of the technology which is also known as 3D printing technology. It is defined as the process of joining materials to make objects from 3D model data, and it is usually layer upon layer, as opposed to subtractive manufacturing methodologies. This technology has gained significant interest within the academic, research institute and industry because of its ability to create complex geometries with customizable material properties. Despite the late adoption of the technology, additive manufacturing has been active in South Africa for past 21 years and it is predicted that additive manufacturing technology will play a significant and game-changing role in the fourth industrial revolution and in particular it promises to play an ever-growing role in efforts to re-industrialize the economy of South Africa. At the end of 2006, there are approximately ninety 3D printers in South Africa and in 2015 it was estimated that there are 3500 additive manufacturing systems and 3D printers in circulation in South Africa. A reasonable number of these additive manufacturing machines are in the high end of the market, in science councils and higher education institutions and this shows that the future of additive manufacturing in South Africa is very brighter compared to other African countries. This paper reviews the past and current industrial applications of additive manufacturing in South Africa from the academic research and industry perspective and what are the benefits of this technology to manufacturing companies and industrial sectors in the country.

Keywords: additive manufacturing, 3D printing technology, industrial applications, manufacturing

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Authors: Patcharakamon Nooeaid, Piyachat Chuysrinuan

Abstract:

Electrospun natural polymers-based nanofibers are one of the most interesting materials used in tissue engineering and drug delivery applications. Bead-on-string nanofibers have gained considerable interest for sustained drug release. Vancomycin was used as the model drug and sodium alginate (SA)/soy protein isolated (SPI) as the polymer blend to fabricate the bead-on-string nanofibers by aqueous-based electrospinning. The bead-on-string SA/SPI nanofibers were successfully fabricated by the addition of poly(ethylene oxide) (PEO) as a co-blending polymer. SA-PEO with mass ratio of 70/30 showed the best spinnability with continuous nanofibers without the occurrence of beads. Bead structure formed with the addition of SPI and bead number increased with increasing SPI content. The electrospinning of 80/20 SA-PEO/SPI was obtained as a great promising bead-on-string nanofibers for drug loading, while the solution of 50/50 was not able to obtain continuous fibers. In vitro release tests showed that a more sustainable release profile up to 14 days with less initial burst release on day 1 could be obtained from the bead-on-string fibers than from smooth fibers with uniform diameter. In addition, vancomycin-loaded beaded fibers inhibited the growth of Staphylococcus aureus (S. aureus) bacteria. Therefore, the SA-PEO/SPI nanofibers showed the potential to be used as biomaterials for tissue engineering and drug delivery.

Keywords: bead-on-string fibers, electrospinning, drug delivery, tissue engineering

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Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Guoen Cao, Yibo Wang, Honghua Xu

Abstract:

Grid connected photovoltaic (PV) power system is to be developed in the direction of large-scale, clustering. Large-scale PV generation systems connected to HVDC grid have many advantages compared to its counterpart of AC grid, and DC connection is the tendency. DC/DC converter as the most important device in the system, has become one of the hot spots recently. The paper proposes a Quasi Z-Source(QZS) based Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology as a basis power module and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid. The topology has both traditional voltage source and current source advantages, it permit the H-bridge short through and open circuit, which adopt utility duty cycle control and achieved input current and output voltage balancing through input current sharing control strategy. A ±10kV/200kW system model is built in MATLAB/SIMULINK to verify the proposed topology and control strategy.

Keywords: PV Generation System, Cascaded DC/DC converter, HVDC, Quasi Z Source Converter

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Authors: Ankur P. Sati, Manju Mohan

Abstract:

The hazardous combination of smoke and pollutant gases, smog, is harmful for health. There are strong evidences that the Agricultural waste burning (AWB) in the Northern India leads to adverse air quality in Delhi and its surrounding regions. A severe smog episode was observed over Delhi, India during November 2012 which resulted in very low visibility and various respiratory problems. Very high values of pollutants (PM10 as high as 989 µg m-3, PM2.5 as high as 585 µg m-3 an NO2 as high as 540 µg m-3) were measured all over Delhi during the smog episode. Ultra Violet Aerosol Index (UVAI) from Aura satellite and Aerosol Optical Depth (AOD) are used in the present study along with the output trajectories from HYSPLIT model and the in-situ data. Satellite data also reveal that AOD, UVAI are always at its highest during the farmfires duration in Punjab region of India and the extent of these farmfires may be increasing. It is observed that during the smog episode all the AOD, UVAI, PM2.5 and PM10 values surpassed those of the Diwali period (one of the most polluted events in the city) by a considerable amount at all stations across Delhi. The parameters used from the remote sensing data and the ground based observations at various stations across Delhi are very well in agreement about the intensity of Smog episode. The analysis clearly shows that regional pollution can have greater contributions in deteriorating the air quality than the local under adverse meteorological conditions.

Keywords: smog, farmfires, AOD, remote sensing

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