Search results for: mathematical morphology

Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: Sibani Bisoyi, Ute Zschieschang, Alexander Hoyer, Hagen Klauk

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Abstract— Organic thin-film transistors (TFTs) have great potential to be used for various applications such as flexible displays or sensors. For some of these applications, the TFTs must be able to withstand temperatures in excess of 100 °C, for example to permit the integration with devices or components that require high process temperatures, or to make it possible that the devices can be subjected to the standard sterilization protocols required for biomedical applications. In this work, we have investigated how the thermal stability of low-voltage small-molecule semiconductor dinaphtho[2,3-b:2’,3’-f]thieno[3,2-b]thiophene (DNTT) TFTs is affected by the encapsulation of the TFTs and by the ambient in which the thermal stress is performed. We also studied to which extent the thermal stability of the TFTs depends on the channel length. Some of the TFTs were encapsulated with a layer of vacuum-deposited Teflon, while others were left without encapsulation, and the thermal stress was performed either in nitrogen or in air. We found that the encapsulation with Teflon has virtually no effect on the thermal stability of our TFTs. In contrast, the ambient in which the thermal stress is conducted was found to have a measurable effect, but in a surprising way: When the thermal stress is carried out in nitrogen, the mobility drops to 70% of its initial value at a temperature of 160 °C and to close to zero at 170 °C, whereas when the stress is performed in air, the mobility remains at 75% of its initial value up to a temperature of 160 °C and at 60% up to 180 °C. To understand this behavior, we studied the effect of the thermal stress on the semiconductor thin-film morphology by scanning electron microscopy. While the DNTT films remain continuous and conducting when the heating is carried out in air, the semiconductor morphology undergoes a dramatic change, including the formation of large, thick crystals of DNTT and a complete loss of percolation, when the heating is conducted in nitrogen. We also found that when the TFTs are heated to a temperature of 200 °C in air, all TFTs with a channel length greater than 50 µm are destroyed, while TFTs with a channel length of less than 50 µm survive, whereas when the TFTs are heated to the same temperature (200 °C) in nitrogen, only the TFTs with a channel smaller than 8 µm survive. This result is also linked to the thermally induced changes in the semiconductor morphology.

Keywords: organic thin-film transistors, encapsulation, thermal stability, thin-film morphology

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: T. G. Kassem, A. K. Adunchezor, J. P. Chollom

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This paper describes a mathematical model developed to predict the dynamics of Hepatitis B virus (HBV) infection and to evaluate the potential impact of vaccination and treatment on its dynamics. We used a compartmental model expressed by a set of differential equations based on the characteristic of HBV transmission. With these, we find the threshold quantity R0, then find the local asymptotic stability of disease free equilibrium and endemic equilibrium. Furthermore, we find the global stability of the disease free and endemic equilibrium.

Keywords: hepatitis B virus, epidemiology, vaccination, mathematical model

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Authors: Retno Supriyanti, Ahmad Chuzaeri, Yogi Ramadhani, A. Haris Budi Widodo

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The use of ultrasonography in the medical world has been very popular including the diagnosis of pregnancy. In determining pregnancy, ultrasonography has many roles, such as to check the position of the fetus, abnormal pregnancy, fetal age and others. Unfortunately, all these things still need to analyze the role of the obstetrician in the sense of image raised by ultrasonography. One of the most striking is the determination of gestational age. Usually, it is done by measuring the length of the fetus manually by obstetricians. In this study, we developed a computer-aided diagnosis for the determination of gestational age by measuring the length of the fetus automatically using edge detection method and image morphology. Results showed that the system is sufficiently accurate in determining the gestational age based image processing.

Keywords: computer aided diagnosis, gestational age, and diameter of uterus, length of fetus, edge detection method, morphology image

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Authors: Aroob Binhimd, Lyan Sayoti, Rana Almansour

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In recent years, artificial intelligence has grown drastically. This has led to the growth of educational programs to help students in solving educational problems and assist them in understanding certain topics. The purpose of this report is to investigate the Mathway application. Mathway is a mathematics software that teaches students how to solve and handle mathematical issues. The app allows students to insert questions manually on the platform or take a picture of the question, and then they get an answer to this mathematical question. It helps students enhance their performance in mathematics. This app can also be used to verify or check if their answers are correct. The report will include a questionnaire to collect data and analyze the users of this application.

Keywords: artificial intelligence, Mathway, mathematics, mathematical problems

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Authors: S. Jursová, P. Pustějovská, S. Brožová, J. Bilík

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The paper deals with possibilities of interpretation of iron ore reducibility tests. It presents a mathematical model developed at Centre ENET, VŠB–Technical University of Ostrava, Czech Republic for an evaluation of metallurgical material of blast furnace feedstock such as iron ore, sinter or pellets. According to the data from the test, the model predicts its usage in blast furnace technology and its effects on production parameters of shaft aggregate. At the beginning, the paper sums up the general concept and experience in mathematical modelling of iron ore reduction. It presents basic equation for the calculation and the main parts of the developed model. In the experimental part, there is an example of usage of the mathematical model. The paper describes the usage of data for some predictive calculation. There are presented material, method of carried test of iron ore reducibility. Then there are graphically interpreted effects of used material on carbon consumption, rate of direct reduction and the whole reduction process.

Keywords: blast furnace technology, iron ore reduction, mathematical model, prediction of iron ore reduction

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Authors: Nikolai A. Khlebnikov, Vladimir N. Krasilnikov, Evgenii V. Polyakov, Anastasia A. Maltceva

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Carbon materials with advanced surfaces are widely used both in modern industry and in environmental protection. The physical-chemical nature of these materials is determined by the morphology of primary atomic and molecular carbon structures, which are the basis for synthesizing the following materials: zero-dimensional (fullerenes), one-dimensional (fiber, tubes), two-dimensional (graphene) carbon nanostructures, three-dimensional (multi-layer graphene, graphite, foams) with unique physical-chemical and functional properties. Experience shows that the microscopic morphological level is the basis for the creation of the next mesoscopic morphological level. The dependence of the morphology on the chemical way and process prehistory (crystallization, colloids formation, liquid crystal state and other) is the peculiarity of the last called level. These factors determine the consumer properties of carbon materials, such as specific surface area, porosity, chemical resistance in corrosive environments, catalytic and adsorption activities. Based on the developed ideology of thin precursor synthesis, the authors discuss one of the approaches of the porosity control of carbon-containing materials with a given aggregates morphology. The low-temperature thermolysis of precursors in a gas environment of a given composition is the basis of the above-mentioned idea. The processes of carbothermic precursor synthesis of two different compounds: tungsten carbide WC:nC and zinc oxide ZnO:nC containing an impurity phase in the form of free carbon were selected as subjects of the research. In the first case, the transition metal (tungsten) forming carbides was the object of the synthesis. In the second case, there was selected zinc that does not form carbides. The synthesis of both kinds of transition metals compounds was conducted by the method of precursor carbothermic synthesis from the organic solution. ZnO:nC composites were obtained by thermolysis of succinate Zn(OO(CH2)2OO), formate glycolate Zn(HCOO)(OCH2CH2O)1/2, glycerolate Zn(OCH2CHOCH2OH), and tartrate Zn(OOCCH(OH)CH(OH)COO). WC:nC composite was synthesized from ammonium paratungstate and glycerol. In all cases, carbon structures that are specific for diamond- like carbon forms appeared on the surface of WC and ZnO particles after the heat treatment. Tungsten carbide and zinc oxide were removed from the composites by selective chemical dissolution preserving the amorphous carbon phase. This work presents the results of investigating WC:nC and ZnO:nC composites and carbon nanopowders with tubular, tape, plate and onion morphologies of aggregates that are separated by chemical dissolution of WC and ZnO from the composites by the following methods: SEM, TEM, XPA, Raman spectroscopy, and BET. The connection between the carbon morphology under the conditions of synthesis and chemical nature of the precursor and the possibility of regulation of the morphology with the specific surface area up to 1700-2000 m2/g of carbon-structured materials are discussed.

Keywords: carbon morphology, composite materials, precursor synthesis, tungsten carbide, zinc oxide

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Authors: M. Kheirandish, S. Borhani

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In this experiment Polystyrene/Zinc-oxide (PS/ZnO) nanocomposite fibers were produced by electrospinning technique using limonene as a green solvent. First, the morphology of electrospun pure polystyrene (PS) and PS/ZnO nanocomposite fibers investigated by SEM. Results showed the PS fiber diameter decreased by increasing concentration of Zinc Oxide nanoparticles (ZnO NPs). Thermo Gravimetric Analysis (TGA) results showed thermal stability of nanocomposites increased by increasing ZnO NPs in PS electrospun fibers. Considering Differential Scanning Calorimeter (DSC) thermograms for electrospun PS fibers indicated that introduction of ZnO NPs into fibers affects the glass transition temperature (Tg) by reducing it. Also, UV protection properties of nanocomposite fibers were increased by increasing ZnO concentration. Evaluating the effect of metal oxide NPs amount on mechanical properties of electrospun layer showed that tensile strength and elasticity modulus of the electrospun layer of PS increased by addition of ZnO NPs. X-ray diffraction (XRD) pattern of nanopcomposite fibers confirmed the presence of NPs in the samples.

Keywords: electrospininng, nanoparticle, polystyrene, ZnO

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Authors: Michael Lousis

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Mathematical competence is the great aim of every mathematical teaching and learning endeavour. This can be defined as an idealised conceptualisation of the quality of cognition and the ability of implementation in practice of the mathematical subject matter, which is included in the curriculum, and is displayed only through performance of doing mathematics. The present study gives a clear definition of mathematical competence in the domains of Arithmetic and Algebra that stems from the explanation of the learners’ errors in these domains. The learners, whose errors are explained, were Greek and English participants of a large, international, longitudinal, comparative research program entitled the Kassel Project. The participants’ errors emerged as results of their work in dealing with mathematical questions and problems of the tests, which were presented to them. The construction of the tests was such as only the outcomes of the participants’ work was to be encompassed and not their course of thinking, which resulted in these outcomes. The intention was that the tests had to provide undeviating comparable results and simultaneously avoid any probable bias. Any bias could stem from obtaining results by involving so many markers from different countries and cultures, with so many different belief systems concerning the assessment of learners’ course of thinking. In this way the validity of the research was protected. This fact forced the implementation of specific research methods and theoretical prospects to take place in order the participants’ erroneous way of thinking to be disclosed. These were Methodological Pragmatism, Symbolic Interactionism, Philosophy of Mind and the ideas of Computationalism, which were used for deciding and establishing the grounds of the adequacy and legitimacy of the obtained kinds of knowledge through the explanations given by the error analysis. The employment of this methodology and of these theoretical prospects resulted in the definition of the learners’ mathematical competence, which is the thesis of the present study. Thus, learners’ mathematical competence is depending upon three key elements that should be developed in their minds: appropriate representations, appropriate meaning, and appropriate developed schemata. This definition then determined the development of appropriate teaching practices and interventions conducive to the achievement and finally the entailment of mathematical competence.

Keywords: representations, meaning, appropriate developed schemata, computationalism, error analysis, explanations for the probable causes of the errors, Kassel Project, mathematical competence

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Authors: O. Atli Eklioglu

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Atypical antipsychotics such as quetiapine, olanzapine, and risperidone have been frequently and chronically used to treat psychiatric disorders accompanied by psychosis mainly schizophrenia. Since these drugs are commonly used in male patients of reproductive age, it is required to determine the possible effects of them on the reproductive system. In this study, it was aimed to evaluate the possible toxic effects of quetiapine, olanzapine and risperidone, which are the most frequently prescribed and chronically used psychiatric drugs, on sperm parameters. For this purpose, quetiapine (10, 20 and 40 mg/kg), olanzapine (2.5, 5 and 10 mg/kg), and risperidone (1.25, 2.5 and 3 mg/kg) were administered to male rats for 28 consecutive days. At the end of this period, sperm concentration, motility, and morphology were investigated by a computer-assisted sperm analysis system. According to the results, sperm parameters were negatively affected by antipsychotic use.

Keywords: quetiapine, olanzapine, risperidone, sperm count, motility, sperm morphology, computer-assisted sperm analysis

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Authors: V. Nagaraju, G. Murali, Nagarjunavarma Ganna, Atluri Pavan Kalyan, N. Sree Sai Ganesh, V. S. V. S. Badrinath

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The present work focuses on the development of a mathematical model for the yield obtained by single slope solar still incorporated with cylindrical pipes filled with sand. The mathematical results obtained were validated with the experimental results for the 3 cm of water level at the basin. The mathematical model and results obtained with the experimental investigation are within 11% of deviation. The theoretical model to predict the yield obtained due to the capillary effect was proposed first. And then, to predict the total yield obtained, the thermal effect model was integrated with the capillary effect model. With the obtained results, it is understood that the yield obtained is more in the case of solar stills with sand-filled cylindrical pipes when compared to solar stills without sand-filled cylindrical pipes. And later model was used for predicting yield for 1 cm and 2 cm of water levels at the basin. And it is observed that the maximum yield was obtained for a 1 cm water level at the basin. It means solar still produces better yield with the lower depth of water level at the basin; this may be because of the availability of more space in the sand for evaporation.

Keywords: solar still, cylindrical pipes, still efficiency, mathematical modeling, capillary effect model, yield, solar desalination

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Authors: Sasan Talebnezhad, Saeed Pormahdian, Naghi Assali

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Homogeneous α-diimine nickel (II) catalyst complexes, with and without amino para-aryl position functionality, were synthesized. These complexes were immobilized on carboxyl, hydroxyl, and acyl chloride functionalized multi-walled carbon nanotubes to form five novel heterogeneous α-diiminonickel catalysts. Immobilization was performed by covalent or electrostatic bonding via methylaluminoxane (MAO) linker or amide linkage. Both the nature of α-diimine ligands and the kind of interaction between anchored catalyst complexes and multi-walled carbon nanotube surface influenced the catalytic performance, microstructure, and morphology of obtained polyethylenes. The catalyst prepared by amide bonding showed lowest relative weight loss in thermogravimetry analysis and highest activities up to 5863 gr PE mmol-1Ni.hr-1. This catalyst produced polyethylene with dense botryoidal morphology.

Keywords: α-diimine nickel (II) complexes, immobilization, multi-walled carbon nanotubes, ethylene polymerization

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Authors: Sasan Talebnezhad, Saeed Pourmahdian, Naghi Assali

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Homogeneous α-diimine nickel (II) catalyst complexes, with and without amino para-aryl position functionality, were synthesized. These complexes were immobilized on carboxyl, hydroxyl and acyl chloride functionalized multi-walled carbon nanotubes to form five novel heterogeneous α diiminonickel catalysts. Immobilization was performed by covalent or electrostatic bonding via methylaluminoxane (MAO) linker or amide linkage. Both the nature of α-diimine ligands and the kind of interaction between anchored catalyst complexes and multi-walled carbon nanotube surface influenced the catalytic performance, microstructure, and morphology of obtained polyethylenes. The catalyst prepared by amide bonding showed lowest relative weight loss in thermogravimetry analysis and highest activities up to 5863 gr PE mmol-1Ni.hr-1. This catalyst produced polyethylene with dense botryoidal morphology.

Keywords: α-diimine nickel (II) complexes, immobilization, multi-walled carbon nanotubes, ethylene polymerization

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Authors: Han Hyuk Cho, Hanik Jo

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In recent years, coding education has been globally emphasized, and the Free Semester System and coding education were introduced to the public schools from the beginning of 2016 and 2018 respectively in Korea. With the introduction of the Free Semester System and the rising demand of Computational Thinking (CT) capacity, this paper aims to design ‘Coding Environment’ and Minecraft-like Turtlecraft in which learners can design and construct mathematical objects through mathematical symbolic expressions. Students can transfer the constructed mathematical objects to the Turtlecraft environment (open-source codingmath website), and also can print them out through 3D printers. Furthermore, we design learnable mathematics and coding curriculum by representing the figurate numbers and patterns in terms of executable expression in the coding context and connecting them to algebraic symbols, which will allow students to experience mathematical patterns and symbolic coding expressions.

Keywords: coding education, computational thinking, mathematics education, TurtleMAL and Turtlecraft

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Authors: Paul C. Njoku, Archana Swati Njoku

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The study deals with the development of a mathematical model to characterize the oil production in Nigeria. This is calculated by initiating the dynamics of oil production in million barrels revenue plan cost of oil production in million nairas and unit cost of production from 1974-1982 in the contest of the federal Republic of Nigeria. This country export oil to other countries as well as importing specialized crude. The transport network from origin/destination tij to pairs is taking into account simulation runs, optimization have been considered in this study.

Keywords: mathematical oil model development dynamics, Nigeria, characterization barrels, dynamics of oil production

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Authors: Kazuhisa Takagi

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This paper is about movies and dynamic objects for mobile phones. Dynamic objects are the software programmed by JavaScript. They consist of geometric figures and work on HTML5-compliant browsers. Mobile phones are very popular among teenagers. They like watching movies and playing games on them. So, mathematics movies and dynamic objects would enhance teaching and learning processes. In the movies, manga characters speak with artificially synchronized voices. They teach trigonometry together with dynamic mathematical objects. Many movies are created. They are Windows Media files or MP4 movies. These movies and dynamic objects are not only used in the classroom but also distributed to students. By watching movies, students can study trigonometry before or after class.

Keywords: dynamic mathematical object, javascript, google drive, transfer jet

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Authors: Reshma Jolly, Mohammad Shakir, Mohammad Shoeb Khan, Noor E. Iram

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A nanocomposite system integrating hydroxyapatite, chitin and starch (n-HA/CT/ST) has been synthesized via co-precipitation approach at room temperature, addressing the issues of biocompatibility, mechanical strength and cytotoxicity required for Bone tissue engineering. The interactions, crystallite size and surface morphology against n-HA/CT (nano-hydroxyapatite/chitin) nanocomposite have been obtained by correlating and comparing the results of FTIR, SEM, TEM and XRD. The comparative study of the bioactivity of n-HA/CT and n-HA/CT/ST nanocomposites revealed that the incorporation of starch as templating agent improved these properties in n-HA/CT/ST nanocomposite. The rise in thermal stability in n-HA/CT/ST nanocomposite as compared to n-HA/CT has been observed by comparing the TGA results. The comparison of SEM images of both the scaffolds indicated that the addition of ST influenced the surface morphology of n-HA/CT scaffold which appeared to be rougher and porous. The MTT assay on murine fibroblast L929 cells and in-vitro bioactivity of n-HA/CT/ST matrix referred superior non-toxic property of n-HA/CT/ST nanocomposite and higher possibility of osteo-integration in-vivo, respectively.

Keywords: bioactive, chitin, hyroxyapatite, nanocomposite

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Authors: Saurav Bhattacharjee, Syam Nair

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Lime stabilization is a sustainable and economically viable option to address strength deficiencies of subgrade soils. However, exposure of stabilized layers to environmental elements can lead to a reduction in post stabilization strength gain expected in these layers. The current study investigates the impact of carbonation on strength properties of lime-treated soils. Manufactured soils prepared using varying proportions of bentonite silica mixtures was used in the study. Lime treated mixtures were exposed to different atmospheric conditions created by varying the concentrations of CO₂ in the testing chamber. Impact of CO₂ diffusion was identified based on changes in carbonate content and strength (UCS) properties. Changes in soil morphology were also investigated as part of the study. Rate of carbonation was observed to vary polynomially (2nd order) with exposure time. Strength properties of the mixes were observed to decrease with exposure time.

Keywords: carbonation, soil, stabilization, morphology

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Authors: A. Fernandez Zuvich, I. Gana Watkins, H. Zolotucho, H. Troiani, A. Caneiro, M. Prado, A. L. Soldati

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The study of actinide nanoparticles (NPs) has attracted the attention of the scientific community not only because the lack of information about their ecotoxicological effects but also because the use of NPs could open a new way in the production of nuclear energy. Indeed, it was recently demonstrated that UO2 NPs sintered pellets exhibit closed porosity with improved fission gas retention and radiation-tolerance , ameliorated mechanical properties, and less detriment of the thermal conductivity upon use, making them an interesting option for new nuclear fuels. In this work, we used a combination of diffraction and microscopy tools to characterize the morphology, the crystalline structure and the composition of UO2 nanoparticles doped with 10%wt Gd2O3. The particles were synthesized by a modified sol-gel method at low temperatures. X-ray Diffraction (XRD) studies determined the presence of a unique phase with the cubic structure and Fm3m spatial group, supporting that Gd atoms substitute U atoms in the fluorite structure of UO2. In addition, Field Emission Gun Scanning (FEG-SEM) and Transmission (FEG-TEM) Electron Microscopy images revealed the presence of micrometric agglomerates of nanoparticles, with rounded morphology and an average crystallite size < 50 nm. Energy Dispersive Spectroscopy (EDS) coupled to TEM determined the presence of Gd in all the analyzed crystallites. Besides, FEG-SEM-EDS showed a homogeneous concentration distribution at the micrometer scale indicating that the small size of the crystallites compensates the variation in composition by averaging a large number of crystallites. These techniques, as combined tools resulted thus essential to find out details of morphology and composition distribution at the sub-micrometer scale, and set a standard for developing and analyzing nanoparticulated nuclear fuels.

Keywords: actinide nanoparticles, burnable poison, nuclear fuel, sol-gel

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Authors: Rafayel Azizyan, Valeri Arakelyan, Aram Gevorgyan, Varduhi Balayan, Emil Gevorgyan

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Currently, mathematical and computer modeling are widely used in different biological studies to predict or assess behavior of such complex systems as biological ones. This study deals with mathematical and computer modeling of bi-substrate enzymatic reactions, which play an important role in different biochemical pathways. The main objective of this study is to represent the results from in silico investigation of bi-substrate enzymatic reactions in the presence of uncompetitive inhibitors, as well as to describe in details the inhibition effects. Four models of uncompetitive inhibition were designed using different software packages. Particularly, uncompetitive inhibitor to the first [ES1] and the second ([ES1S2]; [FS2]) enzyme-substrate complexes have been studied. The simulation, using the same kinetic parameters for all models allowed investigating the behavior of reactions as well as determined some interesting aspects concerning influence of different cases of uncompetitive inhibition. Besides that shown, that uncompetitive inhibitors exhibit specific selectivity depending on mechanism of bi-substrate enzymatic reaction.

Keywords: mathematical modeling, bi-substrate enzymatic reactions, reversible inhibition

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Authors: Babak Moradi, Hassan Zare-Maivan

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A greenhouse investigation has been conducted to study the effect of crude oil on morphology and protein content of Avicennia marina plant. Avicennia marina seeds were sown in different concentrations of the crude oil mixed soil (i.e., 2.5, 5, 7.5, and 10 w/w). Controls and replicates were also set up. Morphological traits were recorded 4 months after plantation. Avicennia marina seedlings could tolerate up to 10% (w/w). Results demonstrated that there was a reduction in plant shoot and root biomass with the increase of crude oil concentration. Plant height, total leaf number and length reduced significantly with increase of crude oil contamination. Investigation revealed that there is a great impact of crude oil contamination on protein content of the roots of the experimental plant. Protein content of roots grown in different concentrations of crude oil were more than those of the control plant. Further, results also showed that protein content was increased with increased concentration of crude oil.

Keywords: Avicennia marina, morphology, oil contamination, protein content

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: S. Jahangir, S. H. I. Jaffery, M. Khan, Z. Zareef, A. Yar, A. Mubashir, S. Butt, L. Ali

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In this work, drilling responses and behavior of MMC was investigated in Al-Mg2Si composites. For the purpose Al-15% wt. Mg2Si, was selected from the hypereutectic region of Al- Mg2Si phase diagram. Based on hardness and tensile strength, drill bit of appropriate material and morphology was selected. The performance of different drill bits of different morphology and material was studied and analysed using experimental data. For theoretical calculations of axial thrust force and required power calculation, material factor “K” was obtained from different data charts and at the same time cutting forces (drilling forces) were practically obtained using a Peizo electric force dynamometer. These results show the role of reinforcement particles on the machinability of MMCs and provide a useful guide for a better control and optimized drilling parameters for the drilling process. Furthermore, in this work, comparison of MMC with non -reinforced Aluminum Alloy regarding drilling operation was also studied.

Keywords: drilling, metal matrix composite (MMC), cutting forces, thrust force

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Authors: Yidan Shao

Abstract:

With the advancement of the economy, technology promotes online teaching, and learning has become one of the common features in the educational field. Meanwhile, the dramatic expansion of the online environment provides opportunities for more learners, including second language learners. A greater command of vocabulary improves students’ learning capacity, and word acquisition and development play a critical role in learning. Furthermore, the Word Wall is an effective tool to improve students’ knowledge of words, which works for a wide range of age groups. Therefore, this study is going to use the Word Wall as an intervention to examine whether it can bring some memorization changes in an online English language class for a second language learner based on the word morphology method. The participant will take ten courses in the experiment as it plans. The findings show that the Word Wall activity plays a slight role in improving word memorizing, but it does affect instant memorization. If longer periods and more comprehensive designs of research can be applied, it is expected to have more value.

Keywords: second language acquisition, word morphology, word memorization, the Word Wall

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Authors: Ganesh K. Maurya, Reema Chaudhary, Neha Pandey, Hari S. Misra

Abstract:

PprA, a pleiotropic protein participating in radioresistance, has been reported for its roles in DNA replication initiation, genome segregation, cell division and DNA repair in polyextremophile Deinococcus radiodurans. Interestingly, expression of deinococcal PprA in E. coli suppresses its growth by reducing the number of colony forming units and provide better resistance against γ-radiation than control. We employed different biochemical and cell biology studies using PprA and its DNA binding/polymerization mutants (K133E & W183R) in E. coli. Cells expressing wild type PprA or its K133E mutant showed reduction in the amount of genomic DNA as well as chromosome copy number in comparison to W183R mutant of PprA and control cells, which suggests the role of PprA protein in regulation of DNA replication initiation in E. coli. Further, E. coli cells expressing PprA or its mutants exhibited different impact on cell morphology than control. Expression of PprA or K133E mutant displayed a significant increase in cell length upto 5 folds while W183R mutant showed cell length similar to uninduced control cells. We checked the interaction of deinococcal PprA and its mutants with E. coli DnaA using Bacterial two-hybrid system and co-immunoprecipitation. We observed a functional interaction of EcDnaA with PprA and K133E mutant but not with W183R mutant of PprA. Further, PprA or K133E mutant has suppressed the ATPase activity of EcDnaA but W183R mutant of PprA failed to do so. These observations suggested that PprA protein regulates DNA replication initiation and cell morphology of surrogate E. coli.

Keywords: DNA replication, radioresistance, protein-protein interaction, cell morphology, ATPase activity

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Authors: Rosli Mohd Yunus, Zianor Azrina Zianon Abdin, Mohammad Dalour Hossen Beg, Ridzuan Ramli

Abstract:

Recently, nanocrystalline cellulose (NCC) has gained considerable interest as a promising biomaterial due to their outstanding properties such as high surface area, high mechanical properties, hydrophilicity, biocompatibility and biodegradability. The NCC also has good stability in water which is compatible for mixing of water based polymer solution or emulsions with NCC. Oil palm empty fruit bunch (EFB) contained different amount of lignocellulosic materials such as lignin, hemicellulose and cellulose. Cellulose is the most significant materials that can be extracted from EFB as nanocrystalline cellulose (NCC). In this work the nanocrystalline cellulose were produced through acid hydrolysis together with ultrasound technique. The morphology of NCC was characterized by TEM, thermal behavior has been studied with DSC, TGA analysis. Structural properties were illustrated X-Ray diffraction as well as FTIR. The hydrogel was produced using polyvinyl alcohol (PVA) with different concentration of NCC. The hydrogel composite was characterized by swelling ratio, crosslinking density, mechanical properties and morphology.

Keywords: nanocellulose, oil palm, hydrogel, water treatment

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Authors: Mohammad Mirjalili, Hamid Akbarpour

Abstract:

In this work, a bleached well cotton sample was dyed with reactive yellow105 dye and subsequently, the dyed sample was exposed to the plasma condition containing Nitrogen gas at 1 and 5 minutes of plasma exposure time, respectively. The effect of plasma on surface morphology fabric was studied by Scanning Electronic Microscope (SEM). CIELab, K/S, and %R of samples (treated and untreated samples) were measured by a reflective spectrophotometer, and consequently, the experiments show that the sample dyed with Reactive yellow 105 after being washed, with the increase in the operation time of plasma, its dye fastness decreases. In addition, the increase in plasma operation time at constant pressure would increase the destructing effect on the surface morphology of samples dyed with reactive yellow105.

Keywords: cotton fabric, nitrogen cold plasma, reflective spectrophotometer, scanning electronic microscope (SEM), reactive yellow105 dye

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Authors: Retno Ambarwati Sigit Lestari

Abstract:

Microalga is one of the organisms that can be considered ideal and potential for raw material of bioenergy production, because the content of lipids in microalga is relatively high. Microalga is an aquatic organism that produces complex organic compounds from inorganic molecules using carbon dioxide as a carbon source, and sunlight for energy supply. Microalga-CO₂ fixation has potential advantages over other carbon captures and storage approaches, such as wide distribution, high photosynthetic rate, good environmental adaptability, and ease of operation. The rates of growth and CO₂ capture of microalga are influenced by CO₂ concentration and light intensity. This study quantitatively investigates the effects of CO₂ concentration on the rates of growth and CO₂ capture of a type of microalga, cultivated in bioreactors. The works include laboratory experiments as well as mathematical modelling. The mathematical models were solved numerically and the accuracy of the model was tested by the experimental data. It turned out that the mathematical model proposed can well quantitatively describe the growth and CO₂ capture of microalga, in which the effects of CO₂ concentration can be observed.

Keywords: Microalga, CO2 concentration, photobioreactor, mathematical model

Procedia PDF Downloads 115