Search results for: IVF techniques evolution

Authors: Jalil Badamfirooz

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Soil wind erosion has a negative impact on the environment. Mulching is one of the most efficient soil protection techniques. Bitumen emulsion has recently been utilized as a soil cover that is sprayed directly over the soil and forms a thin film. The thin coating of bitumen emulsion prevents soil erosion and keeps moisture in the soil. Besides, some compounds release into the soil and cause environmental problems. In the present study, the effect of bitumen emulsion on the release of polycyclic aromatic hydrocarbons (PAHs) into the soil is studied in an arid land located in the central part of Iran. The soil was Loamy-Sand and saline with a pH of 8.03. Bitumen emulsion was used in this study as mulch at a rate of 4 L m2. The effect of this mulch on soil properties was investigated after 6 months of mulch application. Then PAHs concentrations were determined in samples collected from different depths in bitumen emulsion sprayed and control soils. In general, bitumen emulsion application on soil led to a significant increase in some PAHs, which was higher than soil pollution standards critical level of pollution for commerce, groundwater protection, pasture forest, and park and residence uses.

Keywords: mulch, bitumen emulsion, arid land, PAH

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Authors: Mehrji Khosravan, Mostafa Fathali-Sianib, Davood Soudbar, Sasan Talebnezhad, Mohammad-Reza Ebrahimi

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The late transition metal catalyst of the end group of transition metals in the periodic table as Ni, Fe, Co, and Pd was grown up rapidly in polyolefin industries recently. These metals with suitable ligands exhibited special characteristic properties and appropriate activities in the production of polyolefins. The ligand 1,4-bis (2,6-diisopropyl phenyl) acenaphthene was synthesized by reaction of 2,6-diisopropyl aniline and acenaphthenequinone. The ligand was added to nickel (II) dibromide salt for synthesis the 1,4-bis (2,6 diisopropylphenyl) acenaphthene nickel (II) dibromide catalyst. The structure of the ligand characterized by IR technique. The catalyst then deposited on graphene and graphene oxide by vander walss-attachment for use in Ethylene slurry polymerization process in the presence of catalyst activator such as methylaluminoxane (MAO) in hexane solvent. The structure of the catalyst characterized by IR and TEM techniques and some of the polymers were characterized by DSC. The highest activity was achieved at 600 C for catalyst.

Keywords: α-diimine nickel (II) complex, graphene as supported catalyst, late transition metal, ethylene polymerization

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Authors: Thiago E. Goto, Carla C. Lopes, Helena B. Nader, Anielle C. A. Silva, Noelio O. Dantas, José R. Siqueira Jr., Luciano Caseli

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Quantum dots (QD) are semiconductor nanocrystals that can be employed in biological research as a tool for fluorescence imagings, having the potential to expand in vivo and in vitro analysis as cancerous cell biomarkers. Particularly, cadmium selenide (CdSe) magic-sized quantum dots (MSQDs) exhibit stable luminescence that is feasible for biological applications, especially for imaging of tumor cells. For these facts, it is interesting to know the mechanisms of action of how such QDs mark biological cells. For that, simplified models are a suitable strategy. Among these models, Langmuir films of lipids formed at the air-water interface seem to be adequate since they can mimic half a membrane. They are monomolecular films formed at liquid-gas interfaces that can spontaneously form when organic solutions of amphiphilic compounds are spread on the liquid-gas interface. After solvent evaporation, the monomolecular film is formed, and a variety of techniques, including tensiometric, spectroscopic and optic can be applied. When the monolayer is formed by membrane lipids at the air-water interface, a model for half a membrane can be inferred where the aqueous subphase serve as a model for external or internal compartment of the cell. These films can be transferred to solid supports forming the so-called Langmuir-Blodgett (LB) films, and an ampler variety of techniques can be additionally used to characterize the film, allowing for the formation of devices and sensors. With these ideas in mind, the objective of this work was to investigate the specific interactions of CdSe MSQDs with tumorigenic and non-tumorigenic cells using Langmuir monolayers and LB films of lipids and specific cell extracts as membrane models for diagnosis of cancerous cells. Surface pressure-area isotherms and polarization modulation reflection-absorption spectroscopy (PM-IRRAS) showed an intrinsic interaction between the quantum dots, inserted in the aqueous subphase, and Langmuir monolayers, constructed either of selected lipids or of non-tumorigenic and tumorigenic cells extracts. The quantum dots expanded the monolayers and changed the PM-IRRAS spectra for the lipid monolayers. The mixed films were then compressed to high surface pressures and transferred from the floating monolayer to solid supports by using the LB technique. Images of the films were then obtained with atomic force microscopy (AFM) and confocal microscopy, which provided information about the morphology of the films. Similarities and differences between films with different composition representing cell membranes, with or without CdSe MSQDs, was analyzed. The results indicated that the interaction of quantum dots with the bioinspired films is modulated by the lipid composition. The properties of the normal cell monolayer were not significantly altered, whereas for the tumorigenic cell monolayer models, the films presented significant alteration. The images therefore exhibited a stronger effect of CdSe MSQDs on the models representing cancerous cells. As important implication of these findings, one may envisage for new bioinspired surfaces based on molecular recognition for biomedical applications.

Keywords: biomembrane, langmuir monolayers, quantum dots, surfaces

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Laredo Alcalá Elan Iñaky, Hernandez Castillo Daniel, Martinez Hernandez José Luis, Arredondo Valdes Roberto, Gonzalez Gallegos Esmeralda, Anguiano Cabello Julia Cecilia

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Plant hormones are a group of molecules that control different processes ranging from the growth and development of the plant until their response to biotic and abiotic stresses. In this study, the capacity of production of various phytohormones was evaluated from a strain of Botryodiplodia theobromae by liquid fermentation system using the modified Mierch medium added with a hydrolyzate compound of mead all in a reactor without agitation at 28 °C for 15 days. Quantification of the metabolites was performed using high performance liquid chromatography techniques. The results showed that a microbial broth with at least five different types of plant hormones was obtained: gibberellic acid, zeatin, kinetin, indoleacetic acid and jasmonic acid, the last one was higher than the others metabolites produced. The production of such hormones using a single type of microorganism could be in the future a great alternative to reduce production costs and similarly reduce the use of synthetic chemicals.

Keywords: biosystem, plant hormones, Botryodiplodia theobromae, fermentation

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Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

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Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

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Authors: E. A. Tkachenko, E. M. Rogova, A. S. Osipenko

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The problems of technological development for the Russian Federation take on special significance in the context of modernization of the production base. The complexity of the position of the Russian economy is that it cannot be attributed fully to developing ones. Russia is a strong industrial power that has gone through the processes of destructive de-industrialization in the conditions of changing its economic and political structure. The need to find ways for re-industrialization is not a unique task for the economies of industrially developed countries. Under the influence of production outsourcing for 20 years, the industrial potential of leading economies of the world was regressed against the backdrop of the ascent of China, a new industrial giant. Therefore, methods, tools, and techniques utilized for industrial renaissance in EU may be used to achieve a technological leap in the Russian Federation, especially since the temporary gap of 5-7 years makes it possible to analyze best practices and use those technological transfer tools that have shown the greatest efficiency. In this article, methods of technological transfer are analyzed, the role of technological audit is justified, and factors are analyzed that influence the successful process of commercialization of technologies.

Keywords: technological transfer, productivity, technological audit, commercialization of technologies

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Somesh Misha, Smita Raghuvanshi, Suresh Gupta

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Increasing concentration of green house gases (GHG's), such as CO2 is of major concern and start showing its impact nowadays. The recent studies are focused on developing the continuous system using photoautotrophs for CO2 mitigation and simultaneous production of primary and secondary metabolites as a value addition. The advent of carbon concentrating mechanism had blurred the distinction between autotrophs and heterotrophs and now the paradigm has shifted towards the carbon capture and utilization (CCU) rather than carbon capture and sequestration (CCS). In the present work, a bioreactor was developed utilizing the chemolithotrophic bacterial species using CO2 mitigation and simultaneous value addition. The kinetic modeling was done and the biokinetic parameters are obtained for developing the bioreactor. The bioreactor was developed and studied for its operation and performance in terms of volumetric loading rate, mass loading rate, elimination capacity and removal efficiency. The characterization of effluent from the bioreactor was carried out for the products obtained using the analyzing techniques such as FTIR, GC-MS, and NMR. The developed bioreactor promised an economic, efficient and effective solution for CO2 mitigation and simultaneous value addition.

Keywords: CO2 mitigation, bio-reactor, chemolithotrophic bacterial species, FTIR, GC-MS, NMR

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Authors: Iram Gul, Maria Manzoor, Muhammad Arshad

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The enhanced phytoextraction techniques have been proposed for the remediation of heavy metals contaminated soil. Chelating agents enhance the availability of Cd, which is the main factor in the phytoremediation. This study was conducted to assessed the potential of two Pelargonium species (Pelargonium zonale, Pelargonium hortorum) in EDTA enhanced phytoextraction of Cd using pot experiment. Different doses of EDTA (0, 1, 2, 3, 4, 5 mmol kg-1) was used, and results showed that there was significant increase (approximately 2.1 folds) in the mobility of Cd at EDTA 5 mg kg-1 as compared to control. Both plants have TF and BCF more than 1 and have potential for the phytoextraction of Cd. However, the Pelargonium hortorum showed higher biomass and Cd uptake as compared to Pleragonium zonale. The maximum Cd accumulation in shoot and root of Pelargonium zonale was 484.4 and 264.41 mg kg-1 respectively at 2 mmol kg-1. However, the Pelargonium hortorum accumulate 996.9 and 350 mg kg-1 of Cd in shoot and root respectively at 4 mmol kg-1. Pelargonium hortorum uptake approximately 10.7 folds higher Cd concentration as compared to the Pelargonium zonale. Results revealed that P. hortorum performed better than P. zonal even at higher Cd and EDTA doses however toxicity and leaching potential of increased Cd and EDTA concentrations needs to be explored before field application.

Keywords: Cadmium, EDTA, Pelargonium, phytoextraction

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Authors: Shyam Mehraaj, Samanthi E. R. Siriwardana, Shehara A. K. G. H., Wanigasinghe N. T., Wandana R. A. K., Wedage C. V.

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A presentation is a critical tool for conveying not just spoken information but also a wide spectrum of human emotions. The single most effective thing to make the presentation successful is to practice it beforehand. Preparing for a presentation has been shown to be essential for improving emotional control, intonation and prosody, pronunciation, and vocabulary, as well as the quality of the presentation slides. As a result, practicing has become one of the most critical parts of giving a good presentation. In this research, the main focus is to analyze the audio, video, and slides of the presentation uploaded by the presenters. This proposed solution is based on the Natural Language Processing and Computer Vision techniques to cater to the requirement for the presenter to do a presentation beforehand using a mobile responsive web application. The proposed system will assist in practicing the presentation beforehand by identifying the presenters’ emotions, body language, tonality, prosody, pronunciations and vocabulary, and presentation slides quality. Overall, the system will give a rating and feedback to the presenter about the performance so that the presenters’ can improve their presentation skills.

Keywords: presentation, self-evaluation, natural learning processing, computer vision

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Authors: F. Esfandyari Darabad, Z. Samadi

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The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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Authors: Upal Barua

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The risk of severe crashes at high-speed right-turns at intersections is a major safety concern these days. The application of a smart right-turn at an intersection is increasing day by day to address is an issue. The design, ‘Smart Right-turn’ consists of a narrow-angle of channelization at approximately 70°. This design increases the cone of vision of the right-tuning drivers towards the crossing pedestrians as well as traffic on the cross-road. As part of the Safety Improvement Program in Austin Transportation Department, several smart right-turns were constructed at high crash intersections where high-speed right-turns were found to be a contributing factor. This paper features the state of the art techniques applied in planning, engineering, designing and construction of this smart right-turn, key factors driving the success, and lessons learned in the process. This paper also presents the significant crash reductions achieved from the application of this smart right-turn design using Empirical Bayes method. The result showed that smart right-turns can reduce overall right-turn crashes by 43% and severe right-turn crashes by 70%.

Keywords: smart right-turn, intersection, cone of vision, empirical Bayes method

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Andrew Wee

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As a result of the Italian Independence Wars starting in 1848, Italy began to change through unification. People gradually moved away from some of their traditional practices and values, such as the long-held belief that women were inferior to men, as part of the Risorgimento. Italians began to take interest in opera as a form of emotional release. As opera became more popular and prominent in their culture, it aided in the dissemination of ideas, especially stimulating the spread of imperialism, in the late 19th century, as Italy began extending its presence to other countries. In order to collect the information needed to analyze Italy’s foreign presence, it was necessary to consult texts concerning the culture of the Risorgimento. These texts included primary sources from operatic composers and contemporary recorded accounts. Letters from Giuseppe Verdi, a leader in opera during the Risorgimento, have been scrutinized for indications of popular attitudes of the time. The cultural context of the Risorgimento is essential to understanding the Italian motives and attitudes towards the outside world. On the more political side, research has also entailed the study of historical data of general laws, policies, and their purposes concerning geopolitical boundaries and foreign affairs, such as Edward Said’s thesis on Orientalism. By establishing these two characteristics of Italy, the paper will thoroughly illustrate Italy’s presence in foreign affairs. Texts have been searched with the intent of using information that reveals Italian attitudes toward exotic countries to determine whether their demeanor was positive or condescending. Motives behind sources have been interpreted in context in order to form a complete picture of the Italian sentiment towards foreigners. Additionally, research pertaining to Italian nationalism and imperialism such as song and literature has been used. The primary form of research has been the division of sources that are culturally based and those that are political in nature. Opera had always been developing since its creation in the 17th century, and in the 19th century, the bel canto movement revolutionized opera and its role in Italian society. This paper uses evidence that popular sentiment was influenced by opera to support the belief that the evolution of opera was as a result of the nationalist sentiment, and in turn fueled the cultural movement known as the Risorgimento. In this way, opera proceeded to affect Italian culture by spreading the idea of imperialism.

Keywords: opera, Italian unification, music history, imperialism

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Authors: Nasreen Thebo, W. Shaikh, A. J. Laghari, P. Nangni

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Prunus dulcis (Almond) shell extract is demonstrated for its biomedical applications. Shell extract prepared by soxhlet method and further characterized by UV-Visible spectrophotometer, atomic absorption spectrophotometer (AAS), FTIR, GC-MS techniques. In this study, the antifungal activity of almond shell extract was observed against clinically isolated pathogenic fungi by strip method. The antioxidant potential of crude shell extract of was evaluated by using DPPH (2-2-diphenyl-1-picryhydrazyl) and radical scavenging system. The possibility of short term therapy was only 20 days. The total antioxidant activity varied from 94.38 to 95.49% and total phenolic content was found as 4.455 mg/gm in almond shell extract. Finally the results provide a great therapeutic potential against Tinea capitis infection of scalp. Included in this study of shell extract that show scientific evidence for clinical efficacy, as well as found to be more useful in the treatment of dermatologic disorders and without any doubt it can be recommended to be Patent.

Keywords: Tinea capitis, DPPH, FTIR, GC-MS therapeutic treatment

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Authors: Sanaa Chafik, Imane Daoudi, Mounim A. El Yacoubi, Hamid El Ouardi

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Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

Keywords: approximate nearest neighbor search, content based image retrieval (CBIR), curse of dimensionality, locality sensitive hashing, multidimensional indexing, scalability

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Authors: Ala Abobakr Abdulhafidh Al-Dubai

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Biomaterials, specifically metals and ceramics, are indispensable components in the realm of medical science, shaping the landscape of implantology and prosthetics. This study delves into the intricate interplay between these materials and biological systems, aiming to scrutinize their suitability, performance, and biocompatibility. Employing a multi-faceted approach, a range of methodologies were meticulously employed to comprehensively characterize these biomaterials. Advanced material characterization techniques were paramount in this research, with scanning electron microscopy providing intricate insights into surface morphology, and X-ray diffraction unraveling the crystalline structures. These analyses were complemented by in vitro assessments, which gauged the biological response of cells to metals and ceramics, shedding light on their potential applications within the human body. A key facet of our investigation involved a comparative study, evaluating the corrosion resistance and osseointegration potential of both metals and ceramics. Through a series of experiments, we sought to understand how these biomaterials interacted with physiological environments, paving the way for informed decisions in medical applications

Keywords: metals, ceramics, biomaterials, biocompatibility, osseointegration

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Authors: Vladimir Simovic, Matija Varga, Robert Svetlacic

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Scientific work analytically explores and demonstrates techniques that can animate objects and geometric characters using CSS3 language by applying proper formatting and positioning of elements. This paper presents examples of optimum application of the CSS3 descriptive language when generating general web animations (e.g., billiards and movement of geometric characters, etc.). The paper presents analytically, the optimal development and animation design with the frames within which the animated objects are. The originally developed content is based on the upgrading of existing CSS3 descriptive language animations with more complex syntax and project-oriented work. The purpose of the developed animations is to provide an overview of the interactive features of CSS3 descriptive language design for computer games and the animation of important analytical data based on the web view. It has been analytically demonstrated that CSS3 as a descriptive language allows inserting of various multimedia elements into websites for public and internal sites.

Keywords: web animation recording, KML GML HTML5 forms, Cascading Style Sheets 3, Google Earth Professional

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Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

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To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Marius Sebastian Secula, Mihaela Darie, Gabriela Carja

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Ibuprofen is a non-steroidal anti-inflammatory drug (NSAIDs) and is among the most frequently detected pharmaceuticals in environmental samples and among the most widespread drug in the world. Its concentration in the environment is reported to be between 10 and 160 ng L-1. In order to improve the abatement efficiency of this compound for water source prevention and reclamation, the development of innovative technologies is mandatory. AOPs (advanced oxidation processes) are known as highly efficient towards the oxidation of organic pollutants. Among the promising combined treatments, photo-Fenton processes using layered double hydroxides (LDHs) attracted significant consideration especially due to their composition flexibility, high surface area and tailored redox features. This work presents the self-supported Fe, Mn or Ti on ZnFeAl LDHs obtained by co-precipitation followed by reconstruction method as novel efficient photo-catalysts for Fenton-like catalysis. Fe, Mn or Ti/ZnFeAl LDHs nano-hybrids were tested for the degradation of a model pharmaceutical agent, the anti-inflammatory agent ibuprofen, by photocatalysis and photo-Fenton catalysis, respectively, by means of a lab-scale system consisting of a batch reactor equipped with an UV lamp (17 W). The present study presents comparatively the degradation of Ibuprofen in aqueous solution UV light irradiation using four different types of LDHs. The newly prepared Ti/ZnFeAl 4:1 catalyst results in the best degradation performance. After 60 minutes of light irradiation, the Ibuprofen removal efficiency reaches 95%. The slowest degradation of Ibuprofen solution occurs in case of Fe/ZnFeAl 4:1 LDH, (67% removal efficiency after 60 minutes of process). Evolution of Ibuprofen degradation during the photo Fenton process is also studied using Ti/ZnFeAl 2:1 and 4:1 LDHs in the presence and absence of H2O2. It is found that after 60 min the use of Ti/ZnFeAl 4:1 LDH in presence of 100 mg/L H2O2 leads to the fastest degradation of Ibuprofen molecule. After 120 min, both catalysts Ti/ZnFeAl 4:1 and 2:1 result in the same value of removal efficiency (98%). In the absence of H2O2, Ibuprofen degradation reaches only 73% removal efficiency after 120 min of degradation process. Acknowledgements: This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS - UEFISCDI, project number PN-II-RU-TE-2014-4-0405.

Keywords: layered double hydroxide, advanced oxidation process, micropollutant, heterogeneous Fenton

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Authors: Varun Kumar, Chandra Shakher

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Micro-optical components such as microlenses and microlens array have numerous engineering and industrial applications for collimation of laser diodes, imaging devices for sensor system (CCD/CMOS, document copier machines etc.), for making beam homogeneous for high power lasers, a critical component in Shack-Hartmann sensor, fiber optic coupling and optical switching in communication technology. Also micro-optical components have become an alternative for applications where miniaturization, reduction of alignment and packaging cost are necessary. The compliance with high-quality standards in the manufacturing of micro-optical components is a precondition to be compatible on worldwide markets. Therefore, high demands are put on quality assurance. For quality assurance of these lenses, an economical measurement technique is needed. For cost and time reason, technique should be fast, simple (for production reason), and robust with high resolution. The technique should provide non contact, non-invasive and full field information about the shape of micro- optical component under test. The interferometric techniques are noncontact type and non invasive and provide full field information about the shape of the optical components. The conventional interferometric technique such as holographic interferometry or Mach-Zehnder interferometry is available for characterization of micro-lenses. However, these techniques need more experimental efforts and are also time consuming. Digital holography (DH) overcomes the above described problems. Digital holographic microscopy (DHM) allows one to extract both the amplitude and phase information of a wavefront transmitted through the transparent object (microlens or microlens array) from a single recorded digital hologram by using numerical methods. Also one can reconstruct the complex object wavefront at different depths due to numerical reconstruction. Digital holography provides axial resolution in nanometer range while lateral resolution is limited by diffraction and the size of the sensor. In this paper, Mach-Zehnder based digital holographic interferometric microscope (DHIM) system is used for the testing of transparent microlenses. The advantage of using the DHIM is that the distortions due to aberrations in the optical system are avoided by the interferometric comparison of reconstructed phase with and without the object (microlens array). In the experiment, first a digital hologram is recorded in the absence of sample (microlens array) as a reference hologram. Second hologram is recorded in the presence of microlens array. The presence of transparent microlens array will induce a phase change in the transmitted laser light. Complex amplitude of object wavefront in presence and absence of microlens array is reconstructed by using Fresnel reconstruction method. From the reconstructed complex amplitude, one can evaluate the phase of object wave in presence and absence of microlens array. Phase difference between the two states of object wave will provide the information about the optical path length change due to the shape of the microlens. By the knowledge of the value of the refractive index of microlens array material and air, the surface profile of microlens array is evaluated. The Sag of microlens and radius of curvature of microlens are evaluated and reported. The sag of microlens agrees well within the experimental limit as provided in the specification by the manufacturer.

Keywords: micro-optics, microlens array, phase map, digital holographic interferometric microscopy

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Authors: Mikkel Snorre Wilms Boysen

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From a theoretical perspective, expertise is generally considered a precondition for creativity. The assumption is that an individual needs to master the common and accepted rules and techniques within a certain knowledge-domain in order to create something new and valuable. However, real life cases, and a limited amount of empirical studies, demonstrate that this assumption may be overly simple. In this article, this question is explored through a number of semi-experimental case studies conducted within the fields of music, technology, and youth culture. The studies indicate that, in various ways, expertise plays an important part in creative processes. However, the case studies also indicate that expertise sometimes leads to an entrenched perspective, in the sense that knowledge and experience may work as a path into the well-known rather than into the unknown. In this article, these issues are explored with reference to different theoretical approaches to creativity and learning, including actor-network theory, the theory of blind variation and selective retention, and Csikszentmihalyi’s system model. Finally, some educational aspects and implications of this are discussed.

Keywords: creativity, expertise , education, technology

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Authors: Vaclav Mentl, Josef Volak

Abstract:

In many industrial applications, materials are subjected to degradation of mechanical properties as a result of real service conditions, temperature, cyclic loading, humidity or other corrosive media, irradiation, their combination etc. The assessment of the remaining lifetime of components and structures is commonly based on correlated procedures including numerous destructive, non-destructive and mathematical techniques that should guarantee reasonably precise assessment of the current damage extent of materials in question and the remaining lifetime evaluation of the component under consideration. The answers to demands of customers to extend the lifetime of existing components beyond their original design life must be based on detailed assessment of the current degradation extent, what can be rarely realised by means of traditional mechanical (standardised) tests that need relatively large volumes of representative material for the test specimen manufacturing. This fact accelerated the research of miniaturised test specimen that can be sampled non-invasively from the component.

Keywords: small punch test, correlation, creep, mechanical properties

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Authors: Sandesh Achar

Abstract:

Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Iva Košek Bartošová, Andrea Jokešová, Eva Kozlová, Helena Matějová

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The paper presents results of a research team from Faculty of Education, University of Hradec Králové in the Czech Republic. It introduces with the most reading methods used in the 1^st classes of a primary school and presents results of a pilot research focused on mastering reading techniques and the quality of reading comprehension of pupils in the first half of a school year during training in teaching reading by an analytic-synthetic method and by a genetic method. These methods of practicing reading skills are the most used ones in the Czech Republic. During the school year 2015/16 there has been a measurement made of two groups of pupils of the 1^st year and monitoring of quantitative and qualitative parameters of reading pupils’ outputs by several methods. Both of these methods are based on different theoretical basis and each of them has a specific educational and methodical procedure. This contribution represents results during a piloting project and draws pilot conclusions which will be verified in the subsequent broader research at the end of the school year of the first class of primary school.

Keywords: analytic-synthetic method of reading, genetic method of reading, reading comprehension, reading literacy, reading methods, reading speed

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Authors: Rafik Taleb, Farid Bouriche, Mehdi Boukri, Fouad Kehila

Abstract:

The aim of the paper is to investigate the dynamic behavior of an unreinforced masonry (URM) building strengthened by DC-90 dampers by ambient and low-level forced vibration tests. Ambient and forced vibration techniques are usually applied to reinforced concrete or steel buildings to understand and identify their dynamic behavior, however, less is known about their applicability for masonry buildings. Ambient vibrations were measured before and after strengthening of the URM building by DC-90 dampers system. For forced vibration test, a series of low amplitude steady state harmonic forced vibration tests were conducted after strengthening using eccentric mass shaker. The resonant frequency curves, mode shapes and damping coefficients as well as stress distribution in the steel braces of the DC-90 dampers have been investigated and could be defined. It was shown that the dynamic behavior of the masonry building, even if not regular and with deformable floors, can be effectively represented. It can be concluded that the strengthening of the building does not change the dynamic properties of the building due to the fact of low amplitude excitation which do not activate the dampers.

Keywords: ambient vibrations, masonry buildings, forced vibrations, structural dynamic identification

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Authors: Mantas Sakalas, Paulius Sakalas

Abstract:

This paper presents an analysis and design of a ultrawideband 1.8GHz to 43GHz Low Noise Amplifier (LNA) in 0.1 μm Galium Arsenide (GaAs) pseudomorphic High Electron Mobility Transistor (pHEMT) technology. The feedback based bandwidth extension techniques is analyzed and based on the outcome, a two stage LNA is designed. The impedance fine tuning is implemented by using Transmission Line (TL) structures. The measured performance shows a good agreement with simulation results and an outstanding wideband noise matching. The measured small signal gain was 12 dB, whereas a 3 dB gain flatness in range from 1.8 - 43 GHz was reached. The noise figure was below 4 dB almost all over the entire frequency band of 1.8GHz to 43GHz, the output power at 1 dB compression point was 6 dBm and the DC power consumption was 95 mW. To the best knowledge of the authors the designed LNA outperforms the State of the Art (SotA) reported LNA designs in terms of combined parameters of noise figure within the addressed ultra-wide 3 dB bandwidth, linearity and DC power consumption.

Keywords: feedback amplifiers, GaAs pHEMT, monolithic microwave integrated circuit, LNA, noise matching

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Authors: Iniye Irene Wodi, Ibebietei Temple Offor

Abstract:

Adolescence is a transition period from childhood to adulthood and one of the challenges of this period to the adolescent is the choice of a career. Choosing a career can be influenced by various factors some of which could be psychological. The study, therefore, investigated the psychological factors that influence adolescents’ choice of career in the southern part of Nigeria. Adolescents from selected secondary schools were drawn for the study using multi-stage sampling techniques. Motivating factors for adolescent career choice questionnaire (MFACC) was used for the study. The instrument was validated by experts in test and measurement. A reliability coefficient of 0.79 was obtained for the instrument using Pearson Product moment after a test-retest. The findings revealed that students’ occupational needs, interest, self-concept and societal values motivated adolescents career choices. Based on these findings, recommendations were made chief among which was the need for society to place more emphasis on acceptable and beneficial values as this would influence career decisions adolescents make. They also influence the occupational needs and interests of the adolescents.

Keywords: adolescence, career choice, psychological factors, societal values

Procedia PDF Downloads 241