Search results for: nuclear techniques

Authors: Patricia Helena Dos Santos Martins, Mateus Atique, Lucas Oliveira Gomes Ferreira

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There is a growing body of literature that recognizes the importance of bibliometric analysis through the evolutionary nuances of a specific field while shedding light on the emerging areas in that field. Surprisingly, its application in the manufacturing research of vitiviniculture is relatively new and, in many instances, underdeveloped. The aim of this study is to present an overview of the bibliometric methodology, with a particular focus on the Meta-Analytical Approach Theory model – TEMAC, while offering step-by-step results on the available techniques and procedures for carrying out studies about the elements associated with vitiviniculture. Where TEMAC is a method that uses metadata to generate heat maps, graphs of keyword relationships and others, with the aim of revealing relationships between authors, articles and mainly to understand how the topic has evolved over the period study and thus reveal which subthemes were worked on, main techniques and applications, helping to understand that topic under study and guide researchers in generating new research. From the studies carried out using TEMAC, it is possible to raise which are the techniques within the statistical control of processes that are most used within the wine industry and thus assist professionals in the area in the application of the best techniques. It is expected that this paper will be a useful resource for gaining insights into the available techniques and procedures for carrying out studies about vitiviniculture, the cultivation of vineyards, the production of wine, and all the ethnography connected with it.

Keywords: TEMAC, vitiviniculture, statical control of process, quality

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Scott A. Ochsner, Christopher M. Watkins, Apollo McOwiti, David L. Steffen Lauren B. Becnel, Neil J. McKenna

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Understanding signaling by nuclear receptors (NRs) requires an appreciation of their cognate ligand- and tissue-specific transcriptomes. While target gene regulation data are abundant in this field, they reside in hundreds of discrete publications in formats refractory to routine query and analysis and, accordingly, their full value to the NR signaling community has not been realized. One of the mandates of the Nuclear Receptor Signaling Atlas (NURSA) is to facilitate access of the community to existing public datasets. Pursuant to this mandate we are developing a freely-accessible community web resource, Transcriptomine, to bring together the sum total of available expression array and RNA-Seq data points generated by the field in a single location. Transcriptomine currently contains over 25,000,000 gene fold change datapoints from over 1200 contrasts relevant to over 100 NRs, ligands and coregulators in over 200 tissues and cell lines. Transcriptomine is designed to accommodate a spectrum of end users ranging from the bench researcher to those with advanced bioinformatic training. Visualization tools allow users to build custom charts to compare and contrast patterns of gene regulation across different tissues and in response to different ligands. Our resource affords an entirely new paradigm for leveraging gene expression data in the NR signaling field, empowering users to query gene fold changes across diverse regulatory molecules, tissues and cell lines, target genes, biological functions and disease associations, and that would otherwise be prohibitive in terms of time and effort. Transcriptomine will be regularly updated with gene lists from future genome-wide expression array and expression-sequencing datasets in the NR signaling field.

Keywords: target gene database, informatics, gene expression, transcriptomics

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Authors: Tung-Hui Hsu, Wen-Yuh Jywe

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Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Eyibo Ebengeobong Eddie

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Taking advantage of the sun's position to design buildings to ensure human comfort has always been an important aspect in an architectural design. Using cheap and less expensive methods and systems for gaining solar energy, heating and cooling has always been a great advantage to users and occupants of a building. As the years run by, daily techniques and methods have been created and more are being discovered to help reduce the energy demands of any building. Architects have made effective use of a buildings orientation, building materials and elements to achieve less energy demand. This paper talks about the various techniques used in solar heating and passive cooling of buildings and through water techniques and concepts to achieve thermal comfort.

Keywords: comfort, passive, solar, water

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Authors: Muhammad Usman

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Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Aftab Hameed Memon, Shadab Noor, Muhammad Akram Akhund

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Lean construction is a philosophy adopted in the construction industry to increase the value of a project by reducing waste and improving construction productivity. Lean emphasizes on maximizing the value of a project with less expenditure. Globally, lean philosophy has received wider popularity in construction sector. Lean construction has supported the practitioners with several tools and techniques to implement at various stages of a construction project. Following the global trends, this study has investigated the lean practice in Pakistan. The level of implementation of different lean tools and techniques altogether with potential benefits experienced by its implementation in construction projects of Pakistan is analyzed. To achieve the targets, the opinion was sought by the practitioners involved in handling construction projects representing four stakeholders that are a client, consultant, contractors and material suppliers through a structured questionnaire. A total of 34 completed questionnaires were collected and then statistically analyzed. The findings of the analysis have highlighted that pull approach, work standardization, just in time, increase visualization tools, integrated project delivery method and fail-safe for quality are common lean techniques implemented in the local construction industry. While reduction in waste, client’s satisfaction, improved communication, visual control and proper task management are major benefits of the lean construction application.

Keywords: lean construction, lean tools and techniques, lean benefits, waste reduction, Pakistan

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Authors: Brian J. Kozak, Joshua D. Shipman, Peng Hao Wang, Blake Shipp

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The unmanned aerial system (UAS) industry is growing at a rapid pace. This growth has increased the demand for low cost, custom made and high strength unmanned aerial vehicles (UAV). The area of most growth is in the area of 25 kg to 200 kg vehicles. Vehicles this size are beyond the size and scope of simple wood and fabric designs commonly found in hobbyist aircraft. These high end vehicles require stronger materials to complete their mission. Traditional aircraft construction materials such as aluminum are difficult to use without machining or advanced computer controlled tooling. However, by using general aviation composite aircraft homebuilding techniques and materials, a large scale UAV can be constructed cheaply and easily. Furthermore, these techniques could be used to easily manufacture cost made composite shapes and airfoils that would be cost prohibitive when using metals. These homebuilt aircraft techniques are being demonstrated by the researchers in the construction of a 75 kg aircraft.

Keywords: composite aircraft, homebuilding, unmanned aerial system industry, UAS, unmanned aerial vehicles, UAV

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Authors: Nahed O. Bawakid, Walied M. Alarif

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With regard to the uniqueness of the red algae of the genus Laurencia as the source of C₁₅-acetogenins, along with the diversity of biological applications; the acetogenin content of the Red Sea L. obtusa was investigated. Fractionation and purification of the CH₂Cl₂/MeOH extract were done by applying several chromatographic techniques, including column and preparative thin-layer chromatography; followed by a series of ¹H nuclear magnetic resonance measurements to give rise of some interesting notes. A new rare chloroallene-based C₁₅ acetogenin, laurentusenin (1) along with a new furan ring containing C₁₅ acetogenin, laurenfuresenin (2), were isolated from the red alga L. obtusa. Comparing 1D and 2D NMR, MS, UV and IR spectral data for the new isolated compounds with the reported bromoallene containing acetogenins spectral data was played the crucial role for characterization of their hemical structures. The apoptosis induced by these two compounds was demonstrated by DNA fragmentation assay and microscopic observation. These observations suggest that (1) and (2) may be involved in regulation of programmed death in the initiation and propagation of inflammatory responses. The isolated metabolite (1) showed unusual substituted allene side chain, while (2) inserted furan ring as a new acetogenin nucleus.

Keywords: cyclic enyne, anti-inflammatory, fatty acids, marine algae, halogenations

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Authors: Reza Sirjani, Nobosse Tafem Bolan

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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: A. Abdel-Moniem, H. Madkour, K. Farah, A. Abdullah

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The reduction in dapped end beams depth nearby the supports tends to produce stress concentration and hence results in shear cracks, if it does not have an adequate reinforcement detailing. This study investigates numerically the efficiency of applying different external strengthening techniques to the dapped end of such beams. A two-dimensional finite element model was built to predict the structural behavior of dapped ends strengthened with different techniques. The techniques included external bonding of the steel angle at the re-entrant corner, un-bounded bolt anchoring, external steel plate jacketing, exterior carbon fiber wrapping and/or stripping and external inclined steel plates. The FE analysis results are then presented in terms of the ultimate load capacities, load-deflection and crack pattern at failure. The results showed that the FE model, at various stages, was found to be comparable to the available test data. Moreover, it enabled the capture of the failure progress, with acceptable accuracy, which is very difficult in a laboratory test.

Keywords: dapped-end beams, finite element, shear failure, strengthening techniques, reinforced concrete, numerical investigation

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Authors: Wei-Song Hung

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We utilized pressure, vacuum, and evaporation-assisted self-assembly techniques through which graphene oxide (GO) was deposited on modified polyacrylonitrile (mPAN). The fabricated composite GO/mPAN membranes were applied to dehydrate 1-butanol mixtures by pervaporation. Varying driving forces in the self-assembly techniques induced different GO assembly layer microstructures. XRD results indicated that the GO layer d-spacing varied from 8.3 Å to 11.5 Å. The self-assembly technique with evaporation resulted in a heterogeneous GO layer with loop structures; this layer was shown to be hydrophobic, in contrast to the hydrophilic layer formed from the other two techniques. From the pressure-assisted technique, the composite membrane exhibited exceptional pervaporation performance at 30 C: concentration of water at the permeate side = 99.6 wt% and permeation flux = 2.54 kg m-2 h-1. Moreover, the membrane sustained its operating stability at a high temperature of 70 C: a high water concentration of 99.5 wt% was maintained, and a permeation flux as high as 4.34 kg m-2 h-1 was attained. This excellent separation performance stemmed from the dense, highly ordered laminate structure of GO.

Keywords: graphene oxide, self-assembly, alcohol dehydration, polyacrylonitrile (mPAN)

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Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

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New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: information visualization, visual analytics, text mining, visual text analytics tools, big data visualization

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Phongkon Weerpiput

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This research study aimed to compare learning achievement between Jigsaw I and jigsaw IV techniques. The target group was 70 Thai major sophomores enrolled in a course entitled Foreign Language in Thai at the Faculty of Education, Suan Sunandha Rajabhat University. The research methodology was quasi-experimental design. A control group was given the Jigsaw I technique while an experimental group experienced the Jigsaw IV technique. The treatment content focused on Khmer loanwords in Thai language executed for a period of 3 hours per week for total of 3 weeks. The instruments included learning management plans and multiple-choice test items. The result yields no significant difference at level .05 between learning achievement of both techniques.

Keywords: Jigsaw I technique, Jigsaw IV technique, learning achievement, major sophomores

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Authors: Gabriel Wainer

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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.

Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation

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Authors: Y. T. Ku, S. W. Chen, J. R. Wang, C. Shih, Y. F. Chang

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In order to respond the policy decision of non-nuclear homes, Tai Power Company (TPC) will provide the decommissioning project of Kuosheng Nuclear power plant (KSNPP) to meet the regulatory requirement in near future. In this study, the computational fluid dynamics (CFD) methodology has been employed to develop a flow prediction model for boiling water reactor (BWR) with upper pool under decommissioning stage. The model can be utilized to investigate the flow behavior as the vessel combined with upper pool and continuity cooling system. At normal operating condition, different parameters are obtained for the full fluid area, including velocity, mass flow, and mixing phenomenon in the reactor pressure vessel (RPV) and upper pool. Through the efforts of the study, an integrated simulation model will be developed for flow field analysis of decommissioning KSNPP under normal operating condition. It can be expected that a basis result for future analysis application of TPC can be provide from this study.

Keywords: CFD, BWR, decommissioning, upper pool

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Authors: G. Gurguze, I. Turkoglu

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Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.

Keywords: energy management, mobile robot, robot administration, robot management, robot planning

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Authors: Ayed Mouris Gad Elsayed Khalil

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This research focuses on historical techniques associated with the Lajevardin and Haft-Rangi production methods in tile production, with particular attention to identifying techniques for applying gold leaf to the surface of these historical glazed tiles. In this context, the history of the production of glazed, gilded and glazed Lajevardin ceramics from the Khwarizmanshahid and Mongol periods (11th to 13th centuries) was first evaluated in order to better understand the context and history of the methods of historical enameling. After a historical overview of glazed ceramic production techniques and the adoption of these techniques by civilizations, we focused on the niche production methods of glazes and Lajevardin glazes, two categories of decoration commonly found on tiles. A general method for classifying the different types of gold tiles was then introduced, applicable to tiles from to the Safavid period (16th-17th centuries). These categories include gold glazed Lajevardina tiles, haft rangi gold tiles, gold glazed monolithic tiles and gold mosaic tiles.

Keywords: ethnicity, multi-cultural, jewelry, craft techniquemycenaean, ceramic, provenance, pigmentAmorium, glass bracelets, image, Byzantine empire

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Authors: Jade Edey, Andrew Bennett, Gareth Hathway

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Nuclear receptor-related 1 protein (also known as Nurr1 or NR4A2) is an orphan nuclear receptor which plays a vital role in the development, survival and maintenance of dopaminergic (DA) neurons particularly in the substantia nigra (SN). Increasing research has investigated Nurr1’s additional role within microglia and astrocytes where it has been suggested to act as a negative regulator of inflammation; potentially offering neuroprotection. Considering both DA neurodegeneration and neuroinflammation are commonly accepted constituents of Parkinson’s Disease (PD), understanding the mechanisms by which Nurr1 regulates inflammatory processes could provide an attractive therapeutic target. Nurr1 regulates inflammation via a transrepressive mechanism possibly dependent upon SUMOylation. In addition, Nurr1 can transactivate numerous genes involved in DA synthesis, such as Tyrosine Hydroxylase (TH). A C-terminal splice variant of Nurr1, Nurr-1a, has been reported in both neuronal and glial cells. However, research into its transcriptional activity is minimal. We employed in vitro methods such as SUMO-Pulldown experiments alongside Luciferase reporter assays to investigate the SUMOylation status and transactivation capabilities of Nurr1 and Nurr-1a respectively. The SUMO-Pulldown assay demonstrated Nurr-1a undergoes significantly more SUMO modification than its full-length variant. Consequently, despite having less transcriptional activation than Nurr1, Nurr1a may play a more prominent role in repression of microglial inflammation. Contrary to published literature we also identified that SUMOylation enhances transcriptional activation by Nurr1 and Nurr1a. SUMOylation-dependent increases in Nurr1 and Nurr1a transcriptional activation were only evident in neuronal SHSY5Y cells but not in HEK293 cells. This research provides novel insight into the regulation of Nurr-1a and indicates differential effects of SUMOylation dependent regulation in neuronal and inflammatory cells.

Keywords: nuclear receptors, Parkinson’s disease, inflammation, transcriptional regulation

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Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

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Based on a survey conducted for second and third year students of the electrical engineering department at Maharishi Markandeshwar University, India, it was found that around 92% of students felt that it would be better to introduce a virtual environment for laboratory experiments. Hence, a need was felt to perform modern pedagogy techniques for students which consist of a virtual environment using MATLAB/Simulink. In this paper, a virtual environment for the speed control of a DC motor is performed using MATLAB/Simulink. The various speed control methods for the DC motor include the field resistance control method and armature voltage control method. The performance analysis of the DC motor is hence analyzed.

Keywords: DC Motor, field control, pedagogy techniques, speed control, virtual environment, voltage control

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Authors: Radmila Hajkova, Jiri Palecek, Hana Malachova, Alena Oulehlova

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Ensuring of continuity of business is the basic strategy of every company. Continuity of organization activities includes comprehensive procedures that help in solving unexpected situations of natural and anthropogenic character (for example flood, blaze, economic situations). Planning of continuity operations is a process that helps identify critical processes and implement plans for the security and recovery of key processes. The aim of this article demonstrates application of system approach to managing business continuity called business continuity management systems in military issues. This article describes the life cycle of business continuity management which is based on the established cycle PDCA (plan-do-check-act). After this is carried out by activities which are making by the University of Defence during activation of forces and means of the Integrated rescue system in case of emergencies - accidents at a nuclear power plant in Czech republic. Activities of various stages of deployment earmarked forces and resources are managed and evaluated by using MCMS application (military continuity management system).

Keywords: business continuity management system, emergency management, military, nuclear safety

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Authors: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

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The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

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Authors: Makhosi Buthelezi

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Mitochondrial DNA cytochrome c oxidase I (COI) gene analyses linked the South African groundnut leaf miner (GLM) to the Australian soya bean moth Aproaerema simplexella (Walker) and Indian Aproaerema modicella (Deventer). Thus, the genetic relatedness of GLM, A. simplexela, and A. modicella was examined by performing mitochondrial and nuclear (COI, cytochrome oxidase subunit II (COII), mitochondrial cytochrome b (CYTB), nuclear ribosomal 28S (28S) and intergenic spacer elongation factor-1 alpha ( EF-1 ALPHA) on 44 specimens collected from South Africa, four from Mozambique, and three each from single locations in India and Australia. Phylogenetic analyses were conducted using the Maximum Parsimony (MP) and Neighbour-Joining (NJ) methods. All of the datasets of the five DNA gene regions that were sequenced were also analyzed using the Basic Local Alignment Search Tool (BLAST) to find the closest matches for inclusion in the phylogenetic trees as outgroups and for purposes of information. In the phylogenetic trees for COI, COII, cytb and EF-1 ALPHA, a similar pattern was observed in the way that the sequences assembled into different groups; i.e., some sequences of A. simplexella from Australia were grouped separately from the others, but some Australian sequences grouped with those of the GLM from South Africa, India, and Mozambique. In the phylogenetic tree for 28S, all sequences from South Africa, Australia, India, and Mozambique grouped together and formed one group. For COI, genetic pairwise distance ranged from 0.97 to 3.60 %, for COII it ranged from 0.19% to 2.32%, for cytb it ranged from 0.25 to 9.77% and for EF-1 ALPHA it ranged 0.48 to 6.99%. Results of this study indicate that these populations are genetically related and presumably constitute a single species. Thus, further molecular and morphological studies need to be undertaken in order to resolve this apparent conundrum on the taxonomy of these populations.

Keywords: aproaerema modicella, aproaerema simplexella, mitochondrial DNA, nuclear DNA

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Authors: Ibrahim Alshalan

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The Islamic Republic of Iran is one of the greatest and most powerful countries, not only in the Arabian Gulf but in the entire Middle East region. However, the Iranian regime, which came to power as a result of the 1979 revolution that resulted in overthrowing the Shah Mohammad Reza Pahlavi, has been the biggest source of threat to the stability of the Middle East since the revolution until this day. It has ambitions to dominate the neighboring Arab countries, especially Iraq, Syria, Lebanon, Yemen and Bahrain. Iran has bad relationships with countries of the Gulf Cooperation Council (GCC), which includes Saudi Arabia, United Arab Emirates, Kuwait, Qatar, Oman and Bahrain. The main objective of this paper is to shed light on the deteriorating political relations between the Iranian regime on one hand and the GCC on the other, especially Saudi Arabia which is witnessing more challenges as a result of Iran's determination to develop its nuclear program. Another important objective of this paper is to identify the Iranian role in the creation of the hotbeds of conflict in addition to its responsibility for some of the region's problems. It also aims to answer the question; why does Iran insist on developing its controversial nuclear program?

Keywords: Iran, GCC, Gulf, Saudi Arabia

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Authors: Nyathi Mpumelelo; Moeng Thabiso Maria

Abstract:

BACKGROUND AND OBJECTIVES: Radiopharmaceuticals are used for diagnosis, treatment, staging and follow up of various diseases. However, there is concern that the ionizing radiation (gamma rays, α and ß particles) emitted by radiopharmaceuticals may result in exposure of radiographers and nurses with limited knowledge of the principles of radiation protection and safety, raising the risk of cancer induction. This study aimed at investigation radiation safety awareness levels among radiographers and nurses at a small tertiary hospital in South Africa. METHODS: An analytical cross-sectional study. A validated two-part questionnaire was implemented to consenting radiographers and nurses working in a Nuclear Medicine Department. Part 1 gathered demographic information (age, gender, work experience, attendance to/or passing ionizing radiation protection courses). Part 2 covered questions related to knowledge and awareness of radiation protection principles. RESULTS: Six radiographers and five nurses participated (27% males and 73% females). The mean age was 45 years (age range 20-60 years). The study revealed that neither professional development courses nor radiation protection courses are offered at the Nuclear Medicine Department understudy. However, 6/6 (100%) radiographers exhibited a high level of awareness of radiation safety principles on handling and working with radiopharmaceuticals which correlated to their years of experience. As for nurses, 4/5 (80%) showed limited knowledge and awareness of radiation protection principles irrespective of the number of years in the profession. CONCLUSION: Despite their major role of caring for patients undergoing diagnostic and therapeutic treatments, the nurses showed limited knowledge of ionizing radiation and associated side effects. This was not surprising since they never received any formal basic radiation safety course. These findings were not unique to this Centre. A study conducted in a Kuwaiti Radiology Department also established that the vast majority of nurses did not understand the risks of working with ionizing radiation. Similarly, nurses in an Australian hospital exhibited knowledge limitations. However, nursing managers did provide the necessary radiation safety training when requested. In Guatemala and Saudi Arabia, where there was shortage of professional radiographers, nurses underwent radiography training, a course that equipped them with basic radiation safety principles. The radiographers in the Centre understudy unlike others in various parts of the world demonstrated substantial knowledge and awareness on radiation protection. Radiations safety courses attended when an opportunity arose played a critical role in their awareness. The knowledge and awareness levels of these radiographers were comparable to their counterparts in Sudan. However, it was much more above that of their counterparts in Jordan, Nigeria, Nepal and Iran who were found to have limited awareness and inadequate knowledge on radiation dose. Formal radiation safety and awareness courses and workshops can play a crucial role in raising the awareness of nurses and radiographers on radiation safety for their personal benefit and that of their patients.

Keywords: radiation safety, radiation awareness, training, nuclear medicine

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Authors: Manh-Dung Ho, Van-Giap Pham, Van-Doanh Ho, Quang-Thien Tran, Tuan-Anh Tran

Abstract:

The k0-factors and related nuclear data, i.e. the Q0-factors and effective resonance energies (Ēr) of the selected radionuclides which are used in the k0-based neutron activation analysis (k0-NAA), were critically reviewed to be integrated in the “k0-DALAT” software. The k0- and Q0-factors of some short-lived radionuclides: 46mSc, 110Ag, 116m2In, 165mDy, and 183mW, were experimentally determined at the Dalat research reactor. The other radionuclides selected are: 20F, 36S, 49Ca, 60mCo, 60Co, 75Se, 77mSe, 86mRb, 115Cd, 115mIn, 131Ba, 134mCs, 134Cs, 153Gd, 153Sm, 159Gd, 170Tm, 177mYb, 192Ir, 197mHg, 239U and 239Np. The reviewed data as compared with the literature data were biased within 5.6-7.3% in which the experimental re-determined factors were within 6.1 and 7.3%. The NIST standard reference materials: Oyster Tissue (1566b), Montana II Soil (2711a) and Coal Fly Ash (1633b) were used to validate the new reviewed data showing that the new data gave an improved k0-NAA using the “k0-DALAT” software with a factor of 4.5-6.8% for the investigated radionuclides.

Keywords: neutron activation analysis, k0-based method, k0 factor, Q0 factor, effective resonance energy

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