Search results for: graphical vectors

Authors: Shaza Melies, Abeer Refky, Nihad Mansoor

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Multimodality involves the communication between verbal and visual components in various discourses. A painting represents a form of communication between the artist and the viewer in terms of colors, shades, objects, and the title. This paper aims to present how multimodality can be used to decode the verbal and visual dimensions a painting holds. For that purpose, this study uses Kress and van Leeuwen’s theoretical framework of visual grammar for the analysis of the multimodal semiotic resources of selected paintings of Salvador Dali. This study investigates the visual decoding of the selected paintings of Salvador Dali and analyzing their social and political meanings using Kress and van Leeuwen’s framework of visual grammar. The paper attempts to answer the following questions: 1. How far can multimodality decode the verbal and non-verbal meanings of surrealistic art? 2. How can Kress and van Leeuwen’s theoretical framework of visual grammar be applied to analyze Dali’s paintings? 3. To what extent is Kress and van Leeuwen’s theoretical framework of visual grammar apt to deliver political and social messages of Dali? The paper reached the following findings: the framework’s descriptive tools (representational, interactive, and compositional meanings) can be used to analyze the paintings’ title and their visual elements. Social and political messages were delivered by appropriate usage of color, gesture, vectors, modality, and the way social actors were represented.

Keywords: multimodal analysis, painting analysis, Salvador Dali, visual grammar

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Authors: Stavros Palavouzis, Alexandra Triantafyllopoulou, Aliki Tzima, Epaminondas Paplomatas

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Mating-type genes are present in most filamentous fungi, even though teleomorphs for all species have not been recorded. Our study tries to explore the effect of different growth conditions on the expression of MAT genes in Neofusicoccum mediterraneum. As such, selected isolates were grown in potato dextrose broth or in water agar supplemented with pine needles under a 12 h photoperiod, as well as in constant darkness. Mycelia and spores were collected at different time points, and RNA extraction was performed, with the extracted product being used for cDNA synthesis. New primers for MAT gene expression were designed while qPCR results are underway. The second part of the study involved the isolation and cloning in a selected pGEM-T vector of the Botryosphaeria dothidea MAT1 1 1 and MAT1 2 1 mating genes, including flanking regions. As a next step, the genes were amplified using newly designed primers with engineered restriction sites. Amplicons were excised and subsequently sub-cloned in appropriate binary vectors. The constructs were afterward inserted into Agrobacterium tumefaciens and utilized for Agrobacterium-mediated transformation (ATMT) of Neofusicoccum mediterraneum. At the same time, the transformation of a Verticillium dahliae tomato race 1 strain (70V) was performed as a control. While the procedure was successful in regards to V. dahliae, transformed strains of N. mediterraneum could not be obtained. At present, a new transformation protocol, which utilizes a combination of protoplast and Agro transformation, is being evaluated.

Keywords: anamorph, heterothallism, perithecia, pycnidia, sexual stage

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Authors: Kanayo Kenneth Asogwa

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The influence of the flow of nanoparticles in nanofluids across a vertical surface is significant, and its application in medical sciences, engineering, pharmaceutical, and food industries is enormous & widely published. However, the comparative examination of alumina nanoparticles with cupric nanoparticles past a rapid progressive Riga plate remains unknown. Thus, this report investigates water-based alumina and cupric nanoparticles passing through an exponentially accelerated Riga plate. Nanofluids containing copper (II) oxide (CuO) and aluminum oxide (Al2O3) nanoparticles are considered. The Laplace transform technique is used to solve the partial differential equations guiding the flow. The effect of various factors on skin friction coefficient, Nusselt number, velocity and temperature profiles is investigated and reported in tabular and graphical form. The upsurge of Modified Hartmann number and radiative impact improves copper (II) oxide nanofluid compared to aluminum oxide nanofluid due to Lorentz force and since CuO is a better heat conductor. At the same time, heat absorption and reactive species favor a slight decline in Alumina nanofluid than Cupric nanofluid in the thermal and velocity fields. The higher density of Cupric nanofluid is enhanced by increasing nanoparticle volume fraction over Alumina nanofluid with a decline in velocity distribution.

Keywords: alumina, cupric, nanoparticles, water-based

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Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: Philippe Dillien, Patrice Forget, Harald Engel, Olivier Cornu, Marc De Kock, Jean Cyr Yombi

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Introduction: Hip fracture precedes commonly death in elderly people. Identification of high-risk patients may contribute to target patients in whom optimal management, resource allocation and trials efficiency is needed. The aim of this study is to construct a predictive score of mortality after hip fracture on the basis of the objective prognostic factors available: Neutrophil-to-lymphocyte ratio (NLR), age, and sex. C-Reactive Protein (CRP), is also considered as an alternative to the NLR. Patients and methods: After the IRB approval, we analyzed our prospective database including 286 consecutive patients with hip fracture. A score was constructed combining age (1 point per decade above 74 years), sex (1 point for males), and NLR at postoperative day+5 (1 point if >5). A receiver-operating curve (ROC) curve analysis was performed. Results: From the 286 patients included, 235 were analyzed (72 males and 163 females, 30.6%/69.4%), with a median age of 84 (range: 65 to 102) years, mean NLR values of 6.47+/-6.07. At one year, 82/280 patients died (29.3%). Graphical analysis and log-rank test confirm a highly statistically significant difference (P<0.001). Performance analysis shows an AUC of 0.72 [95%CI 0.65-0.79]. CRP shows no advantage on NLR. Conclusion: We have developed a score based on age, sex and the NLR to predict the risk of mortality at one year in elderly patients after surgery for a hip fracture. After external validation, it may be included in clinical practice as in clinical research to stratify the risk of postoperative mortality.

Keywords: neutrophil-to-lymphocyte ratio, hip fracture, postoperative mortality, medical and health sciences

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Authors: Tolga Hayit, Ucman Ergun, Ugur Fidan

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Being healthy is undoubtedly an indispensable necessity for human life. With technological improvements, in the literature, various health monitoring and imaging systems have been developed to satisfy your health needs. In this context, the work of monitoring and recording the data of individual health monitoring data via wireless technology is also being part of these studies. Nowadays, mobile devices which are located in almost every house and which become indispensable of our life and have wireless technology infrastructure have an important place of making follow-up health everywhere and every time because these devices were using in the health monitoring systems. In this study, Arduino an open-source microcontroller card was used in which a sample sugar measuring device was connected in series. In this way, the glucose data (glucose ratio, time) obtained with the glucometer is transferred to the mobile device based on the Android operating system with the Bluetooth technology channel. A mobile application was developed using the Apache Cordova framework for listing data, presenting graphically and reading data over Arduino. Apache Cordova, HTML, Javascript and CSS are used in coding section. The data received from the glucometer is stored in the local database of the mobile device. It is intended that people can transfer their measurements to their mobile device by using wireless technology and access the graphical representations of their data. In this context, the aim of the study is to be able to perform health monitoring by using different wireless technologies in mobile devices that can respond to different wireless technologies at present. Thus, that will contribute the other works done in this area.

Keywords: Arduino, Bluetooth, glucose measurement, mobile health monitoring

Procedia PDF Downloads 322

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: H. E. Ferrari, R. Farengo, C. F. Clauser

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Tungsten (W) will be used in ITER as one of the plasma facing components (PFCs). The W could migrate to the plasma center. This could have a potentially deleterious effect on plasma confinement. Electron cyclotron resonance heating (ECRH) can be used to prevent W accumulation. We simulated a series of H mode discharges in ASDEX U with PFC containing W, where central ECRH was used to prevent W accumulation in the plasma center. The experiments showed that the W density profiles were flat after a sawtooth crash, and become hollow in between sawtooth crashes when ECRH has been applied. It was also observed that a saturated kink mode was active in these conditions. We studied the effect of saturated kink like instabilities on the redistribution of W impurities. The kink was modeled as the sum of a simple analytical equilibrium (large aspect ratio, circular cross section) plus the perturbation produced by the kink. A numerical code that follows the exact trajectories of the impurity ions in the total fields and includes collisions was employed. The code is written in Cuda C and runs in Graphical Processing Units (GPUs), allowing simulations with a large number of particles with modest resources. Our simulations show that when the W ions have a thermal velocity distribution, the kink has no effect on the W density. When we consider the plasma rotation, the kink can affect the W density. When the average passing frequency of the W particles is similar to the frequency of the kink mode, the expulsion of W ions from the plasma core is maximum, and the W density shows a hollow structure. This could have implications for the mitigation of W accumulation.

Keywords: impurity transport, kink instability, tungsten accumulation, tungsten dynamics

Procedia PDF Downloads 171

Authors: Abu Afree Andalib, M. Mezbah Uddin, M. Rafiur Rahman, M. Abir Hossain, Rajia Sultana Kamol

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This paper deals with the analysis of flow past the marine turbine blade which is designed by using the blade element theory and momentum theory for the purpose of using in the field of renewable energy. The designed blade is analyzed for various parameters using FSI module of Ansys. Computational Fluid Dynamics is used for the study of fluid flow past the blade and other fluidic phenomena such as lift, drag, pressure differentials, energy dissipation in water. Finite Element Analysis (FEA) module of Ansys was used to analyze the structural parameter such as stress and stress density, localization point, deflection, force propagation. Fine mesh is considered in every case for more accuracy in the result according to computational machine power. The relevance of design, search and optimization with respect to complex fluid flow and structural modeling is considered and analyzed. The relevancy of design and optimization with respect to complex fluid for minimum drag force using Ansys Adjoint Solver module is analyzed as well. The graphical comparison of the above-mentioned parameter using CFD and FEA and subsequently FSI technique is illustrated and found the significant conformity between both the results.

Keywords: blade element theory, computational fluid dynamics, finite element analysis, fluid-structure interaction, momentum theory

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Authors: Maurice Mbah

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Entomological survey of mosquitoes responsible for the transmission of lymphatic filariasis in Biase Local Government area of Cross River State, Nigeria within March and June 2017. Lymphatic filariasis is a mosquito-borne parasitic disease that is caused by three species of tissue dwelling filaroids (Wuchereria bancrofti; Brugia malayi; Brugia timori): Wuchereria bancrofti is responsible for 90% of cases and is found throughout the tropics and in some sub-tropical areas worldwide. The mosquitoes were caught using human landing catches, and pyrethrum spray catches method. The entomological analysis of mosquitoes which include speciating into genus and dissecting them to unveil any microfilaria in the thoracic region, abdomen, and mouth parts of the mosquitoes. Entomological analysis shows that, from the 1296 mosquitoes caught 795 (61.3%) were Culex species, 342 (26.4%) Anopheles species, 102 (7.9%) Aedes species, and 57 (4.4%) of other Genera. There was a statistically significant difference in the number of mosquitoes caught in the dry and rainy season (X²=0.62, P < 0.05). Out of 1213 mosquitoes dissected, 24(0.02%) contained developed stages (L₁ – L₃) of W. bancrofti larvae. 13 (0.01%) of the infected mosquitoes were of Culex species, and Anopheles species accounted for the other 11 (0.009%). There was a statistically significant difference in the infection rate between the two seasons (X²=0.87, P < 0.05). The correlation analysis showed a positive correlation between the infection rate among mosquitoes in the dry and rainy season (r=0.85, P < 0.05). The entomological studies showed that Anopheles species and the Culex species are the vectors of lymphatic filariasis in the study area.

Keywords: entomological survey, mosquitoes, lymphatic filariasis, biase

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Mahtsente Tadese, Lalit Kumar, Richard Koech

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The aim of this study was to project and analyze climate change in the Awash River Basin (ARB) using bias-corrected Global and Regional Climate Model simulations. The analysis included a baseline period from 1986-2005 and two future scenarios (the 2050s and 2070s) under two representative concentration pathways (RCP4.5 and RCP8.5). Bias correction methods were evaluated using graphical and statistical methods. Following the evaluation of bias correction methods, the Distribution Mapping (DM) and Power Transformation (PT) were used for temperature and precipitation projection, respectively. The 2050s and 2070s RCP4 simulations showed an increase in precipitation during half of the months with 32 and 10%, respectively. Moreover, the 2050s and 2070s RCP8.5 simulation indicated a decrease in precipitation with 18 and 26%, respectively. The 2050s and 2070s RCP8.5 simulation indicated a significant decrease in precipitation in four of the months (February/March to May) with the highest decreasing rate of 34.7%. The 2050s and 2070s RCP4.5 simulation showed an increase of 0.48-2.6 °C in maximum temperature. In the case of RCP8.5, the increase rate reached 3.4 °C and 4.1 °C in the 2050s and 2070s, respectively. The changes in precipitation and temperature might worsen the water stress, flood, and drought in ARB. Moreover, the critical focus should be given to mitigation strategies and management options to reduce the negative impact. The findings of this study provide valuable information on future precipitation and temperature change in ARB, which will help in the planning and design of sustainable mitigation approaches in the basin.

Keywords: variability, climate change, Awash River Basin, precipitation

Procedia PDF Downloads 174

Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

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Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

Procedia PDF Downloads 478

Authors: Swapnila V. Shinde, Hemant P. Joshi, Sumit R. Dhas, Dhananjaysingh B. Rajput

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The objective of the present study is to develop hydro-dynamically balanced system for atenolol, β-blocker as a single unit floating tablet. Atenolol shows pH dependent solubility resulting into a bioavailability of 36%. Thus, site specific oral controlled release floating drug delivery system was developed. Formulation includes novice use of rate controlling polymer such as locust bean gum (LBG) in combination of HPMC K4M and gas generating agent sodium bicarbonate. Tablet was prepared by direct compression method and evaluated for physico-mechanical properties. The statistical method was utilized to optimize the effect of independent variables, namely amount of HPMC K4M, LBG and three dependent responses such as cumulative drug release, floating lag time, floating time. Graphical and mathematical analysis of the results allowed the identification and quantification of the formulation variables influencing the selected responses. To study the gastrointestinal transit of the optimized gastro-retentive formulation, in vivo gamma scintigraphy was carried out in six healthy rabbits, after radio labeling the formulation with 99mTc. The transit profiles demonstrated that the dosage form was retained in the stomach for more than 5 hrs. The study signifies the potential of the developed system for stomach targeted delivery of atenolol with improved bioavailability.

Keywords: floating tablet, factorial design, gamma scintigraphy, antihypertensive model drug, HPMC, locust bean gum

Procedia PDF Downloads 275

Authors: R. Gounina-Allouane, N. Ouali, F. Z. Berrabah, A. Bentaleb

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For a long time, the Gram-positive spore-forming bacteria Bacillus thuringiensis (Bt) has been widely used in biological control against devastating and disease vectors insects. This is due to the insecticidal activity of its crystalline parasporal inclusion (crystals) predominantly comprised of one or more proteins (Cry and Cyt proteins) also called δ-endotoxins, produced during sporulation. The shape and composition of Bt crystals vary among strains and crystalline proteins are extremely varied (more than 475 cry gene were discovered). The insecticidal activity of Bt crystals is very well studied, thus their insecticidal mode of action is well established, however, their antimicrobial effect is largely unknown. The lack of data on the antimicrobial effect of crystalline proteins of Bt and the need for searching new antimicrobial molecules encouraged us to carried out this study. The antibacterial effect of δ-endotoxines produced by two Bt stains; a strain isolated from soil at northern of Algeria (Bt 7.2.B), and a strain isolated from a bioinsecticide (Bacillus thuringiensis var aizawai), activated by proteolysis, was assayed on clinical bacterial strains and ATCC collection ones respectively. Gram positive and negative clinical bacterial strains (Escherichia coli, Klebsiella pneumonaie, Pseudomonas aeruginosa, Staphylococcus aureus) were sensitive to activated Bt 72B endotoxins. Similarly, bacterial strains from ATCC collection (Escherichia coli ATCC 25922, Pseudomonas aerugenosa ATCC 27853, Staphylococcus aureus ATCC 25923) were sensitive to activated B. thuringiensis var aizawai δ-endotoxines. The activated δ-endotoxins were separated by SDS-PAGE.

Keywords: Bacillus thuringiensis, crystals, cry proteins, δ-endotoxins, antibacterial activity

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Authors: Angel G. De Leon Hernandez

Abstract:

A structure is defined as a physical system or, in certain cases, an arrangement of connected elements, capable of bearing certain loads. The structures are presented in every part of the daily life, e.g., in the designing of buildings, vehicles and mechanisms. The main goal of a structure designer is to develop a secure, aesthetic and maintainable system, considering the constraint imposed to every case. With the advances in the technology during the last decades, the capabilities of solving engineering problems have increased enormously. Nowadays the computers, play a critical roll in the structural analysis, pitifully, for university students the vast majority of these software are inaccessible due to the high complexity and cost they represent, even when the software manufacturers offer student versions. This is exactly the reason why the idea of developing a more reachable and easy-to-use computing tool. This program is designed as a tool for the university students enrolled in courser related to the structures analysis and designs, as a complementary instrument to achieve a better understanding of this area and to avoid all the tedious calculations. Also, the program can be useful for graduated engineers in the field of structural design and analysis. A graphical user interphase is included in the program to make it even simpler to operate it and understand the information requested and the obtained results. In the present document are included the theoretical basics in which the program is based to solve the structural analysis, the logical path followed in order to develop the program, the theoretical results, a discussion about the results and the validation of those results.

Keywords: stiffness matrix method, structural analysis, Matlab® applications, programming

Procedia PDF Downloads 122

Authors: R. Gounina-Allouane, N. Ouali, F. Z. Berrabah, A. Bentaleb

Abstract:

For a long time, the Gram-positive spore-forming bacteria Bacillus thuringiensis (Bt) has been widely used in biological control against devastating and disease vectors insects. This is due to the insecticidal activity of its crystalline parasporal inclusion (crystals) predominantly comprised of one or more proteins (Cry and Cyt proteins) also called δ-endotoxins, produced during sporulation. The shape and composition of Bt crystals vary among strains and crystalline proteins are extremely varied (more than 475 cry gene were discovered). The insecticidal activity of Bt crystals is very well studied, thus their insecticidal mode of action is well established, however, their antimicrobial effect is largely unknown. The lack of data on the antimicrobial effect of crystalline proteins of Bt and the need for searching new antimicrobial molecules encouraged us to carried out this study. The antibacterial effect of δ-endotoxines produced by two Bt stains; a strain isolated from soil at northern of Algeria (Bt 7.2.B), and a strain isolated from a bioinsecticide (Bacillus thuringiensis var aizawai), activated by proteolysis, was assayed on clinical bacterial strains and ATCC collection ones respectively. Gram positive and negative clinical bacterial strains (Escherichia coli, Klebsiella pneumonaie, Pseudomonas aeruginosa, Staphylococcus aureus) were sensitive to activated Bt 72B endotoxins. Similarly, bacterial strains from ATCC collection (Escherichia coli ATCC 25922, Pseudomonas aerugenosa ATCC 27853, Staphylococcus aureus ATCC 25923) were sensitive to activated B. thuringiensis var aizawai δ-endotoxines. The activated δ-endotoxins were separated by SDS-PAGE.

Keywords: Bacillus thuringiensis, crystals, cry proteins, δ-endotoxins, antibacterial activity

Procedia PDF Downloads 430

Authors: Cristina Maria Ribeiro Martins Pereira Caridade, Ana Rita Ferreira Morais

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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with healthcare facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool developed in MATLAB using a graphical user interface for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing you to view original images and fusion images, compare processed and original images, adjust parameters, and save images. The tool proposed in an innovative teaching and learning environment consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques and necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.

Keywords: image fusion, image processing, teaching-learning simulation tool, biomedical engineering education

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Wan Liu, Haibo Wang, Cathy Huang, Zhiwu Tan, Zhiwei Chen

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The tremendous diversity of HIV-1 has been a major challenge for an effective AIDS vaccine development. Mosaic approach presents the potential for vaccine design aiming for global protection. The mosaic antigen of HIV-1 Gag allows antigenic breadth for vaccine-elicited immune response against a wider spectrum of viral strains. However, the enhancement of immune response using vaccines is dependent on the strategy used. Heterologous prime/boost regimen has been shown to elicit high levels of immune responses. Here, we investigated whether priming using plasmid DNA with electroporation followed by boosting with the live replication-competent modified vaccinia virus vector TianTan (MVTT) combined with the mosaic antigenic sequence could elicit a greater and broader antigen-specific response against HIV-1 Gag in mice. When compared to DNA or MVTT alone, or MVTT/MVTT group, DNA/MVTT group resulted in coincidentally high frequencies of broadly reactive, Gag-specific, polyfunctional, long-lived, and cytotoxic CD8+ T cells and increased anti-Gag antibody titer. Meanwhile, the vaccination could upregulate PD-1+, and Tim-3+ CD8+ T cell, myeloid-derived suppressive cells and Treg cells to balance the stronger immune response induced. Importantly, the prime/boost vaccination could help control the EcoHIV and mesothelioma AB1-gag challenge. The stronger protective Gag-specific immunity induced by a Mosaic DNA/MVTT vaccine corroborate the promise of the mosaic approach, and the potential of two acceptably safe vectors to enhance anti-HIV immunity and cancer prevention.

Keywords: DNA/MVTT vaccine, EcoHIV, mosaic antigen, mesothelioma AB1-gag

Procedia PDF Downloads 242

Authors: Alina Goldberg Cavalleri, Sara Franco Ortega, Nawaporn Onkokesung, Richard Dale, Melissa Brazier-Hicks, Robert Edwards

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Non-target site based resistance (NTSR) to herbicides in weeds is a polygenic trait associated with the upregulation of proteins involved in xenobiotic detoxification and translocation we have termed the xenome. Among the xenome proteins, ABC transporters play a key role in enhancing herbicide metabolism by effluxing conjugated xenobiotics from the cytoplasm into the vacuole. The importance of ABC transporters is emphasized by the fact that they often contribute to multidrug resistance in human cells and antibiotic resistance in bacteria. They also play a key role in insecticide resistance in major vectors of human diseases and crop pests. By surveying available databases, transcripts encoding ABCs have been identified as being enhanced in populations exhibiting NTSR in several weed species. Based on a transcriptomics data in black grass (Alopecurus myosuroides, Am), we have identified three proteins from the ABC-C subfamily that are upregulated in NTSR populations. ABC-C transporters are poorly characterized proteins in plants, but in Arabidopsis localize to the vacuolar membrane and have functional roles in transporting glutathionylated (GSH)-xenobiotic conjugates. We found that the up-regulation of AmABCs strongly correlates with the up-regulation of a glutathione transferase termed AmGSTU2, which can conjugate GSH to herbicides. The expression profile of the ABC transcripts was profiled in populations of black grass showing different degree of resistance to herbicides. This, together with a phylogenetic analysis, revealed that AmABCs cluster in different groups which might indicate different substrate and roles in the herbicide resistance phenotype in the different populations

Keywords: black grass, herbicide, resistance, transporters

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Yoshifumi Hino

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An infinitely repeated prisoner’s dilemma is a typical model that represents teamwork situation. If both players choose costly actions and contribute to the team, then both players are better off. However, each player has an incentive to choose a selfish action. We analyze the game under costly observation. Each player can observe the action of the opponent only when he pays an observation cost in that period. In reality, teamwork situations are often costly observation. Members of some teams sometimes work in distinct rooms, areas, or countries. In those cases, they have to spend their time and money to see other team members if they want to observe it. The costly observation assumption makes the cooperation difficult substantially because the equilibrium must satisfy the incentives not only on the action but also on the observational decision. Especially, it is the most difficult to cooperate each other when the stage-game is prisoner's dilemma because players have to communicate through only two actions. We examine whether or not players can cooperate each other in prisoner’s dilemma under costly observation. Specifically, we check whether symmetric Pareto efficient payoff vectors in repeated prisoner’s dilemma can be approximated by sequential equilibria or not (efficiency result). We show the efficiency result without any randomization device under certain circumstances. It means that players can cooperate with each other without any randomization device even if the observation is costly. Next, we assume that public randomization device is available, and then we show that any feasible and individual rational payoffs in prisoner’s dilemma can be approximated by sequential equilibria under a specific situation (folk theorem). It implies that players can achieve asymmetric teamwork like leadership situation when public randomization device is available.

Keywords: cost observation, efficiency, folk theorem, prisoner's dilemma, private monitoring, repeated games.

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Authors: Davidson E. Egirani, Nanfe R. Poyi, Napoleon Wessey

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This paper would report on the effect of solid waste on water resource quality in the Gbarain catchment of the Niger Delta Region of Nigeria. The Gbarain catchment presently hosts two waste-dump sites located along the flanks of a seasonal flow stream and perennially waterlogged terrain. The anthropogenic activity has significantly affected the quality of surface and groundwater in the Gbarain catchment. These wastes have made the water resource environment toxic leading to the poisoning of aquatic life. The contaminated water resources could lead to serious environmental and human health challenges such as low agricultural yields to loss of vital human organs. The contamination is via geological processes such as seepage and direct infiltration of contaminants into watercourses. The results obtained from field and experimental investigations followed by modeling, and graphical interpretation indicate heavy metal load and fecal pollution in some of the groundwater. The metal load, Escherichia coli, and total coliforms counts exceed the international and regional recommended limits. The contaminate values include Lead (> 0.01 mg/L), Mercury (> 0.006 mg/L), Manganese (> 0.4 mg/L and Escherichia coli (> 0 per 100ml) of the samples. Land use planning, enactment, and implementation of environmental laws are necessary for this region, for effective surface water and groundwater resource management.

Keywords: aquatic life, solid waste, environmental health, human health, waste-dump site, water-resource environment

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: Navneet Kaur, S. D. Tiwari

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Magnetic nanoparticles possess fascinating properties which make their behavior unique in comparison to corresponding bulk materials. Superparamagnetism is one such interesting phenomenon exhibited only by small particles of magnetic materials. In this state, the thermal energy of particles become more than their magnetic anisotropy energy, and so particle magnetic moment vectors fluctuate between states of minimum energy. This situation is similar to paramagnetism of non-interacting ions and termed as superparamagnetism. The magnetization of such systems has been described by Langevin function. But, the estimated fit parameters, in this case, are found to be unphysical. It is due to non-consideration of particle size distribution. In this work, analysis of magnetization data on NiO nanoparticles is presented considering the effect of particle size distribution. Nanoparticles of NiO of two different sizes are prepared by heating freshly synthesized Ni(OH)₂ at different temperatures. Room temperature X-ray diffraction patterns confirm the formation of single phase of NiO. The diffraction lines are seen to be quite broad indicating the nanocrystalline nature of the samples. The average crystallite size are estimated to be about 6 and 8 nm. The samples are also characterized by transmission electron microscope. Magnetization of both sample is measured as function of temperature and applied magnetic field. Zero field cooled and field cooled magnetization are measured as a function of temperature to determine the bifurcation temperature. The magnetization is also measured at several temperatures in superparamagnetic region. The data are fitted to an appropriate expression considering a distribution in particle size following a least square fit procedure. The computer codes are written in PYTHON. The presented analysis is found to be very useful for estimating the particle size distribution present in the samples. The estimated distributions are compared with those determined from transmission electron micrographs.

Keywords: anisotropy, magnetization, nanoparticles, superparamagnetism

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Fahad Abbasi

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Flow of electrically conducting nanofluids is of pivotal importance in countless industrial and medical appliances. Fluctuations in thermophysical properties of such fluids due to variations in temperature have not received due attention in the available literature. Present investigation aims to fill this void by analyzing the flow of copper-water nanofluid with temperature dependent viscosity past a Riga plate. Strong wall suction and viscous dissipation have also been taken into account. Numerical solutions for the resulting nonlinear system have been obtained. Results are presented in the graphical and tabular format in order to facilitate the physical analysis. An estimated expression for skin friction coefficient and Nusselt number are obtained by performing linear regression on numerical data for embedded parameters. Results indicate that the temperature dependent viscosity alters the velocity, as well as the temperature of the nanofluid and, is of considerable importance in the processes where high accuracy is desired. Addition of copper nanoparticles makes the momentum boundary layer thinner whereas viscosity parameter does not affect the boundary layer thickness. Moreover, the regression expressions indicate that magnitude of rate of change in effective skin friction coefficient and Nusselt number with respect to nanoparticles volume fraction is prominent when compared with the rate of change with variable viscosity parameter and modified Hartmann number.

Keywords: heat transfer, peristaltic flows, radially varying magnetic field, curved channel

Procedia PDF Downloads 166