Search results for: activity learning

Authors: Naheed Niaz, Nimra Naeem, Bushra Uzair, Riffat Tahira

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Antibacterial activity of different traditional plants essential oils against clinical isolates of Methicillin-resistant Staphylococcus aureus (MRSA) through disk diffusion method was evaluated. All the tested essential oils, in different concentrations, inhibited growth of S. aureus to varying degrees. Cinnamon and Thyme essential oils were observed to be the “best” against test pathogen. Even at lowest concentration of these essential oils i.e. 25 µl/ml, clear zone of inhibition was recorded 9+0.085mm and 8+0.051mm respectively, and at higher concentrations there was a total reduction in growth of MRSA. The study also focused on analyzing the synergistic effects of essential oils in combination with amoxicillin. Results showed that oregano and pennyroyal mint essential oils which were not very effective alone turned out to be strong synergistic enhancers. The activity increased with increase in concentration of the essential oils. It may be concluded from present results that cinnamon and thyme essential oils could be used as potential antimicrobial source for the treatment of infections caused by Methicillin-resistant Staphylococcus aureus (MRSA).

Keywords: Staphylococcus aureus, essential oils, antibiotics, combination therapy, minimum inhibitory concentration

Procedia PDF Downloads 433

Authors: Vesna Tumbas Šaponjac, Sonja Djilas, Jasna Čanadanović-Brunet, Gordana Ćetković, Jelena Vulić, Slađana Stajčić, Milica Vinčić

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Substantial interest has been expressed in fruits and berries due to their potential favourable health effects and high content of polyphenols, especially flavonoids and anthocyanins. Chokeberries (Aronia melanocarpa) are dark berries, similar to blackcurrants, that have been used by native Americans both as a food resource and in traditional medicine for treatment of cold. Epidemiological studies revealed positive effects of chokeberries on colorectal cancer, cardiovascular diseases, and various inflammatory conditions. Chokeberries are well known as good natural antioxidants, which contain phenolic compounds, flavonoids, anthocyanidins and antioxidant vitamins. The aim of this study was to provide information on polyphenolic compounds present in fresh chokeberries as well as to determine its antioxidant activity. Individual polyphenolic compounds have been identified and quantified using HPLC/UV-Vis. Results showed that the most dominant phenolic acid was protocatechuic acid (274.23 mg/100 g FW), flavonoid rutin (319.66 mg/100 g FW) and anthocyanin cyanidin-3-galactoside (1532.68 mg/100 g FW). Generally, anthocyanins were predominant compounds in fresh chokeberry (2342.82 mg/100 g FW). Four anthocyanins have been identified in fresh chokeberry and all of them were cyanidin glicosides. Antioxidant activity was determined using spectrophotometric DPPH assay and compared to standard antioxidant compound vitamin C. The resulting EC50 value (amount of fresh chokeberries that scavenge 50% of DPPH radicals) is 0.33 mg vitamin C equivalent/100 g FW. The results of this investigation provide evidence on high contents of phenolic compounds, especially anthocyanins, in chokeberries as well as high antioxidant activity of this fruit.

Keywords: chokeberry, polyphenols, antioxidant, DPPH radicals

Procedia PDF Downloads 561

Authors: Sibawu Witness Siyepu

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This study explores the effects of instructional design using blended learning in the learning of radian measures among Engineering students. Blended learning is an education programme that combines online digital media with traditional classroom methods. It requires the physical presence of both lecturer and student in a mathematics computer laboratory. Blended learning provides element of class control over time, place, path or pace. The focus was on the use of Khan Academy to supplement traditional classroom interactions. Khan Academy is a non-profit educational organisation created by educator Salman Khan with a goal of creating an accessible place for students to learn through watching videos in a computer assisted computer. The researcher who is an also lecturer in mathematics support programme collected data through instructing students to watch Khan Academy videos on radian measures, and by supplying students with traditional classroom activities. Classroom activities entails radian measure activities extracted from the Internet. Students were given an opportunity to engage in class discussions, social interactions and collaborations. These activities necessitated students to write formative assessments tests. The purpose of formative assessments tests was to find out about the students’ understanding of radian measures, including errors and misconceptions they displayed in their calculations. Identification of errors and misconceptions serve as pointers of students’ weaknesses and strengths in their learning of radian measures. At the end of data collection, semi-structure interviews were administered to a purposefully sampled group to explore their perceptions and feedback regarding the use of blended learning approach in teaching and learning of radian measures. The study employed Algebraic Insight Framework to analyse data collected. Algebraic Insight Framework is a subset of symbol sense which allows a student to correctly enter expressions into a computer assisted systems efficiently. This study offers students opportunities to enter topics and subtopics on radian measures into a computer through the lens of Khan Academy. Khan academy demonstrates procedures followed to reach solutions of mathematical problems. The researcher performed the task of explaining mathematical concepts and facilitated the process of reinvention of rules and formulae in the learning of radian measures. Lastly, activities that reinforce students’ understanding of radian were distributed. Results showed that this study enthused the students in their learning of radian measures. Learning through videos prompted the students to ask questions which brought about clarity and sense making to the classroom discussions. Data revealed that sense making through reinvention of rules and formulae assisted the students in enhancing their learning of radian measures. This study recommends the use of Khan Academy in blended learning to be introduced as a socialisation programme to all first year students. This will prepare students that are computer illiterate to become conversant with the use of Khan Academy as a powerful tool in the learning of mathematics. Khan Academy is a key technological tool that is pivotal for the development of students’ autonomy in the learning of mathematics and that promotes collaboration with lecturers and peers.

Keywords: algebraic insight framework, blended learning, Khan Academy, radian measures

Procedia PDF Downloads 295

Authors: S. Studente, S. Ellis, S. F. Garivaldis

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We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.

Keywords: chatbot, e-learning, learning communities, student engagement

Procedia PDF Downloads 109

Authors: Ayorinde B. Ogunremi, Kehinde A. Adewoyin, Adebamwo Adebayo

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Record of radionuclide concentration in an environment is essential to ensure human safety due to exposure to ionizing radiation. This study aimed at assessing the radionuclide concentration and doses from soil samples in the study area. Twenty soil samples were collected and dried in the oven at 110°C to remove the moisture, pulverized, and sieved. 200 g of each of the samples were sealed in cylindrical sample holders; they were left for four weeks to attain secular equilibrium between ²²⁶Ra and its decay daughters, after which the sample was analyzed using gamma-ray spectrometry. After the well-guided procedure for the calibrations, the analysis of the samples was carried out using a well-calibrated NaI (TI) and well-shielded detector coupled to a computer resident quantum MCA2100 R Multichannel analyzer for 36,000 s. The mean activity concentrations of ⁴⁰K, ²²⁶Ra, and ²³²Th obtained were calculated to be 272.37 ± 33.58, 10.97 ± 3.24, 9.39 ± 2.27 Bqkg-1 respectively. The average absorbed dose obtained was 22.10 nGy/h. The radium equivalent activity (Raeq) was estimated to be 43.27 Bq/kg. The activity concentrations (Bq/kg) were below the recommended values, which are 420, 33, and 45 for ⁴⁰K, ²²⁶Ra, and ²³²Th, respectively. Considering the results, we conclude thus, the radiation level within the estate poses no significant health risk on dwellers and workers.

Keywords: absorbed, effective, multichannel, radionuclide

Procedia PDF Downloads 195

Authors: Maria Visitacion N. Gumabay, Byron Joseph A. Hallar, Annjeannette Alain D. Galang

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This study was intended to provide a more efficient and convenient way for mobile users to enhance their knowledge about ASEAN countries. The researchers evaluated the utility of the developed crossword puzzle application and assessed the general usability of its user interface for its intended purpose and audience of users. The descriptive qualitative research method for the research design and the Mobile-D methodology was employed for the development of the software application output. With a generally favorable reception from its users, the researchers concluded that the iSEA Mobile Based Learning Application can be considered ready for general deployment and use. It was also concluded that additional studies can also be done to make a more complete assessment of the knowledge gained by its users before and after using the application.

Keywords: mobile learning, eLearning, crossword, ASEAN, iSEA

Procedia PDF Downloads 295

Authors: Yasmin Hussein Embaby

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Introduction: Athletic Training has its essentials, rules, and methods that help individual in reaching the maximum possible athletic level during the exercised physical activity, therefore; it is important for those working in athletic field to recognize and understand what is going on inside our bodies. This will show the close relationship between physiology and athletic training as the science that explains the various changes that happen to respond to the practice of physical activities. Swimming is one of the water sports that play a major role in influencing the full compatibility of body parts and its systems during the practice of different swimming methods, which uses aqueous to move. It is the initial nucleus in swimming learning and through which the beginner gain a sense of security, safety and the ability to move in aqueous by learning basic skills. Research Methodology: The researcher used the experimental methodology by using pre and post measurement on two equal groups (experimental – control) because it is appropriate for the research. Conclusions: Through the results and information found by the researcher, and in light of the related studies, theoretical readings and the statistical treatments of data; the researcher reached the following conclusions: 1. Muscle relaxation exercises have a positive effect on performance level in crawl swimming and on endorphin hormone as it helps in increasing its normal rater in body, the improvement percentage for experimental group in the relaxation ability, level of endorphin hormone exceeds those of control group. 2. The validity of muscle relaxation exercises proposed for the application, which achieved its objectives, namely increasing the level of endorphin hormone in the body; where research results showed a statistically significant difference in the level of endorphin hormone in favor of the experimental sample.

Keywords: beginners, endorphin hormone, relaxing exercises, swimming

Procedia PDF Downloads 191

Authors: Romisaa Ali

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This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

Procedia PDF Downloads 76

Authors: Eddy Neuhaus, Hanif Shirinzadeh, Cigdem Karaaslan, Elif Ince, Hande Gurer-Orhan, Sibel Suzen

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Reactive oxygen species (ROS) and oxidative stress can cause fatal damage to essential cell structures, including DNA. It is known that use of antioxidants could be advantageous in the prevention of various diseases such as cancer, cardiovascular diseases and neurodegenerative disorders. Since antioxidant properties of the indole ring-containing melatonin (MLT) has been described and evaluated, MLT-related compounds such as MLT metabolites and synthetic analogues are under investigation to determine which exhibit the highest activity with the lowest side-effects. Owing to indole and hydrazones appealing physiological properties and are mostly found in numerous biologically active compounds a series of indole-7-carbaldehyde hydrazone derivatives were synthesized, characterized and in vitro antioxidant activity was investigated by evaluating their reducing effect against oxidation of a redox-sensitive fluorescent probe. Cytotoxicity potential of all indole-based MLT analogues was investigated both by lactate dehydrogenase leakage assay and by MTT assay. This work was supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) Research and Development Grant 112S599.

Keywords: melatonin, antioxidant activity, indole, hydrazone, oxidative stress

Procedia PDF Downloads 468

Authors: Gülay Dalgıç, Gildis Tachir

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Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

Procedia PDF Downloads 126

Authors: Van Tang Nguyen, Jennette A. Sakoff, Christopher J. Scarlett

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Phyllanthus amarus (P. amarus) has been used as a traditional herbal plant for the treatment of chronic ailments such as hepatitis, diabetes and cancer. The objectives of this study were to determine the physicochemical properties, antioxidant and cytotoxic activities of crude P. amarus extracts and fractions using MTT and CCK-8 assays for cytotoxic evaluation. The outcomes indicated that P. amarus methanol (PAM) extract had lower residual moisture (7.40%) and water activity (0.24) and higher contents of saponins, phenolics, flavonoids and proanthocyanidins (1657.86 mg escin equivalents, 250.45 mg gallic acid equivalents, 274.73 mg rutin equivalents and 61.22 mg catechin equivalents/g dried extract, respectively) than those of P. amarus water (PAW) extract, resulting antioxidant activity of PAM extract was significantly higher (P < 0.05) than that of PAW extract, PAM fractions and phyllanthin (a major compound in P. amarus). Cytotoxic activity of PAM extract for cancer cell lines of MiaPaCa-2 (pancreas), HT29 (colon), A2780 (ovarian), H460 (lung), A431 (skin), Du145 (prostate), BE2-C (neuroblastoma), MCF-7 (breast), MCF-10A (normal breast), and U87, SJ-G2, SMA (glioblastoma) was higher than those of PAW extract and PAM fractions. Therefore, we can conclude that the PA extracts are a potential source for the development of natural antioxidant products and/or novel anticancer drugs.

Keywords: antioxidant, cytotoxicity, Phyllanthus amarus, physicochemical

Procedia PDF Downloads 304

Authors: Alexander Huang

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Online learning sessions have become an indispensable complement to in-classroom-learning sessions in the past two years due to the emergence of Covid-19. Due to social distance requirements, many courses and interaction-intensive sessions, ranging from music classes to debate camps, are online. However, online learning imposes a significant challenge for engaging students effectively during the learning sessions. To resolve this problem, Project PWR, a non-profit organization formed by high school students, developed an online kid-teach-kid learning environment to boost students' learning interests and further improve students’ engagement during online learning. Fundamentally, the kid-teach-kid learning model creates an affinity space to form learning groups, where like-minded peers can learn and teach their interests. The role of the teacher can also help a kid identify the instructional task and set the rules and procedures for the activities. The approach also structures initial discussions to reveal a range of ideas, similar experiences, thinking processes, language use, and lower student-to-teacher ratio, which become enriched online learning experiences for upcoming lessons. In such a manner, a kid can practice both the teacher role and the student role to accumulate experiences on how to convey ideas and questions over the online session more efficiently and effectively. In this research work, we conducted two case studies involving a 3D-Design course and a Speech and Debate course taught by high-school kids. Through Project PWR, a kid first needs to design the course syllabus based on a provided template to become a student-teacher. Then, the Project PWR academic committee evaluates the syllabus and offers comments and suggestions for changes. Upon the approval of a syllabus, an experienced and voluntarily adult mentor is assigned to interview the student-teacher and monitor the lectures' progress. Student-teachers construct a comprehensive final evaluation for their students, which they grade at the end of the course. Moreover, each course requires conducting midterm and final evaluations through a set of surveyed replies provided by students to assess the student-teacher’s performance. The uniqueness of Project PWR lies in its established kid-teach-kids affinity space. Our research results showed that Project PWR could create a closed-loop system where a student can help a teacher improve and vice versa, thus improving the overall students’ engagement. As a result, Project PWR’s approach can train teachers and students to become better online learners and give them a solid understanding of what to prepare for and what to expect from future online classes. The kid-teach-kid learning model can significantly improve students' engagement in the online courses through the Project PWR to effectively supplement the traditional teacher-centric model that the Covid-19 pandemic has impacted substantially. Project PWR enables kids to share their interests and bond with one another, making the online learning environment effective and promoting positive and effective personal online one-on-one interactions.

Keywords: kid-teach-kid, affinity space, online learning, engagement, student-teacher

Procedia PDF Downloads 131

Authors: Mohd Khairezan Rahmat

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Since the impetus of becoming a develop country by the year 2020, the Malaysian government have been proactive in strengthening the integration of ICT into the national educational system. Teacher-education programs have the responsibility to prepare the nation future teachers by instilling in them the desire, confidence, and ability to fully utilized the potential of ICT into their instruction process. In an effort to fulfill this responsibility, teacher-education program are beginning to create alternatives means for preparing cutting-edge teachers. One of the alternatives is the student’s learning portal. In line with this mission, this study investigates the Faculty of Education, University Teknologi MARA (UiTM) pre-service teachers’ perception of usefulness, attitude, and ability toward the usage of the university learning portal, known as iLearn. The study also aimed to predict factors that might hinder the pre-service teachers’ decision to used iLearn as their platform in learning. The Structural Equation Modeling (SEM), was employed in analyzed the survey data. The suggested findings informed that pre-service teacher’s successful integration of the iLearn was highly influenced by their perception of usefulness of the system. The findings also suggested that the more familiar the pre-service teacher with the iLearn, the more possibility they will use the system. In light of similar study, the present findings hope to highlight the important to understand the user’s perception toward any proposed technology.

Keywords: e-learning, prediction factors, pre-service teacher, structural equation modeling (SEM)

Procedia PDF Downloads 319

Authors: Claire Griffin

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Recent years have witnessed a surge in the use of innovative teaching approaches to support student engagement and higher-order learning within higher education. This paper seeks to explore the use of collaborative, interactive teaching and learning strategies to support student engagement in a final year undergraduate Developmental Psychology module. In particular, the use of the jigsaw method, in-class presentations and online discussion fora were adopted in a ‘lectorial’ style teaching approach, aimed at scaffolding learning, fostering social interdependence and supporting various levels of student engagement in higher education. Using the ‘Student Course Engagement Questionnaire’, the impact of such teaching strategies on students’ college classroom experience was measured, with additional qualitative student feedback gathered. Results illustrate the positive impact of the teaching methodologies on students’ levels of engagement, with positive implications emerging across the four engagement factors: skills engagement, emotional engagement, participation/interaction engagement and performance engagement. Thematic analysis on students’ qualitative comments also provided greater insight into the positive impact of the ‘lectorial’ teaching approach on students’ classroom experience within higher level education. Implications of the findings are presented in terms of informing effective teaching practices within higher education. Additional avenues for future research and strategy usage will also be discussed, in light of evolving practice and cutting edge literature within the field.

Keywords: learning, higher education, scaffolding, student engagement

Procedia PDF Downloads 358

Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

Procedia PDF Downloads 417

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

Procedia PDF Downloads 290

Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

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For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

Procedia PDF Downloads 146

Authors: Sadi-Guettaf Hassiba, Hadj-Bekkouche Fatima

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Dexamethasone (Dex) is a synthetic glucocorticoid that is used in therapy. However prolonged treatments with high doses are often required. This causes side effects that interfere with the activity of several endocrine systems, including the gonadotropic axis. The aim of our study is to determine the effect of Dex on testicular function in prepubertal Wistar rats. Newborn Wistar rats are submitted to intraperitoneal injection of Dex (1μg of Dex dissolved in NaCl 0.9% / 5g bw) for 20 days and then sacrificed at the age of 40days. A control group received NaCl 0.9%. The rat is weighed daily. The plasmatic levels of testosterone, LH and FSH were measured by radioimmunoassay. A histo-morphometric study was performed on sections of testis. Treated groups showed a significant decrease in body weight (p < 0.05), testis weight (p < 0.05) and plasma levels of testosterone (p < 0.05), of LH (P < .05) and FSH (p> 0.05). There is a reduction of seminiferous tubules average diameter and also of the seminiferous epithelium thickness with an increasing of lumen tubular. The diameter of the Leydig cells and Sertoli cell nucleus is also significantly reduced. Spermatogenesis is blocked at the stage round spermatid unlike witnesses or elongated spermatid stage is found. These results suggest that Dex administered during neonatal life influences testicular activity in the long term.

Keywords: dexamethasone, FSH, LH, rat, testis, testosterone

Procedia PDF Downloads 238

Authors: Asma Osivand, Hossein Mardani, Hiroshi Araya, Yoshiharu Fujii

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Wild mushrooms have always been considered as valuable source of bioactive compounds, while edible mushrooms have been known for their importance as food source. However, their interaction with plants through chemicals that could lead to find new biochemical have not been well undertaken. A special bioassay method (Sandwich method) was applied to compare eight common edible mushrooms (Pleurotus eryngii, Pleurotus citrinopileatus, Pleurotus ostreatus, Lentinula edodes, Grifola frondosa, Flammulina velutipes, Hypsizygus tessellatus and Pholiota namako) with some wild species (Ganoderma appelanatum, Amanita pantherina, Artomyces pyxidatus, Morchella conica, Tricholosporum porphyrophyllum, Trametes hirsuta) for their phytotoxicity against lettuce. Among all tested edible mushrooms, application of 5 mg of P. ostreatus showed stronger allelopathic activity by inhibiting the growth of radicle and hypocotyl of lettuce by 84% and 63% respectively. Moreover, same amount of T. porphyrophyllum exerted 77% and 67% growth inhibition on radicle and hypocotyl of lettuce. In general, biochemicals contributed in tested mushrooms could be the main cause for their inhibitory activity and could lead to find new allelochemicals.

Keywords: allelopathy, interaction, mushroom, phytotoxicity, Pleurotus sp., sandwich method

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Authors: Mahmoud I. Syam, Osama K. El-Hafy

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With lack of student motivation, there will be a little or no real learning in the class and this directly effects student achievement and test scores. Some students are naturally motivated to learn, but many students are not motivated, they do care little about learning and need their instructors to motivate them. Thus, motivating students is part of the instructor’s job. It’s a tough task to motivate students and make them have more attention and enthusiasm. As a part of this research, a questionnaire has been distributed among a sample of 155 students out of 1502 students from Foundation Program at Qatar University. The questionnaire helped us to determine some methods to motivate the students and encourage them to study such as variety of teaching activities, encouraging students to participate during the lectures, creating intense competition between the students, using instructional technology, not using grades as a threat and respecting the students and treating them in a good manner. Accordingly, some hypotheses are tested and some recommendations are presented.

Keywords: learning, motivating, student, teacher, testing hypotheses

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Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Ghiwa Dandach

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By challenging the anti-failure bias and contributing to the theoretical territory of the attribution theory, this thesis develops a comprehensive process for entrepreneurial learning from failure. The practical implication of the findings suggests assisting entrepreneurs (current, failing, and nascent) in effectively anticipating and reflecting upon failure. Additionally, the process is suggested to enhance the level of institutional and private (accelerators and financers) support provided to entrepreneurs, the implications of which may improve future opportunities for entrepreneurial success. Henceforth, exploring learning from failure is argued to impact the potential survival of future ventures, subsequently revitalizing the economic contribution of entrepreneurship. This learning process can be enhanced with the cognitive development of causal ascriptions for failure, which eventually impacts learning outcomes. However, the mechanism with which entrepreneurs make sense of failure, reflect on the journey, and transform experience into knowledge is still under-researched. More specifically, the cognitive process of failure attribution is under-explored, majorly in the context of developing economies, calling for a more insightful understanding on how entrepreneurs ascribe failure. Responding to the call for more thorough research in such cultural contexts, this study expands the understanding of the dimensions of failure attributions as perceived by entrepreneurs and the impact of these dimensions on learning outcomes in the Lebanese context. The research adopted the exploratory interpretivism paradigm and collected data from interviews with industry experts first, followed by narratives of entrepreneurs using the qualitative multimethod approach. The holistic and categorical content analysis of narratives, preceded by the thematic analysis of interviews, unveiled how entrepreneurs ascribe failure by developing minor and major dimensions of each failure attribution. The findings have also revealed how each dimension impacts the learning from failure when accompanied by emotional resilience. The thesis concludes that exploring in-depth the dimensions of failure attributions significantly determines the level of learning generated. They are moving beyond the simple categorisation of ascriptions as primary internal or external unveiled how learning may occur with each attribution at the individual, venture, and ecosystem levels. This has further accentuated that a major internal attribution of failure combined with a minor external attribution generated the highest levels of transformative and double-loop learning, emphasizing the role of personal blame and responsibility on enhancing learning outcomes.

Keywords: attribution, entrepreneurship, reflection, sense-making, emotions, learning outcomes, failure, exit

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Authors: Mostafa Heidari

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Nitrogen fertilization has played a significant role in increasing crop yield, and solving problems of hunger and malnutrition worldwide. However, excessive of heavy metals such as arsenic can interfere on growth and reduced grain yield. In order to investigate the effects of different concentrations of arsenic and nitrogen fertilizer on photosynthetic pigments and antioxidant enzyme activities in safflower (cv. Goldasht), a factorial plot experiment as randomized complete block design with three replication was conducted in university of Zabol. Arsenic treatment included: A1= control or 0, A2=30, A3=60 and A4=90 mg. kg-1 soil from the Na2HASO4 source and three nitrogen levels including W1=75, W2=150 and W3=225 kg.ha-1 from urea source. Results showed that, arsenic had a significant effect on the activity of antioxidant enzymes. By increasing arsenic levels from A1 to A4, the activity of ascorbate peroxidase (APX) and gayacol peroxidase (GPX) increased and catalase (CAT) was decreased. In this study, arsenic had no significant on chlorophyll a, b and cartoneid content. Nitrogen and interaction between arsenic and nitrogen treatment, except APX, had significant effect on CAT and GPX. The highest GPX activity was obtained at A4N3 treatment. Nitrogen increased the content of chlorophyll a, b and cartoneid.

Keywords: arsenic, physiological parameters, oxidative enzymes, nitrogen

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

Abstract:

We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

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Authors: Alhusein Almahjoub, Dongyu Qiu

Abstract:

This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Xiao Zhou, Jianlin Cheng

Abstract:

A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

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Authors: Gabriela Teodorescu, Ioana Daniela Dulama

Abstract:

In an ever-changing society, the education system needs to constantly evolve to meet market demands. During its 30 years of existence, Valahia University of Targoviste (VUT) tried to offer its students a series of teaching-learning schemes that would prepare them for a remarkable career. In VUT, the achievement of performance through innovation can be analyzed by reference to several key indicators (i.e., university climate, university resources, and innovative methods applied to classes), but it is possible to differentiate between activities in the classic format: participate to courses; interactive seminars and tutorials; laboratories, workshops, project-based learning; entrepreneurial activities, through simulated enterprises; mentoring activities. Thus, VUT has implemented over time a series of schemes and projects based on innovation and entrepreneurship, and in this paper, some of them will be briefly presented. All these schemes were implemented by facilitating an effective dialog with students and the opportunity to listen to their views at all levels of the University and in all fields of study, as well as by developing a partnership with students to set out priority areas. VUT demonstrates innovation and entrepreneurial capacity through its new activities for higher education, which will attract more partnerships and projects dedicated to students.

Keywords: Romania, project-based learning, entrepreneurial activities, simulated enterprises

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Authors: Sultan Ahmed Arishi

Abstract:

The objective of the study was to investigate the attitude of the Saudi students attending the English Language programmes of the Royal Commission for Jubail towards using CALL, as well as to discover whether computer-assisted teaching is useful and valuable for students in learning English. Data were collected with the help of interviews and survey questionnaires. The outcomes of the investigation showed that students had a positive attitude towards CALL. Moreover, the listening skills of the students had the most substantial effect on students learning English through CALL. Unexpectedly, the teaching staff, equipment, curriculum, or even a student's poor English background was a distinct barrier that attributed to any weaknesses of using CALL, or in other words, all these factors were of a similar attitude.

Keywords: CALL, teaching aids, teaching technology, teaching English with technology, teaching English in Saudi Arabia

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Authors: Maryam Ehsanpou, Majid Afkhami, Flora Mohammadizadeh, Amirhoushang Bahri, Rastin Afkhami

Abstract:

Within the frame of a biodiversity and bioactivity study of marine macro organisms from the Persian Gulf, three hard coral species extracts were investigated for cytotoxic, antibacterial and antifungal activities against five human pathogenic microorganisms. All concentrations of extracts from three hard corals showed no antifungal activity towards the tested strains. In antibacterial assays, the hard coral extracts showed significant activity solely against Staphylococcus aureus with MICs ranging from 3 to 9 μg/ml. The highest antibacterial activity was found in the aqueous methanol extract of Porites compressa with an inhibition zone of 22 mm against Staphylococcus aureus at 18 μg/ml extract concentration. Methanol extracts from Porites harrisoi and Porites compressa exhibited only weak cytotoxic activities. It is important for future research to concentrate on finding the mechanisms employed by corals to defend themselves against invasion, the mechanism of infections and the type of chemical compounds in coral extracts that inhibit antibacterial growth or proliferation in underexplored areas such as the Persian Gulf.

Keywords: antibacterial, antifungal, cytotoxic, hard corals, Persian Gulf

Procedia PDF Downloads 471