Search results for: activity learning

Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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Recently tourism is a major foreign exchange earner in the World. In this paper, we propose the mathematical model to study the impact of tourists on the spread of HIV incidences using compartmental differential equation models. Simulation studies of reproduction number are used to demonstrate new insights on the spread of HIV disease. The periodogram analysis of a time series was used to determine the speed at which the disease is spread. The results indicate that with the persistent flow of tourism into a country, the disease status has increased the epidemic rate. The result suggests that the government must put more control on illegal prostitution, unprotected sexual activity as well as to emphasis on prevention policies that include the safe sexual activity through the campaign by the tourism board.

Keywords: HIV/AIDS, mathematical transmission modeling, tourists, stability, simulation

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Authors: Nilgun Karatas, Bihter Sakin

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In this study, the relationships between the use of language learning strategies and English language exit exam success were investigated in the university EFL learners’ context. The study was conducted at Fatih University Prep School. To collect data 3 classes from the A1 module in English language classes completed a questionnaire known as the English Language Learning Strategy Inventory or ELLSI. The data for the present study were collected from the preparatory class students who are studying English as a second language at the School of Foreign Languages. The students were placed into four different levels of English, namely A1, A2, B1, and B2 level of English competency according to European Union Language Proficiency Standard, by means of their English placement test results. The Placement test was conveyed at the beginning of the spring semester in 2014-2015.The ELLSI consists of 30 strategy items which students are asked to rate from 1 (low frequency) to 5 (high frequency) according to how often they use them. The questionnaire and exit exam results were entered onto SPSS and analyzed for mean frequencies and statistical differences. Spearman and Pearson correlation were used in a detailed way. There were no statistically significant results between the frequency of strategy use and exit exam results. However, most questions correlate at a significant level with some of the questions.

Keywords: individual differences, language learning strategies, Fatih University, English language

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Authors: Shamie Kumar

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Background: Radiologists and radiographers (RR) need to educate themselves and their colleagues to ensure that AI is integrated safely, useful, and in a meaningful way with the direction it always benefits the patients. AI education and training are fundamental to the way RR work and interact with it, such that they feel confident using it as part of their clinical practice in a way they understand it. Methodology: This exploratory research will outline the current educational and training gaps for radiographers and radiologists in AI radiology diagnostics. It will review the status, skills, challenges of educating and teaching. Understanding the use of artificial intelligence within daily clinical practice, why it is fundamental, and justification on why learning about AI is essential for wider adoption. Results: The current knowledge among RR is very sparse, country dependent, and with radiologists being the majority of the end-users for AI, their targeted training and learning AI opportunities surpass the ones available to radiographers. There are many papers that suggest there is a lack of knowledge, understanding, and training of AI in radiology amongst RR, and because of this, they are unable to comprehend exactly how AI works, integrates, benefits of using it, and its limitations. There is an indication they wish to receive specific training; however, both professions need to actively engage in learning about it and develop the skills that enable them to effectively use it. There is expected variability amongst the profession on their degree of commitment to AI as most don’t understand its value; this only adds to the need to train and educate RR. Currently, there is little AI teaching in either undergraduate or postgraduate study programs, and it is not readily available. In addition to this, there are other training programs, courses, workshops, and seminars available; most of these are short and one session rather than a continuation of learning which cover a basic understanding of AI and peripheral topics such as ethics, legal, and potential of AI. There appears to be an obvious gap between the content of what the training program offers and what the RR needs and wants to learn. Due to this, there is a risk of ineffective learning outcomes and attendees feeling a lack of clarity and depth of understanding of the practicality of using AI in a clinical environment. Conclusion: Education, training, and courses need to have defined learning outcomes with relevant concepts, ensuring theory and practice are taught as a continuation of the learning process based on use cases specific to a clinical working environment. Undergraduate and postgraduate courses should be developed robustly, ensuring the delivery of it is with expertise within that field; in addition, training and other programs should be delivered as a way of continued professional development and aligned with accredited institutions for a degree of quality assurance.

Keywords: artificial intelligence, training, radiology, education, learning

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Authors: Amal Saafan, Kareem Al Sofy, Sameh AbdelGhani, Magdy Amin

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Background: Acinetobacter spp. resistance towards β-lactam antibiotics is mediated mainly by different classes of β-lactamases production; detection of some genes responsible for production of β-lactamases is the objective of the study. Methods: One hundred fifty bacterial isolates were recovered from blood, sputum, and urine specimens from different hospitals in Egypt. Sixty-nine isolate were identified as Acinetobacter baumannii using traditional biochemical tests, CHROM agar, MicroScan and PCR amplification of blaoxa-51like gene. Acinetobacterbaumannii isolates were grouped into carbapenem resistant group (GP1), cefotaxime, ceftazidime and cefoxitin resistant group (GP2) and carbapenem and cephalosporin non-resistant group (GP3). Carbapenemase activity was screened using modified Hodge test (MHT) for GP1.Metallo-β-lactamases screening was performed for MHT positive isolates using double disk synergy test (DDST) and combined disk test (CDT). Amp C activity was screened using Amp C disk test with Tris-EDTA, DDST, and CDT for GP2. Finally, PCR amplification of blaoxa-51like, blaoxa-23like, blaIMP-like, blaVIM-like, and blaADC-like genes was performed for isolates that showed, at least, two positive results of three for both AmpC and carbapenemases phenotypic screening tests (obvious activity), in addition to GP3 (for comparison). Detection of blaoxa-51like and blaADC-like genes preceded by ISAba1 was also performed. Results: Antibiogram of 69 pure Acinetobacter baumannii isolates resulted in 57, 64, and 2 isolates enrolled into GP1, GP2, and GP3, respectively. Carbapenemase activity was shown by 49(85.9%) isolate using MHT. Metallo-β-lactamases screening revealed 32(65.3%) and 35(71.4%) using DDST and CDT, respectively.AmpC activity was shown by 43(67.2%) and 50 (78.1%) isolates using AmpC disk test with Tris-EDTA, and both DDST and CDT, respectively. Twenty-seven isolates showed obvious activity, all of them (100%) were harboring blaoxa-51like and blaADC-like genes, while blaoxa-23like, blaIMP-like andblaVIM-like genes were harbored by 23(85.2%), 9 (33.%) and no isolate respectively. Only 12 (44.4%) isolates harbored blaoxa-51like and blaADC-like genes preceded by ISAba1. GP3 isolates showed only positive blaoxa-51like and blaADC-like genes. Conclusion: It is not possible to correlate resistance with presence of blaoxa-51like and blaADC-like genes and presence of ISAba1 was immediate as transcriptional promoter. A blaoxa-23like gene played an important role in carbapenem resistance when compared with blaIMP-like and blaVIM-like gene.

Keywords: acinetobacter, beta-lactams, resistance, antimicrobial agents

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Authors: Kyungae Jo, Eun Young Kim, Byungsoo Shin, Kwang Soon Shin, Hyung Joo Suh

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Gamma-aminobutyric acid (GABA) and 5-hydroxytryptophan (5-HTP) are amino acids of digested nutrients or food ingredients and these can possibly be utilized as non-pharmacologic treatment for sleep disorder. We previously investigated the GABA/5-HTP mixture is the principal concept of sleep-promoting and activity-repressing management in nervous system of D. melanogaster. Two experiments in this study were designed to evaluate sleep-promoting effect of GABA/5-HTP mixture, to clarify the possible ratio of sleep-promoting action in the Drosophila invertebrate model system. Behavioral assays were applied to investigate distance traveled, velocity, movement, mobility, turn angle, angular velocity and meander of two amino acids and GABA/5-HTP mixture with caffeine treated flies. In addition, differentially expressed gene (DEG) analyses from next generation sequencing (NGS) were applied to investigate the signaling pathway and functional interaction network of GABA/5-HTP mixture administration. GABA/5-HTP mixture resulted in significant differences between groups related to behavior (p < 0.01) and significantly induced locomotor activity in the awake model (p < 0.05). As a result of the sequencing, the molecular function of various genes has relationship with motor activity and biological regulation. These results showed that GABA/5-HTP mixture administration significantly involved the inhibition of motor behavior. In this regard, we successfully demonstrated that using a GABA/5-HTP mixture modulates locomotor activity to a greater extent than single administration of each amino acid, and that this modulation occurs via the neuronal system, neurotransmitter release cycle and transmission across chemical synapses.

Keywords: sleep, γ-aminobutyric acid, 5-hydroxytryptophan, Drosophila melanogaster

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: K. M. Seddik

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This paper explores the implementation of 5S elements in the Egyptian garment enterprises. The paper depended on a survey questionnaire (established from Summit Business Solutions, New York) and observations to collect data from the respondents. The observations are based on the on-site visits and interviews with the managers, supervisors and labors. The enterprises divided into three groups according to the nature activity. The first group of enterprises encompassed 49.52% of the total samples, the second and third group of enterprises represented 50.48% The results of this research indicated to the influence of the nature activity in implementing 5S systems and conclude that sustain is a difficult element which involve encourage workers for developing and practicing a highly discipline. In addition the results demonstrate that although the enterprises may achieve a higher executing of 5S elements but it may realize a low coherence in implementation.

Keywords: 5S elements, garment enterprises, implementation, lean manufacturing

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Authors: A. M. Isakhanyan, F. N. Tkhruni, N. N. Yakimovich, Z. I. Kuvaeva, T. V. Khachatryan

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Introduction: At present, the simbiotics based on different genera and species of lactic acid bacteria (LAB) and yeasts are used. One of the basic properties of probiotics is presence of antimicrobial activity and therefore selection of LAB and yeast strains for their co-cultivation with the aim of increasing of the activity is topical. Since probiotic yeast and bacteria have different mechanisms of action, natural synergies between species, higher viability and increasing of antimicrobial activity might be expected from mixing both types of probiotics. Endemic strains of LAB Enterococcus faecium БТK-64, Lactobaccilus plantarum БТK-66, Pediococcus pentosus БТK-28, Lactobacillus rhamnosus БТK-109 and Kluyveromyces lactis БТX-412, Saccharomycopsis sp. БТX- 151 strains of yeast, with probiotic properties and hight antimicrobial activity, were selected. Strains are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB and yeast strains were isolated from different dairy products from rural households of Armenia. The genotyping by 16S rRNA sequencing for LAB and 26S RNA sequencing for yeast were used. Combined cultivation of LAB and yeast strains was carried out in the nutrient media on the basis of milk whey, in anaerobic conditions (without shaker, in a thermostat at 37oC, 48 hours). The complex preparations were obtained by purification of cell free culture broth (CFC) broth by the combination of ion-exchange chromatography and gel filtration methods. The spot-on-lawn method was applied for determination of antimicrobial activity and expressed in arbitrary units (AU/ml). Results. The obtained data showed that at the combined growth of bacteria and yeasts, the cultivation conditions (medium composition, time of growth, genera of LAB and yeasts) affected the display of antimicrobial activity. Purification of CFC broth allowed obtaining partially purified antimicrobial complex preparation which contains metabiotics from both bacteria and yeast. The complex preparation inhibited the growth of pathogenic and conditionally pathogenic bacteria, isolated from various internal organs from diseased animals and poultry with greater efficiency than the preparations derived individually alone from yeast and LAB strains. Discussion. Thus, our data shown perspectives of creation of a new class of antimicrobial preparations on the basis of combined cultivation of endemic strains of LAB and yeast. Obtained results suggest the prospect of use of the partially purified complex preparations instead antibiotics in the agriculture and for food safety. Acknowledgments: This work was supported by the RA MES State Committee of Science and Belarus National Foundation for Basic Research in the frames of the joint Armenian - Belarusian joint research project 13РБ-064.

Keywords: co-cultivation, antimicrobial activity, biosafety, metabiotics, lactic acid bacteria, yeast

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Authors: Yasser Gaber, Mohamed Ismail, Serena Bisagni, Mohamad Takwa, Rajni Hatti-Kaul

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Enzymes are safe and selective catalysts. They skillfully catalyze chemical reactions; however, the native form is not usually suitable for industrial applications. Enzymes are therefore engineered by several techniques to meet the required catalytic task. Clopidogrel is recorded among the five best selling pharmaceutical in 2010 under the brand name Plavix. The commonly used route for production of the drug on an industrial scale is the synthesis of the racemic mixture followed by diastereomeric resolution to obtain the pure S isomer. The process consumes a lot of solvents and chemicals. We have evaluated a biocatalytic cleaner approach for asymmetric hydrolysis of racemic clopidogrel. Initial screening of a selected number of hydrolases showed only one enzyme EST to exhibit activity and selectivity towards the desired stereoisomer. As the crude EST is a mixture of several isoenzymes, a homology model of EST-1 was used in molecular dynamic simulations to study the interaction of the enzyme with R and S isomers of clopidogrel. Analysis of the geometric hindrances of the tetrahedral intermediates revealed a potential site for mutagenesis in order to improve the activity and the selectivity. Single point mutation showed dramatic increase in activity and inversion of the enantioselectivity (400 fold change in E value).

Keywords: biocatalysis, biotechnology, enzyme, protein engineering, molecular modeling

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Authors: Armenia Nazar, Sally M. J. Anggelya, Rose Dinda

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Hypertension prevalence in Indonesian has increased from time to time since 2013, especially in women. This cross-sectional analysis study was made to observe the incidence of hypertension on the reproductive women (20-49 years old) with several risk factors who use contraceptive pills. Data was collected from June - October 2016 in the Andalas Public Health Center, East Padang District, Indonesia. An amount of 167 respondents who were taken using consecutive sampling technique were participate in this study. Data of social demography, contraceptive used, duration of use, hypertension risk factors (age, family history, central obesity, body mass index, physical activity, and stress) were collected and analyzed statistically using Chi-Square analysis. Significant was taken at p < 0.05. Results showed that the woman with contraceptive pill was tent to get hypertension (OR = 3,90 and p < 0,001). In addition, woman with a family history OR of 6,77 (p = 0,09), mild physical activity OR of 3,67 (p = 0,33), moderate physical activity OR of 3,33 (p = 0,16), and stressed OR of 5.11 (p = 0.18). These indicated that the contraceptive pill user is 3.9 times more risk to develop hypertension than non-users, especially one with a family history of hypertension. Other risk factors were not associated with hypertension risk in these sex productive women.

Keywords: hypertension, oral contraceptive, sex productive woman, risk factors

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Authors: Mukesh Saran, Ashima Bagaria

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Green nanotechnology is the most researched field in the current scenario. Herein we study the synthesis of Zinc and Ferrous nanoparticles using Moringa oleifera leaf extracts. Our protocol using established protocols heat treatment of plant extracts along with the solution of copper sulphate in the ratio of 1:1. The leaf extracts of Moringa oleifera were prepared in deionized water. Copper sulfate solution (1mM) was added to this, and the change in color of the solution was observed indicating the formation of Cu nanoparticles. The as biosynthesized Cu nanoparticles were characterized with the help of Scanning Electron Microscopy (SEM), and Fourier Transforms Infrared Spectroscopy (FTIR). It was observed that the leaf extracts of Moringa oleifera can reduce copper ions into copper nanoparticles within 8 to 10 min of reaction time. The method thus can be used for rapid and eco-friendly biosynthesis of stable copper nanoparticles. Further, we checked their antimicrobial and antioxidant potential, and it was observed that maximum antioxidant activity was observed for the particles prepared using the heating method. The maximum antibacterial activity was observed in Streptomyces grisveus particles and in Triochoderma Reesei for the maximum antifungal activity. At present, we are engaged in studying the anti-inflammatory activities of these as prepared nanoparticles.

Keywords: green synthesis, antibacterial, antioxidant, antifungal, anti-inflammatory

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Authors: Xi Liu, Fan Yuan

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In the evolving landscape of physics-based machine learning (PBML), particularly within fluid dynamics and its applications in electromechanical engineering, robot vision, and robot learning, achieving precision and alignment with researchers' specific needs presents a formidable challenge. In response, this work proposes a methodology that integrates neural transformation with a modified smoothed particle hydrodynamics model for generating transformed 3D fluid simulations. This approach is useful for nanoscale science, where the unique and complex behaviors of viscoelastic medium demand accurate neurally-transformed simulations for materials understanding and manipulation. In electromechanical engineering, the method enhances the design and functionality of fluid-operated systems, particularly microfluidic devices, contributing to advancements in nanomaterial design, drug delivery systems, and more. The proposed approach also aligns with the principles of PBML, offering advantages such as multi-fluid stylization and consistent particle attribute transfer. This capability is valuable in various fields where the interaction of multiple fluid components is significant. Moreover, the application of neurally-transformed hydrodynamical models extends to manufacturing processes, such as the production of microelectromechanical systems, enhancing efficiency and cost-effectiveness. The system's ability to perform neural transfer on 3D fluid scenes using a deep learning algorithm alongside physical models further adds a layer of flexibility, allowing researchers to tailor simulations to specific needs across scientific and engineering disciplines.

Keywords: physics-based machine learning, robot vision, robot learning, hydrodynamics

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Authors: Patel Parul, Harsh Ganvit

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The construction industry is the second highest industry after agriculture provides employment in India. In developing countries like India, many construction projects are coming up to meet the demand. On the one hand, construction projects are increasing; on the other hand still, construction companies are struggling with many problems. One of the major problems is to ensure safe working conditions at the construction site. Due to a lack of safety awareness and ignorance of safety aspects, many fatal accidents are very common at the construction site in India. One of the key success factors for construction projects is “Accident-Free Construction Projects”. The construction projects can be divided into various categories like Infrastructure projects, industrial construction and real estate construction. Real estate projects are mainly comprised of commercial and residential projects. In the construction industry, private sectors play a huge role in urban and rural development and also contribute significantly to the growth of the nation. Infrastructure and Industrial projects are mainly executed by well-qualified construction contractors. For such projects, ensuring safety at construction projects is inevitable and probably one of the major clauses of contract documents as well. These projects are monitored from time to time by national agencies and researchers, too. However, Real estate projects are rarely monitored for safety aspects. No systematic contract system is followed for these projects. Safety is the most neglected aspect of these projects. In the current research projects, an attempt is made to carry out safety auditing for about 75 real estate projects. The objective of this work is to collect the activity-based safety survey of real estate projects in western India. The analysis of activity-based safety implementation for real estate projects is discussed in the present work. The activities are divided into three categories based on the data collected. The findings of this work will help local monitoring authorities to implement a safety management plan for real estate projects.

Keywords: construction safety, safety assessment, activity-based safety, real estate projects

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Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Mary-Luz Olivares-Tenorio, Ruud Verkerk, Matthijs Dekker, Martinus A. J. S. van Boekel

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Cape gooseberry, the fruit of the plant Physalis peruviana L. has gained interest in research given its contents of promising health-promoting compounds like contents. The presence of carotenoids, ascorbic acid, minerals, polyphenols, vitamins and antioxidants. This project aims to study thermal stability of β-carotene, ascorbic acid, catechin and epicatechin and antioxidant activity in the matrix of the Cape Gooseberry. Fruits were obtained from a Colombian field in Cundinamarca. Ripeness stage was 4 (According to NTC 4580, corresponding to mature stage) at the moment of the experiment. The fruits have been subjected to temperatures of 40, 60, 80, 100 and 120°C for several times. β-Carotene, ascorbic acid, catechin and epicatechin content were assessed with HPLC and antioxidant activity with the DPPH method. β-Carotene was stable upon 100°C, and showed some degradation at 120°C. The same behavior was observed for epicatechin. Catechin increased during treatment at 40°C, at 60°C it remained stable and it showed degradation at 80°C, 100°C and 120°C that could be described by a second order kinetic model. Ascorbic acid was the most heat-sensitive of the analyzed compounds. It showed degradation at all studied temperatures, and could be described by a first order model. The activation energy for ascorbic acid degradation in cape gooseberry was 46.0 kJ/mol and its degradation rate coefficient at 100 °C was 6.53 x 10-3 s-1. The antioxidant activity declined for all studied temperatures. Results from this study showed that cape gooseberry is an important source of different health-promoting compounds and some of them are stable to heat. That makes this fruit a suitable raw material for processed products such as jam, juices and dehydrated fruit, giving the consumer a good intake of these compounds.

Keywords: goldenberry, health-promoting compounds, phytochemical, processing, heat treatment

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Authors: Zahra Alikhani Koopaei

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In the fifth lesson of the third-grade mathematics book, students are introduced to the concept of multiplication. However, some students showed a lack of interest in learning this topic. To address this, a simple electronic multiplication table was designed with the aim of making the concept of multiplication entertaining and engaging for students. It provides them with moments of excitement during the learning process. To achieve this goal, a device was created that produced a bell sound when two wire ends were connected. Each wire end was connected to a specific number in the multiplication table, and the other end was linked to the corresponding answer. Consequently, if the answer is correct, the bell will ring. This study employs interactive and engaging methods to teach mathematics, particularly to students who have previously shown little interest in the subject. By integrating game-based learning and critical thinking, we observed an increase in understanding and interest in learning multiplication compared to before using this method. This further motivated the students. As a result, the intelligent multiplication table was successfully designed. Students, under the instructor's supervision, could easily construct the device during the lesson. Through the implementation of these operations, the concept of multiplication was firmly established in the students' minds. Engaging multiple intelligences in each student enhances a more stable and improved understanding of the concept of multiplication.

Keywords: intelligent multiplication table, design, construction, education, increased interest, students

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Authors: Lyndsee Baumann-Birkbeck, Sohil A. Khan, Shailendra Anoopkumar-Dukie, Gary D. Grant

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Technology-enhanced education tools are being rapidly integrated into health programs globally. These tools provide an interactive platform for students and can be used to deliver topics in various modes including games and simulations. Simulations are of particular interest to healthcare education, where they are employed to enhance clinical knowledge and help to bridge the gap between theory and practice. Simulations will often assess competencies for practical tasks, yet limited research examines the effects of simulation on student perceptions of their learning. The aim of this study was to determine the effects of an interactive virtual patient simulation for pharmacology education and clinical practice on student knowledge, skills and confidence. Ethics approval for the study was obtained from Griffith University Research Ethics Committee (PHM/11/14/HREC). The simulation was intended to replicate the pharmacy environment and patient interaction. The content was designed to enhance knowledge of proton-pump inhibitor pharmacology, role in therapeutics and safe supply to patients. The tool was deployed into a third-year clinical pharmacology and therapeutics course. A number of core practice areas were examined including the competency domains of questioning, counselling, referral and product provision. Baseline measures of student self-reported knowledge, skills and confidence were taken prior to the simulation using a specifically designed questionnaire. A more extensive questionnaire was deployed following the virtual patient simulation, which also included measures of student engagement with the activity. A quiz assessing student factual and conceptual knowledge of proton-pump inhibitor pharmacology and related counselling information was also included in both questionnaires. Sixty-one students (response rate >95%) from two cohorts (2014 and 2015) participated in the study. Chi-square analyses were performed and data analysed using Fishers exact test. Results demonstrate that student knowledge, skills and confidence within the competency domains of questioning, counselling, referral and product provision, show improvement following the implementation of the virtual patient simulation. Statistically significant (p<0.05) improvement occurred in ten of the possible twelve self-reported measurement areas. Greatest magnitude of improvement occurred in the area of counselling (student confidence p<0.0001). Student confidence in all domains (questioning, counselling, referral and product provision) showed a marked increase. Student performance in the quiz also improved, demonstrating a 10% improvement overall for pharmacology knowledge and clinical practice following the simulation. Overall, 85% of students reported the simulation to be engaging and 93% of students felt the virtual patient simulation enhanced learning. The data suggests that the interactive virtual patient simulation developed for clinical pharmacology and therapeutics education enhanced students knowledge, skill and confidence, with respect to the competency domains of questioning, counselling, referral and product provision. These self-reported measures appear to translate to learning outcomes, as demonstrated by the improved student performance in the quiz assessment item. Future research of education using virtual simulation should seek to incorporate modern quantitative measures of student learning and engagement, such as eye tracking.

Keywords: clinical simulation, education, pharmacology, simulation, virtual learning

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Authors: Laura Vitola, Diana Bajare, Genadijs Sahmenko, Girts Bumanis

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About 8 % of CO2 emission in the world is produced by concrete industry therefore replacement of cement in concrete composition by additives with pozzolanic activity would give a significant impact on the environment. Material which contains silica SiO2 or amorphous silica SiO2 together with aluminum dioxide Al2O3 is called pozzolana type additives in the concrete industry. Pozzolana additives are possible to obtain from recycling industry and different production by-products such as processed bulb boric silicate (DRL type) and lead (LB type) glass, coal combustion bottom ash, utilized brick pieces and biomass ash, thus solving utilization problem which is so important in the world, as well as practically using materials which previously were considered as unusable. In the literature, there is no summarized method which could be used for quick waste-product pozzolana activity evaluation without the performance of wide researches related to the production of innumerable concrete contents and samples in the literature. Besides it is important to understand which parameters should be predicted to characterize the efficiency of waste-products. Simple methods of pozzolana activity increase for different types of waste-products are also determined. The aim of this study is to evaluate effectiveness of the different types of waste materials and industrial by-products (coal combustion bottom ash, biomass ash, waste glass, waste kaolin and calcined illite clays), and determine which parameters have the greatest impact on pozzolanic activity. By using materials, which previously were considered as unusable and landfilled, in concrete industry basic utilization problems will be partially solved. The optimal methods for treatment of waste materials and industrial by–products were detected with the purpose to increase their pozzolanic activity and produce substitutes for cement in the concrete industry. Usage of mentioned pozzolanic allows us to replace of necessary cement amount till 20% without reducing the compressive strength of concrete.

Keywords: cement substitutes, micro and nano fillers, pozzolanic properties, specific surface area, particle size, waste products

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Authors: J. Mano Ranjini

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Each and every child is special, born with a unique talent to explore this world. The word Dyslexia is derived from the Greek language in which “dys” meaning poor or inadequate and “lexis” meaning words or language. Dyslexia describes about a different kind of mind, which is often gifted and productive, that learns the concept differently. The main aim of the study is to bring the positive outcome of the reading level by examining the effectiveness of Visual Auditory Kinesthetic Tactile technique on Reading Level among Dyslexic Children at Helikx Open School and Learning Centre. A Quasi experimental one group pretest post test design was adopted for this study. The Reading Level was assessed by using the Schonell Graded Word Reading Test. Thirty subjects were drawn by using purposive sampling technique and the intervention Visual Auditory Kinesthetic Tactile technique was implemented to the Dyslexic Children for 30 consecutive days followed by the post Reading Level assessment revealed the improvement in the mean score value of reading level by 12%. Multi-sensory (VAKT) teaching uses all learning pathways in the brain (visual, auditory, kinesthetic-tactile) in order to enhance memory and learning and the ability in uplifting emotional, physical and societal dimensions. VAKT is an effective method to improve the reading skill of the Dyslexic Children that ensures the enormous significance of learning thereby influencing the wholesome of the child’s life.

Keywords: visual auditory kinesthetic tactile technique, reading level, dyslexic children, Helikx Open School

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Authors: Yahia Massinissa, Henhouda Affaf, Yahia Mouloud

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The aim of this study was to investigate the toxicity; analgesic and anti-pyretic properties of standardized HA methanolic extract (HAMeOH) in vivo. The acute toxicity study was performed on rats while adopting the OECD-420 Guidelines (fixed dose procedure). Assessment of analgesic activity was performed in rats with two analgesic models. One was acetic acid induced writhing response and the other formalin-induced paw licking. The anti-pyretic effect was tested by brewer’s yeast induced fever in rats. For the acute toxicity test, the higher dose administration of 2000 mg/kg bw. of Hyoscyamus albus did not produce any toxic signs or deaths in rats. There were no significant differences (p>0.05) in the body and organ weights between control and treated groups. The (LD50) of Hyoscyamus albus was higher than 2000 g/kg bw. In subacute toxicity study, no mortality and toxic signs were observed with the doses of 100 and 200 mg/kg bw. of extracts of for 28 consecutive days. These analgesic experimental results indicated that HAMeOH (100 mg/kg and 200 mg/kg) decreased the acetic acid-induced writhing responses and HAMeOH (100 mg/kg and 200 mg/kg) decreased the licking time in the second phase of the formalin test. Moreover, in the model of yeast induced elevation of the body temperature HAMeOH showed dose-dependent lowering of the body temperature up to 3h at both the doses these results obtained, were comparable to that of paracetamol. The present findings indicate that the leaves of Hyoscyamus albus L. possess potent analgesic and antipyretic activity.

Keywords: Hyoscyamus albus, methanolic extract, toxicity, analgesic activity, antipyretic activity, formalin test

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Authors: A. Alshabeb

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Vocabulary is one of the elements that links the four skills of reading, writing, speaking, and listening and is very critical in learning a foreign language. This study aims to determine how Saudi Arabian EFL students learn English vocabulary via Twitter. The study adopts a mixed sequential research design in collecting and analysing data. The results of the study provide several recommendations for vocabulary learning. Moreover, the study can help teachers to consider the possibilities of using Twitter further, and perhaps to develop new approaches to vocabulary teaching and to support students in their use of social media.

Keywords: social media, twitter, vocabulary, web 2

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Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

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The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Amanda Sheard, Garry Lee, Katherine Stockham

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Introduction: Health benefits associated with wine consumption have been well documented; these include anticancer, anti-inflammatory, and cardiovascular protection. The majority of these health benefits have been linked to polyphenols found within wine and grapes. Once consumed polyphenols exhibit free radical quenching capabilities. Environmental factors such as rainfall, temperature, CO2 levels and sunlight exposure have been shown to affect the polyphenol content of grapes. The objective of this work was to evaluate the effect of growing conditions on the antioxidant capacity of grapes obtained from a single plot vineyard in Perth. This was achieved through the analysis of samples using; oxygen radical antioxidant capacity (ORAC), cellular antioxidant activity (CAA) in human red blood cells, ICP-MS and ICP-OES, total polyphenols (PP’s), and total flavonoid’s (FLa). The data obtained was compared to observed climate data. The 14 Selected Vitis Vinefera L. cultivars included Cabernet franc, Cabernet Sauvignon, Carnelian, Chardonnay, Grenache, Melbec, Merlot, Orange muscat, Rousanne, Sauvignon Blanc, Shiraz, Tempernillo, Verdelho, and Voignier. Results: Notable variation’s between cultivars included results ranging from 125 mg/100 g-350 mg/100 g for PP’s, 93 mg/100 g–300 mg/100 g for FLa, 13 mM T.E/kg–33 mM T.E/kg for ORAC and 0.3 mM Q.E/kg–27 mM Q.E/kg CAA were found between red and white grape cultivars. No correlation was found between CAA and the ORAC obtained in this study; except that white cultivars were consistently lower than red. ICP analysis showed that seeds contained the highest concentration of copper followed by skins and flesh of the grape. A positive correlation between copper and ORAC was found. The ORAC, PP’s, and FLa in red grapes were consistently higher than white grape cultivars; these findings were supported by literature values. Significance: The cellular antioxidant activities of white and red wine cultivars were used to compare the bioactivity of these grapes against the chemical ORAC measurement. The common method of antioxidant activity measurement is the chemical value from ORAC analysis; however this may not reflect the activity within the human body. Hence, the measurements were also carried out using the cellular antioxidant activity to perform a comparison. Additionally, the study explored the influence of weather systems such as El Niño and La Niña on the polyphenol content of Australian wine cultivars grown in Perth.

Keywords: oxygen radical antioxidant activity, cellular antioxidant activity, total polyphenols, total flavonoids, wine grapes, climate

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Authors: Walter M. Millanzi, Stephen M. Kibusi

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Background: Currently, there has been a progressive shortage not only to the number but also the quality of medical practitioners for the most of nursing. Despite that, those who are present exhibit unethical and illegal practices, under standard care and malpractices. The concern is raised in the ways they are prepared, or there might be something missing in nursing curricula or how it is delivered. There is a need for transforming or testing new teaching modalities to enhance competent health workforces. Objective: to investigate the Effect of Facilitation in a Problem-based Environment (FPBE) on metacognition, self-directed learning and learning motivation to undergraduate nurse student in Tanzanian higher learning institutions. Methods: quasi-experimental study (quantitative research approach). A purposive sampling technique was employed to select institutions and achieving a sample size of 401 participants (interventional = 134 and control = 267). Self-administered semi-structured questionnaire; was the main data collection methods and the Statistical Package for Service Solution (v. 20) software program was used for data entry, data analysis, and presentations. Results: The pre-post test results between groups indicated noticeably significant change on metacognition in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05). SDL in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05. Motivation to learn in an intervention (M = 62.67, SD = 14.14) and the control (n = 267, M = 57.75), t (399) = 2.907, p < 0.01). A FPBE teaching pedagogy, was observed to be effective on the metacognition (AOR = 1.603, p < 0.05), SDL (OR = 1.729, p < 0.05) and Intrinsic motivation in learning (AOR = 1.720, p < 0.05) against conventional teaching pedagogy. Needless, was less likely to enhance Extrinsic motivation (AOR = 0.676, p > 0.05) and Amotivation (AOR = 0.538, p > 0.05). Conclusion and recommendation: FPBE teaching pedagogy, can improve student’s metacognition, self-directed learning and intrinsic motivation to learn among nurse students. Nursing curricula developers should incorporate it to produce 21st century competent and qualified nurses.

Keywords: facilitation, metacognition, motivation, self-directed

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Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

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Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Kuek Teik Sheng, Leaw Zee Guan, Lim Wah Kien, Ting Tin Tin

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Educational technology such as YouTube and Kahoot have arisen as an alternative to effective learning among higher education institutions. There are many researches done in carrying out experiments to test different educational technologies and received positive feedback from students. Yet, similar study is hardly found in Malaysia especially study that includes the latest educational technologies. As a developing country, it is crucial to ensure that these emerging technologies are assisting students in learning process before it is widely adopted in institutions. This paper conducted a study to explore the perception of higher education institution students on the current educational technologies in Malaysia which include online educational games, online videos/course, social media, presentation tools and resource management tool. Some of these technologies have not been looked into its potential in effective learning process. An online survey using questionnaire is conducted among a target of 300 university/college. In the survey, the result shows that majority of the target students in Malaysia agree that the current educational technologies help them in learning, understanding and manage their studies. It is necessary to discover students’ perceptions on the educational technologies in order to provide guidelines for the educators/institutions in selecting appropriate technology to conduct the lecture/tutorial efficiently and effectively.

Keywords: education, educational technology, Facebook, PowerPoint, YouTube

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Authors: Sanjay Singh, Swati Jaiswal, Prashant Mishra

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Nanoparticle based formulations of drug delivery systems have shown their potential in improving the performance of existing drugs and have opened avenues for new therapies. Calendula extract is a low cost, wide spectrum bioactive material that has been used for a long term therapy of various infections. Aim: The aim of this study was to develop Calendula officinalis extract based nanoformulations and to study the antibacterial activity of either Calendula extract loaded chitosan nanoparticles or Calendula extract coated silver nanoparticles for increased bioavailability and their long term effect. Methods: Chitosan nanoparticles were prepared by the process of ionotropic gelation, based on interaction between the negative groups of tri polyphosphate (TPP) and positively charged amino groups of chitosan. The size of the Calendula extract-loaded chitosan particles was determined using dynamic light scattering and scanning electron microscopy. Antibacterial activities of these formulations were determined based on minimum inhibitory concentration and time kill studies. In addition, silver nanoparticles were also synthesized in the presence of Calendula extract and characterized by UV visible spectrum, DLS and XRD. Experiments were conducted on 96-plates against two Gram-positive bacteria; Staphylococcus aureus and Bacillus subtilis two Gram-negative bacteria; Escherichia coli and Pseudomonas aeruginosa. Results: Results demonstrated time dependent antibacterial activity against different microbes studied. Both Calendula extract and Calendula extract loaded chitosan nanoparticles have shown good antimicrobial activity against both Gram positive and Gram negative bacteria. Conclusion: Calendula extract loaded chitosan nanoparticles and calendula extract coated silver nanoparticles are potential antibacterial for their long term antibacterial effects.

Keywords: antibacterial, Calendula extract, chitosan nanoparticles, silver nanoparticles

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Authors: Ahilya Singh, Brad Carte, Ramesh Subramani, William Aalbersberg

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A total of 37 actinomycete strains were purified from 25 Solomon Islands marine sediments using four different types of isolation media. Among them, 54% of the strains had obligate requirement of seawater for growth. The ethyl acetate extract of 100 ml fermentation product of each strain was screened for antimicrobial activity against multidrug resistant human pathogens and cytotoxic activity against brine shrimps. A total of 67% of the ethyl acetate extracts showed antimicrobial and/or cytotoxic activities. A strain F-1915 was selected for isolation and evaluation of bioactive compound(s) based on its bioactive properties and chemical profile analysis using the LC-MS. The strain F-1915 was identified to have 96% sequence similarity to Streptomyces violaceusniger on the basis of 16S rDNA sequences using BLAST analysis. The 16S rDNA revealed that the strain F-1915 is a new member of MAR4 clade of actinomycetes. The MAR4 clade is an interesting clade of actinomycetes known for the production of pharmaceutically important hybrid isoprenoid compounds. The ethyl acetate extract of the fermentation product of this strain was purified by silica gel column chromatography and afforded the isolation of one bioactive pure compound. Based on the 1D and 2D NMR spectral data of compound 1 it was identified as a new mono-brominated phenazinone, Marinophenazimycin A, a structure which has already been studied by external collaborators at Scripps Institution of Oceanography but is yet to be published. Compound 1 displayed significant antimicrobial activity against drug resistant human pathogens. The minimum inhibitory concentration (MIC) of compound 1 was against Methicillin Resistant Staphylococcus aureus (MRSA) was about 1.9 μg/ml and MIC recorded against Amphotericin Resistant Candida albicans (ARCA) was about 0.24 μg/ml. The bioactivity of compound 1 against ARCA was found to be better than the standard antifungal agent amphotericin B. Compound 1 however did not show any cytotoxic activity against brine shrimps.

Keywords: actinomycetes, antimicrobial activity, brominated phenazine, MAR4 clade, marine natural products, multidrug resistent, 1D and 2D NMR

Procedia PDF Downloads 318