Search results for: step potential

Authors: Graciela Soares Marcelli, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Claudineia Brazil, Rafael Haag

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The sun is a source of renewable energy, and its use as both a source of heat and light is one of the most promising energy alternatives for the future. To measure the thermal or photovoltaic systems a solar irradiation database is necessary. Brazil still has a reduced number of meteorological stations that provide frequency tests, as an alternative to the radio data platform, with reanalysis systems, quite significant. ERA-Interim is a global fire reanalysis by the European Center for Medium-Range Weather Forecasts (ECMWF). The data assimilation system used for the production of ERA-Interim is based on a 2006 version of the IFS (Cy31r2). The system includes a 4-dimensional variable analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the dataset is approximately 80 km at 60 vertical levels from the surface to 0.1 hPa. This work aims to make a comparative analysis between the ERA-Interim data and the data observed in the Solarimmetric Atlas of the State of Rio Grande do Sul, to verify its applicability in the absence of an observed data network. The analysis of the results obtained for a study region as an alternative to the energy potential of a given region.

Keywords: energy potential, reanalyses, renewable energy, solar radiation

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Neelma Ashraf

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Actinomycetes, particularly genus Streptomyces is of great importance due to their role in the discovery of new natural products, particularly antimicrobial secondary metabolites in the medicinal science and biotechnology industry. Different Streptomyces strains were isolated from Helianthus annuus plants and tested for antibacterial and antifungal activities. The most promising five strains were chosen for further investigation, and growth conditions for antibiotic synthesis were optimised. The supernatants were extracted in different solvents, and the extracted products were analyzed using liquid chromatography-mass spectrometry (LC-MS) and biological testing. From one of the potent strains Streptomyces globusus sp. BR123, a compound lavendamycin was identified using these analytical techniques. In addition, this potent strain also produces a strong antifungal polyene compound with a quasimolecular ion of 2072. Streptomyces sp. BR123 was genome sequenced because of its promising antimicrobial potential in order to identify the gene cluster responsible for analyzed compound “lavendamycin”. The genome analysis yielded candidate genes responsible for the production of this potent compound. The genome sequence of 8.15 Mb of Streptomyces sp. isolate BR123 with a GC content of 72.63% and 8103 protein coding genes was attained. Many antimicrobial, antiparasitic, and anticancerous compounds were detected through multiple biosynthetic gene clusters predicted by in-Silico analysis. Though, the novelty of metabolites was determined through the insignificant resemblance with known biosynthetic gene clusters. The current study gives insight into the bioactive potential of Streptomyces sp. isolate BR123 with respect to the synthesis of bioactive secondary metabolites through genomic and spectrometric analysis. Moreover, the comparative genome study revealed the connection of isolate BR123 with other Streptomyces strains, which could expand the knowledge of this genus and the mechanism involved in the discovery of new antimicrobial metabolites.

Keywords: streptomyces, secondary metabolites, genome, biosynthetic gene clusters, high performance liquid chromatography, mass spectrometry

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Authors: Michael Graz, Natasha Hurril, Andrew Shearer

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Research on feed supplementation with natural compounds is currently being intensively pursued with a view to improving energy utilisation in ruminants and mitigating the production of methane by these animals. Towards this end, a novel combination of extracts from garlic and bitter orange was therefore selected for trials on the basis of their previously published in vitro anti-methanogenic potential. Three separate in vitro experiments were conducted to determine energy utilisation and greenhouse gas production. These included use of rumen fluid from fistulated cows and sheep in batch culture, the Hohenheim gas test, and the Rusitec technique. Experimental and control arms were utilised, with 5g extracts per kilogram of total dietary dry matter (0.05g/kg active compounds) being used to supplement or not supplement the in vitro systems. Respiratory measurements were conducted on experimental day 1 for the batch culture and Hohenheim gas test and on day 14-21 for the Rusitec Technique (in a 21-day trial). Measurements included methane (CH4) production, total volatile fatty acid (VFA) concentration, molar proportions of acetate, propionate and butyrate and degradation of organic matter (Rusitec). CH4 production was reduced by 82% (±16%), 68% (±11%) and 37% (±4%) in the batch culture, Hohenheim gas test and Rusitec, respectively. Total VFA production was reduced by 13% (±2%) and 2% (±0.1%) in the batch culture and Hohenheim gas test whilst it was increased by 8% (±2%) in the Rusitec. Total VFA production was reduced in all tests between 2 and 10%, whilst acetate production was reduced between 10% and 29%. Propionate production which is an indicator of weight gain was increased in all cases between 16% and 30%. Butyrate production which is considered an indicator of potential milk yield was increased by between 6 and 11%. Degradation of organic matter in the Rusitec experiments was improved by 10% (±0.1%). In conclusion, the study demonstrated the potential of the combination of garlic and citrus extracts to improve digestion, enhance body energy retention and limit CH4 formation in relation to feed intake.

Keywords: citrus, garlic, methane, ruminants

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Authors: Rong Guo, Mengshi Huang, Yujing Bai

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With the rapid development of urbanization, the urban population increases and urban sprawl appeared. And these issues led to a sharp deterioration of the ecological environment. So, the urban ecological security evaluation was imminent. The weights identify of index was a key step of the research of ecological security evaluation. The AHP was widely used in the extensive research of weights identify of ecological security index. The characteristics of authority and quantitative can fully reflect the views of relevant experts. On the basis of building the ecological security evaluation index of Harbin, the paper combed and used the basic principle of the AHP, and calculated the weights of Harbin ecological security evaluation index through the process of the expert opinions “summary-feedback-summary”. And lay a foundation of future study of Harbin ecological security index, and guide the quantitative evaluation of Harbin ecological security.

Keywords: AHP, ecological security, evaluation Index, weights identify, harbin

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Authors: Ana C. Sousa, Beatriz C. Santos, Fátima N. Serralha

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The Tagus estuary is heavily affected by industrial and urban activities, making bioremediation studies crucial for environmental preservation. Fuel contamination in the area can arise from various anthropogenic sources, such as oil spills from shipping, fuel storage and transfer operations, and industrial discharges. These pollutants can cause severe harm to the ecosystem and the organisms, including humans, that inhabit it. Nonetheless, there are always natural organisms with the ability to resist these pollutants and transform them into non-toxic or harmless substances, which defines the process of bioremediation. Exploring the microbial communities existing in soil and their capacity to break down hydrocarbons has the potential to enhance the development of more efficient bioremediation approaches. The aim of this investigation was to explore the existence of hydrocarbonoclastic microorganisms in six locations within the Tagus estuary, three on the north bank: Trancão River, Praia Fluvial do Cais das Colinas and Praia de Algés, and three on the south bank: Praia Fluvial de Alcochete, Praia Fluvial de Alburrica, and Praia da Trafaria. In all studied locations, native microorganisms of the genus Pseudomonas were identified. The bioremediation rate of common hydrocarbons like gasoline, hexane, and toluene was assessed using the redox indicator 2,6-dichlorophenolindophenol (DCPIP). Effective hydrocarbon-degrading bacterial strains were identified in all analyzed areas, despite adverse environmental conditions. The highest bioremediation rates were achieved for gasoline (68%) in Alburrica, hexane (65%) in Algés, and toluene (79%) in Algés. Generally, the bacteria demonstrated efficient degradation of hydrocarbons added to the culture medium, with higher rates of aerobic biodegradation of hydrocarbons observed. These findings underscore the necessity for further in situ studies to better comprehend the relationship between native microbial communities and the potential for pollutant degradation in soil.

Keywords: biodegradability rate, hydrocarbonoclastic microorganisms, soil bioremediation, tagus estuary

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Authors: Trinh Bui, A. Cappellieri

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The fashion industry has become one of the most polluting industries in the world. In this context, designers can contribute solutions to the problem by applying Design for Sustainability (DfS) criteria, which will enable to promote designing products and services toward Sustainability. Therefore, 'Slow Fashion' movement has been receiving the attention of researchers, designers, and customers who are sensitive to sustainable development. The purpose of this paper is to contribute to a better understanding of DfS in fashion. In particular, how can apply sustainable design principles to the fashion accessory in order to minimize the negative impact on the environment and society? The research method of this study is qualitative, utilising a multi-method case study approach. Grounded theory analysis was applied to analyse the data of the case studies collected and the results obtained. Also, research findings indicate that DfS applied to Fashion Accessory design processes might have great potential and win-win approaches toward a sustainable future. An important implication is that understanding the concepts and applying DfS to fashion accessory design processes can support designers to face challenges and seize opportunities. Furthermore, identify the key concept of sustainability and social responsibility could raise awareness on sustainable fashion for both producers and customers more effectively.

Keywords: design for sustainability, fashion accessory, sustainable fashion, sustainability

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Authors: Shunpu Zhang

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We propose a new multiple test called the minPOP test for testing multiple hypotheses simultaneously. Under the assumption that the test statistics are independent, we show that the minPOP test has higher global power than the existing multiple testing methods. We further propose a stepwise multiple-testing procedure based on the minPOP test and two of its modified versions (the Double Truncated and Left Truncated minPOP tests). We show that these multiple tests have strong control of the family-wise error rate (FWER). A method for finding the p-values of the proposed tests after adjusting for multiplicity is also developed. Simulation results show that the Double Truncated and Left Truncated minPOP tests, in general, have a higher number of rejections than the existing multiple testing procedures.

Keywords: multiple test, single-step procedure, stepwise procedure, p-value for multiple testing

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Authors: Boudjelal Amel

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Arisarum vulgare, a member of the Araceae family, is an herbaceous perennial widely distributed in the Mediterranean region. A. vulgare is recognized for its medicinal properties and holds significant traditional importance in Algeria for the treatment of various human ailments, including pain, infections, inflammation, digestive disorders, skin problems, eczema, cancer, wounds, burns and gynecological diseases. Despite its extensive traditional use, scientific exploration of A. vulgare remains limited. The study aims to investigate for the first time the therapeutic potential of A. vulgare ethanolic extract obtained by ultrasound-assisted extraction. The chemical composition of the extract was determined by LC-MS/MS analysis. For in vitro phytopharmacological evaluation, several assays, including DPPH, ABTS, FRAP and reducing power, were employed to evaluate the antioxidant activity. The antibacterial activity was assessed againt Escherichia coli, Salmonella typhimurium, Staphylococus aureus, Enterococcus feacium by disk diffusion and microdilution methods. The possible inhibitory activity of ethanolic extract was analyzed against the cholinesterases enzymes (AChE and BChE). The DNA protection activity of A. vulgare ethanolic extract was estimated using the agarose gel electrophoresis method. The capacities of the extract to protect plasmid DNA (pBR322) from the oxidizing effects of H2O2 and UV treatment were evaluated by their DNA-breaking forms. The in vivo wound healing potential of a traditional ointment containing 5% of A. vulgare ethanolic extract was also investigated. The LC-MS/MS profiling of the extract revealed the presence of various bioactive compounds, including naringenin, chlorogenic, vanillic, cafeic, coumaric acids, trans-cinnamic and trans ferrulic acids. The plant extract presented considerable antioxidant potential, being the most active for Reducing power (0,07326±0.001 mg/ml) and DPPH (0.14±0.004 mg/ml). The extract showed the highest inhibition zone diameter against Enterococcus feacium (36±0.1 mm). The ethanolic extract of A. vulgare suppressed the growth of Staphylococus aureus, Escherichia coli and Salmonella typhimurium according to the MIC values. The extract of the plant significantly inhibited both AChE and BChE enzymes. DNA protection activity of the A. vulgare extract was determined as 90.41% for form I and 51.92% for form II. The in vivo experiments showed that 5% ethanolic extract ointment accelerated the wound healing process. The topical application of the traditional formulation enhanced wound closure (95,36±0,6 %) and improved histological parameters in the treated group compared to the control groups. The promising biological properties of Arisarum vulgare revealed that the plant could be appraised as a potential origin of bioactive molecules having multifunctional medicinal uses.

Keywords: arisarum vulgare, LC-MS/MS, antioxidant activity, antimicrobial activity, cholinesterases enzymes inhibition, dna-damage activity, in vivo wound healing

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Authors: Abduladim Maitieg, Mark Johnson

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Developing a coastal oil spill management plan for the Misratah coast is the motivating factor for building a database for coastal and marine systems and energy resources. Wind direction and speed, currents, bathymetry, coastal topography and offshore dynamics influence oil spill deposition in coastal water. Therefore, oceanographic and climatological data can be used to understand oil slick movement and potential oil deposits on shoreline area and the behaviour of oil spill trajectories on the sea surface. The purpose of this study is to investigate the effects of the coastal and marine physical factors under strong wave conditions and various bathymetric and coastal topography gradients in the western coastal area of Libya on the movement of oil slicks. The movement of oil slicks was computed using a GNOME simulation model based on current and wind speed/direction. The results in this paper show that (1) Oil slick might reach the Misratah shoreline area in two days in the summer and winter. Seasons. (2 ) The North coast of Misratah is the potential oil deposit area on the Misratah coast. (3) Tarball pollution was observed along the North coast of Misratah. (4) Two scenarios for the summer and the winter season were run, along the western coast of Libya . (5) The eastern coast is at a lower potential risk due to the influence of wind and current energy in the Gulf of Sidra. (6) The Misratah coastline is more vulnerable to oil spill movement in the summer than in winter seasons. (7) Oil slick takes from 2 to 5 days to reach the saltmarsh in the eastern Misratah coast. (8) Oil slick moves 300 km in 30 days from the spill resource location near the Libyan western border to the Misratah coast.(9) Bathymetric features have a profound effect on oil spill movement. (9)Oil dispersion simulations using GNOME are carried out taking into account high-resolution wind and current data.

Keywords: oil spill movement, coastal and marine physical factors, coast area, Libyan

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Authors: Aboussalih Amira, Zarza Tahar, Fedaoui Kamel, Hammoudi Saleh

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This work focuses on the simulation of the prediction of the behaviour of austenitic stainless steel (SS) 304L under complex loading in stress and imposed strain. The Chaboche model is a cable to describe the response of the material by the combination of two isotropic and nonlinear kinematic work hardening, the model is implemented in the ZébuLon computer code. First, we represent the evolution of the axial stress as a function of the plastic strain through hysteresis loops revealing a hardening behaviour caused by the increase in stress by stress in the direction of tension/compression. In a second step, the study of the ratcheting phenomenon takes a key place in this work by the appearance of the average stress. In addition to the solicitation of the material in the biaxial direction in traction / torsion.

Keywords: damage, 304L, Ratcheting, plastic strain

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Authors: Suresh Lokiah

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The emerging trend of integrating robots into elderly care, particularly for assisting patients with dementia, holds the potential to greatly transform the sector. Assisted living facilities, which house a significant number of elderly individuals and dementia patients, constantly strive to engage their residents in stimulating activities. However, due to staffing shortages, they often rely on volunteers to introduce new activities. Despite the availability of social interaction, these residents, frequently overlooked in society, are in desperate need of additional support. Robots designed for elder care are categorized based on their design and functionality. These categories include companion robots, telepresence robots, health monitoring robots, and rehab robots. However, the integration of such robots raises significant ethical concerns, notably regarding privacy, autonomy, and the risk of dehumanization. Privacy issues arise as these robots may need to continually monitor patient activities. There is also a risk of patients becoming overly dependent on these robots, potentially undermining their autonomy. Furthermore, the replacement of human touch with robotic interaction may lead to the dehumanization of care. This paper delves into the ethical considerations of incorporating robotic assistance in eldercare. It proposes a series of guidelines and strategies to ensure the ethical deployment of these robots. These guidelines suggest involving patients in the design and development process of the robots and emphasize the critical need for human oversight to respect the dignity and rights of the elderly and dementia patients. The paper also recommends implementing robust privacy measures, including secure data transmission and data anonymization. In conclusion, this paper offers a thorough examination of the ethical implications of using robotic assistance in elder care. It provides a strategic roadmap to ensure this technology is utilized ethically, thereby maximizing its potential benefits and minimizing any potential harm.

Keywords: human-robot interaction, robots for eldercare, ethics, health, dementia

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Authors: I. D. Mngutyo, T. T. Gyuse, D. S. A. Alaci, J. Atser

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Streets are public spaces that are meaningful to all people because of lack of restriction on streets. Studies show that conditions, activities and people contribute to the success of public spaces. Also, self-organization potential in activity patterns offers a prospect for the revitalization of an urban area. This potential is mostly ignored hence many African streets appear disorganized giving African urban areas an unplanned look. Therefore, this study aims to analyze street utilization patterns and explore the relationship between the pattern of street use and condition of streets in Makurdi.These activity patterns form a data base for the revitalization of public space. Three major and minor arterials streets in nine out of the eleven wards that make up the built up part of Makurdi were purposively selected as units for measurement. A street activity audit was done on streets for activities that can be observed. For activities that cannot be easily observed 4 questionnaires were randomly administered on each of the three streets giving a total of 108 questionnaires. Multivariate statistical tools such as factor analysis and regression will be used to show emerging streets activity patterns and spatial variation among the nine wards.

Keywords: streets, utilization patterns, revitalization, urban design, urban, areas, developing countries

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Authors: Danna Jia, Bin Li

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Background: Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. The global prevalence of AD ranges from 1~ 20%, and its incidence rates are increasing. It affects individuals from infancy to adulthood, significantly impacting their daily lives and social activities. Despite its major health burden, the precise mechanisms underlying AD remain unknown. Understanding the genetic differences associated with AD is crucial for advancing diagnosis and targeted treatment development. This study aims to identify candidate genes of AD by using bioinformatics analysis. Methods: We conducted a comprehensive analysis of four pooled transcriptomic datasets (GSE16161, GSE32924, GSE130588, and GSE120721) obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using the R statistical language. The differentially expressed genes (DEGs) between AD patients and normal individuals were functionally analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, a protein-protein interaction (PPI) network was constructed to identify candidate genes. Results: Among the patient-level gene expression datasets, we identified 114 shared DEGs, consisting of 53 upregulated genes and 61 downregulated genes. Functional analysis using GO and KEGG revealed that the DEGs were mainly associated with the negative regulation of transcription from RNA polymerase II promoter, membrane-related functions, protein binding, and the Human papillomavirus infection pathway. Through the PPI network analysis, we identified eight core genes: CD44, STAT1, HMMR, AURKA, MKI67, and SMARCA4. Conclusion: This study elucidates key genes associated with AD, providing potential targets for diagnosis and treatment. The identified genes have the potential to contribute to the understanding and management of AD. The bioinformatics analysis conducted in this study offers new insights and directions for further research on AD. Future studies can focus on validating the functional roles of these genes and exploring their therapeutic potential in AD. While these findings will require further verification as achieved with experiments involving in vivo and in vitro models, these results provided some initial insights into dysfunctional inflammatory and immune responses associated with AD. Such information offers the potential to develop novel therapeutic targets for use in preventing and treating AD.

Keywords: atopic dermatitis, bioinformatics, biomarkers, genes

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Authors: Georgia H. Mega

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Art street, a category of artwork displayed in public spaces, has been recognized as a potential tool for promoting reflective thinking in both adult and primary education. Educational techniques that encourage critical and creative thinking, as well as deeper reflection, have been developed and applied in educational curricula. This paper aims to explore the potential of art street in cultivating learners' reflective awareness toward multiculturalism. The main objective of this case study is to investigate the possibilities that art street offers in terms of developing learners' critical reflection, regardless of their age. The study compares two art street works from Greece and Norway, focusing on their common theme of multiculturalism. The study adopts a qualitative methodology, specifically a case study approach. This approach allows for an in-depth analysis of the two selected art street works and their impact on learners' reflective thinking. The study demonstrates that art street can effectively cultivate learners' reflective awareness of multiculturalism. The selected works of art, despite being created by different artists and displayed in different cities, share similar content and convey messages that facilitate reflective dialogue on cultural osmosis. Both adult and primary education approaches utilize the same art street works to achieve reflective awareness. This paper contributes to the existing literature on reflective learning processes by highlighting the potential of art street as a means for encouraging reflective thinking. It builds upon the theoretical frameworks of adult education theorists such as Freire and Mezirow, as well as those of primary education theorists such as Perkins and Project Zero. Data for this study were collected through observation and analysis of two art street works, one from Greece and one from Norway. These works were selected based on their common theme of multiculturalism. Analysis Procedures: The collected data were analyzed using qualitative analysis techniques. The researchers examined the content and messages conveyed by the selected art street works and explored their impact on learners' reflective thinking. The central question addressed in this study is whether art street can develop learners' critical reflection toward multiculturalism, regardless of their age. The findings of this study support the notion that art street can effectively cultivate learners' reflective awareness toward multiculturalism. The selected art street works, despite their differences in origin and location, share common themes that encourage reflective dialogue. The use of art street in both adult and primary education approaches showcases its potential as a tool for promoting reflective learning processes. Overall, this paper contributes to the understanding of art street as a means for reflective thinking in the field of adult and primary education.

Keywords: art street, educational techniques, multiculturalism, observation of artworks, reflective awareness

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Authors: Amir Jalalian-Khakshour, T. N. Croft

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Vertical Axis Wind Turbine (VAWT) systems are becoming increasingly popular as they have a number of advantages over traditional wind turbines. The advantages are reliability, ease of transportation and manufacturing. These attributes could make these technologies useful in developing economies. The performance characteristics of a VAWT are different from a horizontal axis wind turbine, which can be attributed to the low tip speed ratio operation. To unlock the potential of these VAWT systems, the operational behaviour in a number of system topologies and environmental conditions needs to be understood. In this study, a non-linear dynamic simulation method was developed in Matlab and validated against in field data of a large scale, 8-meter rotor diameter prototype. This simulation method has been utilised to determine the performance characteristics of a number of control methods and system topologies. The motivation for this research was to develop a simulation method which accurately captures the operating behaviour and is computationally inexpensive. The model was used to evaluate the performance through parametric studies and optimisation techniques. The study gave useful insights into the applications and energy generation potential of this technology.

Keywords: power generation, renewable energy, rotordynamics, wind energy

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

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Many global firms and corporations derive new technology and opportunity by identifying vacant technology from patent analysis. However, previous studies failed to focus on technologies that promised continuous growth in industrial fields. Most studies that derive new technology opportunities do not test practical effectiveness. Since previous studies depended on expert judgment, it became costly and time-consuming to evaluate new technologies based on patent analysis. Therefore, research suggests a quantitative and systematic approach to technology evaluation indicators by using patent data to and from customer communities. The first step involves collecting two types of data. The data is used to construct evaluation indicators and apply these indicators to the evaluation of new technologies. This type of data mining allows a new method of technology evaluation and better predictor of how new technologies are adopted.

Keywords: data mining, evaluating new technology, technology opportunity, patent analysis

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: D. A. Bruzon, G. Tapang, I. S. Martinez

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Global warming and climate change are significant environmental concerns, which require immediate global action in carbon emission mitigation. The capture, sequestration, and conversion of carbon dioxide to other products such as methane or ethanol are ways to control excessive emissions. Ionic liquids have shown great potential among the materials studied as carbon capture solvents and catalysts in the reduction of CO2. In this study, ionic liquids comprising of a methoxy (-OCH3) and cyano (-CN) functionalized imidazolium cation, [MOBMIM] and [CNBMIM] respectively, paired with tris(pentafluoroethyl)trifluorophosphate [FAP] anion were evaluated as effective capture solvents, and organocatalysts in the reduction of CO2. An in-situ electrochemical set-up, which can measure controlled amounts of CO2 both in the gas and in the ionic liquid phase, was used. Initially, reduction potentials of CO2 in the CO2-saturated ionic liquids containing the internal standard cobaltocene were determined using cyclic voltammetry. Chronoamperometric transients were obtained at potentials slightly less negative than the reduction potentials of CO2 in each ionic liquid. The time-dependent current response was measured under a controlled atmosphere. Reduction potentials of CO2 in methoxy and cyano-functionalized [FAP] ionic liquids were observed to occur at ca. -1.0 V (vs. Cc+/Cc), which was significantly lower compared to the non-functionalized analog [PMIM][FAP], with an observed reduction potential of CO2 at -1.6 V (vs. Cc+/Cc). This decrease in the potential required for CO2 reduction in the functionalized ionic liquids shows that the functional groups methoxy and cyano effectively decreased the free energy of formation of the radical anion CO2●⁻, suggesting that these electrolytes may be used as organocatalysts in the reduction of the greenhouse gas. However, upon analyzing the solubility of the gas in each ionic liquid, [PMIM][FAP] showed the highest absorption capacity, at 4.81 mM under saturated conditions, compared to [MOBMIM][FAP] at 1.86 mM, and [CNBMIM][FAP] at 0.76 mM. Also, calculated Henry’s constant determined from the concentration-pressure graph of each functionalized ionic liquid shows that the groups -OCH3 and -CN attached terminal to a C4 alkyl chain do not significantly improve CO2 solubility.

Keywords: carbon capture, CO2 reduction, electrochemistry, ionic liquids

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Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

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Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: S. L. J. Tan, N. Billa, C. J. Roberts

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Oral delivery of amphotericin B (AmpB) potentially eliminates constraints and side effects associated with intravenous administration, but remains challenging due to the physicochemical properties of the drug such that it results in meagre bioavailability (0.3%). In an advanced formulation, 1) nanostructured lipid carriers (NLC) were formulated as they can accommodate higher levels of cargoes and restrict drug expulsion and 2) a mucoadhesion feature was incorporated so as to impart sluggish transit of the NLC along the gastrointestinal tract and hence, maximize uptake and improve bioavailability of AmpB. The AmpB-loaded NLC formulation was successfully formulated via high shear homogenisation and ultrasonication. A chitosan coating was adsorbed onto the formed NLC. Physical properties of the formulations; particle size, zeta potential, encapsulation efficiency (%EE), aggregation states and mucoadhesion as well as the effect of the variable pH on the integrity of the formulations were examined. The particle size of the freshly prepared AmpB-loaded NLC was 163.1 ± 0.7 nm, with a negative surface charge and remained essentially stable over 120 days. Adsorption of chitosan caused a significant increase in particle size to 348.0 ± 12 nm with the zeta potential change towards positivity. Interestingly, the chitosan-coated AmpB-loaded NLC (ChiAmpB NLC) showed significant decrease in particle size upon storage, suggesting 'anti-Ostwald' ripening effect. AmpB-loaded NLC formulation showed %EE of 94.3 ± 0.02 % and incorporation of chitosan increased the %EE significantly, to 99.3 ± 0.15 %. This suggests that the addition of chitosan renders stability to the NLC formulation, interacting with the anionic segment of the NLC and preventing the drug leakage. AmpB in both NLC and ChiAmpB NLC showed polyaggregation which is the non-toxic conformation. The mucoadhesiveness of the ChiAmpB NLC formulation was observed in both acidic pH (pH 5.8) and near-neutral pH (pH 6.8) conditions as opposed to AmpB-loaded NLC formulation. Hence, the incorporation of chitosan into the NLC formulation did not only impart mucoadhesive property but also protected against the expulsion of AmpB which makes it well-primed as a potential oral delivery system for AmpB.

Keywords: Amphotericin B, mucoadhesion, nanostructured lipid carriers, oral delivery

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Authors: Shruti Hajirnis

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In May 2014, FASB issued Accounting Standards Update (ASU) 2014-09, Revenue from Contracts with Customers (Topic 606), and the International Accounting Standards Board (IASB) issued International Financial Reporting Standards (IFRS) 15, Revenue from Contracts with Customers that will supersede virtually all revenue recognition requirements in IFRS and US GAAP. FASB and the IASB have basically achieved convergence with these standards, with only some minor differences such as collectability threshold, interim disclosure requirements, early application and effective date, impairment loss reversal and nonpublic entity requirements. This paper discusses the impact of five-step model prescribed in new revenue standard on the entities operating in Pharma industry. It also outlines the considerations for these entities while implementing the new standard.

Keywords: revenue recognition, pharma industry, standard, requirements

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Authors: Riccardo Zanni, Maria Galvez-Llompart, Ramon Garcia-Domenech, Jorge Galvez

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Biopesticides, such as naturally occurring chemicals, pheromones, fungi, bacteria and insect predators are often a winning choice in crop protection because of their environmental friendly profile. They are considered to have lower toxicity than traditional pesticides. After almost a century of pesticides use, resistances to traditional insecticides are wide spread, while those to bioinsecticides have raised less attention, and resistance management is frequently neglected. This seems to be a crucial mistake since resistances have already occurred for many marketed biopesticides. With an eye to the future, we present here a selection of new natural occurring chemicals as potential bioinsecticides. The molecules were selected using a consolidated mathematical paradigm called molecular topology. Several QSAR equations were depicted and subsequently applied for the virtual screening of hundred thousands molecules of natural origin, which resulted in the selection of new potential bioinsecticides. The most innovative aspect of this work does not only reside in the importance of the identification of new molecules overcoming biopesticides’ resistances, but on the possibility to promote shared knowledge in the field of green chemistry through this unique in silico discipline named molecular topology.

Keywords: green chemistry, QSAR, molecular topology, biopesticide

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Authors: Ishaq Ahmad, Zhaomin Li, Liu Chengwen, Song Yan Li, Zihan Gu, Li Shaopeng

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In order to manage gas mobility in the reservoir, only a small amount of surfactant or polymer is needed because nanoparticles have the potential to improve foam stability. The aim is to enhance foam formation and stability, so it was decided to investigate the foam stability and foam ability of black rice husk ash. Several characterization techniques were used to investigate the properties of black rice husk ash. The best-performing anionic foaming surfactants were combined with black rice husk ash at different concentrations (ppm). Sodium dodecyl benzene sulphonate was used as the anionic surfactant. This study demonstrates the value of black rice husk ash (BRHA), which has a high silica concentration, for foam stability and ability. For the test, black rice husk ash and raw ash were used with SDS (Sodium Dodecyl Sulfate) and SDBS (Sodium dodecyl benzenesulfonate) surfactants under different parameters. Different concentration percentages were utilized to create the foam, and the hydrophobic test and shaking method were applied. The foam scanner was used to observe the behavior of the black rice husk ash foam. The high silica content of black rice husk ash has the potential to improve foam stability, which is favorable and could possibly improve oil recovery.

Keywords: black rice husk ash nanoparticle, surfactant, foam life, foam scanning

Procedia PDF Downloads 147

Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

Procedia PDF Downloads 102

Authors: Auzair Mehmood, Mohammad Arif

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The LCT (Li, Cs and Ta rich)-type pegmatites, genetically related to peraluminous S-type granites, are being mined for strategic metals (SMs) and rare earth elements (REEs) around the world. This study investigates the SMs and REEs potentials of pegmatites that are spatially associated with an S-type granitic suite of the Himalayan sequence, specifically Mansehra Granitic Complex (MGC), northwest Pakistan. Geochemical signatures of the pegmatites and some of their mineral extracts were analyzed using Inductive Coupled Plasma Mass Spectroscopy (ICP-MS) technique to explore and generate potential prospects (if any) for SMs and REEs. In general, the REE patterns of the studied whole-rock pegmatite samples show tetrad effect and possess low total REE abundances, strong positive Europium (Eu) anomalies, weak negative Cesium (Cs) anomalies and relative enrichment in heavy REE. Similar features have been observed on the REE patterns of the feldspar extracts. However, the REE patterns of the muscovite extracts reflect preferential enrichment and possess negative Eu anomalies. The trace element evaluation further suggests that the MGC pegmatites have undergone low levels of fractionation. Various trace elements concentrations (and their ratios) including Ta versus Cs, K/Rb (Potassium/Rubidium) versus Rb and Th/U (Thorium/Uranium) versus K/Cs, were used to analyze the economically viable mineral potential of the studied rocks. On most of the plots, concentrations fall below the dividing line and confer either barren or low-level mineralization potential of the studied rocks for both SMs and REEs. The results demonstrate paucity of the MGC pegmatites with respect to Ta-Nb (Tantalum-Niobium) mineralization, which is in sharp contrast to many Pan-African S-type granites around the world. The MGC pegmatites are classified as muscovite pegmatites based on their K/Rb versus Cs relationship. This classification is consistent with the occurrence of rare accessory minerals like garnet, biotite, tourmaline, and beryl. Furthermore, the classification corroborates with an earlier sorting of the MCG pegmatites into muscovite-bearing, biotite-bearing, and subordinate muscovite-biotite types. These types of pegmatites lack any significant SMs and REEs mineralization potentials. Field relations, such as close spatial association with parent granitic rocks and absence of internal zonation structure, also reflect the barren character and hence lack of any potential prospects of the MGC pegmatites.

Keywords: exploration, fractionation, Himalayas, pegmatites, rare earth elements

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Authors: Maria Manzoor, Iram Gul, Muhammad Arshad, Jean Kallerhoff

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The potential of fungal isolates to be used in phytoremediation of widespread lead contaminated soil has been evaluated in this study. Five different fungal isolates (Trichoderma harzianum, Penicillium simplicissimum, Aspergillus flavus, Aspergillus niger and Mucor spp.) were obtained and tested for their tolerance to increasing concentration of lead (Pb) i.e. 100, 200, 300, 400 and 500 mgL-1 on PDA and PDB culture experiment. All strains were tolerant up to 500 mgL-1 following sequence; A. flavus > A. niger > Mucor spp. > P. simplicissimum > T. harzianum. Further the isolates were then monitored for possible effect on Pb solubility/mobility through soil incubation experiments and characterized for essays including pathogenicity, germination and root elongation and plant growth promoting activities including IAA (indole acetic acid), phosphorus solubilization and gibberellic acid (GA3) production. Results revealed that fungal isolates have positive effect on Pb mobility in soil and plant biomass production. Pb solubility was significantly (P> 0.05) increased in soil upon application of Mucor spp. P. simplicissimum and T. harzianum. when compared to control. Among different strains three isolates (Mucor spp., P. simplicissimum and T. harzianum) were nonpathogenic because no inhibitory effect of fungus was observed to plant growth when exposed to these strains in root shoot elongation essay. Particularly T. harzianum and P. simplicissimum showed great ability to increase root length by 1.1 and 1.3 folds and shoot length by 1.47 and 1.5 folds respectively under Pb stress (500 mgL-1). Significantly high production of IAA was observed in A. niger (26.7 μg/ml), Phosphorus solubilization was observed in T. harzianum (9.15 μg/ml) and GA3 production was observed in P. simplicissimum (11.02 μg/ml). From results it is concluded that Mucor spp., P. simplicissimum and T. harzianum have potential to increase Pb mobility and improving plant growth under highy Pb contamination, therefore can be used in microbially assisted phytoremediation of Pb contaminated soil.

Keywords: Pb tolerant fungus, Pb mobility, plant growth promoting activities, indole acetic acid (IAA)

Procedia PDF Downloads 266

Authors: Khan Md. Abdus Subhan, Rabeya Bushra

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Bangladesh has already seen significant growth in Islamic banking and finance, contributing to the rapid expansion of this sector in the global banking and finance industry. The objective of this study is to analyse the Islamic finance and banking industry's ability to contribute to sustainable development in Bangladesh. It aims to assess the current state, potential, and limitations of Islamic banking and finance in the country. Bangladesh has significant growth potential for Islamic banking and finance. However, addressing several challenges is imperative. These challenges include the absence of a well-developed infrastructure for Islamic banking and finance, a lack of a solid legal framework, limited attention from the central bank, the absence of an Islamic capital market, and a shortage of experts in Sharia law as well as public awareness. Bangladesh, a nation characterized by a primarily Muslim populace, has acknowledged the importance of Islamic finance and banking in promoting sustainable development. Islamic banking principles advocate for ethical practices, risk sharing, and the avoidance of interest-based transactions. This article examines the impact of Islamic finance and banking on promoting sustainable development in Bangladesh and emphasizes its capacity to tackle socio-economic difficulties. The Islamic banking sector, as a trailblazer in funding sustainable development, has the potential to play a significant role in facilitating the shift toward a circular economy. According to Shari'ah rules and the Sustainable Development Goals (SDGs), Islamic finance principles will help change the linear economy into a circular one. They will also provide a strong framework and a lot of funding sources. This study aims to offer crucial recommendations and techniques for the successful implementation of Islamic finance institutions in Bangladesh. The study will use quantitative research methodology, collecting data from secondary sources. This research offers a thorough understanding of the reasoning for the payment of Zakat and its socio-economic importance. Furthermore, the study provides significant insights that could assist Bangladeshi policymakers and governments in implementing Islamic financing systems.

Keywords: sustainable development, Islamic fintech, Islamic banking, Bangladesh

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Authors: Madhavi-Priya Singh, Liam Lowe, Farouk Arnaout, Ludmilla Pillay, Giordan Perez, Luke Mischker, Steve Costa

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An Emergency Department consultant identified the failure of medical students to complete the task of clerking a patient in its entirety. As six medical students on our first clinical placement, we recognised our own failure and endeavoured to examine why this failure was consistent among all medical students that had been given this task, despite our best motivations as adult learner. Our aim is to understand and investigate the elements which impeded our ability to learn and perform as medical students in the clinical environment, with reference to the prescribed task. We also aim to generate a discussion around the delivery of medical education with potential solutions to these barriers. Six medical students gathered together to have a comprehensive reflective discussion to identify possible factors leading to the failure of the task. First, we thoroughly analysed the delivery of the instructions with reference to the literature to identify potential flaws. We then examined personal, social, ethical, and cultural factors which may have impacted our ability to complete the task in its entirety. Through collation of our shared experiences, with support from discussion in the field of medical education and ethics, we identified two major areas that impacted our ability to complete the set task. First, we experienced an ethical conflict where we believed the inconvenience and potential harm inflicted on patients did not justify the positive impact the patient interaction would have on our medical learning. Second, we identified a lack of confidence stemming from multiple factors, including the conflict between preclinical and clinical learning, perceptions of perfectionism in the culture of medicine, and the influence of upward social comparison. After discussions, we found that the various factors we identified exacerbated the fears and doubts we already had about our own abilities and that of the medical education system. This doubt led us to avoid completing certain aspects of the tasks that were prescribed and further reinforced our vulnerability and perceived incompetence. Exploration of philosophical theories identified the importance of the role of doubt in education. We propose the need for further discussion around incorporating both pedagogic and andragogic teaching styles in clinical medical education and the acceptance of doubt as a driver of our learning. Doubt will continue to permeate our thoughts and actions no matter what. The moral or psychological distress that arises from this is the key motivating factor for our avoidance of tasks. If we accept this doubt and education embraces this doubt, it will no longer linger in the shadows as a negative and restrictive emotion but fuel a brighter dialogue and positive learning experience, ultimately assisting us in achieving our full potential.

Keywords: medical education, clinical education, andragogy, pedagogy

Procedia PDF Downloads 126