Search results for: Goldstein social skill streaming model

Authors: Irina-Emily Hansen, Ola Jon Mork

Abstract:

The European economic growth strategy and supporting it framework for research and innovation highlight the importance of nurturing new open innovation in order to strengthen Europe’s competitiveness. One of the main approaches to enhance innovation in European society is the Triple Helix model that centres on science- industry collaboration where the universities are assigned the managerial role. In spite of the defined collaboration strategy, the collaboration between academics and in-dustry in Europe has still many challenges. Many of them are explained by culture difference: academic culture aims towards scientific knowledge, while businesses are oriented towards pro-duction and profitable results; also execution of collaborative projects is seen differently by part-ners involved. That proves that traditional management strategies applied to collaboration between researchers and businesses are not effective. There is a need for dynamic strategies that can support the interaction between researchers and industry intensifying knowledge co-creation and contributing to development of national innovation system (NIS) by incorporating individual, organizational and inter-organizational learning. In order to find a good subject to follow, the researchers of a given paper have investigated one of the most rapidly developing knowledge-based, innovation society, Singapore. Singapore does not dispose much land- or sea- resources that normally provide income for any country. Therefore, Singapore was forced to think differently and build society on resources that are available: talented people and knowledge. Singapore has during the last twenty years developed attracting high rated university camps, research institutions and leading industrial companies from all over the world. This article elucidates and elaborates Singapore’s national innovation strategies from Knowledge Management perspective. The research is done on the variety of organizations that enable and support knowledge development in this state: governmental research and development (R&D) centers in universities, private talent incubators for entrepreneurs, and industrial companies with own R&D departments. The research methods are based on presentations, documents, and visits at a number of universities, research institutes, innovation parks, governmental institutions, industrial companies and innovation exhibitions in Singapore. In addition, a literature review of science articles is made regarding the topic. The first finding is that objectives of collaboration between researchers, entrepreneurs and industry in Singapore correspond primary goals of the state: knowledge- and economy growth. There are common objectives for all stakeholders on all national levels. The second finding is that Singapore has enabled system on a national level that supports innovation the entire way from fostering or capturing the new knowledge, providing knowledge exchange and co-creation to application of it in real-life. The conclusion is that innovation means not only new idea, but also the enabling mechanism for its execution and the marked-oriented approach in order that new knowledge can be absorbed in society. The future research can be done with regards to application of Singapore knowledge management strategy in innovation to European countries.

Keywords: knowledge management strategy, national innovation system, research industry and business collaboration, knowledge enabling

Procedia PDF Downloads 182

Authors: Marcus Goh Tian Xi, Alicia Chua Si Wen, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee

Abstract:

The Map of Dialogical Inquiry provides a conceptual look at the underlying nature of future-oriented skills. According to the Map, learning is learner-oriented, with conversational time shifted from teachers to learners, who play a strong role in deciding what and how they learn. For example, in courses operating on the principles of Dialogical Inquiry, learners were able to leave the classroom with a deeper understanding of the topic, broader exposure to differing perspectives, and stronger critical thinking capabilities, compared to traditional approaches to teaching. Despite its contributions to learning, the Map is grounded in a qualitative approach both in its development and its application for providing feedback to learners and educators. Studies hinge on openended responses by Map users, which can be time consuming and resource intensive. The present research is motivated by this gap in practicality by aiming to develop and validate a quantitative measure of the Map. In addition, a quantifiable measure may also strengthen applicability by making learning experiences trackable and comparable. The Map outlines eight learning aspects that learners should holistically engage. This research focuses on the Analysing aspect of learning. According to the Map, Analysing has four key components: liking or engaging in logic, using interpretative lenses, seeking patterns, and critiquing and deconstructing. Existing scales of constructs (e.g., critical thinking, rationality) related to these components were identified so that the current scale could adapt items from. Specifically, items were phrased beginning with an “I”, followed by an action phrase, to fulfil the purpose of assessing learners' engagement with Analysing either in general or in classroom contexts. Paralleling standard scale development procedure, the 26-item Analysing scale was administered to 330 participants alongside existing scales with varying levels of association to Analysing, to establish construct validity. Subsequently, the scale was refined and its dimensionality, reliability, and validity were determined. Confirmatory factor analysis (CFA) revealed if scale items loaded onto the four factors corresponding to the components of Analysing. To refine the scale, items were systematically removed via an iterative procedure, according to their factor loadings and results of likelihood ratio tests at each step. Eight items were removed this way. The Analysing scale is better conceptualised as unidimensional, rather than comprising the four components identified by the Map, for three reasons: 1) the covariance matrix of the model specified for the CFA was not positive definite, 2) correlations among the four factors were high, and 3) exploratory factor analyses did not yield an easily interpretable factor structure of Analysing. Regarding validity, since the Analysing scale had higher correlations with conceptually similar scales than conceptually distinct scales, with minor exceptions, construct validity was largely established. Overall, satisfactory reliability and validity of the scale suggest that the current procedure can result in a valid and easy-touse measure for each aspect of the Map.

Keywords: analytical thinking, dialogical inquiry, education, lifelong learning, pedagogy, scale development

Procedia PDF Downloads 87

Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

Abstract:

Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

Procedia PDF Downloads 266

Authors: Desmond Appiah, Fan Zhang, Shouqi Yuan, Wei Xueyuan, Stephen N. Asomani

Abstract:

The side channel pump has distinctive hydraulic performance characteristics over other vane pumps because of its generation of high pressure heads in only one impeller revolution. Hence, there is soaring utilization and application in the fields of petrochemical, food processing fields, automotive and aerospace fuel pumping where high heads are required at low flows. The side channel pump is characterized by unstable flow because after fluid flows into the impeller passage, it moves into the side channel and comes back to the impeller again and then moves to the next circulation. Consequently, the flow leaves the side channel pump following a helical path. However, the pressure fluctuation exhibited in the flow greatly contributes to the unwanted noise and vibration which is associated with the flow. In this paper, a side channel pump prototype was examined thoroughly through numerical calculations based on SST k-ω turbulence model to ascertain the pressure fluctuation behavior. The pressure fluctuation intensity of the 3D unstable flow dynamics were carefully investigated under different working conditions 0.8QBEP, 1.0 QBEP and 1.2QBEP. The results showed that the pressure fluctuation distribution around the pressure side of the blade is greater than the suction side at the impeller and side channel interface (z=0) for all three operating conditions. Part-load condition 0.8QBEP recorded the highest pressure fluctuation distribution because of the high circulation velocity thus causing an intense exchanged flow between the impeller and side channel. Time and frequency domains spectra of the pressure fluctuation patterns in the impeller and the side channel were also analyzed under the best efficiency point value, QBEP using the solution from the numerical calculations. It was observed from the time-domain analysis that the pressure fluctuation characteristics in the impeller flow passage increased steadily until the flow reached the interrupter which separates low-pressure at the inflow from high pressure at the outflow. The pressure fluctuation amplitudes in the frequency domain spectrum at the different monitoring points depicted a gentle decreasing trend of the pressure amplitudes which was common among the operating conditions. The frequency domain also revealed that the main excitation frequencies occurred at 600Hz, 1200Hz, and 1800Hz and continued in the integers of the rotating shaft frequency. Also, the mass flow exchange plots indicated that the side channel pump is characterized with many vortex flows. Operating conditions 0.8QBEP, 1.0 QBEP depicted less and similar vortex flow while 1.2Q recorded many vortex flows around the inflow, middle and outflow regions. The results of the numerical calculations were finally verified experimentally. The performance characteristics curves from the simulated results showed that 0.8QBEP working condition recorded a head increase of 43.03% and efficiency decrease of 6.73% compared to 1.0QBEP. It can be concluded that for industrial applications where the high heads are mostly required, the side channel pump can be designed to operate at part-load conditions. This paper can serve as a source of information in order to optimize a reliable performance and widen the applications of the side channel pumps.

Keywords: exchanged flow, pressure fluctuation, numerical simulation, side channel pump

Procedia PDF Downloads 133

Authors: Dedjo Yao Simon, Takahiro Saito, Norikazu Inuzuka, Ikuo Sugiyama

Abstract:

The megacity of Abidjan is a coastal urban area where the number of floods reported and the associated impacts are on a rapid increase due to climate change, an uncontrolled urbanization, a rapid population increase, a lack of flood disaster mitigation and citizens’ awareness. The objective of this research is to reduce in the short and long term period, the human and socio-economic impact of the flood. Hydrological simulation is applied on free of charge global spatial data (digital elevation model, satellite-based rainfall estimate, landuse) to identify the flood-prone area and to map the risk of flood. A direct interview to a sample residents is used to validate the simulation results. Then a mobile application (Flood Locator) is prototyped to disseminate the risk information to the citizen. In addition, a value capture strategy is proposed to mobilize financial resource for disaster risk reduction (DRRf) to reduce the impact of the flood. The town of Cocody in Abidjan is selected as a case study area to implement this research. The mapping of the flood risk reveals that population living in the study area is highly vulnerable. For a 5-year flood, more than 60% of the floodplain is affected by a water depth of at least 0.5 meters; and more than 1000 ha with at least 5000 buildings are directly exposed. The risk becomes higher for a 50 and 100-year floods. Also, the interview reveals that the majority of the citizen are not aware of the risk and severity of flooding in their community. This shortage of information is overcome by the Flood Locator and by an urban flood database we prototype for accumulate flood data. Flood Locator App allows the users to view floodplain and depth on a digital map; the user can activate the GPS sensor of the mobile to visualize his location on the map. Some more important additional features allow the citizen user to capture flood events and damage information that they can send remotely to the database. Also, the disclosure of the risk information could result to a decrement (-14%) of the value of properties locate inside floodplain and an increment (+19%) of the value of property in the suburb area. The tax increment due to the higher tax increment in the safer area should be captured to constitute the DRRf. The fund should be allocated to the reduction of flood risk for the benefit of people living in flood-prone areas. The flood prevention system discusses in this research will minimize in the short and long term the direct damages in the risky area due to effective awareness of citizen and the availability of DRRf. It will also contribute to the growth of the urban area in the safer zone and reduce human settlement in the risky area in the long term. Data accumulated in the urban flood database through the warning app will contribute to regenerate Abidjan towards the more resilient city by means of risk avoidable landuse in the master plan.

Keywords: abidjan, database, flood, geospatial techniques, risk communication, smartphone, value capture

Procedia PDF Downloads 282

Authors: L. J. de Jager

Abstract:

In the South African English school curriculum, one of the aims is to achieve communicative competence, the knowledge of using language competently and appropriately in a speech community. Communicatively competent speakers should not only produce grammatically correct sentences but also produce contextually appropriate sentences for various purposes and in different situations. As most speakers of English are non-native speakers, achieving communicative competence remains a complex challenge. Moreover, the changing needs of society necessitate not merely language proficiency, but also technological proficiency. One of the burning issues in the South African educational landscape is the replacement of the standardised literacy model by the pedagogy of multiliteracies that incorporate, by default, the exploration of technological text forms that are part of learners’ everyday lives. It foresees learners as decoders, encoders, and manufacturers of their own futures by exploiting technological possibilities to constantly create and recreate meaning. As such, 21st century learners will feel comfortable working with multimodal texts that are intrinsically part of their lives and by doing so, become authors of their own learning experiences while teachers may become agents supporting learners to discover their capacity to acquire new digital skills for the century of multiliteracies. The aim is transformed practice where learners use their skills, ideas, and knowledge in new contexts. This paper reports on a research project on the integration of technology for language learning, based on the technological pedagogical content knowledge framework, conceptually founded in the theory of multiliteracies, and which aims to achieve communicative competence. The qualitative study uses the community of inquiry framework to answer the research question: How does the integration of technology transform language teaching of preservice teachers? Pre-service teachers in the Postgraduate Certificate of Education Programme with English as methodology were purposively selected to source and evaluate apps for teaching and learning English. The participants collaborated online in a dedicated Blackboard module, using discussion threads to sift through applicable apps and develop interactive lessons using the Apps. The selected apps were entered on to a predesigned Qualtrics form. Data from the online discussions, focus group interviews, and reflective journals were thematically and inductively analysed to determine the participants’ perceptions and experiences when integrating technology in lesson design and the extent to which communicative competence was achieved when using these apps. Findings indicate transformed practice among participants and research team members alike with a better than average technology acceptance and integration. Participants found value in online collaboration to develop and improve their own teaching practice by experiencing directly the benefits of integrating e-learning into the teaching of languages. It could not, however, be clearly determined whether communicative competence was improved. The findings of the project may potentially inform future e-learning activities, thus supporting student learning and development in follow-up cycles of the project.

Keywords: apps, communicative competence, English teaching, technology integration, technological pedagogical content knowledge

Procedia PDF Downloads 160

Authors: Bensaid A., Mostephaoui T., Nedjai R.

Abstract:

A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 104

Authors: Marta Paszkiewicz, Justyna Łuczak, Martyna Marchelek, Adriana Zaleska-Medynska

Abstract:

In recent years, photocatalytical processes have been intensively investigated for destruction of pollutants, hydrogen evolution, disinfection of water, air and surfaces, for the construction of self-cleaning materials (tiles, glass, fibres, etc.). Titanium dioxide (TiO2) is the most popular material used in heterogeneous photocatalysis due to its excellent properties, such as high stability, chemical inertness, non-toxicity and low cost. It is well known that morphology and microstructure of TiO2 significantly influence the photocatalytic activity. This characteristics as well as other physical and structural properties of photocatalysts, i.e., specific surface area or density of crystalline defects, could be controlled by preparation route. In this regard, TiO2 particles can be obtained by sol-gel, hydrothermal, sonochemical methods, chemical vapour deposition and alternatively, by ionothermal synthesis using ionic liquids (ILs). In the TiO2 particles synthesis ILs may play a role of a solvent, soft template, reagent, agent promoting reduction of the precursor or particles stabilizer during synthesis of inorganic materials. In this work, the effect of the ILs anion type on morphology and photoactivity of TiO2 is presented. The preparation of TiO2 microparticles with spherical structure was successfully achieved by solvothermal method, using tetra-tert-butyl orthotitatane (TBOT) as the precursor. The reaction process was assisted by an ionic liquids 1-butyl-3-methylimidazolium bromide [BMIM][Br], 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4] and 1-butyl-3-methylimidazolium haxafluorophosphate [BMIM][PF6]. Various molar ratios of all ILs to TBOT (IL:TBOT) were chosen. For comparison, reference TiO2 was prepared using the same method without IL addition. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brenauer-Emmett-Teller surface area (BET), NCHS analysis, and FTIR spectroscopy were used to characterize the surface properties of the samples. The photocatalytic activity was investigated by means of phenol photodegradation in the aqueous phase as a model pollutant, as well as formation of hydroxyl radicals based on detection of fluorescent product of coumarine hydroxylation. The analysis results showed that the TiO2 microspheres had spherical structure with the diameters ranging from 1 to 6 µm. The TEM micrographs gave a bright observation of the samples in which the particles were comprised of inter-aggregated crystals. It could be also observed that the IL-assisted TiO2 microspheres are not hollow, which provides additional information about possible formation mechanism. Application of the ILs results in rise of the photocatalytic activity as well as BET surface area of TiO2 as compared to pure TiO2. The results of the formation of 7-hydroxycoumarin indicated that the increased amount of ·OH produced at the surface of excited TiO2 for samples TiO2_ILs well correlated with more efficient degradation of phenol. NCHS analysis showed that ionic liquids remained on the TiO2 surface confirming structure directing role of that compounds.

Keywords: heterogeneous photocatalysis, IL-assisted synthesis, ionic liquids, TiO2

Procedia PDF Downloads 265

Authors: Zenaida Chitu, Roxana Bojariu, Liliana Velea, Roxana Burcea

Abstract:

A number of studies show that extreme air temperature affects mortality related to cardiovascular diseases, particularly among elderly people. In Romania, the summer thermal discomfort expressed by Universal Thermal Climate Index (UTCI) is highest in the Southern part of the country, where Bucharest, the largest Romanian urban agglomeration, is also located. The urban characteristics such as high building density and reduced green areas enhance the increase of the air temperature during summer. In Bucharest, as in many other large cities, the effect of heat urban island is present and determines an increase of air temperature compared to surrounding areas. This increase is particularly important during heat wave periods in summer. In this context, the researchers performed a temperature-mortality analysis based on daily deaths related to cardiovascular diseases, recorded between 2010 and 2019 in Bucharest. The temperature-mortality relationship was modeled by applying distributed lag non-linear model (DLNM) that includes a bi-dimensional cross-basis function and flexible natural cubic spline functions with three internal knots in the 10th, 75th and 90th percentiles of the temperature distribution, for modelling both exposure-response and lagged-response dimensions. Firstly, this study applied this analysis for the present climate. Extrapolation of the exposure-response associations beyond the observed data allowed us to estimate future effects on mortality due to temperature changes under climate change scenarios and specific assumptions. We used future projections of air temperature from five numerical experiments with regional climate models included in the EURO-CORDEX initiative under the relatively moderate (RCP 4.5) and pessimistic (RCP 8.5) concentration scenarios. The results of this analysis show for RCP 8.5 an ensemble-averaged increase with 6.1% of heat-attributable mortality fraction in future in comparison with present climate (2090-2100 vs. 2010-219), corresponding to an increase of 640 deaths/year, while mortality fraction due to the cold conditions will be reduced by 2.76%, corresponding to a decrease by 288 deaths/year. When mortality data is stratified according to the age, the ensemble-averaged increase of heat-attributable mortality fraction for elderly people (> 75 years) in the future is even higher (6.5 %). These findings reveal the necessity to carefully plan urban development in Bucharest to face the public health challenges raised by the climate change. Paper Details: This work is financed by the project URCLIM which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by Ministry of Environment, Romania with co-funding by the European Union (Grant 690462). A part of this work performed by one of the authors has received funding from the European Union’s Horizon 2020 research and innovation programme from the project EXHAUSTION under grant agreement No 820655.

Keywords: cardiovascular diseases, climate change, extreme air temperature, mortality

Procedia PDF Downloads 126

Authors: Farideh Tabatabaee Yazdi, Fereshteh Falah, Alireza Vasiee

Abstract:

Introduction: Gamma-aminobutyric acid (GABA) is a non-protein amino acid that is widely present in organisms. GABA is a kind of pharmacological and biological component and its application is wide and useful. Several important physiological functions of GABA have been characterized, such as neurotransmission and induction of hypotension. GABA is also a strong secretagogue of insulin from the pancreas and effectively inhibits small airway-derived lung adenocarcinoma and tranquilizer. Many microorganisms can produce GABA, and lactic acid bacteria have been a focus of research in recent years because lactic acid bacteria possess special physiological activities and are generally regarded as safe. Among them, the Lb. Brevis produced the highest amount of GABA. The major factors affecting GABA production have been characterized, including carbon sources and glutamate concentration. The use of food industry waste to produce valuable products such as amino acids seems to be a good way to reduce production costs and prevent the waste of food resources. In a dairy factory, a high volume of sludge is produced from a separator that contains useful compounds such as growth factors, carbon, nitrogen, and organic matter that can be used by different microorganisms such as Lb.brevis as carbon and nitrogen sources. Therefore, it is a good source of GABA production. GABA is primarily formed by the irreversible α-decarboxylation reaction of L-glutamic acid or its salts, catalysed by the GAD enzyme. In the present study, this aim was achieved for the fast-growing of Lb.brevis and producing GABA, using the dairy industry sludge as a suitable growth medium. Lactobacillus Brevis strains obtained from Microbial Type Culture Collection (MTCC) were used as model strains. In order to prepare dairy sludge as a medium, sterilization should be done at 121 ° C for 15 minutes. Lb. Brevis was inoculated to the sludge media at pH=6 and incubated for 120 hours at 30 ° C. After fermentation, the supernatant solution is centrifuged and then, the GABA produced was analyzed by the Thin Layer chromatography (TLC) method qualitatively and by the high-performance liquid chromatography (HPLC) method quantitatively. By increasing the percentage of dairy sludge in the culture medium, the amount of GABA increased. Also, evaluated the growth of bacteria in this medium showed the positive effect of dairy sludge on the growth of Lb.brevis, which resulted in the production of more GABA. GABA-producing LAB offers the opportunity of developing naturally fermented health-oriented products. Although some GABA-producing LAB has been isolated to find strains suitable for different fermentations, further screening of various GABA-producing strains from LAB, especially high-yielding strains, is necessary. The production of lactic acid, bacterial gamma-aminobutyric acid, is safe and eco-friendly. The use of dairy industry waste causes enhanced environmental safety. Also provides the possibility of producing valuable compounds such as GABA. In general, dairy sludge is a suitable medium for the growth of Lactic Acid Bacteria and produce this amino acid that can reduce the final cost of it by providing carbon and nitrogen source.

Keywords: GABA, Lactobacillus, HPLC, dairy sludge

Procedia PDF Downloads 136

Authors: Anna M. Pretorius

Abstract:

The emerging markets category for portfolio investment was introduced in 1986 in an attempt to promote capital market development in less developed countries. Investors traditionally diversified their portfolios by investing in different developed markets. However, high growth opportunities forced investors to consider emerging markets as well. Examples include the rapid growth of the “Asian Tigers” during the 1980s, growth in Latin America during the 1990s and the increased interest in emerging markets during the global financial crisis. As such, portfolio flows to emerging markets have increased substantially. In 2002 7% of all equity allocations from advanced economies went to emerging markets; this increased to 20% in 2012. The stronger links between advanced and emerging markets led to increased synchronization of asset price movements. This increased level of stock market integration for emerging markets is confirmed by various empirical studies. Against the background of increased interest in emerging market assets and the increasing level of integration of emerging markets, this paper focuses on the determinants of stock market integration of emerging market countries. Various studies have linked the level of financial market integration with specific economic variables. These variables include: economic growth, local inflation, trade openness, local investment, budget surplus/ deficit, market capitalization, domestic bank credit, domestic institutional and legal environment and world interest rates. The aim of this study is to empirically investigate to what extent trade-related determinants have an impact on stock market integration. The panel data sample include data of 16 emerging market countries: Brazil, Chile, China, Colombia, Czech Republic, Hungary, India, Malaysia, Pakistan, Peru, Philippines, Poland, Russian Federation, South Africa, Thailand and Turkey for the period 1998-2011. The integration variable for each emerging stock market is calculated as the explanatory power of a multi-factor model. These factors are extracted from a large panel of global stock market returns. Trade related explanatory variables include: exports as percentage of GDP, imports as percentage of GDP and total trade as percentage of GDP. Other macroeconomic indicators – such as market capitalisation, the size of the budget deficit and the effectiveness of the regulation of the securities exchange – are included in the regressions as control variables. An initial analysis on a sample of developed stock markets could not identify any significant determinants of stock market integration. Thus the macroeconomic variables identified in the literature are much more significant in explaining stock market integration of emerging markets than stock market integration of developed markets. The three trade variables are all statistically significant at a 5% level. The market capitalisation variable is also significant while the regulation variable is only marginally significant. The global financial crisis has highlighted the urgency to better understand the link between the financial and real sectors of the economy. This paper comes to the important finding that, apart from the level of market capitalisation (as financial indicator), trade (representative of the real economy) is a significant determinant of stock market integration of countries not yet classified as developed economies.

Keywords: emerging markets, financial market integration, panel data, trade

Procedia PDF Downloads 303

Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

Abstract:

Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

Procedia PDF Downloads 138

Authors: Alena Semeradtova, Marcel Stofik, Lucie Mareckova, Petr Maly, Ondrej Stanek, Jan Maly

Abstract:

Recently, novel strategies based on so-called molecular evolution were shown to be effective for the production of various peptide ligand libraries with high affinities to molecular targets of interest comparable or even better than monoclonal antibodies. The major advantage of these peptide scaffolds is mainly their prevailing low molecular weight and simple structure. This study describes a new high-affinity binding molecules based immunesensor using a simple optical system for human serum albumin (HSA) detection as a model molecule. We present a comparison of two variants of recombinant binders based on albumin binding domain of the protein G (ABD) performed on micropatterned glass chip. Binding domains may be tailored to any specific target of interest by molecular evolution. Micropatterened glass chips were prepared using UV-photolithography on chromium sputtered glasses. Glass surface was modified by (3-aminopropyl)trietoxysilane and biotin-PEG-acid using EDC/NHS chemistry. Two variants of high-affinity binding molecules were used to detect target molecule. Firstly, a variant is based on ABD domain fused with TolA chain. This molecule is in vivo biotinylated and each molecule contains one molecule of biotin and one ABD domain. Secondly, the variant is ABD domain based on streptavidin molecule and contains four gaps for biotin and four ABD domains. These high-affinity molecules were immobilized to the chip surface via biotin-streptavidin chemistry. To eliminate nonspecific binding 1% bovine serum albumin (BSA) or 6% fetal bovine serum (FBS) were used in every step. For both variants range of measured concentrations of fluorescently labelled HSA was 0 – 30 µg/ml. As a control, we performed a simultaneous assay without high-affinity binding molecules. Fluorescent signal was measured using inverse fluorescent microscope Olympus IX 70 with COOL LED pE 4000 as a light source, related filters, and camera Retiga 2000R as a detector. The fluorescent signal from non-modified areas was substracted from the signal of the fluorescent areas. Results were presented in graphs showing the dependence of measured grayscale value on the log-scale of HSA concentration. For the TolA variant the limit of detection (LOD) of the optical immunosensor proposed in this study is calculated to be 0,20 µg/ml for HSA detection in 1% BSA and 0,24 µg/ml in 6% FBS. In the case of streptavidin-based molecule, it was 0,04 µg/ml and 0,07 µg/ml respectively. The dynamical range of the immunosensor was possible to estimate just in the case of TolA variant and it was calculated to be 0,49 – 3,75 µg/ml and 0,73-1,88 µg/ml respectively. In the case of the streptavidin-based the variant we didn´t reach the surface saturation even with the 480 ug/ml concentration and the upper value of dynamical range was not estimated. Lower value was calculated to be 0,14 µg/ml and 0,17 µg/ml respectively. Based on the obtained results, it´s clear that both variants are useful for creating the bio-recognizing layer on immunosensors. For this particular system, it is obvious that the variant based on streptavidin molecule is more useful for biosensing on glass planar surfaces. Immunosensors based on this variant would exhibit better limit of detection and wide dynamical range.

Keywords: high affinity binding molecules, human serum albumin, optical immunosensor, protein G, UV-photolitography

Procedia PDF Downloads 364

Authors: Bryana Woodard, Monica Mitchell, Kasey Harry, Ebony Washington, Megan Harris, Marcia Boyd, Regina Lynch, Daphene Baines, Surbi Bankar

Abstract:

Introduction: African Americans experience mental health illnesses (i.e., depression, anxiety, etc.) at higher rates than their white counterparts. Despite this, they utilize mental health resources less and have lower mental health literacy, perhaps due to cultural barriers- including but not limited to mistrust. Research acknowledges African Americans’ close ties to community networks, identifying these linkages as key to establishing comfort and trust. Similarly, the church has historically been a space that creates unity and community among African Americans. Studies show that longstanding academic-community partnerships with organizations, such as churches and faith-based entities, have the capability to effectively address health and mental health barriers and needs in African Americans. The importance of implementing faith-based approaches is supported in the literature, however few empirical studies exist. This project describes the First Ladies for Health and Cincinnati Children's Hospital Medical Center (CCHMC) Partnership (FLFH-CCHMC Partnership) and the implementation and assessment of an annual Mental Health Symposium, the overall aim of which was to increase mental health awareness and decrease stigma in African American communities. Methods: The specific goals of the FLFH Mental Health Symposium were to (1) Collaborate with trusted partners to build trust with community participants; (2) Increase mental health literacy and decrease mental health stigma; (3) Understand the barriers to improving mental health and improving trust; (4) Assess the short-term outcomes two months following the symposium. Data were collected through post-event and follow-up surveys using a mixed methods approach. Results: More than 100 participants attended each year with over 350 total participants over three years. 98.7% of participants were African American, 86.67% female, 11.6% male, and 11.6% LGBTQ+/non-binary; 10.5% of participants were teens, with the remainder aged 20 to 80 plus. The event was successful in achieving its goals: (1a) Eleven different speakers from 8 community and church organizations presented; (1b) 93% of participants rated the overall symposium as very good or excellent (2a) Mental health literacy significantly increased each year with over 90% of participants reporting improvement in their “understanding” and “awareness of mental health (2b) Participants 'personal stigma surrounding mental health illness decreased each year with 92.3% of participants reporting changes in their “willingness to talk about and share” mental health challenges; (3) Barriers to mental health care were identified and included social stigma, lack of trust, and the cost of care. Data were used to develop priorities and an action plan for the FLFH-CCHMC Mental Health Partnership; (4) Follow-up data showed that participants sustained benefits of the FLFH Symposium and took actionable steps (e.g., meditation, referrals, etc.). Additional quantitative and qualitative data will be shared. Conclusions: Lower rates of mental health literacy and higher rates of stigma among participants in this initiative demonstrate the importance of mental health providers building trust and partnerships in communities. Working with faith-based entities provides an opportunity to mitigate and address mental health equity in African American communities.

Keywords: community psychology, faith-based, african-american, culturally competent care, mental health equity

Procedia PDF Downloads 31

Authors: Ali Raza

Abstract:

The dynamic landscape of communication has brought about significant advancements that intersect with the realms of public health and journalism. This abstract explores the evolving synergy between these fields, highlighting how their intersection has contributed to informed societies and improved public health outcomes. In the digital age, communication plays a pivotal role in shaping public perception, policy formulation, and collective action. Public health, concerned with safeguarding and improving community well-being, relies on effective communication to disseminate information, encourage healthy behaviors, and mitigate health risks. Simultaneously, journalism, with its commitment to accurate and timely reporting, serves as the conduit through which health information reaches the masses. Advancements in communication technologies have revolutionized the ways in which public health information is both generated and shared. The advent of social media platforms, mobile applications, and online forums has democratized the dissemination of health-related news and insights. This democratization, however, brings challenges, such as the rapid spread of misinformation and the need for nuanced strategies to engage diverse audiences. Effective collaboration between public health professionals and journalists is pivotal in countering these challenges, ensuring that accurate information prevails. The synergy between public health and journalism is most evident during public health crises. The COVID-19 pandemic underscored the pivotal role of journalism in providing accurate and up-to-date information to the public. However, it also highlighted the importance of responsible reporting, as sensationalism and misinformation could exacerbate the crisis. Collaborative efforts between public health experts and journalists led to the amplification of preventive measures, the debunking of myths, and the promotion of evidence-based interventions. Moreover, the accessibility of information in the digital era necessitates a strategic approach to health communication. Behavioral economics and data analytics offer insights into human decision-making and allow tailored health messages to resonate more effectively with specific audiences. This approach, when integrated into journalism, enables the crafting of narratives that not only inform but also influence positive health behaviors. Ethical considerations emerge prominently in this alliance. The responsibility to balance the public's right to know with the potential consequences of sensational reporting underscores the significance of ethical journalism. Health journalists must meticulously source information from reputable experts and institutions to maintain credibility, thus fortifying the bridge between public health and the public. As both public health and journalism undergo transformative shifts, fostering collaboration between these domains becomes essential. Training programs that familiarize journalists with public health concepts and practices can enhance their capacity to report accurately and comprehensively on health issues. Likewise, public health professionals can gain insights into effective communication strategies from seasoned journalists, ensuring that health information reaches a wider audience. In conclusion, the convergence of public health and journalism, facilitated by communication advancements, is a cornerstone of informed societies. Effective communication strategies, driven by collaboration, ensure the accurate dissemination of health information and foster positive behavior change. As the world navigates complex health challenges, the continued evolution of this synergy holds the promise of healthier communities and a more engaged and educated public.

Keywords: public awareness, journalism ethics, health promotion, media influence, health literacy

Procedia PDF Downloads 66

Authors: Ajay Ivan

Abstract:

This paper focuses on the cultural politics of health-promotional and disease-preventive pedagogic practices in the context of the national tobacco control programme in India. Tobacco consumption is typically problematised as a paradox: tobacco poses objective health risks such as cancer and heart disease, but its production, sale and export contribute significantly to state revenue. A blanket ban on tobacco products, therefore, is infeasible though desirable. Instead, initiatives against tobacco use have prioritised awareness creation and behaviour change to reduce its demand. This paper argues that public health communication is not, as commonly assumed, an apolitical and neutral transmission of disease-preventive information. Drawing on Michel Foucault’s concept of governmentality, it examines such campaigns as techniques of disciplining people rather than coercing them to give up tobacco use, which would be both impractical and counter-productive. At the level of the population, these programmes constitute a security mechanism that reduces risks without eliminating them, so as to ensure an optimal level of public health without hampering the economy. Anti-tobacco pedagogy thus aligns with a contemporary paradigm of health that emphasises risk-assessment and lifestyle management as tools of governance, using pedagogic techniques to teach people how to be healthy. The paper analyses the pictorial health warnings on tobacco packets and anti-tobacco advertisements in movie theatres mandated by the state, along with awareness-creation messages circulated by anti-tobacco advocacy groups in India, to show how they discursively construct tobacco and its consumption as a health risk. Smoking is resignified from a pleasurable and sociable practice to a deadly addiction that jeopardises the health of those who smoke and those who passively inhale the smoke. While disseminating information about the health risks of tobacco, these initiatives employ emotional and affective techniques of persuasion to discipline tobacco users. They incite fear of death and of social ostracism to motivate behaviour change, complementing their appeals to reason. Tobacco is portrayed as a grave moral danger to the family and a detriment to the vitality of the nation, such that using it contradicts one’s duties as a parent or citizen. Awareness programmes reproduce prevailing societal assumptions about health and disease, normalcy and deviance, and proper and improper conduct. Pedagogy thus functions as an apparatus of public health governance, recruiting subjects as volunteers in their own regulation and aligning their personal goals and aspirations to the objectives of tobacco control. The paper links this calculated management of subjectivity and the self-responsibilisation of the pedagogic subject to a distinct mode of neoliberal civic governance in contemporary India. Health features prominently in this mode of governance that serves the biopolitical obligation of the state as laid down in Article 39 of the Constitution, which includes a duty to ensure the health of its citizens. Insofar as the health of individuals is concerned, the problem is how to balance this duty of the state with the fundamental right of the citizen to choose how to live. Public health pedagogy, by directing the citizen’s ‘free’ choice without unduly infringing upon it, offers a tactical solution.

Keywords: public health communication, pedagogic power, tobacco control, neoliberal governance

Procedia PDF Downloads 76

Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

Abstract:

The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

Procedia PDF Downloads 59

Authors: Amy Heaps, Amy Burns, Una McMahon-Beattie

Abstract:

Shock and fear tactics have been used to encourage consumer behaviour change within the UK regarding lifestyle choices such as smoking and alcohol abuse, yet such measures have not been applied to food labels to encourage healthier purchasing decisions. Obesity levels are continuing to rise within the UK, despite efforts made by government and charitable bodies to encourage consumer behavioural changes, which will have a positive influence on their fat, salt, and sugar intake. We know that taking extreme measures to shock consumers into behavioural changes has worked previously; for example, the anti-smoking television adverts and new standardised cigarette and tobacco packaging have reduced the numbers of the UK adult population who smoke or encouraged those who are currently trying to quit. The USA has also introduced new front-of-pack labelling, which is clear, easy to read, and includes concise health warnings on products high in fat, salt, or sugar. This model has been successful, with consumers reducing purchases of products with these warning labels present. Therefore, investigating if shock labels would have an impact on UK consumer behaviour and purchasing decisions would help to fill the gap within this research field. This study aims to develop an understanding of consumer’s initial responses to shock advertising with an interest in the perceived impact of long-term effect shock advertising on consumer food purchasing decisions, behaviour, and attitudes and will achieve this through a mixed methodological approach taken with a sample size of 25 participants ages ranging from 22 and 60. Within this research, shock mock labels were developed, including a graphic image, health warning, and get-help information. These labels were made for products (available within the UK) with large market shares which were high in either fat, salt, or sugar. The use of online focus groups and mouse-tracking experiments results helped to develop an understanding of consumer’s initial responses to shock advertising with interest in the perceived impact of long-term effect shock advertising on consumer food purchasing decisions, behaviour, and attitudes. Preliminary results have shown that consumers believe that the use of graphic images, combined with a health warning, would encourage consumer behaviour change and influence their purchasing decisions regarding those products which are high in fat, salt and sugar. Preliminary main findings show that graphic mock shock labels may have an impact on consumer behaviour and purchasing decisions, which will, in turn, encourage healthier lifestyles. Focus group results show that 72% of participants indicated that these shock labels would have an impact on their purchasing decisions. During the mouse tracking trials, this increased to 80% of participants, showing that more exposure to shock labels may have a bigger impact on potential consumer behaviour and purchasing decision change. In conclusion, preliminary results indicate that graphic shock labels will impact consumer purchasing decisions. Findings allow for a deeper understanding of initial emotional responses to these graphic labels. However, more research is needed to test the longevity of these labels on consumer purchasing decisions, but this research exercise is demonstrably the foundation for future detailed work.

Keywords: consumer behavior, decision making, labelling legislation, purchasing decisions, shock advertising, shock labelling

Procedia PDF Downloads 65

Authors: Mariyah Poonawala, Selvan Ravindran, Anuradha Vaidya

Abstract:

Despite much progress in understanding the regulatory factors and cytokines that support the maturation of the various cell lineages of the hematopoietic system, factors that govern the self-renewal and proliferation of hematopoietic stem cells (HSCs) is still a grey area of research. Hematopoietic stem cell transplantation (HSCT) has evolved over the years and gained tremendous importance in the treatment of both malignant and non-malignant diseases. However, factors such as graft rejection and multiple organ failure have challenged HSCT from time to time, underscoring the urgent need for development of milder processes for successful hematopoietic transplantation. An emerging concept in the field of stem cell biology states that the interactions between the bone-marrow micro-environment and the hematopoietic stem and progenitor cells is essential for regulation, maintenance, commitment and proliferation of stem cells. Understanding the role of mesenchymal stromal cells in modulating the functionality of HSCs is, therefore, an important area of research. Trans-resveratrol has been extensively studied for its various properties to combat and prevent cancer, diabetes and cardiovascular diseases etc. The aim of the present study was to understand the effect of trans-resveratrol on HSCs using single and co-culture systems. We have used KG1a cells since it is a well accepted hematopoietic stem cell model system. Our preliminary experiments showed that low concentrations of trans-resveratrol stimulated the HSCs to undergo proliferation whereas high concentrations of trans-resveratrol did not stimulate the cells to proliferate. We used a murine fibroblast cell line, M210B4, as a stromal feeder layer. On culturing the KG1a cells with M210B4 cells, we observed that the stimulatory as well as inhibitory effects of trans-resveratrol at low and high concentrations respectively, were enhanced. Our further experiments showed that low concentration of trans-resveratrol reduced the generation of reactive oxygen species (ROS) and nitric oxide (NO) whereas high concentrations increased the oxidative stress in KG1a cells. We speculated that perhaps the oxidative stress was imposing inhibitory effects at high concentration and the same was confirmed by performing an apoptotic assay. Furthermore, cell cycle analysis and growth kinetic experiments provided evidence that low concentration of trans-resveratrol reduced the doubling time of the cells. Our hypothesis is that perhaps at low concentration of trans-resveratrol the cells get pushed into the G0/G1 phase and re-enter the cell cycle resulting in their proliferation, whereas at high concentration the cells are perhaps arrested at G2/M phase or at cytokinesis and therefore undergo apoptosis. Liquid Chromatography-Quantitative-Time of Flight–Mass Spectroscopy (LC-Q-TOF MS) analyses indicated the presence of trans-resveratrol and its metabolite(s) in the supernatant of the co-cultured cells incubated with high concentration of trans-resveratrol. We conjecture that perhaps the metabolites of trans-resveratrol are responsible for the apoptosis observed at the high concentration. Our findings may shed light on the unsolved problems in the in vitro expansion of stem cells and may have implications in the ex vivo manipulation of HSCs for therapeutic purposes.

Keywords: co-culture system, hematopoietic micro-environment, KG1a cell line, M210B4 cell line, trans-resveratrol

Procedia PDF Downloads 253

Authors: Alena Cejkova, Martina Paldrychova, Jana Michailidu, Olga Matatkova, Jan Masak

Abstract:

Increasing the resistance of pathogenic microorganisms to many antibiotics is a serious threat to the treatment of infectious diseases and cleaning medical instruments. It should be added that the resistance of microbial populations growing in biofilms is often up to 1000 times higher compared to planktonic cells. Biofilm formation in a number of microorganisms is largely influenced by the quorum sensing regulatory mechanism. Finding external factors such as natural substances or physical processes that can interfere effectively with quorum sensing signal molecules should reduce the ability of the cell population to form biofilm and increase the effectiveness of antibiotics. The present work is devoted to the effect of chitosan as a representative of natural substances with anti-biofilm activity and non- thermal plasma (NTP) alone or in combination with polymyxin B on biofilm formation of Pseudomonas aeruginosa. Particular attention was paid to the influence of these agents on the level of quorum sensing signal molecules (acyl-homoserine lactones) during planktonic and biofilm cultivations. Opportunistic pathogenic strains of Pseudomonas aeruginosa (DBM 3081, DBM 3777, ATCC 10145, ATCC 15442) were used as model microorganisms. Cultivations of planktonic and biofilm populations in 96-well microtiter plates on horizontal shaker were used for determination of antibiotic and anti-biofilm activity of chitosan and polymyxin B. Biofilm-growing cells on titanium alloy, which is used for preparation of joint replacement, were exposed to non-thermal plasma generated by cometary corona with a metallic grid for 15 and 30 minutes. Cultivation followed in fresh LB medium with or without chitosan or polymyxin B for next 24 h. Biofilms were quantified by crystal violet assay. Metabolic activity of the cells in biofilm was measured using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) colorimetric test based on the reduction of MTT into formazan by the dehydrogenase system of living cells. Activity of N-acyl homoserine lactones (AHLs) compounds involved in the regulation of biofilm formation was determined using Agrobacterium tumefaciens strain harboring a traG::lacZ/traR reporter gene responsive to AHLs. The experiments showed that both chitosan and non-thermal plasma reduce the AHLs level and thus the biofilm formation and stability. The effectiveness of both agents was somewhat strain dependent. During the eradication of P. aeruginosa DBM 3081 biofilm on titanium alloy induced by chitosan (45 mg / l) there was an 80% decrease in AHLs. Applying chitosan or NTP on the P. aeruginosa DBM 3777 biofilm did not cause a significant decrease in AHLs, however, in combination with both (chitosan 55 mg / l and NTP 30 min), resulted in a 70% decrease in AHLs. Combined application of NTP and polymyxin B allowed reduce antibiotic concentration to achieve the same level of AHLs inhibition in P. aeruginosa ATCC 15442. The results shown that non-thermal plasma and chitosan have considerable potential for the eradication of highly resistant P. aeruginosa biofilms, for example on medical instruments or joint implants.

Keywords: anti-biofilm activity, chitosan, non-thermal plasma, opportunistic pathogens

Procedia PDF Downloads 198

Authors: Arti Singh, Carolyn Jenkins, Oyedunni S. Arulogun, Mayowa O. Owolabi, Fred S. Sarfo, Bruce Ovbiagele, Enzinne Sylvia

Abstract:

Background: Stroke, the leading cause of adult-onset disability and the second leading cause of death, is a major public health concern particularly pertinent in Sub-Saharan Africa (SSA), where nearly 80% of all global stroke mortalities occur. The Stroke Investigative Research and Education Network (SIREN) seeks to comprehensively characterize the genomic, sociocultural, economic, and behavioral risk factors for stroke and to build effective teams for research to address and decrease the burden of stroke and other non communicable diseases in SSA. One of the first steps to address this goal was to effectively engage the communities that suffer the high burden of disease in SSA. This study describes how the SIREN project engaged six sites in Ghana and Nigeria over the past three years, describing the community engagement activities that have arisen since inception. Aim: The aim of community engagement (CE) within SIREN is to elucidate information about knowledge, attitudes, beliefs, and practices (KABP) about stroke and its risk factors from individuals of African ancestry in SSA, and to educate the community about stroke and ways to decrease disabilities and deaths from stroke using socioculturally appropriate messaging and messengers. Methods: Community Advisory Board (CABs), Focus Group Discussions (FGDs) and community outreach programs. Results: 27 FGDs with 168 participants including community heads, religious leaders, health professionals and individuals with stroke among others, were conducted, and over 60 CE outreaches have been conducted within the SIREN performance sites. Over 5,900 individuals have received education on cardiovascular risk factors and about 5,000 have been screened for cardiovascular risk factors during the outreaches. FGDs and outreach programs indicate that knowledge of stroke, as well as risk factors and follow-up evidence-based care is limited and often late. Other findings include: 1) Most recognize hypertension as a major risk factor for stroke. 2) About 50% report that stroke is hereditary and about 20% do not know organs affected by stroke. 3) More than 95% willing to participate in genetic testing research and about 85% willing to pay for testing and recommend the test to others. 4) Almost all indicated that genetic testing could help health providers better treat stroke and help scientists better understand the causes of stroke. The CABs provided stakeholder input into SIREN activities and facilitated collaborations among investigators, community members and stakeholders. Conclusion: The CE core within SIREN is a first-of-its kind public outreach engagement initiative to evaluate and address perceptions about stroke and genomics by patients, caregivers, and local leaders in SSA and has implications as a model for assessment in other high-stroke risk populations. SIREN’s CE program uses best practices to build capacity for community-engaged research, accelerate integration of research findings into practice and strengthen dynamic community-academic partnerships within our communities. CE has had several major successes over the past three years including our multi-site collaboration examining the KABP about stroke (symptoms, risk factors, burden) and genetic testing across SSA.

Keywords: community advisory board, community engagement, focus groups, outreach, SSA, stroke

Procedia PDF Downloads 424

Authors: Adine Gericke, Jiri Militky, Mohanapriya Venkataraman

Abstract:

Mohair, obtained from the Angora goat, is a luxury fiber and recognized as one of the best quality natural fibers. Expansion of the use of mohair into technical and functional textile products necessitates the need for a better understanding of how the use of mohair in fabrics will impact on its thermo-physiological comfort related properties. Despite its popularity, very little information is available on the quantification of the thermal and moisture management properties of mohair fabrics. This study investigated the effect of fibrous matter composition and fabric structural parameters on conductive and convective heat transfers to attain more information on the thermal comfort properties of mohair fabrics. Dry heat transfer through textiles may involve conduction through the fibrous phase, radiation through fabric interstices and convection of air within the structure. Factors that play a major role in heat transfer by conduction are fabric areal density (g/m2) and derived quantities such as cover factor and porosity. Convective heat transfer through fabrics is found in environmental conditions where there is wind-flow or the object is moving (e.g. running or walking). The thermal comfort properties of mohair fibers were objectively evaluated firstly in comparison with other textile fibers and secondly in a variety of fabric structures. Two sample sets were developed for this purpose, with fibre content, yarn structure and fabric design as main variables. SEM and microscopic images were obtained to closely examine the physical structures of the fibers and fabrics. Thermal comfort properties such as thermal resistance and thermal conductivity, as well as fabric thickness, were measured on the well-known Alambeta test instrument. Clothing insulation (clo) was calculated from the above. The thermal properties of fabrics under heat convection was evaluated using a laboratory model device developed at the Technical University of Liberec (referred to as the TP2-instrument). The effects of the different variables on fabric thermal comfort properties were analyzed statistically using TIBCO Statistica Software. The results showed that fabric structural properties, specifically sample thickness, played a significant role in determining the thermal comfort properties of the fabrics tested. It was found that regarding thermal resistance related to conductive heat flow, the effect of fiber type was not always statistically significant, probably as a result of the amount of trapped air within the fabric structure. The very low thermal conductivity of air, compared to that of the fibers, had a significant influence on the total conductivity and thermal resistance of the samples. This was confirmed by the high correlation of these factors with sample thickness. Regarding convective heat flow, the most important factor influencing the ability of the fabric to allow dry heat to move through the structure, was again fabric thickness. However, it would be wrong to totally disregard the effect of fiber composition on the thermal resistance of textile fabrics. In this study, the samples containing mohair or mohair/wool were consistently thicker than the others even though weaving parameters were kept constant. This can be ascribed to the physical properties of the mohair fibers that renders it exceptionally well towards trapping air among fibers (in a yarn) as well as among yarns (inside a fabric structure). The thicker structures trap more air to provide higher thermal insulation, but also prevent the free flow of air that allow thermal convection.

Keywords: mohair fabrics, convective heat transfer, thermal comfort properties, thermal resistance

Procedia PDF Downloads 139

Authors: Lesly Y Carmona-Sarabia, Luisa Barraza-Vergara, Vilmalí López-Mejías, Wandaliz Torres-García, Maribella Domenech-Garcia, Madeline Torres-Lugo

Abstract:

Biosensors are used in many applications providing real-time monitoring to treat long-term conditions. Thus, understanding the physicochemical properties and biological side effects on the skin of polymers (e. g., poly(methyl methacrylate), PMMA) employed in the fabrication of wearable biosensors is crucial for the selection of manufacturing materials within this field. The PMMA (hydrophobic and thermoplastic polymer) is commonly employed as a coating material or substrate in the fabrication of wearable devices. The cytotoxicityof PMMA (including residual monomers or degradation products) on the skin, in terms of cells and tissue, is required to prevent possible adverse effects (cell death, skin reactions, sensitization) on human health. Within this work, accelerated aging of PMMA (Mw ~ 15000) through thermal and photochemical degradation was under-taken. The accelerated aging of PMMA was carried out by thermal (200°C, 1h) and photochemical degradation (UV-Vis, 8-15d) adapted employing ISO protocols (ISO-10993-12, ISO-4892-1:2016, ISO-877-1:2009, ISO-188: 2011). In addition, in vitro cytotoxicity evaluation of PMMA degradation products was performed using NIH3T3 fibroblast cells to assess the response of skin tissues (in terms of cell viability) exposed with polymers utilized to manufacture wearable biosensors, such as PMMA. The PMMA (Mw ~ 15000) before and after accelerated aging experiments was characterized by thermal gravimetric analysis (TGA), differential scanning calorimetric (DSC), powder X-ray diffractogram (PXRD), and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) to determine and verify the successful degradation of this polymer under the specific conditions previously mention. The degradation products were characterized through nuclear magnetic resonance (NMR) to identify possible byproducts generated after the accelerated aging. Results demonstrated a percentage (%) weight loss between 1.5-2.2% (TGA thermographs) for PMMA after accelerated aging. The EDS elemental analysis reveals a 1.32 wt.% loss of carbon for PMMA after thermal degradation. These results might be associated with the amount (%) of PMMA degrade after the accelerated aging experiments. Furthermore, from the thermal degradation products was detected the presence of the monomer and methyl formate (low concentrations) and a low molecular weight radical (·COOCH3) in higher concentrations by NMR. In the photodegradation products, methyl formate was detected in higher concentrations. These results agree with the proposed thermal or photochemical degradation mechanisms found in the literature.1,2 Finally, significant cytotoxicity on the NIH3T3 cells was obtained for the thermal and photochemical degradation products. A decrease in cell viability by > 90% (stock solutions) was observed. It is proposed that the presence of byproducts (e.g. methyl formate or radicals such as ·COOCH₃) from the PMMA degradation might be responsible for the cytotoxicity observed in the NIH3T3 fibroblast cells. Additionally, experiments using skin models will be employed to compare with the NIH3T3 fibroblast cells model.

Keywords: biosensors, polymer, skin irritation, degradation products, cell viability

Procedia PDF Downloads 138

Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

Abstract:

Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

Procedia PDF Downloads 181

Authors: D. Mokatsanyane, J. Jansen Van Rensburg

Abstract:

This paper analyses the influence and impact of COVID-19 on major agricultural commodity prices in South Africa. According to a World Bank report, the agricultural sector in South Africa has been unable to reduce the domestic food crisis that has been occurring over the past years, hence the increased rate of poverty, which is currently at 55.5 percent as of April 2020. Despite the significance of this sector, empirical findings concluded that the agricultural sector now accounts for 1.88 percent of South Africa's gross domestic product (GDP). Suggesting that the agricultural sector's contribution to the economy has diminished. Despite the low contribution to GDP, this primary sector continues to play an essential role in the economy. Over the past years, multiple factors have contributed to the soaring commodities prices, namely, climate shocks, biofuel demand, demand and supply shocks, the exchange rate, speculation in commodity derivative markets, trade restrictions, and economic growth. The COVID-19 outbursts have currently disturbed the supply and demand of staple crops. To address the disruption, the government has exempted the agricultural sector from closure and restrictions on movement. The spread of COVID-19 has caused turmoil all around the world, but mostly in developing countries. According to Statistic South Africa, South Africa's economy decreased by seven percent in 2020. Consequently, this has arguably made the agricultural sector the most affected sector since slumped economic growth negatively impacts food security, trade, farm livelihood, and greenhouse gas emissions. South Africa is sensitive to the fruitfulness of global food chains. Restrictions in trade, reinforced sanitary control systems, and border controls have influenced food availability and prices internationally. The main objective of this study is to evaluate the behavior of agricultural commodity prices pre-and during-COVID to determine the impact of volatility drivers on these crops. Historical secondary data of spot prices for the top five major commodities, namely white maize, yellow maize, wheat, soybeans, and sunflower seeds, are analysed from 01 January 2017 to 1 September 2021. The timeframe was chosen to capture price fluctuations between pre-COVID-19 (01 January 2017 to 23 March 2020) and during-COVID-19 (24 March 2020 to 01 September 2021). The Generalised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be used to measure the influence of price fluctuations. The results reveal that the commodity market has been experiencing volatility at different points. Extremely high volatility is represented during the first quarter of 2020. During this period, there was high uncertainty, and grain prices were very volatile. Despite the influence of COVID-19 on agricultural prices, the demand for these commodities is still existing and decent. During COVID-19, analysis indicates that prices were low and less volatile during the pandemic. The prices and returns of these commodities were low during COVID-19 because of the government's actions to respond to the virus's spread, which collapsed the market demand for food commodities.

Keywords: commodities market, commodity prices, generalised autoregressive conditional heteroscedasticity (GARCH), Price volatility, SAFEX

Procedia PDF Downloads 168

Authors: Aditya Sharma

Abstract:

Profits earned from relative strength strategy of zero-cost portfolio i.e. taking long position in winner stocks and short position in loser stocks from recent past are termed as momentum profits. In recent times, there has been lot of controversy and concern about sources of momentum profits, since the existence of these profits acts as an evidence of earning non-normal returns from publicly available information directly contradicting Efficient Market Hypothesis. Literature review reveals conflicting theories and differing evidences on sources of momentum profits. This paper aims at re-examining the sources of momentum profits in Indian capital markets. The study focuses on assessing the effect of fundamental as well as behavioral sources in order to understand the role of investor behavior in stock returns and suggest (if any) improvements to existing behavioral asset pricing models. This Paper adopts calendar time methodology to calculate momentum profits for 6 different strategies with and without skipping a month between ranking and holding period. For each J/K strategy, under this methodology, at the beginning of each month t stocks are ranked on past j month’s average returns and sorted in descending order. Stocks in upper decile are termed winners and bottom decile as losers. After ranking long and short positions are taken in winner and loser stocks respectively and both portfolios are held for next k months, in such manner that at any given point of time we have K overlapping long and short portfolios each, ranked from t-1 month to t-K month. At the end of period, returns of both long and short portfolios are calculated by taking equally weighted average across all months. Long minus short returns (LMS) are momentum profits for each strategy. Post testing for momentum profits, to study the role market risk plays in momentum profits, CAPM and Fama French three factor model adjusted LMS returns are calculated. In the final phase of studying sources, decomposing methodology has been used for breaking up the profits into unconditional means, serial correlations, and cross-serial correlations. This methodology is unbiased, can be used with the decile-based methodology and helps to test the effect of behavioral and fundamental sources altogether. From all the analysis, it was found that momentum profits do exist in Indian capital markets with market risk playing little role in defining them. Also, it was observed that though momentum profits have multiple sources (risk, serial correlations, and cross-serial correlations), cross-serial correlations plays a major role in defining these profits. The study revealed that momentum profits do have multiple sources however, cross-serial correlations i.e. the effect of returns of other stocks play a major role. This means that in addition to studying the investors` reactions to the information of the same firm it is also important to study how they react to the information of other firms. The analysis confirms that investor behavior does play an important role in stock returns and incorporating both the aspects of investors’ reactions in behavioral asset pricing models help make then better.

Keywords: investor behavior, momentum effect, sources of momentum, stock returns

Procedia PDF Downloads 299

Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

Abstract:

Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of biomass platform, comprising a potential pool of hydrogen energy that stands as a new energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need of in-situ H2 production, which plays a key role in the hydrogenation reactions of biomass into higher value components. It is reported elsewhere in literature that catalytic decomposition of FA is usually performed in poorly designed setup using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. it work suggests an approach that integrates designing a novel catalyst featuring magnetic property with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H2 gas from FA. Using ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under inert medium. Through a novel approach, FA is charged into the reactor via high-pressure positive displacement pump at steady state conditions. The produced gas (H2+CO2) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The novelty of this work lies in designing a very responsive catalyst, pumping consistent amount of FA into a sealed reactor running at steady state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at lower temperature range (35-50°C) yielded more gas while the catalyst loading and Pd doping wt.% were found to be the most significant factors with a P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

Procedia PDF Downloads 49

Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

Abstract:

Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

Procedia PDF Downloads 131

Authors: Lily Ranjbar, Haori Yang

Abstract:

Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

Procedia PDF Downloads 88

Authors: Caroline Smith, Professor Debi Bhattacharya, Sion Scott

Abstract:

Introduction: Oropharyngeal Dysphagia (OD) effects around 15% of older people, however it is often unrecognised and under diagnosed until they are hospitalised. There is a need for primary care healthcare practitioners (HCPs) to assume a proactive role in identifying and managing OD to prevent adverse outcomes such as aspiration pneumonia. Understanding the determinants of primary care HCPs undertaking this new behaviour provides the intervention targets for addressing. This realist review, underpinned by the Theoretical Domains Framework (TDF), aims to synthesise relevant literature and develop programme theories to understand what interventions work, how they work and under what circumstances to facilitate HCPs to prevent harm from OD. Combining realist methodology with behavioural science will permit conceptualisation of intervention components as theoretical behavioural constructs, thus informing the design of a future behaviour change intervention. Furthermore, through the TDF’s linkage to a taxonomy of behaviour change techniques, we will identify corresponding behaviour change techniques to include in this intervention. Methods & analysis: We are following the five steps for undertaking a realist review: 1) clarify the scope 2) Literature search 3) appraise and extract data 4) evidence synthesis 5) evaluation. We have searched Medline, Google scholar, PubMed, EMBASE, CINAHL, AMED, Scopus and PsycINFO databases. We are obtaining additional evidence through grey literature, snowball sampling, lateral searching and consulting the stakeholder group. Literature is being screened, evaluated and synthesised in Excel and Nvivo. We will appraise evidence in relation to its relevance and rigour. Data will be extracted and synthesised according to its relation to Initial programme theories (IPTs). IPTs were constructed after the preliminary literature search, informed by the TDF and with input from a stakeholder group of patient and public involvement advisors, general practitioners, speech and language therapists, geriatricians and pharmacists. We will follow the Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) quality and publication standards to report study results. Results: In this ongoing review our search has identified 1417 manuscripts with approximately 20% progressing to full text screening. We inductively generated 10 IPTs that hypothesise practitioners require: the knowledge to spot the signs and symptoms of OD; the skills to provide initial advice and support; and access to resources in their working environment to support them conducting these new behaviours. We mapped the 10 IPTs to 8 TDF domains and then generated a further 12 IPTs deductively using domain definitions to fulfil the remaining 6 TDF domains. Deductively generated IPTs broadened our thinking to consider domains such as ‘Emotion,’ ‘Optimism’ and ‘Social Influence’, e.g. If practitioners perceive that patients, carers and relatives expect initial advice and support, then they will be more likely to provide this, because they will feel obligated to do so. After prioritisation with stakeholders using a modified nominal group technique approach, a maximum of 10 IPTs will progress to test against the literature.

Keywords: behaviour change, deglutition disorders, primary healthcare, realist review

Procedia PDF Downloads 81