Search results for: enhancement of bioavailability

Authors: Kanchan Mondal, Adam Sims, Madhav Soti, Jitendra Gautam, David Carron

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Fischer-Tropsch (FT) synthesis is a complex series of heterogeneous reactions between CO and H2 molecules (present in the syngas) on the surface of an active catalyst (Co, Fe, Ru, Ni, etc.) to produce gaseous, liquid, and waxy hydrocarbons. This product is composed of paraffins, olefins, and oxygenated compounds. The key challenge in applying the Fischer-Tropsch process to produce transportation fuels is to make the capital and production costs economically feasible relative to the comparative cost of existing petroleum resources. To meet this challenge, it is imperative to enhance the CO conversion while maximizing carbon selectivity towards the desired liquid hydrocarbon ranges (i.e. reduction in CH4 and CO2 selectivities) at high throughputs. At the same time, it is equally essential to increase the catalyst robustness and longevity without sacrificing catalyst activity. This paper focuses on process development to achieve the above. The paper describes the influence of operating parameters on Fischer Tropsch synthesis (FTS) from coal derived syngas in supercritical carbon dioxide (ScCO2). In addition, the unreacted gas and solvent recycle was incorporated and the effect of unreacted feed recycle was evaluated. It was expected that with the recycle, the feed rate can be increased. The increase in conversion and liquid selectivity accompanied by the production of narrower carbon number distribution in the product suggest that higher flow rates can and should be used when incorporating exit gas recycle. It was observed that this process was capable of enhancing the hydrocarbon selectivity (nearly 98 % CO conversion), reducing improving the carbon efficiency from 17 % to 51 % in a once through process and further converting 16 % CO2 to liquid with integrated recycle of the product gas stream and increasing the life of the catalyst. Catalyst robustness enhancement has been attributed to the absorption of heat of reaction by the compressed CO2 which reduced the formation of hotspots and the dissolution of waxes by the CO2 solvent which reduced the blinding of active sites. In addition, the recycling the product gas stream reduced the reactor footprint to one-fourth of the once through size and product fractionation utilizing the solvent effects of supercritical CO2 were realized. In addition to the negative CO2 selectivities, methane production was also inhibited and was limited to less than 1.5%. The effect of the process conditions on the life of the catalysts will also be presented. Fe based catalysts are known to have a high proclivity for producing CO2 during FTS. The data of the product spectrum and selectivity on Co and Fe-Co based catalysts as well as those obtained from commercial sources will also be presented. The measurable decision criteria were the increase in CO conversion at H2:CO ratio of 1:1 (as commonly found in coal gasification product stream) in supercritical phase as compared to gas phase reaction, decrease in CO2 and CH4 selectivity, overall liquid product distribution, and finally an increase in the life of the catalysts.

Keywords: carbon efficiency, Fischer Tropsch synthesis, low GHG, pressure tunable fractionation

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Authors: Stephen Kyakulumbye, Vivian Kobusingye

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Generally, World over, COVID-19 has had adverse effects on all sectors but with more debilitating effects on the education sector. After reactive lockdowns, education institutions that could continue teaching and learning had to go a distance mediated by digital technological tools. In Uganda, the Ministry of Education thereby issued COVID-19 Online Distance E-learning (ODeL) emergent guidelines. Despite such guidelines, academic institutions in Uganda and similar developing contexts with academically constrained resource environments were caught off-guard and ill-prepared to transform from face-to-face learning to online distance learning mode. Most academic institutions that migrated spontaneously did so with no deliberate tools, systems, strategies, or software to cause active, meaningful, and engaging learning for students. By experience, most of these academic institutions shifted to Zoom and WhatsApp and instead conducted online teaching in real-time than blended synchronous and asynchronous tools. This paper provides students’ experiences while blending synchronous and asynchronous content-creating and learning tools within a technological resource-constrained environment to navigate in such a challenging Uganda context. These conceptual case-based findings, using experience from Uganda Christian University (UCU), point at the design of learning activities with two certain characteristics, the enhancement of synchronous learning technologies with asynchronous ones to mitigate the challenge of system breakdown, passive learning to active learning, and enhances the types of presence (social, cognitive and facilitatory). The paper, both empirical and experiential in nature, uses online experiences from third-year students in Bachelor of Business Administration student lectured using asynchronous text, audio, and video created with Open Broadcaster Studio software and compressed with Handbrake, all open-source software to mitigate disk space and bandwidth usage challenges. The synchronous online engagements with students were a blend of zoom or BigBlueButton, to ensure that students had an alternative just in case one failed due to excessive real-time traffic. Generally, students report that compared to their previous face-to-face lectures, the pre-recorded lectures via Youtube provided them an opportunity to reflect on content in a self-paced manner, which later on enabled them to engage actively during the live zoom and/or BigBlueButton real-time discussions and presentations. The major recommendation is that lecturers and teachers in a resource-constrained environment with limited digital resources like the internet and digital devices should harness this approach to offer students access to learning content in a self-paced manner and thereby enabling reflective active learning through reflective and high-order thinking.

Keywords: synchronous learning, asynchronous learning, active learning, reflective learning, resource-constrained environment

Procedia PDF Downloads 104

Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: land use, spatial resolution, WRF-Chem, air quality assessment

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Authors: Onada Olawale Ahmed

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As the intensification of aquaculture production increases on global scale, the growing concern of fish farmers around the world is related to cost of fish production, where cost of feeding takes substantial percentage. Fishmeal (FM) is one of the most expensive ingredients, and its high dependence in aqua-feed production translates to high cost of feeding of stocked fish. However, to reach a sustainable aquaculture, new alternative protein sources including cheaper plant or animal origin proteins are needed to be introduced for stable aqua-feed production. Spirulina is a cyanobacterium that has good nutrient profile that could be useful in aquaculture. This review therefore emphasizes on the nutritional value of Spirulina as a potential replacement of FM in aqua-feed. Spirulina is a planktonic photosynthetic filamentous cyanobacterium that forms massive populations in tropical and subtropical bodies of water with high levels of carbonate and bicarbonate. Spirulina grows naturally in nutrient rich alkaline lake with water salinity ( > 30 g/l) and high pH (8.5–11.0). Its artificial production requires luminosity (photo-period 12/12, 4 luxes), temperature (30 °C), inoculum, water stirring device, dissolved solids (10–60 g/litre), pH (8.5– 10.5), good water quality, and macro and micronutrient presence (C, N, P, K, S, Mg, Na, Cl, Ca and Fe, Zn, Cu, Ni, Co, Se). Spirulina has also been reported to grow on agro-industrial waste such as sugar mill waste effluent, poultry industry waste, fertilizer factory waste, and urban waste and organic matter. Chemical composition of Spirulina indicates that it has high nutritional value due to its content of 55-70% protein, 14-19% soluble carbohydrate, high amount of polyunsaturated fatty acids (PUFAs), 1.5–2.0 percent of 5–6 percent total lipid, all the essential minerals are available in spirulina which contributes about 7 percent (average range 2.76–3.00 percent of total weight) under laboratory conditions, β-carotene, B-group vitamin, vitamin E, iron, potassium and chlorophyll are also available in spirulina. Spirulina protein has a balanced composition of amino acids with concentration of methionine, tryptophan and other amino acids almost similar to those of casein, although, this depends upon the culture media used. Positive effects of spirulina on growth, feed utilization and stress and disease resistance of cultured fish have been reported in earlier studies. Spirulina was reported to replace up to 40% of fishmeal protein in tilapia (Oreochromis mossambicus) diet and even higher replacement of fishmeal was possible in common carp (Cyprinus carpio), partial replacement of fish meal with spirulina in diets for parrot fish (Oplegnathus fasciatus) and Tilapia (Orechromis niloticus) has also been conducted. Spirulina have considerable potential for development, especially as a small-scale crop for nutritional enhancement and health improvement of fish. It is important therefore that more research needs to be conducted on its production, inclusion level in aqua-feed and its possible potential use of aquaculture.

Keywords: aquaculture, spirulina, fish nutrition, fish feed

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Authors: Lia Marchi, Ernesto Antonini

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The impact of industrial sites on people’s living environment both involves detrimental effects on the ecosystem and perceptual-aesthetic interferences with the scenery. These, in turn, affect the economic and social value of the landscape, as well as the wellbeing of workers and local communities. Given the diffusion of the phenomenon and the relevance of its effects, it emerges the need for a joint approach to assess and thus mitigate the impact of factories on the landscape –being this latest assumed as the result of the action and interaction of natural and human factors. However, the impact assessment tools suitable for the purpose are quite heterogeneous and mostly monodisciplinary. On the one hand, green building rating systems (GBRSs) are increasingly used to evaluate the performance of manufacturing sites, mainly by quantitative indicators focused on environmental issues. On the other hand, methods to detect the visual and social impact of factories on the landscape are gradually emerging in the literature, but they generally adopt only qualitative gauges. The research addresses the integration of the environmental impact assessment and the perceptual-aesthetic interferences of factories on the landscape. The GBRSs model is assumed as a reference since it is adequate to simultaneously investigate different topics which affect sustainability, returning a global score. A critical analysis of GBRSs relevant to industrial facilities has led to select the U.S. GBC LEED protocol as the most suitable to the scope. A revision of LEED v4 Building Design+Construction has then been provided by including specific indicators to measure the interferences of manufacturing sites with the perceptual-aesthetic and social aspects of the territory. To this end, a new impact category was defined, namely ‘PA - Perceptual-aesthetic aspects’, comprising eight new credits which are specifically designed to assess how much the buildings are in harmony with their surroundings: these investigate, for example the morphological and chromatic harmonization of the facility with the scenery or the site receptiveness and attractiveness. The credits weighting table was consequently revised, according to the LEED points allocation system. As all LEED credits, each new PA credit is thoroughly described in a sheet setting its aim, requirements, and the available options to gauge the interference and get a score. Lastly, each credit is related to mitigation tactics, which are drawn from a catalogue of exemplary case studies, it also developed by the research. The result is a modified LEED scheme which includes compatibility with the landscape within the sustainability assessment of the industrial sites. The whole system consists of 10 evaluation categories, which contain in total 62 credits. Lastly, a test of the tool on an Italian factory was performed, allowing the comparison of three mitigation scenarios with increasing compatibility level. The study proposes a holistic and viable approach to the environmental impact assessment of factories by a tool which integrates the multiple involved aspects within a worldwide recognized rating protocol.

Keywords: environmental impact, GBRS, landscape, LEED, sustainable factory

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Authors: Jovana Grahovac, Ivana Pajcin, Natasa Lukic, Jelena Dodic, Aleksandar Jokic

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To obtain purified biomass to be used in the plant pathogen biocontrol or as soil biofertilizer, it is necessary to eliminate residual broth components at the end of the fermentation process. The main drawback of membrane separation techniques is permeate flux decline due to the membrane fouling. Fouling mitigation measures increase the pressure drop along membrane channel due to the increased resistance to flow of the feed suspension, thus increasing the hydraulic power drop. At the same time, these measures lead to an increase in the permeate flux due to the reduced resistance of the filtration cake on the membrane surface. Because of these opposing effects, the energy efficiency of fouling mitigation measures is limited, and the justification of its application is provided by information on a reducing specific energy consumption compared to a case without any measures employed. In this study, the influence of static mixer (Kenics) and air-sparging (two-phase flow) on reduction of specific energy consumption (ER) was investigated. Cultivation Bacillus velezensis was carried out in the 3-L bioreactor (Biostat® Aplus) containing 2 L working volume with two parallel Rushton turbines and without internal baffles. Cultivation was carried out at 28 °C on at 150 rpm with an aeration rate of 0.75 vvm during 96 h. The experiments were carried out in a conventional cross-flow microfiltration unit. During experiments, permeate and retentate were recycled back to the broth vessel to simulate continuous process. The single channel ceramic membrane (TAMI Deutschland) used had a nominal pore size 200 nm with the length of 250 mm and an inner/external diameter of 6/10 mm. The useful membrane channel surface was 4.33×10⁻³ m². Air sparging was brought by the pressurized air connected by a three-way valve to the feed tube by a simple T-connector without diffusor. The different approaches to flux improvement are compared in terms of energy consumption. Reduction of specific energy consumption compared to microfiltration without fouling mitigation is around 49% and 63%, for use of two-phase flow and a static mixer, respectively. In the case of a combination of these two fouling mitigation methods, ER is 60%, i.e., slightly lower compared to the use of turbulence promoter alone. The reason for this result can be found in the fact that flux increase is more affected by the presence of a Kenics static mixer while sparging results in an increase of energy used during microfiltration. By comparing combined method with turbulence promoter flux enhancement method ER is negative (-7%) which can be explained by increased power consumption for air flow with moderate contribution to the flux increase. Another confirmation for this fact can be found by comparing energy consumption values for combined method with energy consumption in the case of two-phase flow. In this instance energy reduction (ER) is 22% that demonstrates that turbulence promoter is more efficient compared to two phase flow. Antimicrobial activity of Bacillus velezensis biomass against phytopathogenic isolates Xanthomonas campestris was preserved under different fouling reduction methods.

Keywords: Bacillus velezensis, microfiltration, static mixer, two-phase flow

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Authors: Andrea Ghermandi

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Natural treatment systems such as constructed wetlands and waste stabilization ponds are increasingly used to treat water and wastewater from a variety of sources, including stormwater and polluted surface water. The provision of ancillary benefits in the form of cultural ecosystem services makes these systems unique among water and wastewater treatment technologies and greatly contributes to determine their potential role in promoting sustainable water management practices. A quantitative analysis of these benefits, however, has been lacking in the literature. Here, a critical assessment of the recreational and educational benefits in natural treatment systems is provided, which combines observed public use from a survey of managers and operators with estimated public use as obtained using geotagged photos from social media as a proxy for visitation rates. Geographic Information Systems (GIS) are used to characterize the spatial boundaries of 273 natural treatment systems worldwide. Such boundaries are used as input for the Application Program Interfaces (APIs) of two popular photo-sharing websites (Flickr and Panoramio) in order to derive the number of photo-user-days, i.e., the number of yearly visits by individual photo users in each site. The adequateness and predictive power of four univariate calibration models using the crowdsourced data as a proxy for visitation are evaluated. A high correlation is found between photo-user-days and observed annual visitors (Pearson's r = 0.811; p-value < 0.001; N = 62). Standardized Major Axis (SMA) regression is found to outperform Ordinary Least Squares regression and count data models in terms of predictive power insofar as standard verification statistics – such as the root mean square error of prediction (RMSEP), the mean absolute error of prediction (MAEP), the reduction of error (RE), and the coefficient of efficiency (CE) – are concerned. The SMA regression model is used to estimate the intensity of public use in all 273 natural treatment systems. System type, influent water quality, and area are found to statistically affect public use, consistently with a priori expectations. Publicly available information regarding the home location of the sampled visitors is derived from their social media profiles and used to infer the distance they are willing to travel to visit the natural treatment systems in the database. Such information is analyzed using the travel cost method to derive monetary estimates of the recreational benefits of the investigated natural treatment systems. Overall, the findings confirm the opportunities arising from an integrated design and management of natural treatment systems, which combines the objectives of water quality enhancement and provision of cultural ecosystem services through public use in a multi-functional approach and compatibly with the need to protect public health.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, waste stabilization ponds

Procedia PDF Downloads 157

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

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Authors: Dayron Camilo Bermudez Mendoza

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Road transportation is a significant source of externalities, notably in terms of environmental degradation and the emission of pollutants. These emissions adversely affect public health, attributable to criteria pollutants like particulate matter (PM2.5 and PM10) and carbon monoxide (CO), and also contribute to climate change through the release of greenhouse gases, such as carbon dioxide (CO2). It is, therefore, crucial to quantify the emissions from mobile sources and develop a methodological framework for their economic valuation, aiding in the assessment of associated costs and informing policy decisions. The forthcoming congress will shed light on the externalities of transportation in Bogotá, showcasing methodologies and findings from the construction of emission inventories and their spatial analysis within the city. This research focuses on the economic valuation of emissions from mobile sources in Bogotá, employing methods like hedonic pricing and contingent valuation. Conducted within the urban confines of Bogotá, the study leverages demographic, transportation, and emission data sourced from the Mobility Survey, official emission inventories, and tailored estimates and measurements. The use of hedonic pricing and contingent valuation methodologies facilitates the estimation of the influence of transportation emissions on real estate values and gauges the willingness of Bogotá's residents to invest in reducing these emissions. The findings are anticipated to be instrumental in the formulation and execution of public policies aimed at emission reduction and air quality enhancement. In compiling the emission inventory, innovative data sources were identified to determine activity factors, including information from automotive diagnostic centers and used vehicle sales websites. The COPERT model was utilized to ascertain emission factors, requiring diverse inputs such as data from the national transit registry (RUNT), OpenStreetMap road network details, climatological data from the IDEAM portal, and Google API for speed analysis. Spatial disaggregation employed GIS tools and publicly available official spatial data. The development of the valuation methodology involved an exhaustive systematic review, utilizing platforms like the EVRI (Environmental Valuation Reference Inventory) portal and other relevant sources. The contingent valuation method was implemented via surveys in various public settings across the city, using a referendum-style approach for a sample of 400 residents. For the hedonic price valuation, an extensive database was developed, integrating data from several official sources and basing analyses on the per-square meter property values in each city block. The upcoming conference anticipates the presentation and publication of these results, embodying a multidisciplinary knowledge integration and culminating in a master's thesis.

Keywords: economic valuation, transport economics, pollutant emissions, urban transportation, sustainable mobility

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Authors: Bosiacki Mateusz, Anna Lubkowska, Dariusz Chlubek, Irena Baranowska-Bosiacka

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Exposure to cold temperatures can be considered a stressor that can lead to adaptive responses. The present study hypothesized the possibility of a positive effect of cold water exercise on mitochondrial biogenesis and muscle energy metabolism in aging rats. The purpose of this study was to evaluate the effects of cold water exercise on energy status, purine compounds, and mitochondrial biogenesis in the muscles of aging rats as indicators of the effects of cold water exercise and their usefulness in monitoring adaptive changes. The study was conducted on 64 aging rats of both sexes, 15 months old at the time of the experiment. The rats (male and female separately) were randomly assigned to the following study groups: control, sedentary animals; 5°C groups animals - training swimming in cold water at 5°C; 36°C groups - animals training swimming in water at thermal comfort temperature. The study was conducted with the approval of the Local Ethical Committee for Animal Experiments. The animals in the experiment were subjected to swimming training for 9 weeks. During the first week of the study, the duration of the first swimming training was 2 minutes (on the first day), increasing daily by 0.5 minutes up to 4 minutes on the fifth day of the first week. From the second to the eighth week, the swimming training was 4 minutes per day, five days a week. At the end of the study, forty-eight hours after the last swim training, the animals were dissected. In the skeletal muscle tissue of the thighs of the rats, we determined the concentrations of ATP, ADP, AMP, Ado (HPLC), PGC-1a protein expression (Western blot), PGC1A, Mfn1, Mfn2, Opa1, and Drp1 gene expression (qRT PCR). The study showed that swimming in water at a thermally comfortable temperature improved the energy metabolism of the aging rat muscles by increasing the metabolic rate (increase in ATP, ADP, TAN, AEC) and enhancing mitochondrial fusion (increase in mRNA expression of regulatory proteins Mfn1 and Mfn2). Cold water swimming improved muscle energy metabolism in aging rats by increasing the rate of muscle energy metabolism (increase in ATP, ADP, TAN, AEC concentrations) and enhancing mitochondrial biogenesis and dynamics (increase in the mRNA expression of proteins of fusion-regulating factors – Mfn1, Mfn2, and Opa1, and the factor regulating mitochondrial fission – Drp1). The concentration of high-energy compounds and the expression of proteins regulating mitochondrial dynamics in the muscle may be a useful indicator in monitoring adaptive changes occurring in aging muscles under the influence of exercise in cold water. It represents a short-term adaptation to changing environmental conditions and has a beneficial effect on maintaining the bioenergetic capacity of muscles in the long term. Conclusion: exercise in cold water can exert positive effects on energy metabolism, biogenesis and dynamics of mitochondria in aging rat muscles. Enhancement of mitochondrial dynamics under cold water exercise conditions can improve mitochondrial function and optimize the bioenergetic capacity of mitochondria in aging rat muscles.

Keywords: cold water immersion, adaptive responses, muscle energy metabolism, aging

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Authors: Mara Aparecida De Castilho Lopes. Maria Eliza Mattosinho Bernardes

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The education of deaf individuals in Brazil is grounded in the bilingual approach, which presupposes Brazilian Sign Language (Libras) as the first language for these students. In this perspective, Portuguese should be taught as a second language in its written form, ensuring that deaf students also have access to various academic subjects in sign language. Brazilian legislation (Federal Decree No. 5626 of 2005) mandates the teaching of Brazilian Sign Language in university teacher training programs, but there is no pre-established minimum workload. As a result, there is a significant disparity in the teaching and quality of teacher education across the Brazilian territory. Added to this fact is the general lack of awareness within society regarding the linguistic status of Libras, leading to a shortage of competent teachers for its use and instruction, particularly in higher education. Recently, Federal Law No. 14191 of 2021 established bilingual education for the deaf as a mode of instruction, indicating the need for adjustments in teacher training within higher education teacher preparation programs. Given this context, the objective of the present study was to analyze the teaching proposals for Brazilian Sign Language for students in teacher training programs at public universities in Brazil, presenting alternatives to overcome the current models and academic pathways of teaching and learning. In addition to analyzing Brazilian teaching models, an analysis of a continuing education model for teachers in a French institution was also conducted - considering the historical Franco-Brazilian path of deaf education in Brazil. The analysis of the current teacher training model for deaf education in Brazil revealed that initial exposure to sign language and its linguistic structure is not sufficient to provide future teachers with opportunities to reflect on bilingual teaching methods and practices, as seen in other definitions of bilingualism - bilingual education for proficient listeners in two oral languages. As a result, a training proposal was developed for an experimental interdisciplinary course, integrating the curriculum of an initial and continuing teacher training program alongside the Alfredo Bossi Chair at the University of São Paulo. This proposal is structured into three disciplines, which constitute consecutive moments in teacher education: Fundamental Aspects of Brazilian Sign Language, Bilingual Teaching Methodology, and Teaching Investigation Project - interdisciplinary engagement in the field of deafness. The last offered discipline represents an interdisciplinary supervised internship proposal, considering the multi-professional context that constitutes deaf education within a bilingual approach. In interdisciplinary work within the field of deafness, dialogue between teachers and other professionals who work with deaf students from different perspectives - teachers, speech therapists, and sign language interpreters - is frequently necessary. Through alternative avenues, these actions aim to direct the linguistic development of deaf students within their learning processes. Based on the innovative curriculum proposal described here, the intention is to contribute to the enhancement of teacher education in Brazil, with the goal of ensuring bilingual education for deaf students.

Keywords: bilingual education, teacher training, historical-cultural approach, interdisciplinary education, inclusive education

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Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

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Authors: Megan L. Srinivas

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Individuals with underlying rheumatologic diseases such as dermatomyositis may not adequately respond to tuberculin (PPD) skin tests, creating false negative results. These illnesses are frequently treated with immunosuppressive therapy making proper identification of TB infection imperative. A 59-year-old Filipino man was diagnosed with dermatomyositis on the basis of rash, electromyography, and muscle biopsy. He was initially treated with IVIG infusions and transitioned to oral prednisone and mycophenolate. The patient’s symptoms improved on this regimen. Six months after starting mycophenolate, the patient began having fevers, night sweats, and productive cough without hemoptysis. He moved from the Philippines 5 years prior to dermatomyositis diagnosis, denied sick contacts, and was PPD negative both at immigration and immediately prior to starting mycophenolate treatment. A third PPD was negative following the onset of these new symptoms. He was treated for community-acquired pneumonia, but symptoms worsened over 10 days and he developed watery diarrhea and a growing non-tender, non-mobile mass on the left side of his neck. A chest x-ray demonstrated a cavitary lesion in right upper lobe suspicious for TB that had not been present one month earlier. Chest CT corroborated this finding also exhibiting necrotic hilar and paratracheal lymphadenopathy. Neck CT demonstrated the left-sided mass as cervical chain lymphadenopathy. Expectorated sputum and stool samples contained acid-fast bacilli (AFB), cultures showing TB bacteria. Fine-needle biopsy of the neck mass (scrofula) also exhibited AFB. An MRI brain showed nodular enhancement suspected to be a tuberculoma. Mycophenolate was discontinued and dermatomyositis treatment was switched to oral prednisone with a 3-day course of IVIG. The patient’s infection showed sensitivity to standard RIPE (rifampin, isoniazid, pyrazinamide, and ethambutol) treatment. Within a week of starting RIPE, the patient’s diarrhea subsided, scrofula diminished, and symptoms significantly improved. By the end of treatment week 3, the patient’s sputum no longer contained AFB; he was removed from isolation, and was discharged to continue RIPE at home. He was discharged on oral prednisone, which effectively addressed his dermatomyositis. This case illustrates the unreliability of PPD tests in patients with long-term inflammatory diseases such as dermatomyositis. Other immunosuppressive therapies (adalimumab, etanercept, and infliximab) have been affiliated with conversion of latent TB to disseminated TB. Mycophenolate is another immunosuppressive agent with similar mechanistic properties. Thus, it is imperative that patients with long-term inflammatory diseases and high-risk TB factors initiating immunosuppressive therapy receive a TB blood test (such as a quantiferon gold assay) prior to the initiation of therapy to ensure that latent TB is unmasked before it can evolve into a disseminated form of the disease.

Keywords: dermatomyositis, immunosuppressant medications, mycophenolate, disseminated tuberculosis

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Authors: Vishnu Asokan, Zaid M. Paloba

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Flow over cavities is an important area of research due to the significant change in flow physics caused by cavity aspect ratio, free stream Mach number and the nature of upstream boundary layer approaching the cavity leading edge. Cavity flow finds application in aircraft wheel well, weapons bay, combustion chamber of scramjet engines, etc. These flows are highly unsteady, compressible and turbulent and it involves mass entrainment coupled with acoustics phenomenon. Variation of flow dynamics in an angled cavity with a heated and cooled pylon upstream to the cavity with spatial combinations of heat flux addition and removal to the wall studied numerically. The goal of study is to investigate the effect of energy addition, removal to the cavity walls and pylon cavity flow dynamics. Preliminary steady state numerical simulations on inclined cavities with heat addition have shown that wall pressure profiles, as well as the recirculation, are influenced by heat transfer to the compressible fluid medium. Such a hybrid control of cavity flow dynamics in the form of heat transfer and pylon geometry can open out greater opportunities in enhancement of mixing and flame holding requirements of supersonic combustors. Addition of pylon upstream to the cavity reduces the acoustic oscillations emanating from the geometry. A numerical unsteady analysis of supersonic flow past cavities exposed to cavity wall heating and cooling with heated and cooled pylon helps to get a clear idea about the oscillation suppression in the cavity. A Cavity of L/D 4 and aft wall angle 22 degree with an upstream pylon of h/D=1.5 mm with a wall angle 29 degree exposed to supersonic flow of Mach number 2 and heat flux of 40 W/cm² and -40 W/cm² modeled for the above study. In the preliminary study, the domain is modeled and validated numerically with a turbulence model of SST k-ω using an HLLC implicit scheme. Both qualitative and quantitative flow data extracted and analyzed using advanced CFD tools. Flow visualization is done using numerical Schlieren method as the fluid medium gives the density variation. The heat flux addition to the wall increases the secondary vortex size of the cavity and removal of energy leads to the reduction in vortex size. The flow field turbulence seems to be increasing at higher heat flux. The shear layer thickness increases as heat flux increases. The steady state analysis of wall pressure shows that there is variation on wall pressure as heat flux increases. Shift in frequency of unsteady wall pressure analysis is an interesting observation for the above study. The time averaged skin friction seems to be reducing at higher heat flux due to the variation in viscosity of fluid inside the cavity.

Keywords: energy addition, frequency shift, Numerical Schlieren, shear layer, vortex evolution

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Margareta Simina Stanc, Aurel Mototolea, Tiberiu Potarniche

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Sacidava archeological site is located in Dobrudja region, Romania, on a hill on the right bank of the Danube - the Musait point, located at about 5 km north-east from Dunareni village. The place-name documents the fact that, prior to the Roman conquest, in the area, there was a Getic settlement. The location of the Sacidava was made possible by corroborating the data provided by the ancient sources with the epigraphic documents (the milial pillar during the time of Emperor Decius). The tegular findings attest that an infantry unit, cohors I Cilicum milliaria equitata, as well as detachments from Legio V Macedonica and Legio XI Claudia, were confined to Sacidava. During the period of the Dominion, the garrison of the fortification is the host of a cavalry unit: cuneus equitum scutariorum. In the immediate vicinity to the Roman fortress, to the east, were identified two other fortifications: a Getic settlement (4th-1st century B.C.) and an Early Medieval settlement (9th-10th century A.C.). The archaeological material recovered during the research is represented by ceramic forms such as amphoras, jugs, pots, cups, plates, to which are added oil lamps, some of them typologically new at the time of discovery. Local ceramic shapes were also founded, worked by hand or by wheel, considered un-Romanized or in the course of Romanization. During the time of the Principality, Sacidava it represented an important military outpost serving mainly the city of Tropaeum Traiani, controlling also the supply and transport on the Danube limes in the Moesic sector. This role will determine the development of the fortress and the appearance of extramuros civil structures, thus becoming an important landmark during the 5th-6th centuries A.C., becoming a representation of power of the Roman empire in an area of continuous conflict. During recent archaeological researches, faunal remains were recovered, and their analysis allowed to estimate the animal resources and subsistence practices (animal husbandry, hunting, fishing) in the settlement. The methodology was specific to archaeozoology, mainly consisting of anatomical, taxonomical, and taphonomical identifications, recording, and quantification of the data. The remains of domestic mammals have the highest proportion indicating the importance of animal husbandry; the predominant species are Bos taurus, Ovis aries/Capra hircus, and Sus domesticus. Fishing and hunting were of secondary importance in the subsistence economy of the community. Wild boar and the red deer were the most frequently hunted species. Just a few fish bones were recovered. Thus, the ancient city of Sacidava is proving to be an important element of cultural heritage of the south-eastern part of Romania, for whose conservation and enhancement efforts must be made, especially by landscape reconstruction.

Keywords: archaeozoology, landscape reconstruction, limes, military outpost

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Authors: Tamar Bikashvili, Tamar Lordkipanidze, Ilia Lazrishvili

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Heavy metals remain one of serious environmental problems due to their toxic effects. The effect of arsenic and manganese compounds on rat behavior and neuromorphology was studied. Wistar rats were assigned to four groups: rats in control group were given regular water, while rats in other groups drank water with final manganese concentration of 10 mg/L (group A), 20 mg/L (group B) and final arsenic concentration 68 mg/L (group C), respectively, for a month. To study exploratory and anxiety behavior and also to evaluate aggressive performance in “home cage” rats were tested in “Open Field” and to estimate learning and memory status multi-branched maze was used. Statistically significant increase of motor and oriental-searching activity in experimental groups was revealed by an open field test, which was expressed in increase of number of lines crossed, rearing and hole reflexes. Obtained results indicated the suppression of fear in rats exposed to manganese. Specifically, this was estimated by the frequency of getting to the central part of the open field. Experiments revealed that 30-day exposure to 10 mg/ml manganese did not stimulate aggressive behavior in rats, while exposure to the higher dose (20 mg/ml), 37% of initially non-aggressive animals manifested aggressive behavior. Furthermore, 25% of rats were extremely aggressive. Obtained data support the hypothesis that excess manganese in the body is one of the immediate causes of enhancement of interspecific predatory aggressive and violent behavior in rats. It was also discovered that manganese intoxication produces non-reversible severe learning disability and insignificant, reversible memory disturbances. Studies of rodents exposed to arsenic also revealed changes in the learning process. As it is known, the distribution of metal ions differs in various brain regions. The principle manganese accumulation was observed in the hippocampus and in the neocortex, while arsenic was predominantly accumulated in nucleus accumbens, striatum, and cortex. These brain regions play an important role in the regulation of emotional state and motor activity. Histopathological analyzes of brain sections illustrated two morphologically distinct altered phenotypes of neurons: (1) shrunk cells with indications of apoptosis - nucleus and cytoplasm were very difficult to be distinguished, the integrity of neuronal cytoplasm was not disturbed; and (2) swollen cells - with indications of necrosis. Pyknotic nucleus, plasma membrane disruption and cytoplasmic vacuoles were observed in swollen neurons and they were surrounded by activated gliocytes. It’s worth to mention that in the cortex the majority of damaged neurons were apoptotic while in subcortical nuclei –neurons were mainly necrotic. Ultrastructural analyses demonstrated that all cell types in the cortex and the nucleus caudatus represent destructed mitochondria, widened neurons’ vacuolar system profiles, increased number of lysosomes and degeneration of axonal endings.

Keywords: arsenic, manganese, behavior, learning, neuron

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Authors: Azza A. Ali, Asmaa Abdelaty, Mona G. Khalil, Mona M. Kamal, Karema Abu-Elfotuh

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Background: Aluminium (Al) is known as a neurotoxin environmental pollutant that can cause certain diseases as Dementia, Alzheimer's disease, and Parkinsonism. It is widely used in antacid drugs as well as in food additives and toothpaste. Stresses have been linked to cognitive impairment; Social isolation (SI) may exacerbate memory deficits while protein malnutrition (PM) increases oxidative damage in cortex, hippocampus and cerebellum. The risk of cognitive decline may be lower by maintaining social connections. Epigallocatechin-3-gallate (EGCG) is the most abundant catechin in green tea and has antioxidant, anti-inflammatory and anti-atherogenic effects as well as health-promoting effects in CNS. Objective: To study the influence of different stressful conditions as social isolation, electric shock (EC) and inadequate Nutritional condition as PM on neurotoxicity induced by Al in rats as well as to investigate the possible protective effect of EGCG in these stressful and PM conditions. Methods: Rats were divided into two major groups; protected group which was daily treated during three weeks of the experiment by EGCG (10 mg/kg, IP) or non-treated. Protected and non-protected groups included five subgroups as following: One normal control received saline and four Al toxicity groups injected daily for three weeks by ALCl3 (70 mg/kg, IP). One of them served as Al toxicity model, two groups subjected to different stresses either by isolation as mild stressful condition (SI-associated Al toxicity model) or by electric shock as high stressful condition (EC- associated Al toxicity model). The last was maintained on 10% casein diet (PM -associated Al toxicity model). Isolated rats were housed individually in cages covered with black plastic. Biochemical changes in the brain as acetyl cholinesterase (ACHE), Aβ, brain derived neurotrophic factor (BDNF), inflammatory mediators (TNF-α, IL-1β), oxidative parameters (MDA, SOD, TAC) were estimated for all groups. Histopathological changes in different brain regions were also evaluated. Results: Rats exposed to Al for three weeks showed brain neurotoxicity and neuronal degenerations. Both mild (SI) and high (EC) stressful conditions as well as inadequate nutrition (PM) enhanced Al-induced neurotoxicity and brain neuronal degenerations; the enhancement induced by stresses especially in its higher conditions (ES) was more pronounced than that of inadequate nutritional conditions (PM) as indicated by the significant increase in Aβ, ACHE, MDA, TNF-α, IL-1β together with the significant decrease in SOD, TAC, BDNF. On the other hand, EGCG showed more pronounced protection against hazards of Al in both stressful conditions (SI and EC) rather than in PM .The protective effects of EGCG were indicated by the significant decrease in Aβ, ACHE, MDA, TNF-α, IL-1β together with the increase in SOD, TAC, BDNF and confirmed by brain histopathological examinations. Conclusion: Neurotoxicity and brain neuronal degenerations induced by Al were more severe with stresses than with PM. EGCG can protect against Al-induced brain neuronal degenerations in all conditions. Consequently, administration of EGCG together with socialization as well as adequate protein nutrition is advised especially on excessive Al-exposure to avoid the severity of its neuronal toxicity.

Keywords: environmental pollution, aluminum, social isolation, protein malnutrition, neuronal degeneration, epigallocatechin-3-gallate, rats

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Authors: Kenechukwu Ikebuaku

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Entrepreneurship has long been offered as the panacea for poor economic growth and high rate of unemployment. Business incubation is considered an effective means for enhancing entrepreneurial actitivities while engendering socio-economic development. Information Technology Developers Entrepreneurship Accelerator (iDEA), is a software business incubation programme established by the Nigerian government as a means of boosting digital entrepreneurship activities and reducing unemployment in the country. This study assessed the contribution of iDEA Nigeria’s entrepreneurship programmes towards enhancing the capabilities of its tenants. Using the capability approach and the sustainable livelihoods approach, the study analysed iDEA programmes’ contribution towards the expansion of participants’ entrepreneurial capabilities. Apart from identifying a set of entrepreneurial capabilities from both the literature and empirical analysis, the study went further to ascertain how iDEA incubation has helped to enhance those capabilities for its tenants. It also examined digital entrepreneurship as a valued functioning and as an intermediate functioning leading to other valuable functioning. Furthermore, the study examined gender as a conversion factor in digital entrepreneurship. Both qualitative and quantitative research methods were used for the study, and measurement of key variables was made. While the entire population was utilised to collect data for the quantitative research, purposive sampling was used to select respondents for semi-structured interviews in the qualitative research. However, only 40 beneficiaries agreed to take part in the survey while 10 respondents were interviewed for the study. Responses collected from questionnaires administered were subjected to statistical analysis using SPSS. The study developed indexes to measure the perception of the respondents, on how iDEA programmes have enhanced their entrepreneurial capabilities. The Capabilities Enhancement Perception Index (CEPI) computed indicated that the respondents believed that iDEA programmes enhanced their entrepreneurial capabilities. While access to power supply and reliable internet have the highest positive deviations around mean, negotiation skills and access to customers/clients have the highest negative deviation. These were well supported by the findings of the qualitative analysis in which the participants unequivocally narrated how the resources provided by iDEA aid them in their entrepreneurial endeavours. It was also found that iDEA programmes have a significant effect on the tenants’ access to networking opportunities, both with other emerging entrepreneurs and established entrepreneurs. While assessing gender as a conversion factor, it was discovered that there was very low female participation within the digital entrepreneurship ecosystem. The root cause of this gender disparity was found in unquestioned cultural beliefs and social norms which relegate women to a subservient position and household duties. The findings also showed that many of the entrepreneurs could be considered opportunity-based entrepreneurs rather than necessity entrepreneurs, and that digital entrepreneurship is a valued functioning for iDEA tenants. With regards to challenges facing digital entrepreneurship in Nigeria, infrastructural/institutional inadequacies, lack of funding opportunities, and unfavourable government policies, were considered inimical to entrepreneurial capabilities in the country.

Keywords: entrepreneurial capabilities, unemployment, business incubators, development

Procedia PDF Downloads 207

Authors: Christina Drosou, Konstantina E. Kyriakopoulou, Andreas Bimpilas, Dimitrios Tsimogiannis, Magdalini C. Krokida

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Rationale: Agiorgitiko is one of the most widely-grown and commercially well-established red wine varieties in Greece. Each year viticulture industry produces a large amount of waste consisting of grape skins and seeds (pomace) during a short period. Grapes contain polyphenolic compounds which are partially transferred to wine during winemaking. Therefore, winery wastes could be an alternative cheap source for obtaining such compounds with important antioxidant activity. Specifically, red grape waste contains anthocyanins and flavonols which are characterized by multiple biological activities, including cardioprotective, anti-inflammatory, anti-carcinogenic, antiviral and antibacterial properties attributed mainly to their antioxidant activity. Ultrasound assisted extraction (UAE) is considered an effective way to recover phenolic compounds, since it combines the advantage of mechanical effect with low temperature. Moreover, green solvents can be used in order to recover extracts intended for used in the food and nutraceutical industry. Apart from the extraction, pre-treatment process like drying can play an important role on the preservation of the grape pomace and the enhancement of its antioxidant capacity. Objective: The aim of this study is to recover natural extracts from winery waste with high antioxidant capacity using green solvents so they can be exploited and utilized as enhancers in food or nutraceuticals. Methods: Agiorgitiko grape pomace was dehydrated by air drying (AD) and accelerated solar drying (ASD) in order to explore the effect of the pre-treatment on the recovery of bioactive compounds. UAE was applied in untreated and dried samples using water and water: ethanol (1:1) as solvents. The total antioxidant potential and phenolic content of the extracts was determined using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin-Ciocalteu method, respectively. Finally, the profile of anthocyanins and flavonols was specified using HPLC-DAD analysis. The efficiency of processes was determined in terms of extraction yield, antioxidant activity, phenolic content and the anthocyanins and flavovols profile. Results & Discussion: The experiments indicated that the pre-treatment was essential for the recovery of highly nutritious compounds from the pomace as long as the extracts samples showed higher phenolic content and antioxidant capacity. Water: ethanol (1:1) was considered a more effective solvent on the recovery of phenolic compounds. Moreover, ASD grape pomace extracted with the solvent system exhibited the highest antioxidant activity (IC50=0.36±0.01mg/mL) and phenolic content (TPC=172.68±0.01mgGAE/g dry extract), followed by AD and untreated pomace. The major compounds recovered were malvidin3-O-glucoside and quercetin3-O-glucoside according to the HPLC analysis. Conclusions: Winery waste can be exploited for the recovery of nutritious compounds using green solvents such as water or ethanol. The pretreatment of the pomace can significantly affect the concentration of phenolic compounds, while UAE is considered a highly effective extraction process.

Keywords: agiorgitico grape pomace, antioxidants, phenolic compounds, ultrasound assisted extraction

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Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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An important tool for the enhancement of cultural sites is serious games (SG), i.e., games designed for educational purposes; SG is applied in cultural sites through trivia, puzzles, and mini-games for participation in interactive exhibitions, mobile applications, and simulations of past events. The combination of Augmented Reality (AR) and digital cultural content has also produced examples of cultural heritage recovery and revitalization around the world. Through AR, the user perceives the information of the visited place in a more real and interactive way. Another interesting technological development for the revitalization of cultural sites is the combination of AR and Global Positioning System (GPS), which integrated have the ability to enhance the user's perception of reality by providing historical and architectural information linked to specific locations organized on a route. To the author’s best knowledge, there are currently no applications that combine GPS AR and SG for cultural heritage revitalization. The present research focused on the development of an SG based on GPS and AR. The study area is the village of Caldana in Tuscany, Italy. Caldana is a fortified Renaissance village; the most important architectures are the walls, the church of San Biagio, the rectory, and the marquis' palace. The historical information is derived from extensive research by the Department of Architecture at the University of Florence. The storyboard of the SG is based on the history of the three characters who built the village: marquis Marcello Agostini, who was commissioned by Cosimo I de Medici, Grand Duke of Tuscany, to build the village, his son Ippolito and his architect Lorenzo Pomarelli. The three historical characters were modeled in 3D using the freeware MakeHuman and imported into Blender and Mixamo to associate a skeleton and blend shapes to have gestural animations and reproduce lip movement during speech. The Unity Rhubarb Lip Syncer plugin was used for the lip sync animation. The historical costumes were created by Marvelous Designer. The application was developed using the Unity 3D graphics and game engine. The AR+GPS Location plugin was used to position the 3D historical characters based on GPS coordinates. The ARFoundation library was used to display AR content. The SG is available in two versions: for children and adults. the children's version consists of finding a digital treasure consisting of valuable items and historical rarities. Players must find 9 village locations where 3D AR models of historical figures explaining the history of the village provide clues. To stimulate players, there are 3 levels of rewards for every 3 clues discovered. The rewards consist of AR masks for archaeologist, professor, and explorer. At the adult level, the SG consists of finding the 16 historical landmarks in the village, and learning historical and architectural information interactively and engagingly. The application is being tested on a sample of adults and children. Test subjects will be surveyed on a Likert scale to find out their perceptions of using the app and the learning experience between the guided tour and interaction with the app.

Keywords: augmented reality, cultural heritage, GPS, serious game

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Authors: Luiza Melo De Lima, Tito Trindade, Jose M. Oliveira

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The development of thermoplastic-based graphene nanocomposites has been of great interest not only to the scientific community but also to different industrial sectors. Due to the possible improvement of performance and weight reduction, thermoplastic nanocomposites are a great promise as a new class of materials. These nanocomposites are of relevance for the automotive industry, namely because the emission limits of CO2 emissions imposed by the European Commission (EC) regulations can be fulfilled without compromising the car’s performance but by reducing its weight. Thermoplastic polymers have some advantages over thermosetting polymers such as higher productivity, lower density, and recyclability. In the automotive industry, for example, poly(propylene) (PP) is a common thermoplastic polymer, which represents more than half of the polymeric raw material used in automotive parts. Graphene-based materials (GBM) are potential nanofillers that can improve the properties of polymer matrices at very low loading. In comparison to other composites, such as fiber-based composites, weight reduction can positively affect their processing and future applications. However, the properties and performance of GBM/polymer nanocomposites depend on the type of GBM and polymer matrix, the degree of dispersion, and especially the type of interactions between the fillers and the polymer matrix. In order to take advantage of the superior mechanical strength of GBM, strong interfacial strength between GBM and the polymer matrix is required for efficient stress transfer from GBM to the polymer. Thus, chemical compatibilizers and physicochemical modifications have been reported as important tools during the processing of these nanocomposites. In this study, PP-based nanocomposites were obtained by a simple melt blending technique, using a Brabender type mixer machine. Graphene nanoplatelets (GnPs) were applied as structural reinforcement. Two compatibilizers were used to improve the interaction between PP matrix and GnPs: PP graft maleic anhydride (PPgMA) and PPgMA modified with tertiary amine alcohol (PPgDM). The samples for tensile and Charpy impact tests were obtained by injection molding. The results suggested the GnPs presence can increase the mechanical strength of the polymer. However, it was verified that the GnPs presence can promote a decrease of impact resistance, turning the nanocomposites more fragile than neat PP. The compatibilizers’ incorporation increases the impact resistance, suggesting that the compatibilizers can enhance the adhesion between PP and GnPs. Compared to neat PP, Young’s modulus of non-compatibilized nanocomposite increase demonstrated that GnPs incorporation can promote a stiffness improvement of the polymer. This trend can be related to the several physical crosslinking points between the PP matrix and the GnPs. Furthermore, the decrease of strain at a yield of PP/GnPs, together with the enhancement of Young’s modulus, confirms that the GnPs incorporation led to an increase in stiffness but to a decrease in toughness. Moreover, the results demonstrated that incorporation of compatibilizers did not affect Young’s modulus and strain at yield results compared to non-compatibilized nanocomposite. The incorporation of these compatibilizers showed an improvement of nanocomposites’ mechanical properties compared both to those the non-compatibilized nanocomposite and to a PP sample used as reference.

Keywords: graphene nanoplatelets, mechanical properties, melt blending processing, poly(propylene)-based nanocomposites

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Angelos Evangelou, Katerina Loizou, Loukas Koutsokeras, Orestes Marangos, Giorgos Constantinides, Stylianos Yiatros, Katerina Sofocleous, Vasileios Drakonakis

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Owing to their outstanding strength to weight properties, carbon fiber reinforced polymer (CFRPs) composites have attracted significant attention finding use in various fields (sports, automotive, transportation, etc.). The current momentum indicates that there is an increasing demand for their employment in high value bespoke applications such as avionics and electronic casings, damage sensing structures, EMI (electromagnetic interference) structures that dictate the use of materials with increased electrical conductivity both in-plane and through the thickness. Several efforts by research groups have focused on enhancing the through-thickness electrical conductivity of FRPs, in an attempt to combine the intrinsically high relative strengths exhibited with improved z-axis electrical response as well. However, only a limited number of studies deal with printing of nano-enhanced polymer inks to produce a pattern on dry fabric level that could be used to fabricate CFRPs with improved through thickness electrical conductivity. The present study investigates the employment of screen-printing process on technical dry fabrics using nano-reinforced polymer-based inks to achieve the required through thickness conductivity, opening new pathways for the application of fiber reinforced composites in niche products. Commercially available inks and in-house prepared inks reinforced with electrically conductive nanoparticles are employed, printed in different patterns. The aim of the present study is to investigate both the effect of the nanoparticle concentration as well as the droplet patterns (diameter, inter-droplet distance and coverage) to optimize printing for the desired level of conductivity enhancement in the lamina level. The electrical conductivity is measured initially at ink level to pinpoint the optimum concentrations to be employed using a “four-probe” configuration. Upon printing of the different patterns, the coverage of the dry fabric area is assessed along with the permeability of the resulting dry fabrics, in alignment with the fabrication of CFRPs that requires adequate wetting by the epoxy matrix. Results demonstrated increased electrical conductivities of the printed droplets, with increase of the conductivity from the benchmark value of 0.1 S/M to between 8 and 10 S/m. Printability of dense and dispersed patterns has exhibited promising results in terms of increasing the z-axis conductivity without inhibiting the penetration of the epoxy matrix at the processing stage of fiber reinforced composites. The high value and niche prospect of the resulting applications that can stem from CFRPs with increased through thickness electrical conductivities highlights the potential of the presented endeavor, signifying screen printing as the process to to nano-enable z-axis electrical conductivity in composite laminas. This work was co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation (Project: ENTERPRISES/0618/0013).

Keywords: CFRPs, conductivity, nano-reinforcement, screen-printing

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Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

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Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

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Authors: G. M. Vlasceanu, H. Iovu, E. Vasile, M. Ionita

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Herein, the synthesis and characterization of chitosan-gelatin highly porous scaffold reinforced with graphene oxide, and hydroxyapatite (HAp), crosslinked with genipin was targeted. In tissue engineering, chitosan and gelatin are two of the most robust biopolymers with wide applicability due to intrinsic biocompatibility, biodegradability, low antigenicity properties, affordability, and ease of processing. HAp, per its exceptional activity in tuning cell-matrix interactions, is acknowledged for its capability of sustaining cellular proliferation by promoting bone-like native micro-media for cell adjustment. Genipin is regarded as a top class cross-linker, while graphene oxide (GO) is viewed as one of the most performant and versatile fillers. The composites with natural bone HAp/biopolymer ratio were obtained by cascading sonochemical treatments, followed by uncomplicated casting methods and by freeze-drying. Their structure was characterized by Fourier Transform Infrared Spectroscopy and X-ray Diffraction, while overall morphology was investigated by Scanning Electron Microscopy (SEM) and micro-Computer Tomography (µ-CT). Ensuing that, in vitro enzyme degradation was performed to detect the most promising compositions for the development of in vivo assays. Suitable GO dispersion was ascertained within the biopolymer mix as nanolayers specific signals lack in both FTIR and XRD spectra, and the specific spectral features of the polymers persisted with GO load enhancement. Overall, correlations between the GO induced material structuration, crystallinity variations, and chemical interaction of the compounds can be correlated with the physical features and bioactivity of each composite formulation. Moreover, the HAp distribution within follows an auspicious density gradient tuned for hybrid osseous/cartilage matter architectures, which were mirrored in the mice model tests. Hence, the synthesis route of a natural polymer blend/hydroxyapatite-graphene oxide composite material is anticipated to emerge as influential formulation in bone tissue engineering. Acknowledgement: This work was supported by the project 'Work-based learning systems using entrepreneurship grants for doctoral and post-doctoral students' (Sisteme de invatare bazate pe munca prin burse antreprenor pentru doctoranzi si postdoctoranzi) - SIMBA, SMIS code 124705 and by a grant of the National Authority for Scientific Research and Innovation, Operational Program Competitiveness Axis 1 - Section E, Program co-financed from European Regional Development Fund 'Investments for your future' under the project number 154/25.11.2016, P_37_221/2015. The nano-CT experiments were possible due to European Regional Development Fund through Competitiveness Operational Program 2014-2020, Priority axis 1, ID P_36_611, MySMIS code 107066, INOVABIOMED.

Keywords: biopolymer blend, ectopic osteoinduction, graphene oxide composite, hydroxyapatite

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Authors: Karen Trimmer, Raelene Ward, Linda Wondunna-Foley

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Within Australian tertiary institutions, the subject of Aboriginal and Torres Strait Islander education has been a major concern for many years. Aboriginal and Torres Strait Islander teachers are significantly under-represented in Australian schools and universities. High attrition rates in teacher education and in the teaching industry have contributed to a minimal growth rate in the numbers of Aboriginal and Torres Strait Islander teachers in previous years. There was an increase of 500 Indigenous teachers between 2001 and 2008 but these numbers still only account for one percent of teaching staff in government schools who identified as Aboriginal and Torres Strait Islander Australians (Ministerial Council for Education, Early Childhood Development and Youth Affairs 2010). Aboriginal and Torres Strait Islander teachers are paramount in fostering student engagement and improving educational outcomes for Indigenous students. Increasing the numbers of Aboriginal and Torres Strait Islander teachers is also a key factor in enabling all students to develop understanding of and respect for Aboriginal and Torres Strait Islander histories, cultures, and language. An ambitious reform agenda to improve the recruitment and retention of Aboriginal and Torres Strait Islander teachers will be effective only through national collaborative action and co-investment by schools and school authorities, university schools of education, professional associations, and Indigenous leaders and community networks. Whilst the University of Southern Queensland currently attracts Indigenous students to its teacher education programs (61 students in 2013 with an average of 48 enrollments each year since 2010) there is significant attrition during pre-service training. The annual rate of exiting before graduation remains high at 22% in 2012 and was 39% for the previous two years. These participation and retention rates are consistent with other universities across Australia. Whilst aspirations for a growing number of Indigenous people to be trained as teachers is present, there is a significant loss of students during their pre-service training and within the first five years of employment as a teacher. These trends also reflect the situation where Aboriginal and Torres Strait Islander teachers are significantly under-represented, making up less than 1% of teachers in schools across Australia. Through a project conducted as part the nationally funded More Aboriginal and Torres Strait Islander Teachers Initiative (MATSITI) we aim to gain an insight into the reasons that impact Aboriginal and Torres Strait Islander student’s decisions to exit their program. Through the conduct of focus groups and interviews with two graduating cohorts of self-identified Aboriginal and Torres Strait Islander students, rich data has been gathered to gain an understanding of the barriers and enhancers to the completion of pre-service qualification and transition to teaching. Having a greater understanding of these reasons then allows the development of collaborative processes and procedures to increase retention and completion rates of new Indigenous teachers. Analysis of factors impacting on exit decisions and transitions has provided evidence to support change of practice, redesign and enhancement of relevant courses and development of policy/procedures to address identified issues.

Keywords: graduation, indigenous, pre-service teacher education, retention

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Authors: Sajjad H. Kasanagh, Perviz Ahmedzade, Alexander Fainleib, Taylan Gunay

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Modification of asphalt is a fundamental method around the world mainly on the purpose of providing more durable pavements which lead to diminish repairing cost during the lifetime of highways. Various polymers such as styrene-butadiene-styrene (SBS) and ethylene vinyl acetate (EVA) make up the greater parts of the all-over asphalt modifiers generally providing better physical properties of asphalt by decreasing temperature dependency which eventually diminishes permanent deformation on highways such as rutting. However, some waste and low-cost materials such as recycled plastics and ground rubber tire have been attempted to utilize in asphalt as modifier instead of manufactured polymer modifiers due to decreasing the eventual highway cost. On the other hand, the usage of recycled plastics has become a worldwide requirement and awareness in order to decrease the pollution made by waste plastics. Hence, finding an area in which recycling plastics could be utilized has been targeted by many research teams so as to reduce polymer manufacturing and plastic pollution. To this end, in this paper, thermoplastic dynamic vulcanizate (TDV) obtained from recycled post-consumer polyethylene and ground tire rubber (GTR) were used to provide an efficient modifier for asphalt which decreases the production cost as well and finally might provide an ecological solution by decreasing polymer disposal problems. TDV was synthesized by the chemists in the research group by means of the abovementioned components that are considered as compatible physical characteristic of asphalt materials. TDV modified asphalt samples having different rate of proportions of 3, 4, 5, 6, 7 wt.% TDV modifier were prepared. Conventional tests, such as penetration, softening point and roll thin film oven (RTFO) tests were performed to obtain fundamental physical and aging properties of the base and modified binders. The high temperature performance grade (PG) of binders was determined by Superpave tests conducted on original and aged binders. The multiple stress creep and recovery (MSCR) test which is relatively up-to-date method for classifying asphalts taking account of their elasticity abilities was carried out to evaluate PG plus grades of binders. The results obtained from performance grading, and MSCR tests were also evaluated together so as to make a comparison between the methods both aiming to determine rheological parameters of asphalt. The test results revealed that TDV modification leads to a decrease in penetration, an increase in softening point, which proves an increasing stiffness of asphalt. DSR results indicate an improvement in PG for modified binders compared to base asphalt. On the other hand, MSCR results that are compatible with DSR results also indicate an enhancement on rheological properties of asphalt. However, according to the results, the improvement is not as distinct as observed in DSR results since elastic properties are fundamental in MSCR. At the end of the testing program, it can be concluded that TDV can be used as modifier which provides better rheological properties for asphalt and might diminish plastic waste pollution since the material is 100% recycled.

Keywords: asphalt, ground tire rubber, recycled polymer, thermoplastic dynamic vulcanizate

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Authors: Yi Li, Rui Lu, Lianjun Wang

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With the rapid development of chemical industry, the consumption of volatile organic compounds (VOCs) has increased extensively. In the process of VOCs production and application, plenty of them have been transferred to environment. As a result, it has led to pollution problems not only in soil and ground water but also to human beings. Thus, it is important to develop a sensitive and cost-effective analytical method for trace VOCs detection in environment. Surface-enhanced Raman Spectroscopy (SERS), as one of the most sensitive optical analytical technique with rapid response, pinpoint accuracy and noninvasive detection, has been widely used for ultratrace analysis. Based on the plasmon resonance on the nanoscale metallic surface, SERS technology can even detect single molecule due to abundant nanogaps (i.e. 'hot spots') on the nanosubstrate. In this work, a self-supported flexible silver nitrate (AgNO3)/ethylene-propylene copolymer (EPM) hybrid nanofibers was fabricated by electrospinning. After an in-situ chemical reduction using ice-cold sodium borohydride as reduction agent, numerous silver nanoparticles were formed on the nanofiber surface. By adjusting the reduction time and AgNO3 content, the morphology and dimension of silver nanoparticles could be controlled. According to the principles of solid-phase extraction, the hydrophobic substance is more likely to partition into the hydrophobic EPM membrane in an aqueous environment while water and other polar components are excluded from the analytes. By the enrichment of EPM fibers, the number of hydrophobic molecules located on the 'hot spots' generated from criss-crossed nanofibers is greatly increased, which further enhances SERS signal intensity. The as-prepared Ag/EPM hybrid nanofibers were first employed to detect common SERS probe molecule (p-aminothiophenol) with the detection limit down to 10-12 M, which demonstrated an excellent SERS performance. To further study the application of the fabricated substrate for monitoring hydrophobic substance in water, several typical VOCs, such as benzene, toluene and p-xylene, were selected as model compounds. The results showed that the characteristic peaks of these target analytes in the mixed aqueous solution could be distinguished even at a concentration of 10-6 M after multi-peaks gaussian fitting process, including C-H bending (850 cm-1), C-C ring stretching (1581 cm-1, 1600 cm-1) of benzene, C-H bending (844 cm-1 ,1151 cm-1), C-C ring stretching (1001 cm-1), CH3 bending vibration (1377 cm-1) of toluene, C-H bending (829 cm-1), C-C stretching (1614 cm-1) of p-xylene. The SERS substrate has remarkable advantages which combine the enrichment capacity from EPM and the Raman enhancement of Ag nanoparticles. Meanwhile, the huge specific surface area resulted from electrospinning is benificial to increase the number of adsoption sites and promotes 'hot spots' formation. In summary, this work provides powerful potential in rapid, on-site and accurate detection of trace VOCs using a portable Raman.

Keywords: electrospinning, ethylene-propylene copolymer, silver nanoparticles, SERS, VOCs

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