Search results for: surface aging features

Authors: Ch. Ramreddy, P. Naveen, D. Srinivasacharya

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The objective of the present study is to investigate the effect of nonlinear temperature and concentration on the mixed convective flow of micropolar fluid over an inclined flat plate in a non-Darcy porous medium in the presence of convective boundary condition. In order to analyze all the essential features, the transformed nonlinear conservation equations are worked out numerically by spectral method. By insisting the comparison between vertical, horizontal and inclined plates, the physical quantities of the flow and its characteristics are exhibited graphically and quantitatively with various parameters. An increase in the coupling number and inclination of angle tend to decrease the skin friction, mass transfer rate and the reverse change is there in wall couple stress and heat transfer rate. The nominal effect on the wall couple stress and skin friction is encountered whereas the significant effect on the local heat and mass transfer rates are found for high enough values of Biot number.

Keywords: convective boundary condition, micropolar fluid, non-darcy porous medium, non-linear convection, spectral method

Procedia PDF Downloads 273

Authors: Anwaar O. Ali, Mahmoud Fathy Mubarak, Mahmoud Ibrahim Abdou, Hector Cano Esteban, Amany A. Aboulrous

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Corrosion resistance and lubrication are crucial characteristics required for geothermal drilling fluids. In this study, a ZnO/Fe₂O₃ nanocomposite was fabricated and incorporated into the structure of Cetyltrimethylammonium bromide (CTAB). Several physicochemical techniques were utilized to analyze and describe the synthesized nanomaterials. The surface morphology of the composite was assessed through scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX). The corrosion inhibition capabilities of these materials were explored across various corrosive environments. The weight loss and electrochemical methods were utilized to determine the corrosion inhibition activity of the prepared nanomaterials. The results demonstrate a high level of protection achieved by the composite. Additionally, the lubricant coefficient and extreme pressure properties were evaluated.

Keywords: nanofluid, corrosion, geothermal drilling fluids, ZnO/Fe2O3

Procedia PDF Downloads 65

Authors: Barbara Urasinska-Wojcik, Neil Chilton, Peter Todd, Christopher Elsworthy, Gregory J. Gibbons

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The recent increase in the application of Additive Manufacturing (AM) of products has resulted in new demands on capability. The ability to integrate both form and function within printed objects is the next frontier in the 3D printing area. To move beyond prototyping into low volume production, we demonstrate a UK-designed and built AM hybrid system that combines polymer based structural deposition with digital deposition of electrically conductive elements. This hybrid manufacturing system is based on a multi-planar build approach to improve on many of the limitations associated with AM, such as poor surface finish, low geometric tolerance, and poor robustness. Specifically, the approach involves a multi-planar Material Extrusion (ME) process in which separated build stations with up to 5 axes of motion replace traditional horizontally-sliced layer modeling. The construction of multi-material architectures also involved using multiple print systems in order to combine both ME and digital deposition of conductive material. To demonstrate multi-material 3D printing, three thermoplastics, acrylonitrile butadiene styrene (ABS), polyamide 6,6/6 copolymers (CoPA) and polyamide 12 (PA) were used to print specimens, on top of which our high viscosity Ag-particulate ink was printed in a non-contact process, during which drop characteristics such as shape, velocity, and volume were assessed using a drop watching system. Spectroscopic analysis of these 3D printed materials in the IR region helped to determine the optimum in-situ curing system for implementation into the AM system to achieve improved adhesion and surface refinement. Thermal Analyses were performed to determine the printed materials glass transition temperature (Tg), stability and degradation behavior to find the optimum annealing conditions post printing. Electrical analysis of printed conductive tracks on polymer surfaces during mechanical testing (static tensile and 3-point bending and dynamic fatigue) was performed to assess the robustness of the electrical circuits. The tracks on CoPA, ABS, and PA exhibited low electrical resistance, and in case of PA resistance values of tracks remained unchanged across hundreds of repeated tensile cycles up to 0.5% strain amplitude. Our developed AM printer has the ability to fabricate fully functional objects in one build, including complex electronics. It enables product designers and manufacturers to produce functional saleable electronic products from a small format modular platform. It will make 3D printing better, faster and stronger.

Keywords: additive manufacturing, conductive tracks, hybrid 3D printer, integrated manufacture

Procedia PDF Downloads 162

Authors: Sreevalli Bokka

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The process of reducing the intensity of the carbon from a process or stream into the atmosphere is termed Decarbonization. Of the various technologies that are emerging to capture or reduce carbon intensity, membranes are emerging as a key player in separating carbon from a gas stream, such as industrial effluent air and others. Due to the advantage of high surface area and low flow resistance, fiber membranes are emerging widely for gas separation applications. A fiber membrane is a semipermeable barrier that is increasingly used for filtration and separation applications needing high packing density. A few of the many applications are in water desalination, medical applications, bioreactors, and gas separations applications. Only a few polymeric membranes were studied for fabricating fiber membranes such as cellulose acetate, Polysulfone, and Polyvinylidene fluoride. A few of the challenges of using fiber membranes are fouling and weak mechanical properties, leading to the breakage of membranes. In this work, the growth of fiber membranes and challenges for future developments in the filtration and gas separation applications are presented.

Keywords: membranes, filtration, separations, polymers, carbon capture

Procedia PDF Downloads 51

Authors: Mansour Al Qubeissi, Sergei S. Sazhin, Cyril Crua, Morgan R. Heikal

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This paper presents the application of the Discrete Component Model for heating and evaporation to multi-component biodiesel fuel droplets in direct injection internal combustion engines. This model takes into account the effects of temperature gradient, recirculation and species diffusion inside droplets. A distinctive feature of the model used in the analysis is that it is based on the analytical solutions to the temperature and species diffusion equations inside the droplets. Nineteen types of biodiesel fuels are considered. It is shown that a simplistic model, based on the approximation of biodiesel fuel by a single component or ignoring the diffusion of components of biodiesel fuel, leads to noticeable errors in predicted droplet evaporation time and time evolution of droplet surface temperature and radius.

Keywords: heat/mass transfer, biodiesel, multi-component fuel, droplet

Procedia PDF Downloads 563

Authors: Amira Ben Rabeh, Faouzi Benzarti, Hamid Amiri, Mouna Bouaziz

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Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD.

Keywords: Alzheimer Diseases (AD), Computer Assisted Diagnostic(CAD), hippocampus, Corpus Callosum (CC), cortex, Support Vector Machine (SVM)

Procedia PDF Downloads 378

Authors: Saurav Dhawan, Sanchit Bansal

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Background T-MACS is a computer-based decision aid that ‘rules in’ and ‘rules out’ ACS using a combination of the presence or absence of six clinical features with only one biomarker measured on arrival: hs-cTnT. T-MACS had 99.3% negative predictive value and 98.7% sensitivity for ACS, ‘ruling out’ ACS in 40% of patients while ‘ruling in’ 5% at the highest risk. We aim at benchmarking the use of T-MACS which could help to conserve healthcare resources, facilitate early discharges, and ensure safe practice. Methodology Randomized retrospective data collection (n=300) was done from ED electronic records across 3 hospital sites within MFT over a period of 2 months. Data was analysed and compared by percentage for the usage of T-MACS, number of admissions/discharges, and in days for length of stay in hospital. Results MRI A&E had the maximum compliance with the use of T-MACS in the trust at 66%, with minimum admissions (44%) and an average length of stay of 1.825 days. NMG A&E had an extremely low compliance rate (8 %), with 75% admission and 3.387 days as the average length of stay. WYT A&E had no TMACS recorded, with a maximum of 79% admissions and the longest average length of stay at 5.07 days. Conclusion All three hospital sites had a RAG rating of ‘RED’ as per the compliance levels. The assurance level was calculated as ‘Very Limited’ across all sites. There was a positive correlation observed between compliance with TMACS and direct discharges from ED, thereby reducing the average length of stay for patients in the hospital.

Keywords: ACS, discharges, ED, T-MACS

Procedia PDF Downloads 55

Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

Procedia PDF Downloads 132

Authors: M. B. Atui, A. M. Silva, M. A. M. Marciano, M. I. Fioravanti, V. A. Franco, L. B. Chasin, A. R. Ferreira, M. D. Nogueira

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Fungi attack large amount of fruits and those who have suffered an injury on the surface are more susceptible to the growth, as they have pectinolytic enzymes that destroy the edible portion forming an amorphous and soft dough. The spores can reach the plant by the wind, rain and insects and fruit may have on its surface, besides the contaminants from the fruit trees, land and water, forming a flora composed mainly of yeasts and molds. Other contamination can occur for the equipment used to harvest, for the use of boxes and contaminated water to the fruit washing, for storage in dirty places. The hyphae in tomato products indicate the use of raw materials contaminated or unsuitable hygiene conditions during processing. Although fungi are inactivated in heat processing step, its hyphae remain in the final product and search for detection and quantification is an indicator of the quality of raw material. Howard Method count of fungi mycelia in industrialized pulps evaluates the amount of decayed fruits existing in raw material. The Brazilian legislation governing processed and packaged products set the limit of 40% of positive fields in tomato pulps. The aim of this study was to evaluate the quality of the tomato pulp sold in greater São Paulo, through a monitoring during the four seasons of the year. All over 2010, 110 samples have been examined; 21 were taking in spring, 31 in summer, 31 in fall and 27 in winter, all from different lots and trademarks. Samples have been picked up in several stores located in the city of São Paulo. Howard method was used, recommended by the AOAC, 19th ed, 2011 16:19:02 technique - method 965.41. Hundred percent of the samples contained fungi mycelia. The count average of fungi mycelia per season was 23%, 28%, 8,2% and 9,9% in spring, summer, fall and winter, respectively. Regarding the spring samples of the 21 samples analyzed, 14.3% were off-limits proposed by the legislation. As for the samples of the fall and winter, all were in accordance with the legislation and the average of mycelial filament count has not exceeded 20%, which can be explained by the low temperatures during this time of the year. The acquired samples in the summer and spring showed high percentage of fungal mycelium in the final product, related to the high temperatures in these seasons. Considering that the limit of 40% of positive fields is accepted for the Brazilian Legislation (RDC nº 14/2014), 3 spring samples (14%) and 6 summer samples (19%) will be over this limit and subject to law penalties. According to gathered data, 82% of manufacturers of this product manage to keep acceptable levels of fungi mycelia in their product. In conclusion, only 9.2% samples were for the limits established by Resolution RDC. 14/2014, showing that the limit of 40% is feasible and can be used by these segment industries. The result of the filament count mycelial by Howard method is an important tool in the microscopic analysis since it measures the quality of raw material used in the production of tomato products.

Keywords: fungi, howard, method, tomato, pulps

Procedia PDF Downloads 373

Authors: Hassina Hafida Boukhalfa, Mathieu Massinon, Fréderic Lebeau, Mohamed Belhamra

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Drop behaviour during impact affects retention. The increase of adhesion is usually seen as the objective when applying crop protection products, while bouncing and shattering are seen as detrimental to spray retention. However, observation of drop impacts using high speed shadow graphy shows that fragmentation can occur in Wenzel wetting regime. In this case, a part of the drop sticks on the surface, what contributes to retention. Using simultaneous measurements of drop impacts with high speed imaging and of retention with fluorometry for 3 spray mixtures on excised barley leaves allowed us to observe that about 50% of the drops fragmented in Wenzel state remain on the leaf. Depending on spray mixture, these impact outcomes accounted for 25 to 50% of retention, the higher contribution being correlated with bigger VMD (Volume Median Diameter). This contribution is non-negligible and should be considered when a modelling of spray retention process is performed.

Keywords: drop impact, retention, fluorometry, high speed imaging

Procedia PDF Downloads 376

Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

Procedia PDF Downloads 38

Authors: V. K. Stalin, M. Kirithika, K. Shanmugam, K. Tharini

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Nanotechnology has been widely used in many applications such as medical, electronics, robotics and also in geotechnical engineering area through stabilization of bore holes, grouting etc. In this paper, an attempt is made for understanding the influence of nano copper slag (1%, 2% & 3%) on the index, compaction and UCC strength properties of natural soil (CH type) with and without lime stabilization for immediate and 7 days curing period. Results indicated that upto 1% of Nano copper slag, there is an increment in UC strength of virgin soil and lime stabilised soil. Beyond 1% nano copper slag, there is a steep reduction in UC strength and increase of plasticity both in lime stabilised soil and virgin soil. The effect of lime is found to show more influence on large surface area of nano copper slag in natural soil. For both immediate and curing effect, with 1% of Nano copper slag, the maximum unconfined compressive strength was 38% and 106% higher than that of the virgin soil strength.

Keywords: lime, nano copper slag, SEM, XRD, stabilisation

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Authors: Rainer Goetz, Zahra Ahaliabadeh, Princess S. Llanos, Aliaksandr S. Bandarenka, Tanja Kallio

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In order to understand the electrochemistry of all-solid-state batteries (ASSBs), the use of electrochemical equivalent circuits with a physical meaning is essential. A model battery is needed whose characterization is independent of the influence of the complex battery assembly. Lithium-Ion Conducting Glass-Ceramic (LICGC), a model solid electrolyte, is chosen for its stability in the air, but on the other hand, it is also well-known for its instability against metallic lithium upon direct contact. Hence, as a first step towards a model ASSB, the interface between lithium and the solid electrolyte (SE) is stabilized with thin (5 nm and 10 nm) coatings of titanium oxide (TO) and lithium titanium oxide (LTO). Impedance data shows that both materials are able to protect the SE surface from rapid degradation due to reducing lithium and, therefore, can serve as a protective interlayer on the anode side of a model ASSB.

Keywords: all-solid-state battery, lithium anode, solid electrolytes, interlayers

Procedia PDF Downloads 107

Authors: Ines Raies, Eric Kohler, Marc Fleury, Béatrice Ledésert

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In this work, the impact of clay minerals on the formation damage of sandstone reservoirs is studied to provide a better understanding of the problem of deep geothermal reservoir permeability reduction due to fine particle dispersion and migration. In some situations, despite the presence of filters in the geothermal loop at the surface, particles smaller than the filter size (<1 µm) may surprisingly generate significant permeability reduction affecting in the long term the overall performance of the geothermal system. Our study is carried out on cores from a Triassic reservoir in the Paris Basin (Feigneux, 60 km Northeast of Paris). Our goal is to first identify the clays responsible for clogging, a mineralogical characterization of these natural samples was carried out by coupling X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). The results show that the studied stratigraphic interval contains mostly illite and chlorite particles. Moreover, the spatial arrangement of the clays in the rocks as well as the morphology and size of the particles, suggest that illite is more easily mobilized than chlorite by the flow in the pore network. Thus, based on these results, illite particles were prepared and used in core flooding in order to better understand the factors leading to the aggregation and deposition of this type of clay particles in geothermal reservoirs under various physicochemical and hydrodynamic conditions. First, the stability of illite suspensions under geothermal conditions has been investigated using different characterization techniques, including Dynamic Light Scattering (DLS) and Scanning Transmission Electron Microscopy (STEM). Various parameters such as the hydrodynamic radius (around 100 nm), the morphology and surface area of aggregates were measured. Then, core-flooding experiments were carried out using sand columns to mimic the permeability decline due to the injection of illite-containing fluids in sandstone reservoirs. In particular, the effects of ionic strength, temperature, particle concentration and flow rate of the injected fluid were investigated. When the ionic strength increases, a permeability decline of more than a factor of 2 could be observed for pore velocities representative of in-situ conditions. Further details of the retention of particles in the columns were obtained from Magnetic Resonance Imaging and X-ray Tomography techniques, showing that the particle deposition is nonuniform along the column. It is clearly shown that very fine particles as small as 100 nm can generate significant permeability reduction under specific conditions in high permeability porous media representative of the Triassic reservoirs of the Paris basin. These retention mechanisms are explained in the general framework of the DLVO theory

Keywords: geothermal energy, reinjection, clays, colloids, retention, porosity, permeability decline, clogging, characterization, XRD, SEM-EDS, STEM, DLS, NMR, core flooding experiments

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Alvaro Valera Sosa

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Background: In recent years, childhood overweight and obesity have become an increasing and challenging phenomenon in Berlin and Germany in general. The highest shares of childhood overweight in Berlin are district localities within the inner city ring with lowest socio-economic levels and the highest number of migration background populations. Most factors explaining overweight and obesity are linked to individual dispositions and nutrition balances. Among various strategies, to target drinking behaviors of children and adolescents has been proven to be effective. On the one hand, encouraging the intake of water – which does not contain energy and thus may support a healthy weight status – on the other hand, reducing the consumption of sugar-containing beverages – which are linked to weight gain and obesity. Anyhow, these preventive approaches have mostly developed into individual or educational interventions widely neglecting environmental modifications. Therefore, little is known on how urban physical environment patterns and features can act as influence factors for childhood overweight. Aiming the development of a physical environment intervention tackling children overweight, this study evaluated urban situations surrounding public playgrounds in Berlin where the issue is evident. It verified the presence and state of physical environmental conditions that can be conducive for children to engage physical activity and water intake. Methods: The study included public playgrounds for children from 0-12 y/o within district localities with the highest prevalence of childhood overweight, highest population density, and highest mixed uses. A systematic observation was realized to describe physical environment patterns and features that may affect children health behavior leading to overweight. Neighborhood walkability for all age groups was assessed using the Walkability for Health framework (TU-Berlin). Playground physical environment conditions were evaluated using Active Living Research assessment sheets. Finally, the food environment in the playground’s pedestrian catchment areas was reviewed focusing on: proximity to suppliers offering sugar-containing beverages, and physical access for 5 y/o children and up to drinking water following the Drinking Fountains and Public Health guidelines of the Pacific Institute. Findings: Out of 114 locations, only 7 had a child population over 3.000. Three with the lowest socio-economic index and highest percentage of migration background were selected. All three urban situations presented similar walkability: large trafficked avenues without buffer bordering at least one side of the playground, and important block to block disconnections for active travel. All three playgrounds rated equipment conditions from good to very good. None had water fountains at the reach of a 5 y/o. and all presented convenience stores and/or fast food outlets selling sugar-containing beverages nearby the perimeter. Conclusion: The three playground situations selected are representative of Berlin locations where most factors that influence children overweight are found. The results delivered urban and architectural design directives for an environmental intervention, used to study children health-related behavior. A post-intervention evaluation could prove associations between designed spaces and children overweight rate reduction creating a precedent in public health interventions and providing novel strategies for the health sector.

Keywords: children overweight, evaluation research, public playgrounds, urban design, urban health

Procedia PDF Downloads 153

Authors: Andrea Paltrinieri, Alberto Dreassi, Stefano Miani, Alex Sclip

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The financial crises caused a collapse in prices of most asset classes, raising the attention on alternative investments such as Sukuk, a smaller, fast growing but often misunderstood market. We study diversification benefits of Sukuk, their correlation with other asset classes and the effects of their inclusion in investment portfolios of institutional and retail investors, through a comprehensive comparison of their risk/return profiles during and after the financial crisis. We find a beneficial performance adjusted for the specific volatility together with a lower correlation especially during the financial crisis. The distribution of Sukuk returns is positively skewed and leptokurtic, with a risk/return profile similarly to high yield bonds. Overall, our results suggest that Sukuk present diversification opportunities, a significant volatility-adjusted performance and lower correlations especially during the financial crisis. Our findings are relevant for a number of institutional investors. Long term investors, such as life insurers would benefit from Sukuk’s protective features during financial crisis yet keeping return and growth opportunities, whereas banks would gain due to their role of placers, advisors, market makers or underwriters.

Keywords: sukuk, zero beta asset, asset allocation, sukuk market

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Authors: Brahim Mahfoud

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A three-dimensional (3D) numerical technique is used to investigate the possibility of reducing the price of manufacturing some silicon-based devices, particularly those in which minor temperature gradients can significantly reduce performance. The silicon melt under the magnetic field produces Lorentz force, which can effectively suppress the flow which is caused by temperature gradients. This might allow some silicon-based products, such as solar cells, to be manufactured using a less pure, and hence less expensive. The thermocapillary effect of the silicon melt flow in thin annular pools subjected to an externally induced magnetic field was observed. The results reveal that with a strong enough magnetic field, isothermal lines change form and become concentric circles. As the amplitude of the magnetic field (Ha) grows, the azimuthal velocity and temperature at the free surface reduce, and the asymmetric 3D flow becomes axisymmetric steady when Ha surpasses a threshold value.

Keywords: magnetic field, manufacturing, silicon melt, thermocapillary

Procedia PDF Downloads 78

Authors: Kailin K. Zhang, Anne W. Thompson

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Electronic learning for continuing professional education (CPE) and interprofessional education (IPE) in healthcare have been shown to improve learners’ satisfaction, attitudes, and performance. Yet, their impact on behavior change in healthcare professionals through continuing interprofessional education (CIPE) is less known. A scoping review of 32 articles from 2010 to 2020 was conducted using the Arksey and O’Malley framework across all healthcare settings. It focused on evaluating the effectiveness of CIPE on behavior change of healthcare professionals, as well as identifying course features of electronic CIPE programs facilitating behavior change. Eight different types of electronic learning methods, including online programs, tele-education, and social media, were identified as interventions. More than 35,542 healthcare professionals participated in the interventions. Electronic learning for CIPE led to positive behavior outcomes in 30 out of 32 studies, especially through a change in patient care practices. The most successful programs provided interactive and authentic learning experiences tailored to learners’ needs while promoting the direct application of what was learned in their clinical settings. Future research should include monitoring of sustained behavior changes and their resultant patient outcomes.

Keywords: behavior change, continuing interprofessional education, distance learning, electronic learning

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Authors: Yueguang Gao, Qi Huang, Shunshan Feng

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In order to study the process and characteristic of the fragments in the warhead with one end cap under full constraint condition, we established a cylindrical casing with two end caps which one of which was fully constrained using the simulation analysis. The result showed that the fragmentation of cylindrical casing with one end full constrained has its own characteristic. The Mach stem was generated when the detonation wave propagated to the fully constrained end cap under the condition of one end detonation, working on unreactive explosives and causing the nearby fragment subjected to nearly 2.5 times the normal pressure to obtain a higher speed. The cylindrical casing first ruptured at the contact surface with the fully constrained end, and then at the end cover of the initiating end, and then the rupture extends to the whole cylindrical casing. The detonation products started to leak out from the rupture. Driving fragments to fly and forming two dense flying areas. The analysis of this paper can provide a reference for the optimal design of this kind of warhead.

Keywords: fragment, cylindrical casing, detonation waves, numerical simulation

Procedia PDF Downloads 122

Authors: Melek Tufan, Filiz Erden, E. Elhan Özus

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Apparel is a fact that has assigned wide cultural functions in development process even if it basically aims at protection during mankind's cultural development and course of live. It is an important cultural element that has been shaped by ecological conditions, social and personal values, traditions, cultural and economic conditions, at the same time it is a bearer of culture. Customs and traditions that maintain culture create differences in dressing styles of the region. These differences create traditional clothing forms specific to each region, which are different from each other or show close similarities. Differences which have dominant features create sense of dress specific to community owned. Samples of a kind of dress worn over salwar, long shirt, jacket, salwar and underpants that are types of local female dresses available in houses of yuruk community in Günaydın village of Balıkesir region have been found. By examining local dresses in terms of material, color, cutting, sewing, ornamentation technique and ornamentation subject and it has been aimed to record them with observation forms and transfer them to the next generations.

Keywords: women, traditional, Turkish Culture, art, fashion

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Authors: E. K. Mendez, N. A. Salazar, C. E. Orrego

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There is undoubted proof that increasing the intake of fruit lessens the risk of hypertension, coronary heart disease, stroke, and probable evidence that lowers the risk of cancer. Proper fruit drying is an excellent alternative to make their shelf-life longer, commercialization easier, and ready-to-eat healthy products or ingredients. The conventional way of drying is by hot air forced convection. However, this process step often requires a very long residence time; furthermore, it is highly energy consuming and detrimental to the product quality. Nowadays, power ultrasound (US) technic has been considered as an emerging and promising technology for industrial food processing. Most of published works dealing with drying food assisted by US have studied the effect of ultrasonic pre-treatment prior to air-drying on food and the airborne US conditions during dehydration. In this work a new approach was tested taking in to account drying time and two quality parameters of mango slices dehydrated by convection assisted by 20 KHz power US applied directly using a holed plate as product support and sound transmitting surface. During the drying of mango (Mangifera indica L.) slices (ca. 6.5 g, 0.006 m height and 0.040 m diameter), their weight was recorded every hour until final moisture content (10.0±1.0 % wet basis) was reached. After previous tests, optimization of three drying parameters - frequencies (2, 5 and 8 minutes each half-hour), air temperature (50-55-60⁰C) and power (45-70-95W)- was attempted by using a Box–Behnken design under the response surface methodology for the optimal drying time, color parameters and rehydration rate of dried samples. Assays involved 17 experiments, including a quintuplicate of the central point. Dried samples with and without US application were packed in individual high barrier plastic bags under vacuum, and then stored in the dark at 8⁰C until their analysis. All drying assays and sample analysis were performed in triplicate. US drying experimental data were fitted with nine models, among which the Verna model resulted in the best fit with R2 > 0.9999 and reduced χ2 ≤ 0.000001. Significant reductions in drying time were observed for the assays that used lower frequency and high US power. At 55⁰C, 95 watts and 2 min/30 min of sonication, 10% moisture content was reached in 211 min, as compared with 320 min for the same test without the use of US (blank). Rehydration rates (RR), defined as the ratio of rehydrated sample weight to that of dry sample and measured, was also larger than those of blanks and, in general, the higher the US power, the greater the RR. The direct contact and intermittent US treatment of mango slices used in this work improve drying rates and dried fruit rehydration ability. This technique can thus be used to reduce energy processing costs and the greenhouse gas emissions of fruit dehydration.

Keywords: ultrasonic assisted drying, fruit drying, mango slices, contact ultrasonic drying

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Authors: Kajetan Deja, Katarzyna Draganska-Deja, Mateusz Ormanczyk, Michał Procajlo

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Two glaciated fjords on Spitsbergen (Hornsund 77°N) and Kongsfjorden (79°N) were studied for the occurrence of macroplankton (mostly euphausids, hyperiids, chaetognaths) with the use of drop down the camera. The underwater imagery demonstrates that closer to the glacier front, where turbid and freshwater occurs, most of the macroplankters leave the upper water column and descends to the bottom (about 100m depth). Concentrations of macroplankton in the immediate vicinity of the sediment reach over 500 specimens per m² - what corresponds to the biomass of 10g C/m³. Such concentrations of macroplankton are of prime interest for fish, seals and other carnivores. Conditions in the near-bottom waters are in many respects better than in the upper water column- better oxygenated, cold, fully saline and transparent waters with rich food deposited on the seabed from the surface (sinking microplankton). We suggest that near bottom occurrence of macroplankton is related to the increase of glacier melt and freshwater discharge intensity.

Keywords: arctic, ecosystem, fjords, Krill

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Guantao Bai

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Public space is an indispensable and important component of the urban built environment. How to more accurately evaluate the usage characteristics of public space can help improve its spatial quality. Compared to traditional survey methods, computer vision technology based on deep learning has advantages such as dynamic observation and low cost. This study takes the public space of Shaping Park as an example and, based on deep learning computer vision technology, processes and analyzes the image data of the public space to obtain the spatial usage characteristics and spatiotemporal characteristics of the public space. Research has found that the spontaneous activity time in public spaces is relatively random with a relatively short average activity time, while social activities have a relatively stable activity time with a longer average activity time. Computer vision technology based on deep learning can effectively describe the spatial usage characteristics of the research area, making up for the shortcomings of traditional research methods and providing relevant support for creating a good public space.

Keywords: computer vision, deep learning, public spaces, using features

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Authors: Allison Futter

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Lifetime use of electronic cigarettes (EC) in college students has been estimated at around 50%; recent research shows Mobile Health (mHealth) technology is a promising tool to help address this public health issue, yet the majority of EC cessation mHealth tools found on smartphone app stores lack empirical support of their effectiveness. The Smiling Instead of Smoking (SiS) app is a positive psychology-based smartphone app for nondaily smokers. Due to previous success with brief, self-administered positive psychology exercises for cigarette cessation, this study examined the SiS App’s feasibility and effectiveness for EC cessation. Sixteen undergraduates used the SiS app for 3 weeks: one week before their quit date and 2 weeks after. As hypothesized, participants had significant declines in their craving and maintained pre-cessation levels of positive affect. There were no significant changes in dependency or self-efficacy. In the one-month follow-up survey, 38% of participants reported being abstinent. The app had an almost 4-star rating for its features (e.g., functionality, aesthetics, information, etc.) and participants reported moderate satisfaction with its use. Participants used the app, on average, 10 out of the 21 days of the prescribed app use. This study highlights the promise of mHealth support and positive psychology for EC cessation, adding to the understanding of possible ways to support EC quit attempts.

Keywords: e-cigarette cessation, mHealth, positive psychology, smartphone app

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Authors: Vanessa Cho, Janet Hsiao, Nigel King, Robert Anthonappa

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Background: The personal protective equipment (PPE) requirements for health care workers (HCWs) have changed significantly during the COVID-19 pandemic. Aim: To ascertain, using eye-tracking technology, what children notice the most when seeing HCWs in various PPE. Design: A Tobii nano pro-eye-tracking camera tracked 156 children's visual attention while they viewed photographs of HCWs in various PPEs. Eye Movement analysis with Hidden Markov Models (EMHMM) was employed to analyse 624 recordings using two approaches, namely (i) data-driven where children's fixation determined the regions of interest (ROIs), and (ii) fixed ROIs where the investigators predefined the ROIs. Results: Two significant eye movement patterns, namely distributed(85.2%) and selective(14.7%), were identified(P<0.05). Most children fixated primarily on the face regardless of the different PPEs. Children fixated equally on all PPE images in the distributed pattern, while a strong preference for unmasked faces was evident in the selective pattern (P<0.01). Conclusion: Children as young as 2.5 years used a top-down visual search behaviour and demonstrated their face processing ability. Most children did not show a strong visual preference for a specific PPE, while a minority preferred PPE with distinct facial features, namely without masks and loupes.

Keywords: COVID-19, PPE, dentistry, pediatric

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Authors: Siba Soren, Purnendu Parhi

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Today, the world is facing a severe challenge due to depletion of traditional fossil fuels. Scientists across the globe are working for a solution that involves a dramatic shift to practical and environmentally sustainable energy sources. High-capacity energy systems, such as metal-air batteries, fuel cells, are highly desirable to meet the urgent requirement of sustainable energies. Among the fuel cells, Direct methanol fuel cells (DMFCs) are recognized as an ideal power source for mobile applications and have received considerable attention in recent past. In this advanced electrochemical energy conversion technologies, Oxygen Reduction Reaction (ORR) is of utmost importance. However, the poor kinetics of cathodic ORR in DMFCs significantly hampers their possibilities of commercialization. The oxygen is reduced in alkaline medium either through a 4-electron (equation i) or a 2-electron (equation ii) reduction pathway at the cathode ((i) O₂ + 2H₂O + 4e⁻ → 4OH⁻, (ii) O₂ + H₂O + 2e⁻ → OH⁻ + HO₂⁻ ). Due to sluggish ORR kinetics the ability to control the reduction of molecular oxygen electrocatalytically is still limited. The electrocatalytic ORR starts with adsorption of O₂ on the electrode surface followed by O–O bond activation/cleavage and oxide removal. The reaction further involves transfer of 4 electrons and 4 protons. The sluggish kinetics of ORR, on the one hand, demands high loading of precious metal-containing catalysts (e.g., Pt), which unfavorably increases the cost of these electrochemical energy conversion devices. Therefore, synthesis of active electrocatalyst with an increase in ORR performance is need of the hour. In the recent literature, there are many reports on transition metal oxide (TMO) based ORR catalysts for their high activity TMOs are also having drawbacks like low electrical conductivity, which seriously affects the electron transfer process during ORR. It was found that 2D graphene layer is having high electrical conductivity, large surface area, and excellent chemical stability, appeared to be an ultimate choice as support material to enhance the catalytic performance of bare metal oxide. g-C₃N₄ is also another candidate that has been used by the researcher for improving the ORR performance of metal oxides. This material provides more active reaction sites than other N containing carbon materials. Rare earth oxide like CeO₂ is also a good candidate for studying the ORR activity as the metal oxide not only possess unique electronic properties but also possess catalytically active sites. Here we will discuss the ORR performance (in alkaline medium) of N-rGO/C₃N₄ supported nano Cerium Oxides hybrid synthesized by microwave assisted Solvothermal method. These materials exhibit superior electrochemical stability and methanol tolerance capability to that of commercial Pt/C.

Keywords: oxygen reduction reaction, electrocatalyst, cerium oxide, graphene

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Authors: Charalambous-Darden Nefi, Antoniou Phivi

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This study presents drawing as an alternative tool for facilitating interaction and communication among the members of a class (teachers and students) in an inclusive school setting. It applies elements of the Collaborative Drawing Method (CDM), an interactive method of drawing where two individuals draw together on the same surface. For the past ten years, the facilitators of this study have been researching the effects of spontaneous and non-spontaneous drawing upon elementary school students with Autism Spectrum Conditions (ASC). This research eventually led them to the application of elements of the CDM. The method was applied to both adults and children and children with one another. The astonishing outcomes of these applications indicate that collaborative drawing, with its inclusive nature, has the potential to help individuals develop interaction and communication among themselves, making it suitable for everyone. This workshop aims to allow the participants to become familiar with the CDM by applying it during the workshop, with the ultimate goal of enhancing their educational approaches by adding the CDM to their teaching methods.

Keywords: autism, collaborative drawing, autism spectrum condition, ASC

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