Search results for: Frank Adam

Authors: Jung Lee, L. G. Pee

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The 'Like' function in social media platforms represents the immediate responses of social media users to postings and other users. A large number of 'likes' is often attributed to fame, agreement, and support from others that many users are proud of and happy with. However, what 'like' implies exactly in social media context is still in discussion. Some argue that it is an accurate parameter of the preferences of social media users, whereas others refute that it is merely an instant reaction that is volatile and vague. To address this gap, this study investigates how social media users perceive the 'like' function and behave differently based on their perceptions. This study posits the following arguments. First, 'like' is interpreted as a quantified form of social capital that resides in social media platforms. This incarnated social capital rationalizes the attraction of people to social media and belief that social media platforms bring benefits to their relationships with others. This social capital is then conceptualized into cognitive and emotive dimensions, where social capital in the cognitive dimension represents the awareness of the 'likes' quantitatively, whereas social capital in the emotive dimension represents the receptions of the 'likes' qualitatively. Finally, the ambivalent perspective of the social media users on 'like' (i.e., social capital) is applied. This view rationalizes why social media users appreciate the reception of 'likes' from others but are aware that those 'likes' can distort the actual responses of other users by sending erroneous signals. The rationale on this ambivalence is based on whether users perceive social media as private or public spheres. When social media is more publicized, the ambivalence is more strongly observed. By combining the ambivalence and dimensionalities of the social capital, four types of social media users with different mechanisms on liking behaviors are identified. To validate this work, a survey with 300 social media users is conducted. The analysis results support most of the hypotheses and confirm that people have ambivalent perceptions on 'like' as a social capital and that perceptions influence behavioral patterns. The implication of the study is clear. First, this study explains why social media users exhibit different behaviors toward 'likes' in social media. Although most of the people believe that the number of 'likes' is the simplest and most frank measure of supports from other social media users, this study introduces the users who do not trust the 'likes' as a stable and reliable parameter of social media. In addition, this study links the concept of social media openness to explain the different behaviors of social media users. Social media openness has theoretical significance because it defines the psychological boundaries of social media from the perspective of users.

Keywords: ambivalent attitude, like function, social capital, social media

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Authors: Gabrielle Veloso, Melanie Porter, Kelsie Boulton, Adam Guastella

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The aim of the current systematic review was to examine child and parent factors and their associations with parent sensitivity towards children with Autism Spectrum Disorder (ASD). Eight bibliographic databases were used to identify peer-reviewed journal articles examining these associations via quantitative analyses, with parent sensitivity measured via validated and reliable observation coding systems. Thirty-one studies were finalized as having met full criteria for inclusion. The review found agreement across studies that parent sensitivity was positively associated with the child’s initiations and responsiveness toward their parent, with more frequent parent-directed behaviors providing greater opportunity for parents to act and react in sensitive manner. There was also substantial evidence that parent sensitivity predicted later growth in child language ability and child social skills. Other factors such as child attachment, parent insightfulness toward their child, and parent resolution of the diagnosis were also identified across a number of studies as being positively associated with parent sensitivity, however, interpretations of these findings were limited by the absence of covariates identified in the literature as explaining much of the variance in parent sensitivity. With respect to non-significant associations, the literature reliably found that parents showed sensitivity toward their child with ASD, regardless of child age, ASD symptomology, concurrent child social skills, and concurrent child cognitive abilities. The robust associations found in this review and their potential explanations can serve as a jump off point in identifying an understanding protective and risk factors for families of children with ASD. With regard to future directions in research, assessment of the studies’ methodological quality identified points for improvement with respect to the measurement of parent sensitivity, as well as the consideration of several important methodological confounds that may be controlled for in statistical analyses.

Keywords: ASD, autism, parenting, parent sensitivity

Procedia PDF Downloads 102

Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

Procedia PDF Downloads 251

Authors: Adam Y. Sulaiman, Donal F. Cotter, Ming J. Huang, Neil J. Hewitt

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Suitable low global warming potential (GWP) refrigerants that conform to F-gas regulations are required to extend the operational envelope of high-temperature heat pumps (HTHPs) used for industrial waste heat recovery processes. The thermophysical properties and characteristics of these working fluids need to be assessed to provide a comprehensive understanding of operational effectiveness in HTHP applications. This paper presents the results of a theoretical simulation to investigate a range of low-GWP refrigerants and their suitability to supersede refrigerants HFC-245fa and HFC-365mfc. A steady-state thermodynamic model of a single-stage HTHP with an internal heat exchanger (IHX) was developed to assess system cycle characteristics at temperature ranges between 50 to 80 °C heat source and 90 to 150 °C heat sink. A practical approach to maximize the operational efficiency was examined to determine the effects of regulating minimum superheat within the process and subsequent influence on energetic and exergetic efficiencies. A comprehensive map of minimum superheat across the HTHP operating variables were used to assess specific tipping points in performance at 30 and 70 K temperature lifts. Based on initial results, the refrigerants HCFO-1233zd(E) and HFO-1336mzz(Z) were found to be closely aligned matches for refrigerants HFC-245fa and HFC-365mfc. The overall results show effective performance for HCFO-1233zd(E) occurs between 5-7 K minimum superheat, and HFO-1336mzz(Z) between 18-21 K dependant on temperature lift. This work provides a method to optimize refrigerant selection based on operational indicators to maximize overall HTHPs system performance.

Keywords: high-temperature heat pump, minimum superheat, energy & exergy efficiency, low GWP refrigerants

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Authors: George N. Prodromidis, Frank A. Coutelieris

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Biogas can be currently considered as an alternative option for electricity production, mainly due to its high energy content (hydrocarbon-rich source), its renewable status and its relatively low utilization cost. Solid Oxide Fuel Cell (SOFC) stacks convert fuel’s chemical energy to electricity with high efficiencies and reveal significant advantages on fuel flexibility combined with lower emissions rate, especially when utilize biogas. Electricity production by biogas constitutes a composite problem which incorporates an extensive parametric analysis on numerous dynamic variables. The main scope of the presented study is to propose a detailed thermodynamic model on the optimization of SOFC-based power plants’ operation based on fundamental thermodynamics, energy and exergy balances. This model named THERMAS (THERmodynamic MAthematical Simulation model) incorporates each individual process, during electricity production, mathematically simulated for different case studies that represent real life operational conditions. Also, THERMAS offers the opportunity to choose a great variety of different values for each operational parameter individually, thus allowing for studies within unexplored and experimentally impossible operational ranges. Finally, THERMAS innovatively incorporates a specific criterion concluded by the extensive energy analysis to identify the most optimal scenario per simulated system in exergy terms. Therefore, several dynamical parameters as well as several biogas mixture compositions have been taken into account, to cover all the possible incidents. Towards the optimization process in terms of an innovative OPF (OPtimization Factor), presented here, this research study reveals that systems supplied by low methane fuels can be comparable to these supplied by pure methane. To conclude, such an innovative simulation model indicates a perspective on the optimal design of a SOFC stack based system, in the direction of the commercialization of systems utilizing biogas.

Keywords: biogas, exergy, efficiency, optimization

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Authors: Fatih Frank Alparslan

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The aviation industry is at a crucial turning point due to modern technologies, environmental concerns, and changing ways of transporting people and goods globally. The paper examines these challenges and opportunities comprehensively. It emphasizes the role of innovative management and advanced technology in shaping the future of air travel. This study begins with an overview of the current state of the aviation industry, identifying key areas where innovation and technology could be highly beneficial. It explores the latest advancements in airplane design, propulsion, and materials. These technological advancements are shown to enhance aircraft performance and environmental sustainability. The paper also discusses the use of artificial intelligence and machine learning in improving air traffic control, enhancing safety, and making flight operations more efficient. The management of these technologies is critically important. Therefore, the research delves into necessary changes in organization, culture, and operations to support innovation. It proposes a management approach that aligns with these modern technologies, underlining the importance of forward-thinking leaders who collaborate across disciplines and embrace innovative ideas. The paper addresses challenges in adopting these innovations, such as regulatory barriers, the need for industry-wide standards, and the impact of technological changes on jobs and society. It recommends that governments, aviation businesses, and educational institutions collaborate to address these challenges effectively, paving the way for a more innovative and eco-friendly aviation industry. In conclusion, the paper argues that the future of aviation relies on integrating new management practices with innovative technologies. It urges a collective effort to push beyond current capabilities, envisioning an aviation industry that is safer, more efficient, and environmentally responsible. By adopting a broad approach, this research contributes to the ongoing discussion about resolving the complex issues facing today's aviation sector, offering insights and guidance to prepare for future advancements.

Keywords: aviation innovation, technology integration, environmental sustainability, management strategies, multidisciplinary approach

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Authors: Hajir Abdllha, Alaa Mohamed, Khansa Almoniem, Naga Adam, Wdeea Alhaadi, Ahmed Elshikh, Ahmed Ali, Ismail Makuar, Anas Elnazeer, Nagat Elrofaei, Samir Abdoelftah, Monier Hemidan

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The present study was designed to investigate antimicrobial, and antioxidant activities of five species from Acacia (Acacia albidia, Acacia mellifera, Acacia nubica, Acacia seyal var. seyal and Acacia tortilis). Phytochemical study was piloted to detect the bioactive compounds, which have been responsible from the biological activities. The ethanol, chloroform and acetone plant extracts were seasoned against standard bacteria strains of gram +ve bacteria Staphylococcus aureus (ATCC 25923), Gram -ve bacteria Pseudomonas aeruginosa (ATCC 27853) and standard fungi Candida albicans (ATCC 90028), using cup-plate method. The antioxidant activities were conducted via DPPH radical scavenging and metal chelating assays. Prospective activity against the five species was observed in acetone extract. Ethanol extract showed highest activities against Staphylococcus aureus, and Candida albicans. Potential antioxidant activity was presented by ethanol. Cholorophorm and acetone extracts via DPPH, the radical scavenging activities were found to be 91±0.03, 88±0.01 and 85±0.04 respectively. The results of phytochemical screening showed that all extracts of studied plant contain flavonoids, saponins, terpenoids, steroids, alkaloids, phenols and tannins. This study gives rise to antioxidant, antimicrobial properties of studied plant, and showed interesting correlation with the phytochemical constituents and biological activities.

Keywords: antimicrobial, antioxidant, Acacia albidia, Acacia mellifera, Acacia nubica, Acacia seyal var. seyal, Acacia tortilis

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Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

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Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

Procedia PDF Downloads 106

Authors: Hajir, B. Abdllha, , Alaa, I. Mohamed, Khansa, A. Almoniem, Naga, I. Adam, Wdeea, Alhaadi, Ahmed, A. Elshikh, Ahmed, J. Ali, Ismail, G. Makuar, Anas, M. Elnazeer, Nagat, A. Elrofaei, Samir, F. Abdoelftah, Monier, N. Hemidan

Abstract:

The present study was designed to investigate antimicrobial, and antioxidant activities of five species from Acacia (Acacia albidia, Acacia mellifera, Acacia nubica, Acacia seyal var.seyal and Acacia tortilis). Phytochemical study was piloted to detect the bioactive compounds, which have been responsible from the biological activities. The ethanol, chloroform and acetone plant extracts were seasoned against standard bacteria strains of gram +ve bacteria Staphylococcus aureus (ATCC 25923) ,Gram -ve bacteria Pseudomonas aeruginosa (ATCC 27853) and standard fungi Candida albicans (ATCC 90028), using cup-plate method. The antioxidant activities were conducted via DPPH radical scavenging and metal chelating assays. Prospective activity against the five species was observed in acetone extract. Ethanol extract showed highest activities against Staphylococcus aureus, and Candida albicans. Potential antioxidant activity was presented by ethanol. Cholorophorm and acetone extracts via DPPH, the radical scavenging activities were found to be 91±0.03, 88±0.01 and 85±0.04 respectively. The results of phytochemical screening showed that all extracts of studied plant contain flavonoids, saponins, terpenoids, steroids, alkaloids, phenols and tannins. This study give rise to antioxidant, antimicrobial properties of studied plant, and showed interesting correlation with the phytochemical constituents and biological activities.

Keywords: antimicrobial, Antioxidant, Acacia albidia, Acacia mellifera, acacia nubica, acacia seyal var.seyal, Acacia tortilis

Procedia PDF Downloads 522

Authors: Hager Elsheikh, Juliane Glaubitz, Frank Ulrich Weiss, Matthias Sendler

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Aim: Acute pancreatitis (AP) and chronic pancreatitis (CP) are both accompanied by a prominent immune response which influences the course of disease. Whereas during AP the pro-inflammatory immune response dominates, during CP a fibroinflammatory response regulates organ remodeling. The transcription factor signal transducer and activator of transcription 6 (STAT6) is a crucial part of the Type 2 immune response. Here we investigate the role of STAT6 in a mouse model of AP and CP. Material and Methods: AP was induced by hourly repetitive i.p. injections of caerulein (50µg/kg/bodyweight) in C57Bl/6 J and STAT6-/- mice. CP was induced by repetitive caerulein injections 6 times a day, 3 days a week over 4 weeks. Disease severity was evaluated by serum amylase/lipase measurement, H&E staining of pancreas. Pancreatic infiltrate was characterized by immunofluorescent labeling of CD68, CD206, CCR2, CD4 and CD8. Pancreas fibrosis was evaluated by Azan blue staining. qRT-PCR was performed of Arg1, Nos2, Il6, Il1b, Col3a, Socs3 and Ym1. Affymetrix chip array analyses were done to illustrate the IL4/IL13/STAT6 signaling in bone marrow derived macrophages. Results: AP severity is mitigated in STAT6-/- mice, as shown by decreased serum amylase and lipase, as well as histological damage. CP mice surprisingly showed only slightly reduced fibrosis of the pancreas. Also staining of CD206 a classical marker of alternatively activated macrophages showed no decrease of M2-like polarization in the absence of STAT6. In contrast, transcription profile analysis in BMDM showed complete blockade of the IL4/IL13 pathway in STAT6-/- animals. Conclusion: STAT6 signaling pathway is protective during AP and mitigates the pancreatic damage. During chronic pancreatitis the IL4/IL13 – STAT6 axisis involved in organ fibrogenesis. Notably, fibrosis is not dependent on a single signaling pathway, and alternative macrophage activation is also complex and involves different subclasses (M2a, M2b, M2c and M2d) which could be independent of the IL4/IL13 STAT6 axis.

Keywords: chronic pancreatitis, macrophages, IL4/IL13, Type immune response

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Authors: Sylvain Chardon, Timotéo Payre, Hugo Grardel, Yann Quentel, Mathieu Thomachot, Gérald Aigouy, Frank Claeyssen

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With the increasing digitalization of society, access to data has become vital and strategic for individuals and nations. In this context, the number of satellite constellation projects is growing drastically worldwide and is a next-generation challenge of the New Space industry. So far, existing satellite constellations have been using radio frequencies (RF) for satellite-to-ground communications, inter-satellite communications, and feeder link communication. However, RF has several limitations, such as limited bandwidth and low protection level. To address these limitations, space optical communication will be the new trend, addressing both very high-speed and secured encrypted communication. Fast Steering Mirrors (FSM) are key components used in optical communication as well as space imagery and for a large field of functions such as Point Ahead Mechanisms (PAM), Raster Scanning, Beam Steering Mirrors (BSM), Fine Pointing Mechanisms (FPM) and Line of Sight stabilization (LOS). The main challenges of space FSM development for optical communication are to propose both a technology and a supply chain relevant for high quantities New Space approach, which requires secured connectivity for high-speed internet, Earth planet observation and monitoring, and mobility applications. CTEC proposes a mini-FSM technology offering a stroke of +/-6 mrad and a resonant frequency of 1700 Hz, with a mass of 50 gr. This FSM mechanism is a good candidate for giant constellations and all applications on board NanoSats and CubeSats, featuring a very high level of miniaturization and optimized for New Space high quantities cost efficiency. The use of piezo actuators offers a high resonance frequency for optimal control, with almost zero power consumption in step and stay pointing, and with very high-reliability figures > 0,995 demonstrated over years of recurrent manufacturing for Optronics applications at CTEC.

Keywords: fast steering mirror, feeder link, line of sight stabilization, optical communication, pointing ahead mechanism, raster scan

Procedia PDF Downloads 50

Authors: Balázs Ádám, Randi Nørgaard Fløe Pedersen, Jørgen Riis Jepsen

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Volatile chemicals that accumulate and release from freight containers constitute significant health risks. Fumigation to prevent spread of pests and off-gassing of freight are sources of hazardous chemicals. The aim of our study was to investigate the regulation and practice of container handling with focus on preventive measures applied against chemical exposures in Denmark. A comprehensive systematic search of scientific literature and organizational domains of international and Danish regulatory bodies was performed to explore regulations related to safe work with transport containers. The practice of container work was investigated in a series of semi-structured interviews with managers and health and safety representatives of organizations that handle transport containers. Although there are several international and national regulations and local safety instructions that relate to container handling, the provided information is not specific or up-to-date enough to conduct safe practice in many aspects. The interviewees estimate high frequency of containers with chemical exposure and deem that they can potentially damage health, although recognizable health effects are rare. Knowledge is limited about the chemicals and most of them cannot be measured by available devices. Typical preventive measures are passive ventilation and personal protective equipment but their use is not consistent and may not provide adequate protection. Hazardous chemicals are frequently present in transport containers; however, managers, workers and even occupational health professionals have limited knowledge about the problem. Detailed risk assessment and specific instructions on risk management are needed to provide safe conditions for work with containers.

Keywords: chemical exposure, fumigation, occupational health and safety regulation, transport container

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Authors: Mattahias Maj, Fabio Tatzgern, Karl Adam, Damir Kahrimanovic, Markus Varga

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Torpedo ladles are necessary transport carriages in steel production to move the molten crude iron from the blast furnace to the steel refining plant. This requires the ladles to be high temperature resistant and insulate well to preserve the temperature and hold the risk of solidification at bay. Therefore, the involved refractories lining the inside of the torpedo ladles are chosen mostly according to their thermal properties, although wear of the materials by the liquid iron is also of major importance. In this work, we combined investigations of the thermal behaviour with wear studies of the lining over the whole lifetime of a torpedo ladle. Additional numerical simulations enabled a detailed model of the mechanical loads and temperature propagation at the various stations (heating, filling, emptying, cooling). The core of the investigation were detailed 3D measurements of the ladle’s cavity and thereby quantitative information of the wear progress at different time intervals during the lifetime of the ladles. The measurements allowed for a separation of different wear zones according to severity, namely the “splash zone” where the melt directly hits the ladle, the “melt zone” where during transport always liquid melt is present, and the “slag zone”, where the slag floats on the melt causing the most severe wear loss. Numerical simulations of the filling process were taken to calculate stress levels and temperature gradients, which led to the different onset of wear on those zones. Thermal imaging and punctual temperature measurements allowed for a study of the thermal consequences entailed by the wear onset. Additional “classical” damage analysis of the worn refractories complete the investigation. Thereby the wear mechanisms leading to the substantial wear loss were disclosed.

Keywords: high temperature, tribology, liquid-solid interaction, refractories, thermography

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Authors: Adam N. Bell, Sarina J. Ergas, Michael Nystrom, Nathan P. Brennan, Kevan L. Main

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Integrated Multi-Trophic Aquaculture systems (IMTA) have the potential to improve the sustainability of seafood production, generate organic fertilizer and feed, remove waste discharges and reduce energy use. IMTA can include periphyton biofilters where algae and microbes grow on surfaces, along with caught detritus and amphipods. Periphyton biofilters provide many advantages: nitrification, denitrification, primary production and ecological diversity. The goal of this study was to determine how biofilter hydraulic residence time (τ) effects periphyton biomass production, dissolved oxygen (DO) and nutrient removal. A pilot scale recirculating aquaculture system (RAS) was designed, constructed and operated at different hydraulic residence times (τ= 1, 2, 4, 6, 8 hours per tank). For each τ, a conservative tracer study was conducted to investigate system hydrodynamics. Data on periphyton weights, pH, nitrogen species, phosphorus, temperature and DO were collected. The tracer study for τ =1 hour revealed that the normalized time < τ, indicating short-circuiting. Periphyton biomass production rate was relatively unaffected by τ (R_e<1 for all τ). Average ammonia nitrogen removal was > 75% for all trials. Nitrate and nitrite did not accumulate in the RAS for τ≥4 hours due to enhanced denitrification in anoxic zones. For τ≥4 hours DO concentration was at a maximum of 4 mg L-1 after 14:00, and decreased to 0 mg L-1 during nighttime. At τ=1 hour, the RAS stayed > 2 mg L-1 and DO was more evenly distributed. For the validation trial, the culture tank was stocked with Centropomus undecimalis (common snook) and the system was operated at τ= 1 hr. Preliminary results showed that a RAS with an integrated periphyton biofilter could support fish health with low nutrient concentrations DO > 6 mg L-1.

Keywords: sustainable aquaculture, resource recovery, nitrogen, microalgae, hydrodynamics, integrated multi-trophic aquaculture

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Authors: Arkadiusz Adam Gardaś

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In his theory of gaps, Wolfgang Iser states that literary texts often lack direct messages. Instead of using straightforward descriptions, authors leave the gaps or blanks, i.e., the spaces within the text that come into existence only when readers fill them with their understanding and experiences. This paper’s aim is to present Iser’s literary theory in an intersectional way by comparing it to the idea of intersemiotic translation. To be more precise, the author uses the example of Netflix’s adaption of Lucy Maud Montgomery’s Anne of Green Gables as a form of rendering a book into a film in such a way that certain textual gaps are filled with film images. Intersemiotic translation is a rendition in which signs of one kind of media are translated into the signs of the other media. Film adaptions are the most common, but not the only, type of intersemiotic translation. In this case, the role of the translator is taken by a screenwriter. A screenwriter’s role can reach beyond the direct meaning presented by the author, and instead, it can delve into the source material (here – a novel) in a deeper way. When it happens, a screenwriter is able to spot the gaps in the text and fill them with images that can later be presented to the viewers. Anne with an E, the Netflix adaption of Montgomery’s novel, may be used as a highly meaningful example of such a rendition. It is due to the fact that the 2017 series was broadcasted more than a hundred years after the first edition of the novel was published. This means that what the author might not have been able to show in her text can now be presented in a more open way. The screenwriter decided to use this opportunity to represent certain groups in the film, i.e., racial and sexual minorities, and women. Nonetheless, the series does not alter the novel; in fact, it adds to it by filling the blanks with more direct images. In the paper, fragments of the first season of Anne with an E are analysed in comparison to its source, the novel by Montgomery. The main purpose of that is to show how intersemiotic translation connected with the Iser’s literary theory can enrich the understanding of works of art, culture, media, and literature.

Keywords: intersemiotic translation, film, literary gaps, representation

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Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Onyekachi Ogbonnaya Iroanya, Taiye Abdullahi Gegele, Frank Tochukwu Egwuatu

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Introduction: Forensic taphonomy is a multifaceted area that incorporates decomposition, chemical and biological cadaver exposure in post-mortem event chronology and reconstruction to predict the Post Mortem Interval (PMI). The aim of this study was to evaluate the integrity of DNA extracted from the remains of embalmed decomposed Sus domesticus tissues buried in different soil types. Method: A total of 12 limbs of Sus domesticus weighing between 0.7-1.4 kg were used. Each of the samples across the groups was treated with 10% formaldehyde, absolute methanol and 50% Pine oil for 24 hours before burial except the control samples, which were buried immediately. All samples were buried in shallow simulated Clay, Sandy and Loamy soil graves for 12 months. The DNA for each sample was extracted and quantified with Nanodrop Spectrophotometer (6305 JENWAY spectrometers). The rate of decomposition was examined through the modified qualitative decomposition analysis. Extracted DNA was amplified through PCR and bands visualized via gel electrophoresis. A biochemical enzyme assay was done for each burial grave soil. Result: The limbs in all burial groups had lost weight over the burial period. There was a significant increase in the soil urease level in the samples preserved in formaldehyde across the 3 soil type groups (p≤0.01). Also, the control grave soils recorded significantly higher alkaline phosphatase, dehydrogenase and calcium carbonate values compared to experimental grave soils (p≤0.01). The experimental samples showed a significant decrease in DNA concentration and purity when compared to the control groups (p≤0.01). Obtained findings of the soil biochemical analysis showed the embalming treatment altered the relationship between organic matter decomposition and soil biochemical properties as observed in the fluctuations that were recorded in the soil biochemical parameters. The PCR amplified DNA showed no bands on the gel electrophoresis plates. Conclusion: In criminal investigations, factors such as burial grave soil, grave soil biochemical properties, antemortem exposure to embalming chemicals should be considered in post-mortem interval (PMI) determination.

Keywords: forensic taphonomy, post-mortem interval (PMI), embalmment, decomposition, grave soil

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Authors: Paul Rowley, Adam Thirkill, Nick Doylend, Philip Leicester, Becky Gough

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The dynamic performance of all energy generation technologies is impacted to varying degrees by the stochastic properties of the wider system within which the generation technology is located. This stochasticity can include the varying nature of ambient renewable energy resources such as wind or solar radiation, or unpredicted changes in energy demand which impact upon the operational behaviour of thermal generation technologies. An understanding of these stochastic impacts are especially important in contexts such as highly distributed (or embedded) generation, where an understanding of issues affecting the individual or aggregated performance of high numbers of relatively small generators is especially important, such as in ESCO projects. Probabilistic evaluation of monitored or simulated performance data is one technique which can provide an insight into the dynamic performance characteristics of generating systems, both in a prognostic sense (such as the prediction of future performance at the project’s design stage) as well as in a diagnostic sense (such as in the real-time analysis of underperforming systems). In this work, we describe the development, application and outcomes of a new approach to the acquisition of datasets suitable for use in the subsequent performance and impact analysis (including the use of Bayesian approaches) for a number of distributed generation technologies. The application of the approach is illustrated using a number of case studies involving domestic and small commercial scale photovoltaic, solar thermal and natural gas boiler installations, and the results as presented show that the methodology offers significant advantages in terms of plant efficiency prediction or diagnosis, along with allied environmental and social impacts such as greenhouse gas emission reduction or fuel affordability.

Keywords: renewable energy, dynamic performance simulation, Bayesian analysis, distributed generation

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Authors: Timothy E. Frank, Peter J. Amaddio, Elizabeth D. Decko, Alexis M. Tri, Darcy A. Farrell, Cole M. Landes

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Ultra high performance concrete (UHPC) is a class of cementitious composites with a relatively large percentage of cement generating high compressive strength. Additionally, UHPC contains disbursed fibers, which control crack width, carry the tensile load across narrow cracks, and limit spalling. These characteristics lend themselves to a wide range of structural applications when UHPC members are reinforced with longitudinal steel. Efficient use of fibers and longitudinal steel is required to keep lifecycle cost competitive in reinforced UHPC members; this requires full utilization of both the compressive and tensile qualities of the reinforced cementitious composite. The objective of this study is to investigate the shear response of steel-reinforced UHPC beams to guide design decisions that keep initial costs reasonable, limit serviceability crack widths, and ensure a ductile structural response and failure path. Five small-scale, reinforced UHPC beams were experimentally tested. Longitudinal steel, transverse steel, and casting direction were varied. Results indicate that an increase in transverse steel in short-spanned reinforced UHPC beams provided additional shear capacity and increased the peak load achieved. Beams with very large longitudinal steel reinforcement ratios did not achieve yield and fully utilized the tension properties of the longitudinal steel. Casting the UHPC beams from the end or from the middle affected load-carrying capacity and ductility, but image analysis determined the fiber orientation was not significantly different. It is believed the presence of transverse and longitudinal steel reinforcement minimized the effect of different UHPC casting directions. Results support recent recommendations in the literature suggesting a 1% fiber volume fraction is sufficient within UHPC to prevent spalling and provide compressive fracture toughness under extreme loading conditions.

Keywords: fiber orientation, reinforced ultra high performance concrete beams, shear, transverse steel

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Authors: Ghalia Shamlan, M. Denise Robertson, Adam Collins

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Appetite control (i.e. control of energy intake) is important for weight maintenance. Exercise contributes to the most variable component of energy expenditure (EE) but its impact is beyond the energy cost of exercise including physiological, behavioural, and appetite effects. Exercise is known to acutely influence effect appetite but evidence as to the independent effect of intensity is lacking. This study investigated the role of exercise intensity on appetite, energy intake (EI), appetite related hormone, fat utilisation and subjective measures of appetite. One hour after a standardised breakfast, 10 sedentary overweight volunteers. Subjects undertook either 8 repeated 60 second bouts of cycling at 95% VO2max (high intensity) or 30 minutes of continuous cycling, at a fixed cadence, equivalent to 50% of the participant’s VO2max (low intensity) in a randomised crossover design. Glucose, NEFA, glucagon-like peptide-1 (GLP-1) were measured fasted, postprandial, and pre and post-exercise. Satiety was assessed subjectively throughout the study using visual analogue scales (VAS). Ad libitum intake of a pasta meal was measured at the end (3-h post-breakfast). Interestingly, there was not significant difference in EE fat oxidation between HI and LI post-exercise. Also, no significant effect of high intensity (HI) was observed on the ad libitum meal, 24h and 48h EI post-exercise. However the mean 24h EI was 3000 KJ lower following HI than low intensity (LI). Despite, no significant differences in hunger score, glucose, NEFA and GLP-1 between both intensities were observed. However, NEFA and GLP-1 plasma level were higher until 30 min post LI. In conclusion, the similarity of EE and oxidation outcomes could give overweight individuals an option to choose between intensities. However, HI could help to reduce EI. There are mechanisms and consequences of exercise in short and long-term appetite control; however, these mechanisms warrant further explanation. These results support the need for future research in to the role of in regulation energy balance, especially for obese people.

Keywords: appetite, exercise, food intake, energy expenditure

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Authors: Xiaojie Cheng, Ulrike Frank, Feng Zhao, Karin Pritsch

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Ragweed (Ambrosia artemisiifolia) is an invasive weed that has become an increasing global problem. In addition to affecting land use and crop yields, ragweed has a strong impact on human health as it produces highly allergenic pollen. Global warming will result in an earlier and longer pollen season enhanced pollen production and an increase in pollen allergenicity with a negative effect on atopic patients. The aims of this study were to investigate the effects of increasing temperature, the future climate scenario in the Munich area, southern Germany, predicted on the basis of RCP8.5 until the end of 2050s, or/and NO₂, a major air pollutant, 1) on the vegetative and reproductive characteristics of ragweed plants, 2) on the total allergenicity of ragweed pollen, 3) on the total pollen proteomic patterns. Ragweed plants were cultivated for the whole plant vegetation period under controlled conditions either under ambient climate conditions or 4°C higher temperatures with or without additional NO₂. Higher temperature resulted in bigger plant sizes, longer male inflorescences, and longer pollen seasons. The total allergenic potential of the pollen was accessed by dot blot using serum from ragweed pollen sensitized patients. The comparative immunoblot analysis revealed that the in vivo fumigation of ragweed plants with elevated NO₂-concentrations significantly increased the allergenic potential of the pollen, and in combination with increased temperature, the allergenic potential was even higher. On the other hand, label-free protein quantification by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed. The results showed that more proteins were significantly up- and down-regulated under higher temperatures with/without elevated NO₂ conditions. Most of the highly expressed proteins were participating intensively in the metabolic process, the cellular process, and the stress defense process. These findings suggest that rising temperature and elevated NO₂ are important environmental factors for higher abiotic stress activities, catalytic activities, and thus higher allergenic potential observed in pollen proteins.

Keywords: climate change, NO₂, pollen proteome, ragweed, temperature

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Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Frank Fan

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PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

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Authors: Adam J. Carinci

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Background: The opioid epidemic is the most pressing healthcare crisis of our time. There is increasing recognition that opioids have limited long-term efficacy and are associated with hyperalgesia, addiction, and increased morbidity and mortality. Therefore, alternative strategies to combat chronic pain are paramount. We initiated a multicenter retrospective case series to review the efficacy of DRG stimulation in facilitating opioid tapering, opioid discontinuation and as a viable alternative to chronic opioid therapy. Purpose: The dorsal root ganglion (DRG) plays a key role in the development and maintenance of pain. Recent innovations in neuromodulation, specifically, dorsal root ganglion stimulation, offers an effective alternative to opioids in the treatment of chronic pain. This retrospective case series demonstrates preliminary evidence that DRG stimulation facilitates opioid tapering, opioid discontinuation and presents a viable alternative to chronic opioid therapy. Procedure: This small multicenter retrospective case series provides preliminary evidence that DRG stimulation facilitates opioid weaning, opioid tapering and is a viable option to opioid therapy in the treatment of chronic pain. A retrospective analysis was completed. Visual analog scale pain scores and pain medication usage were collected at the baseline visit and after four weeks, 3 months and 6 months of treatment. Ten consecutive patients across two study centers were included. The pain was rated 7.38 at baseline and decreased to 1.50 at the 4-week follow-up, a reduction of 79.5%. All patients significantly decreased their opioid pain medication use with an average > 30% reduction in morphine equivalents and four were able to discontinue their medications entirely. Conclusion: This Retrospective case series demonstrates preliminary evidence that DRG stimulation facilitates opioid tapering, opioid discontinuation and presents a viable alternative to chronic opioid therapy.

Keywords: dorsal root ganglion, neuromodulation, opioid sparing, stimulation

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Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

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The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

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Authors: Henok Hailemariam, Frank Wuttke

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Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.

Keywords: collapsible soil, dielectric permittivity, moisture content, relative subsidence

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Authors: N. Harun, E. E. Masiren, W. H. W. Ibrahim, F. Adam

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Amine absorption process is an approach for mitigation of CO2 from flue gas that produces from power plant. This process is the most common system used in chemical and oil industries for gas purification to remove acid gases. On the challenges of this process is high energy requirement for solvent regeneration to release CO2. In the past few years, mixed alkanolamines have received increasing attention. In most cases, the mixtures contain N-methyldiethanolamine (MDEA) as the base amine with the addition of one or two more reactive amines such as PZ. The reason for the application of such blend amine is to take advantage of high reaction rate of CO2 with the activator combined with the advantages of the low heat of regeneration of MDEA. Several experimental and simulation studies have been undertaken to understand this process using blend MDEA/PZ solvent. Despite those studies, the mechanism of CO2 absorption into the aqueous MDEA is not well understood and available knowledge within the open literature is limited. The aim of this study is to investigate the intermolecular interaction of the blend MDEA/PZ using Molecular Dynamics (MD) simulation. MD simulation was run under condition 313K and 1 atm using NVE ensemble at 200ps and NVT ensemble at 1ns. The results were interpreted in term of Radial Distribution Function (RDF) analysis through two system of interest i.e binary and tertiary. The binary system will explain the interaction between amine and water molecule while tertiary system used to determine the interaction between the amine and CO2 molecule. For the binary system, it was observed that the –OH group of MDEA is more attracted to water molecule compared to –NH group of MDEA. The –OH group of MDEA can form the hydrogen bond with water that will assist the solubility of MDEA in water. The intermolecular interaction probability of –OH and –NH group of MDEA with CO2 in blended MDEA/PZ is higher than using single MDEA. This findings show that PZ molecule act as an activator to promote the intermolecular interaction between MDEA and CO2.Thus, blend of MDEA with PZ is expecting to increase the absorption rate of CO2 and reduce the heat regeneration requirement.

Keywords: amine absorption process, blend MDEA/PZ, CO2 capture, molecular dynamic simulation, radial distribution function

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Authors: Marta Błażkiewicz, Adam Konefał

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Currently, boron-neutron therapy is carried out mainly with the use of a neutron beam generated in research nuclear reactors. This fact limits the possibility of realization of a BNCT in centers distant from the above-mentioned reactors. Moreover, the number of active nuclear reactors in operation in the world is decreasing due to the limited lifetime of their operation and the lack of new installations. Therefore, the possibilities of carrying out boron-neutron therapy based on the neutron beam from the experimental reactor are shrinking. However, the use of nuclear power reactors for BNCT purposes is impossible due to the infrastructure not intended for radiotherapy. Therefore, a serious challenge is to find ways to perform boron-neutron therapy based on neutrons generated outside the research nuclear reactor. This work meets this challenge. Its goal is to develop a BNCT technique based on commonly available neutron sources such as Cf-252 and PuBe, which will enable the above-mentioned therapy in medical centers unrelated to nuclear research reactors. Advances in the field of neutron source fabrication make it possible to achieve strong neutron fluxes. The current stage of research focuses on the development of virtual models of the above-mentioned sources using the Monte Carlo simulation method. In this study, the GEANT4 tool was used, including the model for simulating neutron-matter interactions - High Precision Neutron. Models of neutron sources were developed on the basis of experimental verification based on the activation detectors method with the use of indium foil and the cadmium differentiation method allowing to separate the indium activation contribution from thermal and resonance neutrons. Due to the large number of factors affecting the result of the verification experiment, the 10% discrepancy between the simulation and experiment results was accepted.

Keywords: BNCT, virtual models, neutron sources, monte carlo, GEANT4, neutron activation detectors, gamma spectroscopy

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Authors: Sayed M. Ahmed, Sawsan S. Darwish, Mahmoud A. Adam, Nagib A. Elmarzugi, Mohammad A. Al-Dosari, Nadia A. Al-Mouallimi

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Historical stone surfaces and architectural heritage especially which located in open areas may undergo unwanted changes due to the exposure to many physical and chemical deterioration factors, air pollution, soluble salts, Rh/temperature, and biodeterioration are the main causes of decay of stone building materials. The development and application of self-cleaning treatments on historical and architectural stone surfaces could be a significant improvement in conservation, protection, and maintenance of cultural heritage. In this paper, nanometric titanium dioxide has become a promising photocatalytic material owing to its ability to catalyze the complete degradation of many organic contaminants and represent an appealing way to create self-cleaning surfaces, thus limiting maintenance costs, and to promote the degradation of polluting agents. The obtained nano-TiO2 coatings were applied on travertine (Marble and limestone often used in historical and monumental buildings). The efficacy of the treatments has been evaluated after coating and artificial thermal aging, through capillary water absorption, Ultraviolet-light exposure to evaluate photo-induced and the hydrophobic effects of the coated surface, while the surface morphology before and after treatment was examined by scanning electron microscopy (SEM). The changes of molecular structure occurring in treated samples were spectroscopy studied by FTIR-ATR, and Colorimetric measurements have been performed to evaluate the optical appearance. All the results get together with the apparent effect that coated TiO2 nanoparticles is an innovative method, which enhanced the durability of stone surfaces toward UV aging, improved their resistance to relative humidity and temperature, self-cleaning photo-induced effects are well evident, and no alteration of the original features.

Keywords: architectural calcareous stone monuments, coating, photocatalysis TiO2, self-cleaning, thermal aging

Procedia PDF Downloads 231