Search results for: toxicity prediction

Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

Procedia PDF Downloads 259

Authors: Dalila Chaid, Yacine Houmel, Mohamed Lamine Belloulou

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Peripheral neuropathy is a rare but worrying complication of peripheral local anaesthesia. It is caused either by needle contact with the nerve root or by the direct toxicity of local anaesthetics, leading to nerve damage, injury or irritation. Although uncommon, it remains a major concern for anaesthetists. The aim of the study was to assess the prevalence of nerve block-associated neuropathy in knee surgery and to identify the contributing factors in order to minimise the occurrence of this complication. The study also assessed the severity and evolution of lesions, as well as the factors leading to neuropathic pain. Methodology: It is a retrospective observational study on cases of neuropathy related to nerve blocks of the lower limb for knee surgery over a period of seven years (2016-2022). The study included a total of 6,000 patients Analyse the anaesthetic and neuropathic pain-related parameters received from these patients to determine the prevalence and severity of neuropathy. Findings: the prevalence of nerve block-related neuropathy in our study is 5.8‰ for the sciatic nerve and 0.9‰ for the femoral nerve. This was higher compared to the reported rates in the literature, which were between 0.0 to 5‰ for the Sciatic nerve and 0.0 to 3.4‰ for the femoral nerve. These findings highlight the importance of identifying and implementing an ideal anesthesia procedure to reduce the risk of neuropathy associated with nerve blocks. Theoretical Importance: The findings of this study contribute to the existing literature on peripheral neuropathy following locoregional anesthesia. By identifying the prevalence and severity of neuropathy related to nerve blocks, as well as the underlying factors, we provide valuable insights for anesthetists to improve patient safety. This study also emphasizes the need for compliance with technical safety rules to minimize the occurrence of neuropathy. Data Collection and Analysis Procedures: For this study, 25 clinics with retrospective data were collected of neuropathy associated with nerve blocks for knee surgery over a span of seven years. Parameters related to anaesthesia and neuropathic pain were analysed to determine prevalence,severity, and progression of neuropathy. Comparison of our results with the existing literature in order to assess their significance. Questions Addressed: This study aims to define the following points: 1. The prevalence of neuropathy associated with nerve blocks for knee surgery. 2. The factors underlying the development of neuropathy after nerve blocks. 3. Reducing the risk of neuropathy by complying with technical safety rules. 4. Assessing the severity and evolution of neuropathic pain in these cases. Conclusion: this study highlights the need for careful consideration and implementation of anesthesia procedures during nerve blocks for knee surgery. The prevalence of neuropathy linked to these blocks was higher compared to the literature, emphasizing the importance of identifying and minimizing contributing factors. Compliance with technical safety rules is crucial to reduce the risk of peripheral neuropathy. This study provides valuable insights to anesthetists and contributes to improving patient safety in the field of locoregional anesthesia.

Keywords: phantom limb, neuropathic pain, lower limb amputee, ultrasound-guided locoreginal anesthesia

Procedia PDF Downloads 43

Authors: Robin Anderson, David Nisbet

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Nitrate, 3-nitro-1-propionic acid (NPA) and 3-nitro-1-propanol (NPOH) are biologically active chemicals that can accumulate naturally in rangeland grasses forages consumed by grazing cattle, sheep and goats. While toxic to livestock if accumulations and amounts consumed are high enough, particularly in animals having no recent exposure to the forages, these chemicals are known to be potent inhibitors of methane-producing bacteria inhabiting the rumen. Consequently, there is interest in examining their potential use as anti-methanogenic compounds to decrease methane emissions by grazing ruminants. Presently, rumen microbes, collected freshly from a cannulated Holstein cow maintained on 50:50 corn based concentrate:alfalfa diet were mixed (10 mL fluid) in 18 x 150 mm crimp top tubes with 0.5 of high nitrate-containing barley (Hordeum vulgare; containing 272 µmol nitrate per g forage dry matter), and NPA- or NPOH- containing milkvetch forages (Astragalus canadensis and Astragalus miser containing 80 and 174 soluble µmol NPA or NPOH/g forage dry matter respectively). Incubations containing 0.5 g alfalfa (Medicago sativa) were used as controls. Tubes (3 per each respective forage) were capped and incubated anaerobically (using oxygen free carbon dioxide) for 24 h at 39oC after which time amounts of total gas produced were measured via volume displacement and headspace samples were analyzed by gas chromatography to determine concentrations of hydrogen and methane. Fluid samples were analyzed by gas chromatography to measure accumulations of fermentation acids. A completely randomized analysis of variance revealed that the nitrate-containing barley and both the NPA- and the NPOH-containing milkvetches significantly decreased methane production, by > 50%, when compared to methane produced by populations incubated similarly with alfalfa (70.4 ± 3.6 µmol/ml incubation fluid). Accumulations of hydrogen, which are typically increased when methane production is inhibited, by incubations with the nitrate-containing barley and the NPA- and NPOH-containing milkvetches did not differ from accumulations observed in the alfalfa controls (0.09 ± 0.04 µmol/mL incubation fluid). Accumulations of fermentation acids produced in the incubations containing the high-nitrate barley and the NPA- and NPOH-containing milkvetches likewise did not differ from accumulations observed in incubations containing alfalfa (123.5 ± 10.8, 36.0 ± 3.0, 17.1 ± 1.5, 3.5 ± 0.3, 2.3 ± 0.2, 2.2 ± 0.2 µmol/mL incubation fluid for acetate, propionate, butyrate, valerate, isobutyrate, and isovalerate, respectively). This finding indicates the microbial populations did not compensate for the decreased methane production via compensatory changes in production of fermentative acids. Stoichiometric estimation of fermentation balance revealed that > 77% of reducing equivalents generated during fermentation of the forages were recovered in fermentation products and the recoveries did not differ between the alfalfa incubations and those with the high-nitrate barley or the NPA- or NPOH-containing milkvetches. Stoichiometric estimates of amounts of hexose fermented similarly did not differ between the nitrate-, NPA and NPOH-containing incubations and those with the alfalfa, averaging 99.6 ± 37.2 µmol hexose consumed/mL of incubation fluid. These results suggest that forages containing nitrate, NPA or NPOH may be useful to reduce methane emissions of grazing ruminants provided risks of toxicity can be effectively managed.

Keywords: nitrate, nitropropanol, nitropropionic acid, rumen methane emissions

Procedia PDF Downloads 104

Authors: Sharmin Sultana, Nicolas Nuns, Pardis Simon, Jean-Marc Giraudon, Jean-Francois Lamonior, Nathalie D. Geyter, Rino Morent

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Environmental issues, especially air pollution, have become a huge concern of environmental legislation as a consequence of growing awareness in our global world. In this regard, control of volatile organic compounds (VOCs) emission has become an important issue due to their potential toxicity, carcinogenicity, and mutagenicity. The research of innovative technologies for VOC abatement is stimulated to accommodate the new stringent standards in terms of VOC emission. One emerging strategy is the coupling of 2 existing complementary technologies, namely here non-thermal plasma (NTP) and heterogeneous catalysis, to get a more efficient process for VOC removal in air. The objective of this current work is to investigate the abatement of trichloroethylene (TCE-highly toxic chlorinated VOC) from moist air (RH=15%) as a function of time by combined use of multi-pin-to-plate negative DC corona/glow discharge with Fe-doped cryptomelanes catalyst downstream i.e. post plasma-catalysis (PPC) process. For catalyst alone case, experiments reveal that, initially, Fe doped cryptomelane (regardless the mode of Fe incorporation by co-precipitation (Fe-K-OMS-2)/ impregnation (Fe/K-OMS-2)) exhibits excellent activity to decompose TCE compared to cryptomelane (K-OMS-2) itself. A maximum obtained value of TCE abatement after 6 min is as follows: Fe-KOMS-2 (73.3%) > Fe/KOMS-2 (48.5) > KOMS-2 (22.6%). However, with prolonged operation time, whatever the catalyst under concern, the abatement of TCE decreases. After 111 min time of exposure, the catalysts can be ranked as follows: Fe/KOMS-2 (11%) < K-OMS-2 (12.3%) < Fe-KOMS-2 (14.5%). Clearly, this phenomenon indicates catalyst deactivation either by chlorination or by blocking the active sites. Remarkably, in PPC configuration (energy density = 60 J/L, catalyst temperature = 150°C), experiments reveal an enhanced performance towards TCE removal regardless the type of catalyst. After 6 min time on stream, the TCE removal efficiency amount as follows: K-OMS-2 (60%) < Fe/K-OMS-2 (79%) < Fe-K-OMS-2 (99.3%). The enhanced performances over Fe-K-OMS-2 catalyst are attributed to its high surface oxygen mobility and structural defects leading to high O₃ decomposition efficiency to give active species able to oxidize the plasma processed hazardous\by-products and the possibly remaining VOC into CO₂. Moreover, both undoped and doped catalysts remain strongly capable to abate TCE with time on stream. The TCE removal efficiencies of the PPC processes with Fe/KOMS-2 and KOMS-2 catalysts are not affected by time on stream indicating an excellent catalyst stability. When using the Fe-K-OMS-2 as catalyst, TCE abatement slightly reduces with time on stream. However, it is noteworthy to stress that still a constant abatement of 83% is observed during at least 30 minutes. These results prove that the combination of NTP with catalysts not only increases the catalytic activity but also allows to avoid, to some extent, the poisoning of catalytic sites resulting in an enhanced catalyst stability. In order to better understand the different surface processes occurring in the course of the total TCE oxidation in PPC experiments, a detailed X-ray Photoelectron Spectroscopy (XPS) and Time of Flight-Secondary Ion Mass Spectrometry (ToF-SIMS) study on the fresh and used catalysts is in progress.

Keywords: Fe doped cryptomelane, non-thermal plasma, plasma-catalysis, stability, trichloroethylene

Procedia PDF Downloads 189

Authors: Ravi Verma

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Cryosorption pump is the best solution to achieve clean, vibration free ultra-high vacuum. Furthermore, the operation of cryosorption pump is free from the influence of electric and magnetic fields. Due to these attributes, this pump is used in the space simulation chamber to create the ultra-high vacuum. The cryosorption pump comprises of three parts (a) panel which is cooled with the help of cryogen or cryocooler, (b) an adsorbent which is used to adsorb the gas molecules, (c) an epoxy which holds the adsorbent and the panel together thereby aiding in heat transfer from adsorbent to the panel. The performance of cryosorption pump depends on the temperature of the adsorbent and hence, on the thermal conductivity of the epoxy. Therefore we have made an attempt to increase the thermal conductivity of epoxy adhesive by mixing nano-sized graphene filler particles. The thermal conductivity of epoxy-graphene composite adhesive is measured with the help of indigenously developed experimental setup in the temperature range from 4.5 K to 7 K, which is generally the operating temperature range of cryosorption pump for efficiently pumping of hydrogen and helium gas. In this article, we have presented the experimental results of epoxy-graphene composite adhesive in the temperature range from 4.5 K to 7 K. We have also proposed an analytical heat conduction model to find the thermal conductivity of the composite. In this case, the filler particles, such as graphene, are randomly distributed in a base matrix of epoxy. The developed model considers the complete spatial random distribution of filler particles and this distribution is explained by Binomial distribution. The results obtained by the model have been compared with the experimental results as well as with the other established models. The developed model is able to predict the thermal conductivity in both isotropic regions as well as in anisotropic region over the required temperature range from 4.5 K to 7 K. Due to the non-empirical nature of the proposed model, it will be useful for the prediction of other properties of composite materials involving the filler in a base matrix. The present studies will aid in the understanding of low temperature heat transfer which in turn will be useful towards the development of high performance cryosorption pump.

Keywords: composite adhesive, computational modelling, cryosorption pump, thermal conductivity

Procedia PDF Downloads 73

Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

Procedia PDF Downloads 143

Authors: Pierre van Tonder, Dinesh Muthoo, Kim twiname

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Many existing and newly built structures are constructed on the design basis of the engineer and the workmanship of the construction company. However, when considering larger structures where more people are exposed to the building, its structural integrity is of great importance considering the safety of its occupants (Raghu, 2013). But how can the structural integrity of a building be monitored efficiently and effectively. This is where the fourth industrial revolution step in, and with minimal human interaction, data can be collected, analysed, and stored, which could also give an indication of any inconsistencies found in the data collected, this is where the Fibre Bragg Grating (FBG) monitoring system is introduced. This paper illustrates how data can be collected and converted to develop stress – strain behaviour and to produce bending moment diagrams for the utilisation and prediction of the structure’s integrity. Embedded fibre optic sensors were used in this study– fibre Bragg grating sensors in particular. The procedure entailed making use of the shift in wavelength demodulation technique and an inscription process of the phase mask technique. The fibre optic sensors considered in this report were photosensitive and embedded in the slab and beams for data collection and analysis. Two sets of fibre cables have been inserted, one purposely to collect temperature recordings and the other to collect strain and temperature. The data was collected over a time period and analysed used to produce bending moment diagrams to make predictions of the structure’s integrity. The data indicated the fibre Bragg grating sensing system proved to be useful and can be used for structural health monitoring in any environment. From the experimental data for the slab and beams, the moments were found to be64.33 kN.m, 64.35 kN.m and 45.20 kN.m (from the experimental bending moment diagram), and as per the idealistic (Ultimate Limit State), the data of 133 kN.m and 226.2 kN.m were obtained. The difference in values gave room for an early warning system, in other words, a reserve capacity of approximately 50% to failure.

Keywords: fibre bragg grating, structural health monitoring, fibre optic sensors, beams

Procedia PDF Downloads 114

Authors: Tania Viju, Bimal P., Naseer M. A.

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This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

Procedia PDF Downloads 121

Authors: Frederic Heymes, Michael Albrecht Birk, Roland Eyssette

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Boiling Liquid Expanding Vapor Explosion (BLEVE) has been a well know industrial accident for over 6 decades now, and yet it is still poorly predicted and avoided. BLEVE is created when a vessel containing a pressure liquefied gas (PLG) is engulfed in a fire until the tank rupture. At this time, the pressure drops suddenly, leading the liquid to be in a superheated state. The vapor expansion and the violent boiling of the liquid produce several shock waves. This works aimed at understanding the contribution of vapor ad liquid phases in the overpressure generation in the near field. An experimental work was undertaken at a small scale to reproduce realistic BLEVE explosions. Key parameters were controlled through the experiments, such as failure pressure, fluid mass in the vessel, and weakened length of the vessel. Thirty-four propane BLEVEs were then performed to collect data on scenarios similar to common industrial cases. The aerial overpressure was recorded all around the vessel, and also the internal pressure changed during the explosion and ground loading under the vessel. Several high-speed cameras were used to see the vessel explosion and the blast creation by shadowgraph. Results highlight how the pressure field is anisotropic around the cylindrical vessel and highlights a strong dependency between vapor content and maximum overpressure from the lead shock. The time chronology of events reveals that the vapor phase is the main contributor to the aerial overpressure peak. A prediction model is built upon this assumption. Secondary flow patterns are observed after the lead. A theory on how the second shock observed in experiments forms is exposed thanks to an analogy with numerical simulation. The phase change dynamics are also discussed thanks to a window in the vessel. Ground loading measurements are finally presented and discussed to give insight into the order of magnitude of the force.

Keywords: phase change, superheated state, explosion, vapor expansion, blast, shock wave, pressure liquefied gas

Procedia PDF Downloads 54

Authors: Ahmet Erdoğan, Şahin Kesici, Mustafa Baloğlu

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Information technologies have lead to changes in the areas of communication, learning, and teaching. Besides offering many opportunities to the learners, these technologies have changed the teaching methods and beliefs of teachers. What the Technological Pedagogical Content Knowledge (TPACK) means to the teachers is considerably important to integrate technology successfully into teaching processes. It is necessary to understand how to plan and apply teacher training programs in order to balance students’ pedagogical and technological knowledge. Because of many inefficient teacher training programs, teachers have difficulties in relating technology, pedagogy and content knowledge each other. While providing an efficient training supported with technology, understanding the three main components (technology, pedagogy and content knowledge) and their relationship are very crucial. The purpose of this study is to determine whether motivational beliefs and self-regulated learning strategies are significant predictors of mathematics teacher candidates' TPACK perceptions. A hundred seventy five Turkish mathematics teachers candidates responded to the Motivated Strategies for Learning Questionnaire (MSLQ) and the Technological Pedagogical And Content Knowledge (TPACK) Scale. Of the group, 129 (73.7%) were women and 46 (26.3%) were men. Participants' ages ranged from 20 to 31 years with a mean of 23.04 years (SD = 2.001). In this study, a multiple linear regression analysis was used. In multiple linear regression analysis, the relationship between the predictor variables, mathematics teacher candidates' motivational beliefs, and self-regulated learning strategies, and the dependent variable, TPACK perceptions, were tested. It was determined that self-efficacy for learning and performance and intrinsic goal orientation are significant predictors of mathematics teacher candidates' TPACK perceptions. Additionally, mathematics teacher candidates' critical thinking, metacognitive self-regulation, organisation, time and study environment management, and help-seeking were found to be significant predictors for their TPACK perceptions.

Keywords: candidate mathematics teachers, motivational beliefs, self-regulated learning strategies, technological and pedagogical knowledge, content knowledge

Procedia PDF Downloads 459

Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic

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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).

Keywords: Croatia, forest fire, geospatial analysis, hydrological response

Procedia PDF Downloads 108

Authors: Tarek Duzan

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Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.

Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data

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Authors: Akram Abi, Mohammad Hossein Sarrafzadeh

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Because of their several advantages over chemical surfactants, biosurfactants have given rise to a growing interest in the past decades. Advantages such as lower toxicity, higher biodegradability, higher selectivity and applicable at extreme temperature and pH which enables them to be used in a variety of applications such as: enhanced oil recovery, environmental and pharmaceutical applications, etc. Bacillus subtilis produces a cyclic lipopeptide, called surfactin, which is one of the most powerful biosurfactants with ability to decrease surface tension of water from 72 mN/m to 27 mN/m. In addition to its biosurfactant character, surfactin exhibits interesting biological activities such as: inhibition of fibrin clot formation, lyses of erythrocytes and several bacterial spheroplasts, antiviral, anti-tumoral and antibacterial properties. Surfactin is an antibiotic substance and has been shown recently to possess anti-HIV activity. However, application of biosurfactants is limited by their high production cost. The cost can be reduced by optimizing biosurfactant production using cheap feed stock. Utilization of inexpensive substrates and unconventional carbon sources like urban or agro-industrial wastes is a promising strategy to decrease the production cost of biosurfactants. With suitable engineering optimization and microbiological modifications, these wastes can be used as substrates for large-scale production of biosurfactants. As an effort to fulfill this purpose, in this work we have tried to utilize olive oil as second carbon source and also yeast extract as second nitrogen source to investigate the effect on both biomass and biosurfactant production improvement in Bacillus subtilis cultures. Since the turbidity of the culture was affected by presence of the oil, optical density was compromised and no longer could be used as an index of growth and biomass concentration. Therefore, cell Dry Weight measurements with applying necessary tactics for removing oil drops to prevent interference with biomass weight were carried out to monitor biomass concentration during the growth of the bacterium. The surface tension and critical micelle dilutions (CMD-1, CMD-2) were considered as an indirect measurement of biosurfactant production. Distinctive and promising results were obtained in the cultures containing olive oil compared to cultures without it: more than two fold increase in biomass production (from 2 g/l to 5 g/l) and considerable reduction in surface tension, down to 40 mN/m at surprisingly early hours of culture time (only 5hr after inoculation). This early onset of biosurfactant production in this culture is specially interesting when compared to the conventional cultures at which this reduction in surface tension is not obtained until 30 hour of culture time. Reducing the production time is a very prominent result to be considered for large scale process development. Furthermore, these results can be used to develop strategies for utilization of agro-industrial wastes (such as olive oil mill residue, molasses, etc.) as cheap and easily accessible feed stocks to decrease the high costs of biosurfactant production.

Keywords: agro-industrial waste, bacillus subtilis, biosurfactant, fermentation, second carbon and nitrogen source, surfactin

Procedia PDF Downloads 276

Authors: L. Guevara, Glória L. S., Corea E. E, A. Ramírez-Zamora M., Salinas-Martinez J. A., Angeles-Hernandez J. C.

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Mathematical models are useful for identifying the characteristics of sheep lactation curves to develop and implement improved strategies. However, the accuracy of these models is influenced by factors such as the recording regime, mainly the intervals between test day records (TDR). The current study aimed to evaluate the effect of different TDR intervals on the goodness of fit of the Wood model (WM) applied to dairy sheep lactations. A total of 4,494 weekly TDRs from 156 lactations of dairy crossbred sheep were analyzed. Three new databases were generated from the original weekly TDR data (7D), comprising intervals of 14(14D), 21(21D), and 28(28D) days. The parameters of WM were estimated using the “minpack.lm” package in the R software. The shape of the lactation curve (typical and atypical) was defined based on the WM parameters. The goodness of fit was evaluated using the mean square of prediction error (MSPE), Root of MSPE (RMSPE), Akaike´s Information Criterion (AIC), Bayesian´s Information Criterion (BIC), and the coefficient of correlation (r) between the actual and estimated total milk yield (TMY). WM showed an adequate estimate of TMY regardless of the TDR interval (P=0.21) and shape of the lactation curve (P=0.42). However, we found higher values of r for typical curves compared to atypical curves (0.9vs.0.74), with the highest values for the 28D interval (r=0.95). In the same way, we observed an overestimated peak yield (0.92vs.6.6 l) and underestimated time of peak yield (21.5vs.1.46) in atypical curves. The best values of RMSPE were observed for the 28D interval in both lactation curve shapes. The significant lowest values of AIC (P=0.001) and BIC (P=0.001) were shown by the 7D interval for typical and atypical curves. These results represent the first approach to define the adequate interval to record the regime of dairy sheep in Latin America and showed a better fitting for the Wood model using a 7D interval. However, it is possible to obtain good estimates of TMY using a 28D interval, which reduces the sampling frequency and would save additional costs to dairy sheep producers.

Keywords: gamma incomplete, ewes, shape curves, modeling

Procedia PDF Downloads 51

Authors: Hala Raslan, Noha Eltaweel, Hanaa Rasmi, Solaf Kamel, May Magdy, Sherif Ismail, Khalda Amr

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Introduction: Rheumatoid arthritis (RA) is an inflammatory, autoimmune disorder with progressive joint damage. Osteoarthritis (OA) is a degenerative disease of the articular cartilage that shows multiple clinical manifestations or symptoms resembling those of RA. Genetic predisposition is believed to be a principal etiological factor for RA and OA. In this study, we aimed to measure the expression of the top deregulated miRNAs that might be the cause of pathogenesis in both diseases, according to our latest NGS analysis. Six of the deregulated miRNAs were selected as they had multiple target genes in the RA pathway, so they are more likely to affect the RA pathogenesis.Methods: Eighty cases were recruited in this study; 45 rheumatoid arthiritis (RA), 30 osteoarthiritis (OA) patients, as well as 20 healthy controls. The selection of the miRNAs from our latest NGS study was done using miRwalk according to the number of their target genes that are members in the KEGG RA pathway. Total RNA was isolated from plasma of all recruited cases. The cDNA was generated by the miRcury RT Kit then used as a template for real-time PCR with miRcury Primer Assays and the miRcury SYBR Green PCR Kit. Fold changes were calculated from CT values using the ΔΔCT method of relative quantification. Results were compared RA vs Controls and OA vs Controls. Target gene prediction and functional annotation of the deregulated miRNAs was done using Mienturnet. Results: Six miRNAs were selected. They were miR-15b-3p, -128-3p, -194-3p, -328-3p, -542-3p and -3180-5p. In RA samples, three of the measured miRNAs were upregulated (miR-194, -542, and -3180; mean Rq= 2.6, 3.8 and 8.05; P-value= 0.07, 0.05 and 0.01; respectively) while the remaining 3 were downregulated (miR-15b, -128 and -328; mean Rq= 0.21, 0.39 and 0.6; P-value= <0.0001, <0.0001 and 0.02; respectively) all with high statistical significance except miR-194. While in OA samples, two of the measured miRNAs were upregulated (miR-194 and -3180; mean Rq= 2.6 and 7.7; P-value= 0.1 and 0.03; respectively) while the remaining 4 were downregulated (miR-15b, -128, -328 and -542; mean Rq= 0.5, 0.03, 0.08 and 0.5; P-value= 0.0008, 0.003, 0.006 and 0.4; respectively) with statistical significance compared to controls except miR-194 and miR-542. The functional enrichment of the selected top deregulated miRNAs revealed the highly enriched KEGG pathways and GO terms. Conclusion: Five of the studied miRNAs were greatly deregulated in RA and OA, they might be highly involved in the disease pathogenesis and so might be future therapeutic targets. Further functional studies are crucial to assess their roles and actual target genes.

Keywords: MiRNAs, expression, rheumatoid arthritis, osteoarthritis

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Authors: X. King, E. Nazarzadeh, J. Reboud, J. Cooper

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Pulmonary diseases, such as asthma, are generally treated by the inhalation of aerosols that has the advantage of reducing the off-target (e.g., toxicity) effects associated with systemic delivery in blood. Effective respiratory drug delivery requires a droplet size distribution between 1 and 5 µm. Inhalation of aerosols with wide droplet size distribution, out of this range, results in deposition of drug in not-targeted area of the respiratory tract, introducing undesired side effects on the patient. In order to solely deliver the drug in the lower branches of the lungs and release it in a targeted manner, a control mechanism to produce the aerosolized droplets is required. To regulate the drug release and to facilitate the uptake from cells, drugs are often encapsulated into protective liposomes. However, a multistep process is required for their formation, often performed at the formulation step, therefore limiting the range of available drugs or their shelf life. Using surface acoustic waves (SAWs), a pulmonary drug delivery platform was produced, which enabled the formation of defined size aerosols and the formation of liposomes in situ. SAWs are mechanical waves, propagating along the surface of a piezoelectric substrate. They were generated using an interdigital transducer on lithium niobate with an excitation frequency of 9.6 MHz at a power of 1W. Disposable silicon superstrates were etched using photolithography and dry etch processes to create an array of cylindrical through-holes with different diameters and pitches. Superstrates were coupled with the SAW substrate through water-based gel. As the SAW propagates on the superstrate, it enables nebulisation of a lipid solution deposited onto it. The cylindrical cavities restricted the formation of large drops in the aerosol, while at the same time unilamellar liposomes were created. SAW formed liposomes showed a higher monodispersity compared to the control sample, as well as displayed, a faster production rate. To test the aerosol’s size, dynamic light scattering and laser diffraction methods were used, both showing the size control of the aerosolised particles. The use of silicon superstate with cavity size of 100-200 µm, produced an aerosol with a mean droplet size within the optimum range for pulmonary drug delivery, containing the liposomes in which the medicine could be loaded. Additionally, analysis of liposomes with Cryo-TEM showed formation of vesicles with narrow size distribution between 80-100 nm and optimal morphology in order to be used for drug delivery. Encapsulation of nucleic acids in liposomes through the developed SAW platform was also investigated. In vitro delivery of siRNA and DNA Luciferase were achieved using A549 cell line, lung carcinoma from human. In conclusion, SAW pulmonary drug delivery platform was engineered, in order to combine multiple time consuming steps (formation of liposomes, drug loading, nebulisation) into a unique platform with the aim of specifically delivering the medicament in a targeted area, reducing the drug’s side effects.

Keywords: acoustics, drug delivery, liposomes, surface acoustic waves

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Authors: Aliseydi Bozkurt

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Objectives: Benign prostatic hyperplasia (BPH) is the most common benign disease, and prostate cancer (PC) is malign disease of the prostate gland. Transrectal ultrasound-guided biopsy (TRUS-bx) is one of the most important diagnostic tools in PC diagnosis. Identifying men at increased risk for having a biopsy detectable prostate cancer should consider prostate specific antigen density (PSAD), f/t PSA Ratio, an estimate of prostate volume. Method: We retrospectively studied 269 patients who had a prostate specific antigen (PSA) score of 4 or who had suspected rectal examination at any PSA level and received TRUS-bx between January 2015 and June 2018 in our clinic. TRUS-bx was received by 12 experienced urologists with 12 quadrants. Prostate volume was calculated prior to biopsy together with TRUS. Patients were classified as malignant and benign at the end of pathology. Age, PSA value, prostate volume in transrectal ultrasonography, corpuscle biopsy, biopsy pathology result, the number of cancer core and Gleason score were evaluated in the study. The success rates of PV, PSAD, and f/tPSA were compared in all patients and those with PSA 2.5-10 ng/mL and 10.1-30 ng/mL tp foresee prostate cancer. Result: In the present study, in patients with PSA 2.5-10 ng/ml, PV cut-off value was 43,5 mL (n=42 < 43,5 mL and n=102 > 43,5 mL) while in those with PSA 10.1-30 ng/mL prostate volüme (PV) cut-off value was found 61,5 mL (n=31 < 61,5 mL and n=36 > 61,5 mL). Total PSA values in the group with PSA 2.5-10 ng/ml were found lower (6.0 ± 1.3 vs 6.7 ± 1.7) than that with PV < 43,5 mL, this value was nearly significant (p=0,043). In the group with PSA value 10.1-30 ng/mL, no significant difference was found (p=0,117) in terms of total PSA values between the group with PV < 61,5 mL and that with PV > 61,5 mL. In the group with PSA 2.5-10 ng/ml, in patients with PV < 43,5 mL, f/t PSA value was found significantly lower compared to the group with PV > 43,5 mL (0.21 ± 0.09 vs 0.26 ± 0.09 p < 0.001 ). Similarly, in the group with PSA value of 10.1-30 ng/mL, f/t PSA value was found significantly lower in patients with PV < 61,5 mL (0.16 ± 0.08 vs 0.23 ± 0.10 p=0,003). In the group with PSA 2.5-10 ng/ml, PSAD value in patients with PV < 43,5 mL was found significantly higher compared to those with PV > 43,5 mL (0.17 ± 0.06 vs 0.10 ± 0.03 p < 0.001). Similarly, in the group with PSA value 10.1-30 ng/mL PSAD value was found significantly higher in patients with PV < 61,5 mL (0.47 ± 0.23 vs 0.17 ± 0.08 p < 0.001 ). The biopsy results suggest that in the group with PSA 2.5-10 ng/ml, in 29 of the patients with PV < 43,5 mL (69%) cancer was detected while in 13 patients (31%) no cancer was detected. While in 19 patients with PV > 43,5 mL (18,6%) cancer was found, in 83 patients (81,4%) no cancer was detected (p < 0.001). In the group with PSA value 10.1-30 ng/mL, in 21 patients with PV < 61,5 mL (67.7%) cancer was observed while only in10 patients (32.3%) no cancer was seen. In 5 patients with PV > 61,5 mL (13.9%) cancer was found while in 31 patients (86.1%) no cancer was observed (p < 0.001). Conclusions: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider PSA, f/t PSA Ratio, an estimate of prostate volume. Prostate volume in PC was found lower.

Keywords: prostate cancer, prostate volume, prostate specific antigen, free/total PSA ratio

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Authors: Vladimir Berezin, Andrey Bogoyavlenskiy, Pavel Alexyuk, Madina Alexyuk, Aizhan Turmagambetova, Irina Zaitseva, Nadezhda Sokolova, Elmira Omirtaeva

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Introduction: Triterpene saponins of plant origin are one of the most promising candidates for elaboration of novel adjuvants. Due to the combination of immunostimulating activity and the capacity interact with amphipathic molecules with formation of highly immunogenic nanocomplexes, triterpene saponins could serve as a good adjuvant/delivery system for vaccine use. In the research presented adjuvants on the base of nanocomplexes contained triterpene saponins isolated from Glycyrrhiza glabra and Saponaria officinalis plants indigenous to Kazakhstan were elaborated for influenza vaccine use. Methods: Purified triterpene saponins 'Glabilox' and 'SO1' with low toxicity and high immunostimulatory activity were isolated from plants Glycyrrhiza glabra L. and Saponaria officinalis L. by high-performance liquid chromatography (HPLC) and identified using electrospray ionization mass spectrometry (ESI-MS). Influenza virus A/St-Petersburg/5/09 (H1N1) propagated in 9-days old chicken embryos was concentrated and purified by centrifugation in sucrose gradient. Nanocomplexes contained lipids, and triterpene saponins Glabilox or SO1 were prepared by dialysis technique. Immunostimulating activity of experimental vaccine preparations was studied in vaccination/challenge experiments in mice. Results: Humoral and cellular immune responses and protection against influenza virus infection were examined after single subcutaneous and intranasal immunization. Mice were immunized subunit influenza vaccine (HA+NA) or whole virus inactivated influenza vaccine in doses 3.0/5.0/10.0 µg antigen/animal mixed with adjuvant in dose 15.0 µg/animal. Sera were taken 14-21 days following single immunization and mice challenged by A/St-Petersburg/5/09 influenza virus in dose 100 EID₅₀. Study of experimental influenza vaccine preparations in animal immunization experiments has shown that subcutaneous and intranasal immunization with subunit influenza vaccine mixed with nanocomplexes contained Glabilox or SO1 saponins stimulated high levels of humoral immune response (IgM, IgA, IgG1, IgG2a, and IgG2b antibody) and cellular immune response (IL-2, IL-4, IL-10, and IFN-γ cytokines) and resulted 80-90% protection against lethal influenza infection. Also, single intranasal and single subcutaneous immunization with whole virus inactivated influenza vaccine mixed with nanoparticulated adjuvants stimulated high levels of humoral and cellular immune responses and provided 100% protection against lethal influenza infection. Conclusion: The results of study have shown that nanocomplexes contained purified triterpene saponins Glabilox and SO1 isolated from plants indigenous to Kazakhstan can stimulate a broad spectrum of humoral and cellular immune responses and induce protection against lethal influenza infection. Both elaborated adjuvants are promising for incorporation to influenza vaccine intended for subcutaneous and intranasal routes of immunization.

Keywords: influenza vaccine, adjuvants, triterpene saponins, immunostimulating activity

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Authors: Shishay Kidanu, Abdullah Alhaj

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Sinkholes in the karst terrain of Greene County, Missouri, pose significant geohazards, imposing challenges on construction and infrastructure development, with potential threats to lives and property. To address these issues, understanding the influencing factors and modeling sinkhole susceptibility is crucial for effective mitigation through strategic changes in land use planning and practices. This study utilizes geographic information system (GIS) software to collect and process diverse data, including topographic, geologic, hydrogeologic, and anthropogenic information. Nine key sinkhole influencing factors, ranging from slope characteristics to proximity to geological structures, were carefully analyzed. The Frequency Ratio method establishes relationships between attribute classes of these factors and sinkhole events, deriving class weights to indicate their relative importance. Weighted integration of these factors is accomplished using the Analytic Hierarchy Process (AHP) and the Weighted Linear Combination (WLC) method in a GIS environment, resulting in a comprehensive sinkhole susceptibility index (SSI) model for the study area. Employing Jenk's natural break classifier method, the SSI values are categorized into five distinct sinkhole susceptibility zones: very low, low, moderate, high, and very high. Validation of the model, conducted through the Area Under Curve (AUC) and Sinkhole Density Index (SDI) methods, demonstrates a robust correlation with sinkhole inventory data. The prediction rate curve yields an AUC value of 74%, indicating a 74% validation accuracy. The SDI result further supports the success of the sinkhole susceptibility model. This model offers reliable predictions for the future distribution of sinkholes, providing valuable insights for planners and engineers in the formulation of development plans and land-use strategies. Its application extends to enhancing preparedness and minimizing the impact of sinkhole-related geohazards on both infrastructure and the community.

Keywords: sinkhole, GIS, analytical hierarchy process, frequency ratio, susceptibility, Missouri

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Authors: Jemal Ebrahim Dessie, Lukács Zsolt

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High-strength aluminum alloys have drawn a lot of attention because of the expanding demand for lightweight vehicle design in the automotive sector. Due to poor formability at room temperature, warm and hot forming have been advised. However, warm and hot forming methods need more steps in the production process and an advanced tooling system. In contrast, since ordinary tools can be used, forming sheets at room temperature in the W temper condition is advantageous. However, springback of supersaturated sheets and their thinning are critical challenges and must be resolved during the use of this technique. In this study, AA6082-T6 aluminum alloy was solution heat treated at different oven temperatures and times using a specially designed and developed furnace in order to optimize the W-temper heat treatment temperature. A U-shaped bending test was carried out at different time periods between W-temper heat treatment and forming operation. Finite element analysis (FEA) of U-bending was conducted using AutoForm aiming to validate the experimental result. The uniaxial tensile and unload test was performed in order to determine the kinematic hardening behavior of the material and has been optimized in the Finite element code using systematic process improvement (SPI). In the simulation, the effect of friction coefficient & blank holder force was considered. Springback parameters were evaluated by the geometry adopted from the NUMISHEET ’93 benchmark problem. It is noted that the change of shape was higher at the more extended time periods between W-temper heat treatment and forming operation. Die radius was the most influential parameter at the flange springback. However, the change of shape shows an overall increasing tendency on the sidewall as the increase of radius of the punch than the radius of the die. The springback angles on the flange and sidewall seem to be highly influenced by the coefficient of friction than blank holding force, and the effect becomes increases as increasing the blank holding force.

Keywords: aluminum alloy, FEA, springback, SPI, U-bending, W-temper

Procedia PDF Downloads 81

Authors: Tamrat Girma Biru

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Multidrug-resistant tuberculosis (MDR-TB) is defined as resistant to at least Refampicin and Isoniazed: the most two power full TB drugs. It is a leading cause of high rates of morbidity and mortality, and increasing psychosocial challenges to patients, especially when co-infected with Human Immunodeficiency Virus (HIV). Ethiopia faces the highest rates of MDR-TB infection in the world. Objectives: The main objective of this study was to identify the psychosocial challenges of MDR-TB patients, to investigate the extent of the psychosocial challenges on (self-esteem, depression, and stigma) that MDR-TB patients encounter, to examine whether there is a sex difference in experiencing psychosocial challenges and assess the counseling needs of MDR-TB patients. Methodology: A cross-sectional study was conducted at St. Peter TB Specialized Hospital, Addis Ababa on 40 patients (25 males and 15 females) who are hospitalized for treatment. The patients were identified by using purposive sampling and made fill a questionnaire measuring their level of self-esteem, depression and stigma. Besides, data were collected from 16 participants, 28 care providers and 8 guardians, using semi-structured interview. The obtained data were analyzed using SPSS statistical program, descriptive statistics, independent t-test, and qualitative description. Results and Discussion: The results of the study showed that the majority (80%) of the respondents had suffered psychological challenges and social discriminations. Thus, the significance of MDR-TB and its association with HIV/AIDS problems is considered. Besides the psychosocial challenges, various aggravating factors such as length of treatment, drug burden and insecurity in economy together highly challenges the life of patients. In addition, 60% of participants showed low level of self-esteem. The patients also reported that they experienced high self-stigma and stigma by other members of the society. The majority of the participants (75%) showed moderate and severe level of depression. In terms of sex there is no difference between the mean scores of males and females in the level of depression and stigmatization by others and by themselves. But females showed lower level of self-esteem than males. The analysis of the t-test also shows that there were no statistically significant sex difference on the level of depression and stigma. Based on the qualitative data MDR-TB patients face various challenges in their life sphere such as: Psychological (depression, low self value, lowliness, anxiety), social (stigma, isolation from social relations, self-stigmatization,) and medical (drug side effect, drug toxicity, drug burden, treatment length, hospital stays). Recommendations: Based on the findings of this study possible recommendations were forwarded: develop and extend MDR-TB disease awareness creation through by media (printing and electronic), school net TB clubs, and door to door community education. Strengthen psychological wellbeing and social relationship of MDR-TB patients using proper and consistent psychosocial support and counseling. Responsible bodies like Ministry of Health (MOH) and its stakeholders and Non Governmental Organizations (NGOs) need to assess the challenges of patients and take measures on this pressing issue.

Keywords: psychosocial challenges, counseling, multi-drug resistant tuberculosis (MDR-TB), tuberculosis therapy

Procedia PDF Downloads 366

Authors: Md Azizul Islam

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Seam is the line of joining two separate fabric layers for functional or aesthetic purposes. Different kinds of seams are used for assembling the different areas or parts of the garment to increase serviceability. To empirically support the importance of seam efficiency on serviceability of garments, this study is focused on choosing the right type of seams for particular sewing parts of the garments based on the seam efficiency to ensure better serviceability. Seam efficiency is the ratio of seam strength and fabric strength. Single jersey knitted finished fabrics of four different GSMs (gram per square meter) were used to make the test garments T-shirt. Three distinct types of the seam: superimposed, lapped and flat seam was applied to the side seams of T-shirt and sewn by lockstitch (stitch class- 301) in a flat-bed plain sewing machine (maximum sewing speed: 5000 rpm) to make (3x4) 12 T-shirts. For experimental purposes, needle thread count (50/3 Ne), bobbin thread count (50/2 Ne) and the stitch density (stitch per inch: 8-9), Needle size (16 in singer system), stitch length (31 cm), and seam allowance (2.5cm) were kept same for all specimens. The grab test (ASTM D5034-08) was done in the Universal tensile tester to measure the seam strength and fabric strength. The produced T-shirts were given to 12 soccer players who wore the shirts for 20 soccer matches (each match of 90 minutes duration). Serviceability of the shirt were measured by visual inspection of a 5 points scale based on the seam conditions. The study found that T-shirts produced with lapped seam show better serviceability and T-shirts made of flat seams perform the lowest score in serviceability score. From the calculated seam efficiency (seam strength/ fabric strength), it was obvious that the performance (in terms of strength) of the lapped and bound seam is higher than that of the superimposed seam and the performance of superimposed seam is far better than that of the flat seam. So it can be predicted that to get a garment of high serviceability, lapped seams could be used instead of superimposed or other types of the seam. In addition, less stressed garments can be assembled by others seems like superimposed seams or flat seams.

Keywords: seam, seam efficiency, serviceability, T-shirt

Procedia PDF Downloads 181

Authors: Sungin Jeong

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This paper presents a linear oscillating generator of cylindrical type for hybrid electric vehicle application. The focus of the study is the suggestion of the optimal model and the design rule of the cylindrical linear oscillating generator with permanent magnet in the back-iron translator. The cylindrical topology is achieved using equivalent magnetic circuit considering leakage elements as initial modeling. This topology with permanent magnet in the back-iron translator is described by number of phases and displacement of stroke. For more accurate analysis of an oscillating machine, it will be compared by moving just one-pole pitch forward and backward the thrust of single-phase system and three-phase system. Through the analysis and comparison, a single-phase system of cylindrical topology as the optimal topology is selected. Finally, the detailed design of the optimal topology takes the magnetic saturation effects into account by finite element analysis. Besides, the losses are examined to obtain more accurate results; copper loss in the conductors of machine windings, eddy-current loss of permanent magnet, and iron-loss of specific material of electrical steel. The considerations of thermal performances and mechanical robustness are essential, because they have an effect on the entire efficiency and the insulations of the machine due to the losses of the high temperature generated in each region of the generator. Besides electric machine with linear oscillating movement requires a support system that can resist dynamic forces and mechanical masses. As a result, the fatigue analysis of shaft is achieved by the kinetic equations. Also, the thermal characteristics are analyzed by the operating frequency in each region. The results of this study will give a very important design rule in the design of linear oscillating machines. It enables us to more accurate machine design and more accurate prediction of machine performances.

Keywords: equivalent magnetic circuit, finite element analysis, hybrid electric vehicle, linear oscillating generator

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Authors: Khashayar Nasrifar

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Ionic liquids (ILs) exhibit particular properties exemplified by extremely low vapor pressure and high thermal stability. The properties of ILs can be tailored by proper selection of cations and anions. As such, ILs are appealing as potential solvents to substitute traditional solvents with high vapor pressure. One of the IL properties required in chemical and process design is density. In developing corresponding state liquid density correlations, scaling hypothesis is often used. The hypothesis expresses the temperature dependence of saturated liquid densities near the vapor-liquid critical point as a function of reduced temperature. Extending the temperature dependence, several successful correlations were developed to accurately correlate the densities of normal liquids from the triple point to a critical point. Applying mixing rules, the liquid density correlations are extended to liquid mixtures as well. ILs are not molecular liquids, and they are not classified among normal liquids either. Also, ILs are often used where the condition is far from equilibrium. Nevertheless, in calculating the properties of ILs, the use of corresponding state correlations would be useful if no experimental data were available. With well-known generalized saturated liquid density correlations, the accuracy in predicting the density of ILs is not that good. An average error of 4-5% should be expected. In this work, a data bank was compiled. A simplified and concise corresponding state saturated liquid density correlation is proposed by phenomena-logically modifying reduced temperature using the temperature-dependence for an interacting parameter of the Soave-Redlich-Kwong equation of state. This modification improves the temperature dependence of the developed correlation. Parametrization was next performed to optimize the three global parameters of the correlation. The correlation was then applied to the ILs in our data bank with satisfactory predictions. The correlation of IL density applied at 0.1 MPa and was tested with an average uncertainty of around 2%. No adjustable parameter was used. The critical temperature, critical volume, and acentric factor were all required. Methods to extend the predictions to higher pressures (200 MPa) were also devised. Compared to other methods, this correlation was found more accurate. This work also presents the chronological order of developing such correlations dealing with ILs. The pros and cons are also expressed.

Keywords: correlation, corresponding state principle, ionic liquid, density

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Authors: Luyin Liang

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Although sibling relationship has been viewed as one of the most important family relationships that significantly impacted on the quality of life of both adults with Intellectual Disability (AWID) and their brothers/sisters, very few research have been done to investigate this relationship in China. This study investigated Chinese siblings of AWID’s relational motivations in sibling relationship and their determining factors. Quantitative research method has been adopted and 284 samples were recruited in this study. Siblings of AWID’s two types of relational motivations, including obligatory motivations and discretionary motivations were examined. Their emotional closeness, senses of responsibility, experiences of ID stigma, and expectancy of self-reward in sibling relationship were measured by validated scales. Personal, and familial-social demographic characteristics were also investigated. Linear correlation test and standard multiple regression analysis were the major statistical methods that have been used to analyze the data. The findings of this study showed that all the measured factors, including siblings of AWID’s emotional closeness, their senses of responsibility, experiences of ID stigma, and self-reward expectations had significant relationships with their both types of motivations. However, when these factors were grouped together to measure each type of these motivations, the prediction results were varied. The order of factors that best predict siblings of AWID’s obligatory motivations was: their senses of responsibility, emotional closeness, experiences of ID stigma, and their expectancy of self-reward, whereas the order of these factors that best determine siblings of AWID’s discretionary motivations was: their self-reward expectations, experiences of ID stigma, senses of responsibility, and emotional closeness. Among different demographic characteristics, AWID’s disability condition, their siblings’ age, gender, marital status, number of children, both siblings’ living arrangements and family financial status were found to have significant impacts on siblings of AWID’s both types of motivations in sibling relationship. The results of this study could enhance social work practitioners’ understandings about the needs and challenges of siblings of AWID. Suggestions on advocacies for policy changes and services improvements for these siblings were discussed in this study.

Keywords: sibling relationship, intellectual disability, adults, China

Procedia PDF Downloads 383

Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

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This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

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Authors: Georgios Koronis, Arlindo Silva

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This study seeks to understand the mechanical behavior of a natural fiber reinforced composite (epoxy/flax) in more depth, utilizing both experimental and numerical methods. It is attempted to identify relationships between the design parameters and the product performance, understand the effect of noise factors and reduce process variations. Optimization of the mechanical performance of manufactured goods has recently been implemented by numerous studies for green composites. However, these studies are limited and have explored in principal mass production processes. It is expected here to discover knowledge about composite’s manufacturing that can be used to design artifacts that are of low batch and tailored to niche markets. The goal is to reach greater consistency in the performance and further understand which factors play significant roles in obtaining the best mechanical performance. A prediction of response function (in various operating conditions) of the process is modeled by the DoE. Normally, a full factorial designed experiment is required and consists of all possible combinations of levels for all factors. An analytical assessment is possible though with just a fraction of the full factorial experiment. The outline of the research approach will comprise of evaluating the influence that these variables have and how they affect the composite mechanical behavior. The coupons will be fabricated by the vacuum infusion process defined by three process parameters: flow rate, injection point position and fiber treatment. Each process parameter is studied at 2-levels along with their interactions. Moreover, the tensile and flexural properties will be obtained through mechanical testing to discover the key process parameters. In this setting, an experimental phase will be followed in which a number of fabricated coupons will be tested to allow for a validation of the design of the experiment’s setup. Finally, the results are validated by performing the optimum set of in a final set of experiments as indicated by the DoE. It is expected that after a good agreement between the predicted and the verification experimental values, the optimal processing parameter of the biocomposite lamina will be effectively determined.

Keywords: design of experiments, flax fabrics, mechanical performance, natural fiber reinforced composites

Procedia PDF Downloads 187

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 61

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

Abstract:

Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

Procedia PDF Downloads 391