Search results for: atmospheric transport modeling

Authors: S. Ilahi, M. Baira, F. Saidi, N. Yacoubi, L. Auvray, H. Maaref

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Photo-thermal deflection technique (PTD) is used to study the nonradiative recombination process in BGaAs/GaAs alloy with boron composition of 3% and 8% grown by metal organic chemical vapor deposition (MOCVD). A two layer theoretical model has been developed taking into account both thermal and electronic contribution in the photothermal signal allowing to extract the electronic parameters namely electronic diffusivity, surface and interface recombination. It is found that the increase of boron composition alters the BGaAs epilayers transport properties.

Keywords: photothermal defelction technique, two layer model, BGaAs/GaAs alloys, boron composition

Procedia PDF Downloads 291

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Meseret Habtamu, Mekuria Argaw

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Urban forests can help to improve the microclimate and air quality. Urban forests in Addis Ababa are important sinks for GHGs as the number of vehicles and the traffic constrain is steadily increasing. The objective of this study was to characterize the vegetation types in selected public parks and to estimate the carbon stock potential of urban forests by assessing carbon in the above, below ground biomass, in the litter and soil. Species which vegetation samples were taken using a systematic transect sampling within value DBH ≥ 5cm were recorded to measure the above, the below ground biomass and the amount of C stored. Allometric models (Y= 34.4703 - 8.0671(DBH) + 0.6589(DBH2) were used to calculate the above ground and Below ground biomass (BGB) = AGB × 0.2 and sampling of soil and litter was based on quadrates. There were 5038 trees recorded from the selected study sites with DBH ≥ 5cm. Most of the Parks had large number of indigenous species, but the numbers of exotic trees are much larger than the indigenous trees. The mean above ground and below ground biomass is 305.7 ± 168.3 and 61.1± 33.7 respectively and the mean carbon in the above ground and below ground biomass is 143.3±74.2 and 28.1 ± 14.4 respectively. The mean CO2 in the above ground and below ground biomass is 525.9 ± 272.2 and 103.1 ± 52.9 respectively. The mean carbon in dead litter and soil carbon were 10.5 ± 2.4 and 69.2t ha-1 respectively. Urban trees reduce atmospheric carbon dioxide (CO2) through sequestration which is important for climate change mitigation, they are also important for recreational, medicinal value and aesthetic and biodiversity conservation.

Keywords: biodiversity, carbon sequestration, climate change, urban forests

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Authors: Sandra Arango-Caro, Kristine Callis-Duehl

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The Education Research and Outreach Lab at the Donald Danforth Plant Science Center established the Plant and Agriculture Augmented and Virtual Reality Learning Laboratory (PAVRLL) to promote science education through professional development, school programs, internships, and outreach events. Professional development is offered to high school and college science and agriculture educators on the use and applications of zSpace and Oculus platforms. Educators learn to use, edit, or create lesson plans in the zSpace platform that are aligned with the Next Generation Science Standards. They also learn to use virtual reality experiences created by the PAVRLL available in Oculus (e.g. The Soybean Saga). Using a cost-free loan rotation system, educators can bring the AVR units to the classroom and offer AVR activities to their students. Each activity has user guides and activity protocols for both teachers and students. The PAVRLL also offers activities for 3D plant modeling. High school students work in teams of art-, science-, and technology-oriented students to design and create 3D models of plant species that are under research at the Danforth Center and present their projects at scientific events. Those 3D models are open access through the zSpace platform and are used by PAVRLL for professional development and the creation of VR activities. Both teachers and students acquire knowledge of plant and agriculture content and real-world problems, gain skills in AVR technology, 3D modeling, and science communication, and become more aware and interested in plant science. Students that participate in the PAVRLL activities complete pre- and post-surveys and reflection questions that evaluate interests in STEM and STEM careers, students’ perceptions of three design features of biology lab courses (collaboration, discovery/relevance, and iteration/productive failure), plant awareness, and engagement and learning in AVR environments. The PAVRLL was established in the fall of 2019, and since then, it has trained 15 educators, three of which will implement the AVR programs in the fall of 2021. Seven students have worked in the 3D plant modeling activity through a virtual internship. Due to the COVID-19 pandemic, the number of teachers trained, and classroom implementations have been very limited. It is expected that in the fall of 2021, students will come back to the schools in person, and by the spring of 2022, the PAVRLL activities will be fully implemented. This will allow the collection of enough data on student assessments that will provide insights on benefits and best practices for the use of AVR technologies in the classrooms. The PAVRLL uses cutting-edge educational technologies to promote science education and assess their benefits and will continue its expansion. Currently, the PAVRLL is applying for grants to create its own virtual labs where students can experience authentic research experiences using real Danforth research data based on programs the Education Lab already used in classrooms.

Keywords: assessment, augmented reality, education, plant science, virtual reality

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Authors: Sven Borén, Henrik Ny

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Ambitions within the EU for moving towards sustainable transport include major emission reductions for fossil fuel road vehicles, especially for buses, trucks, and cars. The electric driveline seems to be an attractive solution for such development. This study first applied the Framework for Strategic Sustainable Development to compare sustainability effects of today’s fossil fuel vehicles with electric vehicles that have batteries or hydrogen fuel cells. The study then addressed a scenario were electric vehicles might be in majority in Europe by 2050. The methodology called Strategic Lifecycle Assessment was first used, were each life cycle phase was assessed for violations against sustainability principles. This indicates where further analysis could be done in order to quantify the magnitude of each violation, and later to create alternative strategies and actions that lead towards sustainability. A Life Cycle Assessment of combustion engine cars, plug-in hybrid cars, battery electric cars and hydrogen fuel cell cars was then conducted to compare and quantify environmental impacts. The authors found major violations of sustainability principles like use of fossil fuels, which contribute to the increase of emission related impacts such as climate change, acidification, eutrophication, ozone depletion, and particulate matters. Other violations were found, such as use of scarce materials for batteries and fuel cells, and also for most life cycle phases for all vehicles when using fossil fuel vehicles for mining, production and transport. Still, the studied current battery and hydrogen fuel cell cars have less severe violations than fossil fuel cars. The life cycle assessment revealed that fossil fuel cars have overall considerably higher environmental impacts compared to electric cars as long as the latter are powered by renewable electricity. By 2050, there will likely be even more sustainable alternatives than the studied electric vehicles when the EU electricity mix mainly should stem from renewable sources, batteries should be recycled, fuel cells should be a mature technology for use in vehicles (containing no scarce materials), and electric drivelines should have replaced combustion engines in other sectors. An uncertainty for fuel cells in 2050 is whether the production of hydrogen will have had time to switch to renewable resources. If so, that would contribute even more to a sustainable development. Except for being adopted in the GreenCharge roadmap, the authors suggest that the results can contribute to planning in the upcoming decades for a sustainable increase of EVs in Europe, and potentially serve as an inspiration for other smaller or larger regions. Further studies could map the environmental effects in LCA further, and include other road vehicles to get a more precise perception of how much they could affect sustainable development.

Keywords: strategic, electric vehicles, sustainability, LCA

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Authors: Jigar N. Shah, Hiral J. Shah, Praful D. Bharadia

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The major challenge faced by formulation scientists in transdermal drug delivery system is to overcome the inherent barriers related to skin permeation. The stratum corneum layer of the skin is working as the rate limiting step in transdermal transport and reduce drug permeation through skin. Many approaches have been used to enhance the penetration of drugs through this layer of the skin. The purpose of this study is to investigate the development and evaluation of a combined approach of drug carriers and iontophoresis as a vehicle to improve skin permeation of an analgesic drug. Iontophoresis is a non-invasive technique for transporting charged molecules into and through tissues by a mild electric field. It has been shown to effectively deliver a variety of drugs across the skin to the underlying tissue. In addition to the enhanced continuous transport, iontophoresis allows dose titration by adjusting the electric field, which makes personalized dosing feasible. Drug carrier could modify the physicochemical properties of the encapsulated molecule and offer a means to facilitate the percutaneous delivery of difficult-to-uptake substances. Recently, there are some reports about using liposomes, microemulsions and polymeric nanoparticles as vehicles for iontophoretic drug delivery. Niosomes, the nonionic surfactant-based vesicles that are essentially similar in properties to liposomes have been proposed as an alternative to liposomes. Niosomes are more stable and free from other shortcoming of liposomes. Recently, the transdermal delivery of certain drugs using niosomes has been envisaged and niosomes have proved to be superior transdermal nanocarriers. Proniosomes overcome some of the physical stability related problems of niosomes. The proniosomal structure was liquid crystalline-compact niosomes hybrid which could be converted into niosomes upon hydration. The combined use of drug carriers and iontophoresis could offer many additional benefits. The system was evaluated for Encapsulation Efficiency, vesicle size, zeta potential, Transmission Electron Microscopy (TEM), DSC, in-vitro release, ex-vivo permeation across skin and rate of hydration. The use of proniosomal gel as a vehicle for the transdermal iontophoretic delivery was evaluated in-vitro. The characteristics of the applied electric current, such as density, type, frequency, and on/off interval ratio were observed. The study confirms the synergistic effect of proniosomes and iontophoresis in improving the transdermal permeation profile of selected analgesic drug. It is concluded that proniosomal gel can be used as a vehicle for transdermal iontophoretic drug delivery under suitable electric conditions.

Keywords: iontophoresis, niosomes, permeation enhancement, transdermal delivery

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Authors: Sudipt Agarwal, Siddharth Verma, S. M. Iqbal, Hitik Kalra

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Natural gas as a fuel has created wonders, but on the contrary, the ill-effects of methane have been a great worry for professionals. The largest source of methane emission is the oil and gas industry among all industries. Methane depletes groundwater and being a greenhouse gas has devastating effects on the atmosphere too. Methane remains for a decade or two in the atmosphere and later breaks into carbon dioxide and thus damages it immensely, as it warms up the atmosphere 72 times more than carbon dioxide in those two decades and keeps on harming after breaking into carbon dioxide afterward. The property of a fluid to adhere to the surface of a solid, better known as adsorption, can be a great boon to minimize the hindrance caused by methane. Adsorption of methane during upstream processes can save the groundwater and atmospheric depletion around the site which can be hugely lucrative to earn profits which are reduced due to environmental degradation leading to project cancellation. The paper would deal with reasons why casing and cementing are not able to prevent leakage and would suggest methods to adsorb methane during upstream processes with mathematical explanation using volumetric analysis of adsorption of methane on the surface of activated carbon doped with copper oxides (which increases the absorption by 54%). The paper would explain in detail (through a cost estimation) how the proposed idea can be hugely beneficial not only to environment but also to the profits earned.

Keywords: adsorption, casing, cementing, cost estimation, volumetric analysis

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Authors: Dchieche Amina, Aboulaich Rajae

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Profit and loss sharing suggests an equitable sharing of risks and profits between the parts involved in a financial transaction. Salam is a contract in which advance payment is made for goods to be delivered at a future date. The purpose of this work is to price a new contract for profit and loss sharing based on Salam contract, using Khiyar Al Ghabn which is an agreement of choice in case of misrepresent facts.

Keywords: Islamic finance, shariah compliance, profit and loss sharing, derivatives, risks, hedging, salam contract

Procedia PDF Downloads 316

Authors: Aidoud Assia, Bencheikh Messaouda, Boukour Salima

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Polystyrene is often seen in the ocean and on Algerian beaches, mainly as food containers. It's one of the top 10 most common items found there. This happens because it's light and easily carried away from its original source, like packaging or transport, into the environment. Unfortunately, it's not recycled much because it's not very profitable to do so. Hence, turning this waste into a resource can turn challenges into opportunities for a territory's economic and environmental development, which is the focus of this study. the goal is to analyze the physical and mechanical properties of a new type of mortar made from dune sand mixed with recycled polystyrene. it also aim to assess its potential for use in various construction applications. The mixtures were prepared by replacing portions of dune sand with polystyrene waste at varying volumes (10%, 20%, and 30%), while keeping the amount of cement constant. The results indicate a noticeable impact on both the physical and mechanical properties because of incorporating polystyrene waste.

Keywords: polystyrène, eco-mortier, sable de dune, résistance

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Authors: R. Yuan, S. Sivasankaran, N. Dutta, K. Ebrahimi

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This paper investigates the software capability and computer-aided engineering (CAE) method of modelling transient heat transfer process occurred in the vehicle underhood region during vehicle thermal soak phase. The heat retention from the soak period will be beneficial to the cold start with reduced friction loss for the second 14°C worldwide harmonized light-duty vehicle test procedure (WLTP) cycle, therefore provides benefits on both CO₂ emission reduction and fuel economy. When vehicle undergoes soak stage, the airflow and the associated convective heat transfer around and inside the engine bay is driven by the buoyancy effect. This effect along with thermal radiation and conduction are the key factors to the thermal simulation of the engine bay to obtain the accurate fluids and metal temperature cool-down trajectories and to predict the temperatures at the end of the soak period. Method development has been investigated in this study on a light-duty passenger vehicle using coupled aerodynamic-heat transfer thermal transient modelling method for the full vehicle under 9 hours of thermal soak. The 3D underhood flow dynamics were solved inherently transient by the Lattice-Boltzmann Method (LBM) method using the PowerFlow software. This was further coupled with heat transfer modelling using the PowerTHERM software provided by Exa Corporation. The particle-based LBM method was capable of accurately handling extremely complicated transient flow behavior on complex surface geometries. The detailed thermal modelling, including heat conduction, radiation, and buoyancy-driven heat convection, were integrated solved by PowerTHERM. The 9 hours cool-down period was simulated and compared with the vehicle testing data of the key fluid (coolant, oil) and metal temperatures. The developed CAE method was able to predict the cool-down behaviour of the key fluids and components in agreement with the experimental data and also visualised the air leakage paths and thermal retention around the engine bay. The cool-down trajectories of the key components obtained for the 9 hours thermal soak period provide vital information and a basis for the further development of reduced-order modelling studies in future work. This allows a fast-running model to be developed and be further imbedded with the holistic study of vehicle energy modelling and thermal management. It is also found that the buoyancy effect plays an important part at the first stage of the 9 hours soak and the flow development during this stage is vital to accurately predict the heat transfer coefficients for the heat retention modelling. The developed method has demonstrated the software integration for simulating buoyancy-driven heat transfer in a vehicle underhood region during thermal soak with satisfying accuracy and efficient computing time. The CAE method developed will allow integration of the design of engine encapsulations for improving fuel consumption and reducing CO₂ emissions in a timely and robust manner, aiding the development of low-carbon transport technologies.

Keywords: ATCT/WLTC driving cycle, buoyancy-driven heat transfer, CAE method, heat retention, underhood modeling, vehicle thermal soak

Procedia PDF Downloads 142

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Carolina Senabre, Sergio Valero, Miguel Lopez, Antonio Gabaldon

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This paper presents a comprehensive survey of the short-term load forecasting (STLF). Since the behavior of consumers and producers continue changing as new technologies, it is an ongoing process, and moreover, new policies become available. The results of a research study for the Spanish Transport System Operator (REE) is presented in this paper. It is presented the improvement of the forecasting accuracy in the Balearic Islands considering the introduction of meteorological variables, such as temperature to reduce forecasting error. Variables analyzed for the forecasting in terms of overall accuracy are cloudiness, solar radiation, and wind velocity. It has also been analyzed the type of days to be considered in the research.

Keywords: short-term load forecasting, power demand, neural networks, load forecasting

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Authors: Abderrahmane Hemmani, Hamid Khachab, Dennai Benmoussa, Hassane Benslimane, Abderrachid Helmaoui

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Back surface field GaAs with n -p-p+ structures are found to have better characteristics than the conventional solar cells. A theory, based on the transport of both minority carriers under the charge neutrality condition, has been developed in the present paper which explains behavior of the back surface field solar cells. That is reported with an efficiency of 25,05% (Jsc=33.5mA/cm2, Vco=0.87v and fill factor 86% under AM1.5 global conditions). We present the effect of technological parameters of the p+ layer on the conversion efficiency on the solar cell. Good agreement is achieved between our results and the simulation results given the variation of the equivalent recombination velocity to p+ layer as a function of BSF thickness and BSF doping.

Keywords: back surface field, GaAs, solar cell, technological parameters

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Authors: Steven D. P. Moore

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An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

Procedia PDF Downloads 179

Authors: Evanka Madan, Madhu Puri, Dan Zilberstein, Rohini Muthuswami, Rentala Madhubala

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The extensive interaction between the host and pathogen metabolic networks decidedly shapes the outcome of infection. Utilization of arginine by the host and pathogen is critical for determining the outcome of pathogenic infection. Infections with L. donovani, an intracellular parasite, will lead to an extensive competition of arginine between the host and the parasite donovani infection. One of the major amino acid (AA) sensing signaling pathways in mammalian cells are the mammalian target of rapamycin complex I (mTORC1) pathway. mTORC1, as a sensor of nutrient, controls numerous metabolic pathways. Arginine is critical for mTORC1 activation. SLC38A9 is the arginine sensor for the mTORC1, being activated during arginine sufficiency. L. donovani transport arginine via a high-affinity transporter (LdAAP3) that is rapidly up-regulated by arginine deficiency response (ADR) in intracellular amastigotes. This study, to author’s best knowledge, investigates the interaction between two arginine sensing systems that act in the same compartment, the lysosome. One is important for macrophage defense, and the other is essential for pathogen virulence. We hypothesize that the latter modulates lysosome arginine to prevent host defense response. The work presented here identifies an upstream regulatory role of LdAAP3 in regulating the expression of SLC38A9-mTORC1 pathway, and consequently, their function in L. donovani infected THP-1 cells cultured in 0.1 mM and 1.5 mM arginine. It was found that in physiological levels of arginine (0.1 mM), infecting THP-1 with Leishmania leads to increased levels of SLC38A9 and mTORC1 via an increase in the expression of RagA. However, the reversal was observed with LdAAP3 mutants, reflecting the positive regulatory role of LdAAP3 on the host SLC38A9. At the molecular level, upon infection, mTORC1 and RagA were found to be activated at the surface of phagolysosomes which was found to form a complex with phagolysosomal localized SLC38A9. To reveal the relevance of SLC38A9 under physiological levels of arginine, endogenous SLC38A9 was depleted and a substantial reduction in the expression of host mTORC1, its downstream active substrate, p-P70S6K1 and parasite LdAAP3, was observed, thereby showing that silencing SLC38A9 suppresses ADR. In brief, to author’s best knowledge, these results reveal an upstream regulatory role of LdAAP3 in manipulating SLC38A9 arginine sensing in host macrophages. Our study indicates that intra-macrophage survival of L. donovani depends on the availability and transport of extracellular arginine. An understanding of the sensing pathway of both parasite and host will open a new perspective on the molecular mechanism of host-parasite interaction and consequently, as a treatment for Leishmaniasis.

Keywords: arginine sensing, LdAAP3, L. donovani, mTORC1, SLC38A9, THP-1

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Authors: Yurii Bloshko, Oksana Olar

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This paper presents the analysis of 6 different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms.

Keywords: fuzzy petri net, intelligent computational techniques, knowledge representation, triangular norms

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Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

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Authors: Murad Ali, Anderson Konan Seny Kan, Khalid A. Maimani

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Based on the theory of organizational design and the theory of knowledge, this study uses complexity theory to explain and better understand the causal impacts of various patterns of organizational structural factors stimulating absorptive capacity (ACAP). Organizational structure can be thought of as heterogeneous configurations where various components are often intertwined. This study argues that impact of the traditional variables which define a firm’s organizational structure (centralization, formalization, complexity and integration) on ACAP is better understood in terms of set-theoretic relations rather than correlations. This study uses a data sample of 347 from a multiple industrial sector in South Korea. The results from PLS-SEM support all the hypothetical relationships among the variables. However, fsQCA results suggest the possible configurations of centralization, formalization, complexity, integration, age, size, industry and revenue factors that contribute to high level of ACAP. The results from fsQCA demonstrate the usefulness of configurational approaches in helping understand equifinality in the field of knowledge management. A recent fsQCA procedure based on a modeling subsample and holdout subsample is use in this study to assess the predictive validity of the model under investigation. The same type predictive analysis is also made through PLS-SEM. These analyses reveal a good relevance of causal solutions leading to high level of ACAP. In overall, the results obtained from combining PLS-SEM and fsQCA are very insightful. In particular, they could help managers to link internal organizational structural with ACAP. In other words, managers may comprehend finely how different components of organizational structure can increase the level of ACAP. The configurational approach may trigger new insights that could help managers prioritize selection criteria and understand the interactions between organizational structure and ACAP. The paper also discusses theoretical and managerial implications arising from these findings.

Keywords: absorptive capacity, organizational structure, PLS-SEM, fsQCA, predictive analysis, modeling subsample, holdout subsample

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Authors: Yiyuan Tao

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Under the impact of global warming together with the intensification of human activities, the hydrological regimes may be altered, and the traditional stationary assumption was no longer satisfied. However, most of the current design standards of water infrastructures were still based on the hypothesis of stationarity, which may inevitably result in severe biases. Many critical impacts of climate on ecosystems, society, and the economy are controlled by extreme events rather than mean values. Therefore, it is of great significance to identify the non-stationarity of precipitation extremes and model the precipitation extremes in a nonstationary framework. The Wei River Basin (WRB), located in a continental monsoon climate zone in China, is selected as a case study in this study. Six extreme precipitation indices were employed to investigate the changing patterns and stationarity of precipitation extremes in the WRB. To identify if precipitation extremes are stationary, the Mann-Kendall trend test and the Pettitt test, which is used to examine the occurrence of abrupt changes are adopted in this study. Extreme precipitation indices series are fitted with non-stationary distributions that selected from six widely used distribution functions: Gumbel, lognormal, Weibull, gamma, generalized gamma and exponential distributions by means of the time-varying moments model generalized additive models for location, scale and shape (GAMLSS), where the distribution parameters are defined as a function of time. The results indicate that: (1) the trends were not significant for the whole WRB, but significant positive/negative trends were still observed in some stations, abrupt changes for consecutive wet days (CWD) mainly occurred in 1985, and the assumption of stationarity is invalid for some stations; (2) for these nonstationary extreme precipitation indices series with significant positive/negative trends, the GAMLSS models are able to capture well the temporal variations of the indices, and perform better than the stationary model. Finally, the differences between the quantiles of nonstationary and stationary models are analyzed, which highlight the importance of nonstationary modeling of precipitation extremes in the WRB.

Keywords: extreme precipitation, GAMLSSS, non-stationary, Wei River Basin

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Authors: Akhtar Rasool, Tasneem Zahra Rizvi

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In this study, a series of the cadmium sulphide quantum dots/polyaniline nanocomposites with varying compositions were prepared by in-situ polymerization technique and were characterized using X-ray diffraction and Fourier transform infrared spectroscopy. The surface morphology was studied by scanning electron microscopy. UV-Visible spectroscopy was used to find out the energy band gap of the nanoparticles and the nanocomposites. Temperature dependence of DC electrical conductivity and temperature and frequency dependence of AC conductivity were investigated to study the charge transport mechanism in the nanocomposites. DC conductivity was found to be a typical for a semiconducting behavior following Mott’s 1D variable range hoping model. The frequency dependent AC conductivity followed the universal power law.

Keywords: conducting polymers, nanocomposites, polyaniline composites, quantum dots

Procedia PDF Downloads 242

Authors: Zikun Li, Regine Talleyrand

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Negative body image is one of the most common causes of eating disorders, and it is not only happening to women. Regardless of the increasing attention that researchers and practitioners have been paying to the male population and their body image concerns, men of color have yet to be fully represented or studied. Given the consensus that the sociocultural experiences of people of color may play a significant role in their health and well-being, this study focused on assessing the mechanism through which sociocultural factors may influence men of color’s perceptions of body image. In particular, this study focused on untangling how interpersonal and media pressure, as well as ethnic-racial identities and perceptions, would impact body dissatisfaction in terms of muscularity, body fat, and height in men of color and how this mechanism is moderated across different ethnic-racial groups. The structural equation modeling approach was therefore applied to achieve the research goal. With the sample size of 181 self-identified Black, Indigenous, and People of Color male participants aged 20-50 (M=33.33, SD=6.9) through surveying on Amazon’s MTurk platform, the proposed model achieved a modestly acceptable model fit with the pooled sample, X2(836) = 1412.184, CFI = 0.900, RMSEA = 0.062 [0.056, 0.067]. And SRMR = 0.088, And it explained 89.5% of the variance in body dissatisfaction. The results showed that of all the direct effects on body dissatisfaction, interpersonal appearance pressure exhibited the strongest effect (β = 0.410***), followed by media appearance pressure (β = 0.272**) and self-hatred feeling (β = 0.245**). The ethnic-racial related factors (i.e., stereotype endorsement, ethnic-racial salience, and nationalistic assimilation) statistically influenced body dissatisfaction through the mediators of media appearance pressure and/or self-hatred feeling. Furthermore, the moderation analysis between Black/African American men and non-Black/African American men revealed the substantial differences in how ethnic/racial identity impacts one’s perception of body image, and the Black/African American men were found to be influenced by sociocultural factors at a higher level, compared with their counterparts. The impacts of demographic characteristics (i.e., SES, weight, height) on body dissatisfaction were also examined. Instead of considering interpersonal appearance pressure and media pressure as two subscales under one construct, this study considered them as two separate and distinct sociocultural factors. The good model fit to the data indicates this rationality and encourages scholars to reconsider the impacts of two sources of social pressures on body dissatisfaction. In addition, this study also provided empirical evidence of the moderation effect existing within the population of men of color, which reveals the heterogeneity existing across different ethnic-racial groups and implies the necessity to study individual ethnic-racial groups so as to better understand the mechanism of sociocultural influences on men of color’s body dissatisfaction. These findings strengthened the current understanding of the body image concerns exciting among men of color and meanwhile provided empirical evidence for practitioners to provide tailored health prevention and treatment options for this growing population in the United States.

Keywords: men of color, body image concerns, sociocultural factors, structural equation modeling

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Authors: ِAbdallah A. A. Shaheen

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Gaza Strip faces economic and political issues such as conflict, siege and urbanization; all these have led to an increase in the air pollution over Gaza Strip. In this study, Particulate matter 10 (PM10) concentration over Gaza Strip has been estimated by Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) data, based on a multispectral algorithm. Simultaneously, in-situ measurements for the corresponding particulate are acquired for selected time period. Landsat and ground data for eleven years are used to develop the algorithm while four years data (2002, 2006, 2010 and 2014) have been used to validate the results of algorithm. The developed algorithm gives highest regression, R coefficient value i.e. 0.86; RMSE value as 9.71 µg/m³; P values as 0. Average validation of algorithm show that calculated PM10 strongly correlates with measured PM10, indicating high efficiency of algorithm for the mapping of PM10 concentration during the years 2000 to 2014. Overall results show increase in minimum, maximum and average yearly PM10 concentrations, also presents similar trend over urban area. The rate of urbanization has been evaluated by supervised classification of the Landsat image. Urban sprawl from year 2000 to 2014 results in a high concentration of PM10 in the study area.

Keywords: PM10, landsat, atmospheric reflectance, Gaza strip, urbanization

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Authors: F. Benkaci-Ali, R. Mékaoui, G. Scholl, G. Eppe

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The new methods as accelerated steam distillation assisted by microwave (ASDAM) is a combination of microwave heating and steam distillation, performed at atmospheric pressure at very short extraction time. Isolation and concentration of volatile compounds are performed by a single stage. (ASDAM) has been compared with (ASDAM) with cryogrinding of seeds (CG) and a conventional technique, hydrodistillation assisted by microwave (HDAM), hydro-distillation (HD) for the extraction of essential oil from aromatic herb as caraway and cumin seeds. The essential oils extracted by (ASDAM) for 1 min were quantitatively (yield) and qualitatively (aromatic profile) no similar to those obtained by ASDAM-CG (1 min) and HD (for 3 h). The accelerated microwave extraction with cryogrinding inhibits numerous enzymatic reactions as hydrolysis of oils. Microwave radiations constitute the adequate mean for the extraction operations from the yields and high content in major component majority point view, and allow to minimise considerably the energy consumption, but especially heating time too, which is one of essential parameters of artifacts formation. The ASDAM and ASDAM-CG are green techniques and yields an essential oil with higher amounts of more valuable oxygenated compounds comparable to the biosynthesis compounds, and allows substantial savings of costs, in terms of time, energy and plant material.

Keywords: microwave, steam distillation, caraway, cumin, cryogrinding, GC-MS, GCxGC-MS

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Authors: A. Shakoor, M. Arshad

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The utilization of groundwater resources in irrigation has significantly increased during the last two decades due to constrained canal water supplies. More than 70% of the farmers in the Punjab, Pakistan, depend directly or indirectly on groundwater to meet their crop water demands and hence, an unchecked paradigm shift has resulted in aquifer depletion and deterioration. Therefore, a comprehensive research was carried at central Punjab-Pakistan, regarding spatiotemporal variation in groundwater level and quality. Processing MODFLOW for window (PMWIN) and MT3D (solute transport model) models were used for existing and future prediction of groundwater level and quality till 2030. The comprehensive data set of aquifer lithology, canal network, groundwater level, groundwater salinity, evapotranspiration, groundwater abstraction, recharge etc. were used in PMWIN model development. The model was thus, successfully calibrated and validated with respect to groundwater level for the periods of 2003 to 2007 and 2008 to 2012, respectively. The coefficient of determination (R2) and model efficiency (MEF) for calibration and validation period were calculated as 0.89 and 0.98, respectively, which argued a high level of correlation between the calculated and measured data. For solute transport model (MT3D), the values of advection and dispersion parameters were used. The model used for future scenario up to 2030, by assuming that there would be no uncertain change in climate and groundwater abstraction rate would increase gradually. The model predicted results revealed that the groundwater would decline from 0.0131 to 1.68m/year during 2013 to 2030 and the maximum decline would be on the lower side of the study area, where infrastructure of canal system is very less. This lowering of groundwater level might cause an increase in the tubewell installation and pumping cost. Similarly, the predicted total dissolved solids (TDS) of the groundwater would increase from 6.88 to 69.88mg/L/year during 2013 to 2030 and the maximum increase would be on lower side. It was found that in 2030, the good quality would reduce by 21.4%, while marginal and hazardous quality water increased by 19.28 and 2%, respectively. It was found from the simulated results that the salinity of the study area had increased due to the intrusion of salts. The deterioration of groundwater quality would cause soil salinity and ultimately the reduction in crop productivity. It was concluded from the predicted results of groundwater model that the groundwater deteriorated with the depth of water table i.e. TDS increased with declining groundwater level. It is recommended that agronomic and engineering practices i.e. land leveling, rainwater harvesting, skimming well, ASR (Aquifer Storage and Recovery Wells) etc. should be integrated to meliorate management of groundwater for higher crop production in salt affected soils.

Keywords: groundwater quality, groundwater management, PMWIN, MT3D model

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Authors: Dewi Selvia Fardhyanti, Astrilia Damayanti

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Coal tar is a liquid by-product of coal pyrolysis processes. This liquid oil mixture contains various kind of useful compounds such as benzoic aromatic compounds and phenolic compounds. These compounds are widely used as raw material for insecticides, dyes, medicines, perfumes, coloring matters, and many others. The coal tar was collected by pyrolysis process of coal obtained from PT Kaltim Prima Coal and Arutmin-Kalimantan. The experiments typically occurred at the atmospheric pressure in a laboratory furnace at temperatures ranging from 300 to 550oC with a heating rate of 10oC/min and a holding time of 1 hour at the pyrolysis temperature. Nitrogen gas has been used to obtain the inert condition and to carry the gaseous pyrolysis products. The pyrolysis transformed organic materials into gaseous components, small quantities of liquid, and a solid residue (coke) containing fixed amount of carbon and ash. The composition of gas which is produced from the pyrolysis is carbon monoxide, hydrogen, methane, and other hydrocarbon compounds. The gas was condensed and the liquid containing oil/tar and water was obtained. The Gas Chromatography-Mass Spectroscopy (GC-MS) was used to analyze the coal tar components. The obtained coal tar has the viscosity of 3.12 cp, the density of 2.78 g/cm3, the calorific value of 11,048.44 cal/g, and the molecular weight of 222.67. The analysis result showed that the coal tar contained more than 78 chemical compounds such as benzene, cresol, phenol, xylene, naphtalene, etc. The total phenolic compounds contained in coal tar is 33.25% (PT KPC) and 17.58% (Arutmin-Kalimantan). The total naphtalene compounds contained in coal tar is 14.15% (PT KPC) and 17.13% (Arutmin-Kalimantan).

Keywords: coal tar, pyrolysis, gas chromatography-mass spectroscopy

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Authors: Dudam Bharath Kumar, Harsh Kumar, Naveed Ahmed

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Vehicular traffic on the road-side plays a significant role in affecting the noise pollution in most of the cities over the world. To assess the correlation of the road-traffic on noise pollution in the city environment, continuous measurements were carried out in an entire daytime starting from 8:00 AM IST to 6:00 PM IST at a single point for each 5 minutes (8:00-8:05, 9:00-9:05, 10:00-10:05 AM, ...) near the KIIT University campus road. Noise levels were observed using a mobile operated app of android cell phone and a handheld noise meter. Calibration analysis shows high correlation about 0.89 for the study location for the day time period. Results show diurnal variability of atmospheric noise pollution levels go hand-in and with the vehicular number which pass through a point of observation. The range of noise pollution levels in the daytime period is observed as 55 to 75 dB(A). As a day starts, sudden upsurge of noise levels is observed from 65 to 71 dB(A) in the early morning, 64 dB(A) in late morning, regains the same quantity 68-71 dB(A) in the afternoon, and rises 70 dB(A) in the early evening. Vehicular number of the corresponding noise levels exhibits 115-120, 150-160, and 140-160, respectively. However, this preliminary study suggests the importance of vehicular traffic on noise pollution levels in the urban environment and further to study population exposed to noise levels. Innovative approaches help curb the noise pollution through modelling the traffic noise pollution spatially and temporally over the city environments.

Keywords: noise pollution, vehicular traffic, urban environment, noise meter

Procedia PDF Downloads 287

Authors: M. Duk, L. Grabowski, P. Magryta

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Today's very important element relating to air transport is the environment impact issues. Nowadays there are no emissions standards for turbine and piston engines used in air transport. However, it should be noticed that the environmental effect in the form of exhaust gases from aircraft engines should be as small as possible. For this purpose, R&D centers often use special software to simulate and to estimate the negative effect of engine working process. For cooperation between the Lublin University of Technology and the Polish aviation company WSK "PZL-KALISZ" S.A., to achieve more effective operation of the ASz62IR engine, one of such tools have been used. The AVL Boost software allows to perform 1D simulations of combustion process of piston engines. ASz62IR is a nine-cylinder aircraft engine in a radial configuration. In order to analyze the impact of its working process on the environment, the mathematical model in the AVL Boost software have been made. This model contains, among others, model of the operation cycle of the cylinders. This model was based on a volume change in combustion chamber according to the reciprocating movement of a piston. The simplifications that all of the pistons move identically was assumed. The changes in cylinder volume during an operating cycle were specified. Those changes were important to determine the energy balance of a cylinder in an internal combustion engine which is fundamental for a model of the operating cycle. The calculations for cylinder thermodynamic state were based on the first law of thermodynamics. The change in the mass in the cylinder was calculated from the sum of inflowing and outflowing masses including: cylinder internal energy, heat from the fuel, heat losses, mass in cylinder, cylinder pressure and volume, blowdown enthalpy, evaporation heat etc. The model assumed that the amount of heat released in combustion process was calculated from the pace of combustion, using Vibe model. For gas exchange, it was also important to consider heat transfer in inlet and outlet channels because of much higher values there than for flow in a straight pipe. This results from high values of heat exchange coefficients and temperature coefficients near valves and valve seats. A Zapf modified model of heat exchange was used. To use the model with the flight scenarios, the impact of flight altitude on engine performance has been analyze. It was assumed that the pressure and temperature at the inlet and outlet correspond to the values resulting from the model for International Standard Atmosphere (ISA). Comparing this model of operation cycle with the others submodels of the ASz62IR engine, it could be noticed, that a full analysis of the performance of the engine, according to the ISA conditions, can be made. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under

Keywords: aviation propulsion, AVL Boost, engine model, operation cycle, aircraft engine

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Zoran Herceg, Višnja Stulić, Tomislava Vukušić, Anet Režek Jambrak

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High voltage electrical discharge is a new technology used for inactivation of pathogen microorganisms. Pathogen yeasts can cause diseases in humans if they are ingested. Nowadays new technologies have become the focus of researching all over the world. Rhodotorula is known as yeast that can cause diseases in humans. The aim of this study was to examine whether the high voltage electrical discharge treatment generated in gas phase has an influence on yeast reduction and recovery of Rhodotorula spp 74 in pure culture. Rhodotorula spp. 74 was treated in 200 mL of model solution. Treatment time (5 and 10 min), frequency (60 and 90 Hz) and injected gas (air or argon 99,99%) were changed. Titanium high voltage needle was used as high voltage electrode (positive polarity) through which air or argon was injected at the gas flow of 0.6 L/min. Experimental design and statistical analyses were obtained by Statgraphics Centurion software (StatPoint Technologies, Inc., VA, USA). The best inactivation rate 1.7 log10 reduction was observed after the 10 min of treatment, frequency of 90 Hz and injected air. Also with a longer treatment time inactivation rate was higher. After the 24 h recovery of treated samples was observed. Therefore the further optimization of method is needed to understand the mechanism of yeasts inactivation and cells recovery after the treatment. Acknowledgements: The authors would like to acknowledge the support by Croatian Science Foundation and research project ‘Application of electrical discharge plasma for preservation of liquid foods’.

Keywords: rhodotorula spp. 74, electrical discharge plasma, inactivation, stress response

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Authors: Lancelot Boulet, Pierre Benard, Ghislain Lartigue, Vincent Moureau, Nicolas Chauvet, Sheddia Didorally

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International aeronautic standards demand a fire certification for engines that demonstrate their resistance. This demonstration relies on tests performed with prototype engines in the late stages of the development. Hardest tests require to place a kerosene standardized flame in front of the engine casing during a given time with imposed temperature and heat flux. The purpose of this work is to provide a better characterization of a kerosene/air certification burner in order to minimize the risks of test failure. A first Large-Eddy Simulation (LES) study of the certification burner permitted to model and simulate this burner, including both adiabatic and Conjugate Heat Transfer (CHT) computations. Carried out on unstructured grids with 40 million tetrahedral cells, using the finite-volume YALES2 code, spray combustion, forced convection on walls and conduction in the solid parts of the burner were coupled to achieve a detailed description of heat transfer. It highlighted the fact that conduction inside the solid has a real impact on the flame topology and the combustion regime. However, in the absence of radiative heat transfer, unrealistic temperature of the equipment was obtained. The aim of the present study is to include the radiative heat transfer in order to reach the same temperature given by experimental measurements. First, various test-cases are conducted to validate the coupling between the different heat solvers. Then, adiabatic case, CHT case, as well as CHT including radiative transfer are studied and compared. The LES model is finally applied to investigate the heat transfer in a flame impaction configuration. The aim is to progress on fire test modeling so as to reach a good confidence level as far as success of the certification test is concerned.

Keywords: conjugate heat transfer, fire resistance test, large-eddy simulation, radiative transfer, turbulent combustion

Procedia PDF Downloads 217