Search results for: combined immunotherapy and radiation
Commenced in January 2007
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Edition: International
Paper Count: 4049

Search results for: combined immunotherapy and radiation

539 Use of Artificial Neural Networks to Estimate Evapotranspiration for Efficient Irrigation Management

Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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538 Nondestructive Prediction and Classification of Gel Strength in Ethanol-Treated Kudzu Starch Gels Using Near-Infrared Spectroscopy

Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

Abstract:

Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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537 Diverse High-Performing Teams: An Interview Study on the Balance of Demands and Resources

Authors: Alana E. Jansen

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With such a large proportion of organisations relying on the use of team-based structures, it is surprising that so few teams would be classified as high-performance teams. While the impact of team composition on performance has been researched frequently, there have been conflicting findings as to the effects, particularly when examined alongside other team factors. To broaden the theoretical perspectives on this topic and potentially explain some of the inconsistencies in research findings left open by other various models of team effectiveness and high-performing teams, the present study aims to use the Job-Demands-Resources model, typically applied to burnout and engagement, as a framework to examine how team composition factors (particularly diversity in team member characteristics) can facilitate or hamper team effectiveness. This study used a virtual interview design where participants were asked to both rate and describe their experiences, in one high-performing and one low-performing team, over several factors relating to demands, resources, team composition, and team effectiveness. A semi-structured interview protocol was developed, which combined the use of the Likert style and exploratory questions. A semi-targeted sampling approach was used to invite participants ranging in age, gender, and ethnic appearance (common surface-level diversity characteristics) and those from different specialties, roles, educational and industry backgrounds (deep-level diversity characteristics). While the final stages of data analyses are still underway, thematic analysis using a grounded theory approach was conducted concurrently with data collection to identify the point of thematic saturation, resulting in 35 interviews being completed. Analyses examine differences in perceptions of demands and resources as they relate to perceived team diversity. Preliminary results suggest that high-performing and low-performing teams differ in perceptions of the type and range of both demands and resources. The current research is likely to offer contributions to both theory and practice. The preliminary findings suggest there is a range of demands and resources which vary between high and low-performing teams, factors which may play an important role in team effectiveness research going forward. Findings may assist in explaining some of the more complex interactions between factors experienced in the team environment, making further progress towards understanding the intricacies of why only some teams achieve high-performance status.

Keywords: diversity, high-performing teams, job demands and resources, team effectiveness

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536 Development of Oral Biphasic Drug Delivery System Using a Natural Resourced Polymer, Terminalia catappa

Authors: Venkata Srikanth Meka, Nur Arthirah Binti Ahmad Tarmizi Tan, Muhammad Syahmi Bin Md Nazir, Adinarayana Gorajana, Senthil Rajan Dharmalingam

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Biphasic drug delivery systems are designed to release drug at two different rates, either fast/prolonged or prolonged/fast. A fast/prolonged release system provides a burst drug release at initial stage followed by a slow release over a prolonged period of time and in case of prolonged/fast release system, the release pattern is vice versa. Terminalia catappa gum (TCG) is a natural polymer and was successfully proven as a novel pharmaceutical excipient. The main objective of the present research is to investigate the applicability of natural polymer, Terminalia catappa gum in the design of oral biphasic drug delivery system in the form of mini tablets by using a model drug, buspirone HCl. This investigation aims to produce a biphasic release drug delivery system of buspirone by combining immediate release and prolonged release mini tablets into a capsule. For immediate release mini tablets, a dose of 4.5 mg buspirone was prepared by varying the concentration of superdisintegrant; crospovidone. On the other hand, prolonged release mini tablets were produced by using different concentrations of the natural polymer; TCG with a buspirone dose of 3mg. All mini tablets were characterized for weight variation, hardness, friability, disintegration, content uniformity and dissolution studies. The optimized formulations of immediate and prolonged release mini tablets were finally combined in a capsule and was evaluated for release studies. FTIR and DSC studies were conducted to study the drug-polymer interaction. All formulations of immediate release and prolonged release mini tablets were passed all the in-process quality control tests according to US Pharmacopoeia. The disintegration time of immediate release mini tablets of different formulations was varied from 2-6 min, and maximum drug release was achieved in lesser than 60 min. Whereas prolonged release mini tablets made with TCG have shown good drug retarding properties. Formulations were controlled for about 4-10 hrs with varying concentration of TCG. As the concentration of TCG increased, the drug release retarding property also increased. The optimised mini tablets were packed in capsules and were evaluated for the release mechanism. The capsule dosage form has clearly exhibited the biphasic release of buspirone, indicating that TCG is a suitable natural polymer for this study. FTIR and DSC studies proved that there was no interaction between the drug and polymer. Based on the above positive results, it can be concluded that TCG is a suitable polymer for the biphasic drug delivery systems.

Keywords: Terminalia catappa gum, biphasic release, mini tablets, tablet in capsule, natural polymers

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535 A Study on the Magnetic and Submarine Geology Structure of TA22 Seamount in Lau Basin, Tonga

Authors: Soon Young Choi, Chan Hwan Kim, Chan Hong Park, Hyung Rae Kim, Myoung Hoon Lee, Hyeon-Yeong Park

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We performed the marine magnetic, bathymetry and seismic survey at the TA22 seamount (in the Lau basin, SW Pacific) for finding the submarine hydrothermal deposits in October 2009. We acquired magnetic and bathymetry data sets by suing Overhouser Proton Magnetometer SeaSPY (Marine Magnetics Co.), Multi-beam Echo Sounder EM120 (Kongsberg Co.). We conducted the data processing to obtain detailed seabed topography, magnetic anomaly, reduction to the pole (RTP) and magnetization. Based on the magnetic properties result, we analyzed submarine geology structure of TA22 seamount with post-processed seismic profile. The detailed bathymetry of the TA22 seamount showed the left and right crest parts that have caldera features in each crest central part. The magnetic anomaly distribution of the TA22 seamount regionally displayed high magnetic anomalies in northern part and the low magnetic anomalies in southern part around the caldera features. The RTP magnetic anomaly distribution of the TA22 seamount presented commonly high magnetic anomalies in the each caldera central part. Also, it represented strong anomalies at the inside of caldera rather than outside flank of the caldera. The magnetization distribution of the TA22 seamount showed the low magnetization zone in the center of each caldera, high magnetization zone in the southern and northern east part. From analyzed the seismic profile map, The TA22 seamount area is showed for the inferred small mounds inside each caldera central part and it assumes to make possibility of sills by the magma in cases of the right caldera. Taking into account all results of this study (bathymetry, magnetic anomaly, RTP, magnetization, seismic profile) with rock samples at the left caldera area in 2009 survey, we suppose the possibility of hydrothermal deposits at mounds in each caldera central part and at outside flank of the caldera representing the low magnetization zone. We expect to have the better results by combined modeling from this study data with the other geological data (ex. detailed gravity, 3D seismic, petrologic study results and etc).

Keywords: detailed bathymetry, magnetic anomaly, seamounts, seismic profile, SW Pacific

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534 Detection and Identification of Antibiotic Resistant Bacteria Using Infra-Red-Microscopy and Advanced Multivariate Analysis

Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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533 An Investigation into the Influence of Compression on 3D Woven Preform Thickness and Architecture

Authors: Calvin Ralph, Edward Archer, Alistair McIlhagger

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3D woven textile composites continue to emerge as an advanced material for structural applications and composite manufacture due to their bespoke nature, through thickness reinforcement and near net shape capabilities. When 3D woven preforms are produced, they are in their optimal physical state. As 3D weaving is a dry preforming technology it relies on compression of the preform to achieve the desired composite thickness, fibre volume fraction (Vf) and consolidation. This compression of the preform during manufacture results in changes to its thickness and architecture which can often lead to under-performance or changes of the 3D woven composite. Unlike traditional 2D fabrics, the bespoke nature and variability of 3D woven architectures makes it difficult to know exactly how each 3D preform will behave during processing. Therefore, the focus of this study is to investigate the effect of compression on differing 3D woven architectures in terms of structure, crimp or fibre waviness and thickness as well as analysing the accuracy of available software to predict how 3D woven preforms behave under compression. To achieve this, 3D preforms are modelled and compression simulated in Wisetex with varying architectures of binder style, pick density, thickness and tow size. These architectures have then been woven with samples dry compression tested to determine the compressibility of the preforms under various pressures. Additional preform samples were manufactured using Resin Transfer Moulding (RTM) with varying compressive force. Composite samples were cross sectioned, polished and analysed using microscopy to investigate changes in architecture and crimp. Data from dry fabric compression and composite samples were then compared alongside the Wisetex models to determine accuracy of the prediction and identify architecture parameters that can affect the preform compressibility and stability. Results indicate that binder style/pick density, tow size and thickness have a significant effect on compressibility of 3D woven preforms with lower pick density allowing for greater compression and distortion of the architecture. It was further highlighted that binder style combined with pressure had a significant effect on changes to preform architecture where orthogonal binders experienced highest level of deformation, but highest overall stability, with compression while layer to layer indicated a reduction in fibre crimp of the binder. In general, simulations showed a relative comparison to experimental results; however, deviation is evident due to assumptions present within the modelled results.

Keywords: 3D woven composites, compression, preforms, textile composites

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532 Solar Power Forecasting for the Bidding Zones of the Italian Electricity Market with an Analog Ensemble Approach

Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

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531 Interactive Lecture Demonstration and Inquiry-Based Instruction in Addressing Students' Misconceptions in Electric Circuits

Authors: Mark Anthony Casimiro, Ivan Culaba, Cornelia Soto

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Misconceptions are the wrong concepts understood by the students which may come up based on what they experience and observe around their environment. This seemed to hinder students’ learning. In this study, six different misconceptions were determined by the researcher from the previous researches. Teachers play a vital role in the classroom. The use of appropriate strategies can contribute a lot in the success of teaching and learning Physics. The current study aimed to compare two strategies- Interactive Lecture Demonstration (ILD) and Inquiry-Based Instruction (IBI) in addressing students’ misconceptions in electric circuits. These two strategies are both interactive learning activities and student-centered. In ILD, the teacher demonstrates the activity and the students have their predictions while in IBI, students perform the experiments. The study used the mixed method in which quantitative and qualitative researches were combined. The main data of this study were the test scores of the students from the pretest and posttest. Likewise, an interview with the teacher, observer and students was done before, during and after the execution of the activities. Determining and Interpreting Resistive Electric Circuits Test version 2 (DIRECT v.2) was the instrument used in the study. Two sections of Grade 9 students from Kalumpang National High School were the respondents of the study. The two strategies were executed to each section; one class was assigned as the ILD group and the other class was the IBI group. The Physics teacher of the said school was the one who taught and executed the activities. The researcher taught the teacher the steps in doing the two strategies. The Department of Education level of proficiency in the Philippines was adopted in scoring and interpretation. The students’ level of proficiency was used in assessing students’ knowledge on electric circuits. The pretest result of the two groups had a p-value of 0.493 which was greater than the level of significance 0.05 (p >0.05) and it implied that the students’ level of understanding in the topic was the same before the execution of the strategies. The posttest results showed that the p-value (0.228) obtained was greater than the level of significance which is 0.05 (p> 0.05). This implied that the students from the ILD and IBI groups had the same level of understanding after the execution of the two strategies. This could be inferred that either of the two strategies- Interactive Lecture Demonstration and Inquiry-Based Instruction could be used in addressing students’ misconception in electric circuit as both had similar effect on the students’ level of understanding in the topic. The result of this study may greatly help teachers, administration, school heads think of appropriate strategies that can address misconceptions depending on the availability of their materials of their school.

Keywords: inquiry- based instruction, interactive lecture demonstration, misconceptions, mixed method

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530 The Acquisition of /r/ By Setswana-Learning Children

Authors: Keneilwe Matlhaku

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Crosslinguistic studies (theoretical and clinical) have shown delays and significant misarticulation in the acquisition of the rhotics. This article provides a detailed analysis of the early development of the rhotic phoneme, an apical trill /r/, by monolingual Setswana (Tswana S30) children of age ranges between 1 and 4 years. The data display the following trends: (1) late acquisition of /r/; (2) a wide range of substitution patterns involving this phoneme (i.e., gliding, coronal stopping, affrication, deletion, lateralization, as well as, substitution to a dental and uvular fricative). The primary focus of the article is on the potential origins of these variations of /r/, even within the same language. Our data comprises naturalistic longitudinal audio recordings of 6 children (2 males and 4 females) whose speech was recorded in their homes over a period of 4 months with no or only minimal disruptions in their daily environments. Phon software (Rose et al. 2013; Rose & MacWhinney 2014) was used to carry out the orthographic and phonetic transcriptions of the children’s data. Phon also enabled the generation of the children’s phonological inventories for comparison with adult target IPA forms. We explain the children’s patterns through current models of phonological emergence (MacWhinney 2015) as well as McAllister Byun, Inkelas & Rose (2016); Rose et al., (2022), which highlight the perceptual and articulatory factors influencing the development of sounds and sound classes. We highlight how the substitution patterns observed in the data can be captured through a consideration of the auditory properties of the target speech sounds, combined with an understanding of the types of articulatory gestures involved in the production of these sounds. These considerations, in turn, highlight some of the most central aspects of the challenges faced by the child toward learning these auditory-articulatory mappings. We provide a cross-linguistic survey of the acquisition of rhotic consonants in a sample of related and unrelated languages in which we show that the variability and volatility in the substitution patterns of /r/ is also brought about by the properties of the children’s ambient languages. Beyond theoretical issues, this article sets an initial foundation for developing speech-language pathology materials and services for Setswana learning children, an emerging area of public service in Botswana.

Keywords: rhotic, apical trill, Phon, phonological emergence, auditory, articulatory, mapping

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529 Profiling of the Cell-Cycle Related Genes in Response to Efavirenz, a Non-Nucleoside Reverse Transcriptase Inhibitor in Human Lung Cancer

Authors: Rahaba Marima, Clement Penny

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The Health-related quality of life (HRQoL) for HIV positive patients has improved since the introduction of the highly active antiretroviral treatment (HAART). However, in the present HAART era, HIV co-morbidities such as lung cancer, a non-AIDS (NAIDS) defining cancer have been documented to be on the rise. Under normal physiological conditions, cells grow, repair and proliferate through the cell-cycle as cellular homeostasis is important in the maintenance and proper regulation of tissues and organs. Contrarily, the deregulation of the cell-cycle is a hallmark of cancer, including lung cancer. The association between lung cancer and the use of HAART components such as Efavirenz (EFV) is poorly understood. This study aimed at elucidating the effects of EFV on the cell-cycle genes’ expression in lung cancer. For this purpose, the human cell-cycle gene array composed of 84 genes was evaluated on both normal lung fibroblasts (MRC-5) cells and adenocarcinoma (A549) lung cells, in response to 13µM EFV or 0.01% vehicle. The ±2 up or down fold change was used as a basis of target selection, with p < 0.05. Additionally, RT-qPCR was done to validate the gene array results. Next, In-silico bio-informatics tools, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Reactome, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Ingenuity Pathway Analysis (IPA) were used for gene/gene interaction studies as well as to map the molecular and biological pathways influenced by the identified targets. Interestingly, the DNA damage response (DDR) pathway genes such as p53, Ataxia telangiectasia mutated and Rad3 related (ATR), Growth arrest and DNA damage inducible alpha (GADD45A), HUS1 checkpoint homolog (HUS1) and Role of radiation (RAD) genes were shown to be upregulated following EFV treatment, as revealed by STRING analysis. Additionally, functional enrichment analysis by the KEGG pathway revealed that most of the differentially expressed gene targets function at the cell-cycle checkpoint such as p21, Aurora kinase B (AURKB) and Mitotic Arrest Deficient-Like 2 (MAD2L2). Core analysis by IPA revealed that p53 downstream targets such as survivin, Bcl2, and cyclin/cyclin dependent kinases (CDKs) complexes are down-regulated, following exposure to EFV. Furthermore, Reactome analysis showed a significant increase in cellular response to stress genes, DNA repair genes, and apoptosis genes, as observed in both normal and cancerous cells. These findings implicate the genotoxic effects of EFV on lung cells, provoking the DDR pathway. Notably, the constitutive expression of this pathway (DDR) often leads to uncontrolled cell proliferation and eventually tumourigenesis, which could be the attribute of HAART components’ (such as EFV) effect on human cancers. Targeting the cell-cycle and its regulation holds a promising therapeutic intervention to the potential HAART associated carcinogenesis, particularly lung cancer.

Keywords: cell-cycle, DNA damage response, Efavirenz, lung cancer

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528 Aptamers: A Potential Strategy for COVID-19 Treatment

Authors: Mohamad Ammar Ayass, Natalya Griko, Victor Pashkov, Wanying Cao, Kevin Zhu, Jin Zhang, Lina Abi Mosleh

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Respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for coronavirus disease 2019 (COVID-19). Early evidence pointed at the angiotensin-converting enzyme 2 (ACE-2) expressed on the epithelial cells of the lung as the main entry point of SARS-CoV-2 into the cells. The viral entry is mediated by the binding of the Receptor Binding Domain (RBD) of the spike protein that is expressed on the surface of the virus to the ACE-2 receptor. As the number of SARS-CoV-2 variants continues to increase, mutations arising in the RBD of SARS-CoV-2 may lead to the ineffectiveness of RBD targeted neutralizing antibodies. To address this limitation, the objective of this study is to develop a combination of aptamers that target different regions of the RBD, preventing the binding of the spike protein to ACE-2 receptor and subsequent viral entry and replication. A safe and innovative biomedical tool was developed to inhibit viral infection and reduce the harms of COVID-19. In the present study, DNA aptamers were developed against a recombinant trimer S protein using the Systematic Evolution of Ligands by Exponential enrichment (SELEX). Negative selection was introduced at round number 7 to select for aptamers that bind specifically to the RBD domain. A series of 9 aptamers (ADI2010, ADI2011, ADI201L, ADI203L, ADI205L, ADIR68, ADIR74, ADIR80, ADIR83) were selected and characterized with high binding affinity and specificity to the RBD of the spike protein. Aptamers (ADI25, ADI2009, ADI203L) were able to bind and pull down endogenous spike protein expressed on the surface of SARS-CoV-2 virus in COVID-19 positive patient samples and determined by liquid chromatography- tandem mass spectrometry analysis (LC-MS/MS). LC-MS/MS data confirmed that aptamers can bind to the RBD of the spike protein. Furthermore, results indicated that the combination of the 9 best aptamers inhibited the binding of the purified trimer spike protein to the ACE-2 receptor found on the surface of Vero E6 cells. In the same experiment, the combined aptamers displayed a better neutralizing effect than antibodies. The data suggests that the selected aptamers could be used in therapy to neutralize the effect of the SARS-CoV-2 virus by inhibiting the interaction between the RBD and ACE-2 receptor, preventing viral entry into target cells and therefore blocking viral replication.

Keywords: aptamer, ACE-2 receptor, binding inhibitor, COVID-19, spike protein, SARS-CoV-2, treatment

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527 Hybrid Knowledge and Data-Driven Neural Networks for Diffuse Optical Tomography Reconstruction in Medical Imaging

Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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526 Development of Solar Poly House Tunnel Dryer (STD) for Medicinal Plants

Authors: N. C. Shahi, Anupama Singh, E. Kate

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Drying is practiced to enhance the storage life, to minimize losses during storage, and to reduce transportation costs of agricultural products. Drying processes range from open sun drying to industrial drying. In most of the developing countries, use of fossil fuels for drying of agricultural products has not been practically feasible due to unaffordable costs to majority of the farmers. On the other hand, traditional open sun drying practiced on a large scale in the rural areas of the developing countries suffers from high product losses due to inadequate drying, fungal growth, encroachment of insects, birds and rodents, etc. To overcome these problems a middle technology dryer having low cost need to be developed for farmers. In case of mechanical dryers, the heated air is the main driving force for removal of moisture. The air is heated either electrically or by burning wood, coal, natural gas etc. using heaters. But, all these common sources have finite supplies. The lifetime is estimated to range from 15 years for a natural gas to nearly 250 years for coal. So, mankind must turn towards its safe and reliable utilization and may have undesirable side effects. The mechanical drying involves higher cost of drying and open sun drying deteriorates the quality. The solar tunnel dryer is one of promising option for drying various agricultural and agro-industrial products on large scale. The advantage of Solar tunnel dryer is its relatively cheaper cost of construction and operation. Although many solar dryers have been developed, still there is a scope of modification in them. Therefore, an attempt was made to develop Solar tunnel dryer and test its performance using highly perishable commodity i.e. leafy vegetables (spinach). The effect of air velocity, loading density and shade net on performance parameters namely, collector efficiency, drying efficiency, overall efficiency of dryer and specific heat energy consumption were also studied. Thus, the need for an intermediate level technology was realized and an effort was made to develop a small scale Solar Tunnel Dryer . A dryer consisted of base frame, semi cylindrical drying chamber, solar collector and absorber, air distribution system with chimney and auxiliary heating system, and wheels for its mobility were the main functional components. Drying of fenugreek was carried out to analyze the performance of the dryer. The Solar Tunnel Dryer temperature was maintained using the auxiliary heating system. The ambient temperature was in the range of 12-33oC. The relative humidity was found inside and outside the Solar Tunnel Dryer in the range of 21-75% and 35-79%, respectively. The solar radiation was recorded in the range of 350-780W/m2 during the experimental period. Studies revealed that total drying time was in range of 230 to 420 min. The drying time in Solar Tunnel Dryer was considerably reduced by 67% as compared to sun drying. The collector efficiency, drying efficiency, overall efficiency and specific heat consumption were determined and were found to be in the range of 50.06- 38.71%, 15.53-24.72%, 4.25 to 13.34% and 1897.54-3241.36 kJ/kg, respectively.

Keywords: overall efficiency, solar tunnel dryer, specific heat consumption, sun drying

Procedia PDF Downloads 313
525 A Five-Year Experience of Intensity Modulated Radiotherapy in Nasopharyngeal Carcinomas in Tunisia

Authors: Omar Nouri, Wafa Mnejja, Fatma Dhouib, Syrine Zouari, Wicem Siala, Ilhem Charfeddine, Afef Khanfir, Leila Farhat, Nejla Fourati, Jamel Daoud

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Purpose and Objective: Intensity modulated radiation (IMRT) technique, associated with induction chemotherapy (IC) and/or concomitant chemotherapy (CC), is actually the recommended treatment modality for nasopharyngeal carcinomas (NPC). The aim of this study was to evaluate the therapeutic results and the patterns of relapse with this treatment protocol. Material and methods: A retrospective monocentric study of 145 patients with NPC treated between June 2016 and July 2021. All patients received IMRT with integrated simultaneous boost (SIB) of 33 daily fractions at a dose of 69.96 Gy for high-risk volume, 60 Gy for intermediate risk volume and 54 Gy for low-risk volume. The high-risk volume dose was 66.5 Gy in children. Survival analysis was performed according to the Kaplan-Meier method, and the Log-rank test was used to compare factors that may influence survival. Results: Median age was 48 years (11-80) with a sex ratio of 2.9. One hundred-twenty tumors (82.7%) were classified as stages III-IV according to the 2017 UICC TNM classification. Ten patients (6.9%) were metastatic at diagnosis. One hundred-thirty-five patient (93.1%) received IC, 104 of which (77%) were TPF-based (taxanes, cisplatin and 5 fluoro-uracil). One hundred-thirty-eight patient (95.2%) received CC, mostly cisplatin in 134 cases (97%). After a median follow-up of 50 months [22-82], 46 patients (31.7%) had a relapse: 12 (8.2%) experienced local and/or regional relapse after a median of 18 months [6-43], 29 (20%) experienced distant relapse after a median of 9 months [2-24] and 5 patients (3.4%) had both. Thirty-five patients (24.1%) died, including 5 (3.4%) from a cause other than their cancer. Three-year overall survival (OS), cancer specific survival, disease free survival, metastasis free survival and loco-regional free survival were respectively 78.1%, 81.3%, 67.8%, 74.5% and 88.1%. Anatomo-clinic factors predicting OS were age > 50 years (88.7 vs. 70.5%; p=0.004), diabetes history (81.2 vs. 66.7%; p=0.027), UICC N classification (100 vs. 95 vs. 77.5 vs. 68.8% respectively for N0, N1, N2 and N3; p=0.008), the practice of a lymph node biopsy (84.2 vs. 57%; p=0.05), and UICC TNM stages III-IV (93.8 vs. 73.6% respectively for stage I-II vs. III-IV; p=0.044). Therapeutic factors predicting OS were a number of CC courses (less than 4 courses: 65.8 vs. 86%; p=0.03, less than 5 courses: 71.5 vs. 89%; p=0.041), a weight loss > 10% during treatment (84.1 vs. 60.9%; p=0.021) and a total cumulative cisplatin dose, including IC and CC, < 380 mg/m² (64.4 vs. 87.6%; p=0.003). Radiotherapy delay and total duration did not significantly affect OS. No grade 3-4 late side effects were noted in the evaluable 127 patients (87.6%). The most common toxicity was dry mouth which was grade 2 in 47 cases (37%) and grade 1 in 55 cases (43.3%).Conclusion: IMRT for nasopharyngeal carcinoma granted a high loco-regional control rate for patients during the last five years. However, distant relapses remain frequent and conditionate the prognosis. We identified many anatomo-clinic and therapeutic prognosis factors. Therefore, high-risk patients require a more aggressive therapeutic approach, such as radiotherapy dose escalation or adding adjuvant chemotherapy.

Keywords: therapeutic results, prognostic factors, intensity-modulated radiotherapy, nasopharyngeal carcinoma

Procedia PDF Downloads 64
524 Movable Airfoil Arm (MAA) and Ducting Effect to Increase the Efficiency of a Helical Turbine

Authors: Abdi Ismail, Zain Amarta, Riza Rifaldy Argaputra

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The Helical Turbine has the highest efficiency in comparison with the other hydrokinetic turbines. However, the potential of the Helical Turbine efficiency can be further improved so that the kinetic energy of a water current can be converted into mechanical energy as much as possible. This paper explains the effects by adding a Movable Airfoil Arm (MAA) and ducting on a Helical Turbine. The first research conducted an analysis of the efficiency comparison between a Plate Arm Helical Turbine (PAHT) versus a Movable Arm Helical Turbine Airfoil (MAAHT) at various water current velocities. The first step is manufacturing a PAHT and MAAHT. The PAHT and MAAHT has these specifications (as a fixed variable): 80 cm in diameter, a height of 88 cm, 3 blades, NACA 0018 blade profile, a 10 cm blade chord and a 60o inclination angle. The MAAHT uses a NACA 0012 airfoil arm that can move downward 20o, the PAHT uses a 5 mm plate arm. At the current velocity of 0.8, 0.85 and 0.9 m/s, the PAHT respectively generates a mechanical power of 92, 117 and 91 watts (a consecutive efficiency of 16%, 17% and 11%). At the same current velocity variation, the MAAHT respectively generates 74, 60 and 43 watts (a consecutive efficiency of 13%, 9% and 5%). Therefore, PAHT has a better performance than the MAAHT. Using analysis from CFD (Computational Fluid Dynamics), the drag force of MAA is greater than the one generated by the plate arm. By using CFD analysis, the drag force that occurs on the MAA is more dominant than the lift force, therefore the MAA can be called a drag device, whereas the lift force that occurs on the helical blade is more dominant than the drag force, therefore it can be called a lift device. Thus, the lift device cannot be combined with the drag device, because the drag device will become a hindrance to the lift device rotation. The second research conducted an analysis of the efficiency comparison between a Ducted Helical Turbine (DHT) versus a Helical Turbine (HT) through experimental studies. The first step is manufacturing the DHT and HT. The Helical turbine specifications (as a fixed variable) are: 40 cm in diameter, a height of 88 cm, 3 blades, NACA 0018 blade profile, 10 cm blade chord and a 60o inclination angle. At the current speed of 0.7, 0.8, 0.9 and 1.1 m/s, the HT respectively generates a mechanical power of 72, 85, 93 and 98 watts (a consecutive efficiency of 38%, 30%, 23% and 13%). At the same current speed variation, the DHT generates a mechanical power of 82, 98, 110 and 134 watts (a consecutive efficiency of 43%, 34%, 27% and 18%), respectively. The usage of ducting causes the water current speed around the turbine to increase.

Keywords: hydrokinetic turbine, helical turbine, movable airfoil arm, ducting

Procedia PDF Downloads 371
523 Climate Change Impact on Water Resources Management in Remote Islands Using Hybrid Renewable Energy Systems

Authors: Elissavet Feloni, Ioannis Kourtis, Konstantinos Kotsifakis, Evangelos Baltas

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Water inadequacy in small dry islands scattered in the Aegean Sea (Greece) is a major problem regarding Water Resources Management (WRM), especially during the summer period due to tourism. In the present work, various WRM schemes are designed and presented. The WRM schemes take into account current infrastructure and include Rainwater Harvesting tanks and Reverse Osmosis Desalination Units. The energy requirements are covered mainly by wind turbines and/or a seawater pumped storage system. Sizing is based on the available data for population and tourism per island, after taking into account a slight increase in the population (up to 1.5% per year), and it guarantees at least 80% reliability for the energy supply and 99.9% for potable water. Evaluation of scenarios is carried out from a financial perspective, after calculating the Life Cycle Cost (LCC) of each investment for a lifespan of 30 years. The wind-powered desalination plant was found to be the most cost-effective practice, from an economic point of view. Finally, in order to estimate the Climate Change (CC) impact, six different CC scenarios were investigated. The corresponding rate of on-grid versus off-grid energy required for ensuring the targeted reliability for the zero and each climatic scenario was investigated per island. The results revealed that under CC the grid-on energy required would increase and as a result, the reduction in wind turbines and seawater pumped storage systems’ reliability will be in the range of 4 to 44%. However, the range of this percentage change does not exceed 22% per island for all examined CC scenarios. Overall, CC is proposed to be incorporated into the design process for WRM-related projects. Acknowledgements: This research is co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Development of a combined rain harvesting and renewable energy-based system for covering domestic and agricultural water requirements in small dry Greek Islands” (MIS 5004775).

Keywords: small dry islands, water resources management, climate change, desalination, RES, seawater pumped storage system, rainwater harvesting

Procedia PDF Downloads 116
522 Multiperson Drone Control with Seamless Pilot Switching Using Onboard Camera and Openpose Real-Time Keypoint Detection

Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

Procedia PDF Downloads 184
521 Heat Transfer and Trajectory Models for a Cloud of Spray over a Marine Vessel

Authors: S. R. Dehghani, G. F. Naterer, Y. S. Muzychka

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Wave-impact sea spray creates many droplets which form a spray cloud traveling over marine objects same as marine vessels and offshore structures. In cold climates such as Arctic reigns, sea spray icing, which is ice accretion on cold substrates, is strongly dependent on the wave-impact sea spray. The rate of cooling of droplets affects the process of icing that can yield to dry or wet ice accretion. Trajectories of droplets determine the potential places for ice accretion. Combining two models of trajectories and heat transfer for droplets can predict the risk of ice accretion reasonably. The majority of the cooling of droplets is because of droplet evaporations. In this study, a combined model using trajectory and heat transfer evaluate the situation of a cloud of spray from the generation to impingement. The model uses some known geometry and initial information from the previous case studies. The 3D model is solved numerically using a standard numerical scheme. Droplets are generated in various size ranges from 7 mm to 0.07 mm which is a suggested range for sea spray icing. The initial temperature of droplets is considered to be the sea water temperature. Wind velocities are assumed same as that of the field observations. Evaluations are conducted using some important heading angles and wind velocities. The characteristic of size-velocity dependence is used to establish a relation between initial sizes and velocities of droplets. Time intervals are chosen properly to maintain a stable and fast numerical solution. A statistical process is conducted to evaluate the probability of expected occurrences. The medium size droplets can reach the highest heights. Very small and very large droplets are limited to lower heights. Results show that higher initial velocities create the most expanded cloud of spray. Wind velocities affect the extent of the spray cloud. The rate of droplet cooling at the start of spray formation is higher than the rest of the process. This is because of higher relative velocities and also higher temperature differences. The amount of water delivery and overall temperature for some sample surfaces over a marine vessel are calculated. Comparing results and some field observations show that the model works accurately. This model is suggested as a primary model for ice accretion on marine vessels.

Keywords: evaporation, sea spray, marine icing, numerical solution, trajectory

Procedia PDF Downloads 220
520 Causal Inference Engine between Continuous Emission Monitoring System Combined with Air Pollution Forecast Modeling

Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

Procedia PDF Downloads 86
519 Mesocarbon Microbeads Modification of Stainless-Steel Current Collector to Stabilize Lithium Deposition and Improve the Electrochemical Performance of Anode Solid-State Lithium Hybrid Battery

Authors: Abebe Taye

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The interest in enhancing the performance of all-solid-state batteries featuring lithium metal anodes as a potential alternative to traditional lithium-ion batteries has prompted exploration into new avenues. A promising strategy involves transforming lithium-ion batteries into hybrid configurations by integrating lithium-ion and lithium-metal solid-state components. This study is focused on achieving stable lithium deposition and advancing the electrochemical capabilities of solid-state lithium hybrid batteries with anodes by incorporating mesocarbon microbeads (MCMBs) blended with silver nanoparticles. To achieve this, mesocarbon microbeads (MCMBs) blended with silver nanoparticles are coated on stainless-steel current collectors. These samples undergo a battery of analyses employing diverse techniques. Surface morphology is studied through scanning electron microscopy (SEM). The electrochemical behavior of the coated samples is evaluated in both half-cell and full-cell setups utilizing an argyrodite-type sulfide electrolyte. The stability of MCMBs in the electrolyte is assessed using electrochemical impedance spectroscopy (EIS). Additional insights into the composition are gleaned through X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and energy-dispersive X-ray spectroscopy (EDS). At an ultra-low N/P ratio of 0.26, stability is upheld for over 100 charge/discharge cycles in half-cells. When applied in a full-cell configuration, the hybrid anode preserves 60.1% of its capacity after 80 cycles at 0.3 C under a low N/P ratio of 0.45. In sharp contrast, the capacity retention of the cell using untreated MCMBs declines to 20.2% after a mere 60 cycles. The introduction of mesocarbon microbeads (MCMBs) combined with silver nanoparticles into the hybrid anode of solid-state lithium batteries substantially elevates their stability and electrochemical performance. This approach ensures consistent lithium deposition and removal, mitigating dendrite growth and the accumulation of inactive lithium. The findings from this investigation hold significant value in elevating the reversibility and energy density of lithium-ion batteries, thereby making noteworthy contributions to the advancement of more efficient energy storage systems.

Keywords: MCMB, lithium metal, hybrid anode, silver nanoparticle, cycling stability

Procedia PDF Downloads 75
518 Computationally Efficient Electrochemical-Thermal Li-Ion Cell Model for Battery Management System

Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

Procedia PDF Downloads 111
517 Population Diversity of Dalmatian Pyrethrum Based on Pyrethrin Content and Composition

Authors: Filip Varga, Nina Jeran, Martina Biosic, Zlatko Satovic, Martina Grdisa

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Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.), a species endemic to the eastern Adriatic coastline, is the source of natural insecticide pyrethrin. Pyrethrin is a mixture of six compounds (pyrethrin I and II, cinerin I and II, jasmolin I and II) that exhibits high insecticidal activity with no detrimental effects to the environment. A recently optimized matrix-solid phase dispersion method (MSPD), using florisil as the sorbent, acetone-ethyl acetate (1:1, v/v) as the elution solvent, and sodium sulfate anhydrous as the drying agent was utilized to extract the pyrethrins from 10 wild populations (20 individuals per population) distributed along the Croatian coast. All six components in the extracts were qualitatively and quantitatively determined by high-performance liquid chromatography with a diode array detector (HPLC-DAD). Pearson’s correlation index was calculated between pyrethrin compounds, and differences between the populations using the analysis of variance were tested. Additionally, the correlation of each pyrethrin component with spatio-ecological variables (bioclimate, soil properties, elevation, solar radiation, and distance from the coastline) was calculated. Total pyrethrin content ranged from 0.10% to 1.35% of dry flower weight, averaging 0.58% across all individuals. Analysis of variance revealed significant differences between populations based on all six pyrethrin compounds and total pyrethrin content. On average, the lowest total pyrethrin content was found in the population from Pelješac peninsula (0.22% of dry flower weight) in which total pyrethrin content lower than 0.18% was detected in 55% of the individuals. The highest average total pyrethrin content was observed in the population from island Zlarin (0.87% of dry flower weight), in which total pyrethrin content higher than 1.00% was recorded in only 30% of the individuals. Pyrethrin I/pyrethrin II ratio as a measure of extract quality ranged from 0.21 (population from the island Čiovo) to 5.88 (population from island Mali Lošinj) with an average of 1.77 across all individuals. By far, the lowest quality of extracts was found in the population from Mt. Biokovo (pyrethrin I/II ratio lower than 0.72 in 40% of individuals) due to the high pyrethrin II content typical for this population. Pearson’s correlation index revealed a highly significant positive correlation between pyrethrin I content and total pyrethrin content and a strong negative correlation between pyrethrin I and pyrethrin II. The results of this research clearly indicate high intra- and interpopulation diversity of Dalmatian pyrethrum with regards to pyrethrin content and composition. The information obtained has potential use in plant genetic resources conservation and biodiversity monitoring. Possibly the largest potential lies in designing breeding programs aimed at increasing pyrethrin content in commercial breeding lines and reintroduction in agriculture in Croatia. Acknowledgment: This work has been fully supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir/ Sch. Bip.) insecticidal potential’ - (PyrDiv) (IP-06-2016-9034).

Keywords: Dalmatian pyrethrum, HPLC, MSPD, pyrethrin

Procedia PDF Downloads 142
516 The Use of Optical-Radar Remotely-Sensed Data for Characterizing Geomorphic, Structural and Hydrologic Features and Modeling Groundwater Prospective Zones in Arid Zones

Authors: Mohamed Abdelkareem

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Remote sensing data contributed on predicting the prospective areas of water resources. Integration of microwave and multispectral data along with climatic, hydrologic, and geological data has been used here. In this article, Sentinel-2, Landsat-8 Operational Land Imager (OLI), Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Advanced Land Observing Satellite (ALOS) Phased Array Type L‐band Synthetic Aperture Radar (PALSAR) data were utilized to identify the geological, hydrologic and structural features of Wadi Asyuti which represents a defunct tributary of the Nile basin, in the eastern Sahara. The image transformation of Sentinel-2 and Landsat-8 data allowed characterizing the different varieties of rock units. Integration of microwave remotely-sensed data and GIS techniques provided information on physical characteristics of catchments and rainfall zones that are of a crucial role for mapping groundwater prospective zones. A fused Landsat-8 OLI and ALOS/PALSAR data improved the structural elements that difficult to reveal using optical data. Lineament extraction and interpretation indicated that the area is clearly shaped by the NE-SW graben that is cut by NW-SE trend. Such structures allowed the accumulation of thick sediments in the downstream area. Processing of recent OLI data acquired on March 15, 2014, verified the flood potential maps and offered the opportunity to extract the extent of the flooding zone of the recent flash flood event (March 9, 2014), as well as revealed infiltration characteristics. Several layers including geology, slope, topography, drainage density, lineament density, soil characteristics, rainfall, and morphometric characteristics were combined after assigning a weight for each using a GIS-based knowledge-driven approach. The results revealed that the predicted groundwater potential zones (GPZs) can be arranged into six distinctive groups, depending on their probability for groundwater, namely very low, low, moderate, high very, high, and excellent. Field and well data validated the delineated zones.

Keywords: GIS, remote sensing, groundwater, Egypt

Procedia PDF Downloads 98
515 Development of mHealth Information in Community Based on Geographical Information: A Case Study from Saraphi District, Chiang Mai, Thailand

Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

Procedia PDF Downloads 336
514 Double Burden of Malnutrition among Children under Five in Sub-Saharan Africa and Other Least Developed Countries: A Systematic Review

Authors: Getenet Dessie, Jinhu Li, Son Nghiem, Tinh Doan

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Background: Concerns regarding malnutrition have evolved from focusing solely on single forms to addressing the simultaneous occurrence of multiple types, commonly referred to as the double or triple burden of malnutrition. Nevertheless, data concerning the concurrent occurrence of various types of malnutrition are scarce. Therefore, this systematic review and meta-analysis aims to assess the pooled prevalence of the double burden of malnutrition among children under five in Sub-Saharan Africa and other least-developed countries (LDCs). Methods: Electronic, web-based searches were conducted from January 15 to June 28, 2023, across several databases, including PubMed, Embase, Google Scholar, and the World Health Organization's Hinari portal, as well as other search engines, to identify primary studies published up to June 28, 2023. Laboratory-based cross-sectional studies on children under the age of five were included. Two independent authors assessed the risk of bias and the quality of the identified articles. The primary outcomes of this study were micronutrient deficiencies and the comorbidity of stunting and anemia, as well as wasting and anemia. The random-effects model was utilized for analysis. The association of identified variables with the various forms of malnutrition was also assessed using adjusted odds ratios (AOR) with a 95% confidence interval (CI). This review was registered in PROSPERO with the reference number CRD42023409483. Findings: The electronic search generated 6,087 articles, 93 of which matched the inclusion criteria for the final meta-analysis. Micronutrient deficiencies were prevalent among children under five in Sub-Saharan Africa and other LDCs, with rates ranging from 16.63% among 25,169 participants for vitamin A deficiency to 50.90% among 3,936 participants for iodine deficiency. Iron deficiency anemia affected 20.56% of the 63,121 participants. The combined prevalence of wasting anemia and stunting anemia was 5.41% among 64,709 participants and 19.98% among 66,016 participants, respectively. Both stunting and vitamin A supplementation were associated with vitamin A and iron deficiencies, with adjusted odds ratios (AOR) of 1.54 (95% CI: 1.01, 2.37) and 1.37 (95% CI: 1.21, 1.55), respectively. Interpretation: The prevalence of the double burden of malnutrition among children under the age of five was notably high in Sub-Saharan Africa and other LDCs. These findings indicate a need for increased attention and a focus on understanding the factors influencing this double burden of malnutrition.

Keywords: children, Sub-Saharan Africa, least developed countries, double burden of malnutrition, systematic review, meta-analysis

Procedia PDF Downloads 81
513 Cognitive Translation and Conceptual Wine Tasting Metaphors: A Corpus-Based Research

Authors: Christine Demaecker

Abstract:

Many researchers have underlined the importance of metaphors in specialised language. Their use of specific domains helps us understand the conceptualisations used to communicate new ideas or difficult topics. Within the wide area of specialised discourse, wine tasting is a very specific example because it is almost exclusively metaphoric. Wine tasting metaphors express various conceptualisations. They are not linguistic but rather conceptual, as defined by Lakoff & Johnson. They correspond to the linguistic expression of a mental projection from a well-known or more concrete source domain onto the target domain, which is the taste of wine. But unlike most specialised terminologies, the vocabulary is never clearly defined. When metaphorical terms are listed in dictionaries, their definitions remain vague, unclear, and circular. They cannot be replaced by literal linguistic expressions. This makes it impossible to transfer them into another language with the traditional linguistic translation methods. Qualitative research investigates whether wine tasting metaphors could rather be translated with the cognitive translation process, as well described by Nili Mandelblit (1995). The research is based on a corpus compiled from two high-profile wine guides; the Parker’s Wine Buyer’s Guide and its translation into French and the Guide Hachette des Vins and its translation into English. In this small corpus with a total of 68,826 words, 170 metaphoric expressions have been identified in the original English text and 180 in the original French text. They have been selected with the MIPVU Metaphor Identification Procedure developed at the Vrije Universiteit Amsterdam. The selection demonstrates that both languages use the same set of conceptualisations, which are often combined in wine tasting notes, creating conceptual integrations or blends. The comparison of expressions in the source and target texts also demonstrates the use of the cognitive translation approach. In accordance with the principle of relevance, the translation always uses target language conceptualisations, but compared to the original, the highlighting of the projection is often different. Also, when original metaphors are complex with a combination of conceptualisations, at least one element of the original metaphor underlies the target expression. This approach perfectly integrates into Lederer’s interpretative model of translation (2006). In this triangular model, the transfer of conceptualisation could be included at the level of ‘deverbalisation/reverbalisation’, the crucial stage of the model, where the extraction of meaning combines with the encyclopedic background to generate the target text.

Keywords: cognitive translation, conceptual integration, conceptual metaphor, interpretative model of translation, wine tasting metaphor

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512 The Role of Learning in Stimulation Policies to Increase Participation in Lifelong Development: A Government Policy Analysis

Authors: Björn de Kruijf, Arjen Edzes, Sietske Waslander

Abstract:

In an ever-quickly changing society, lifelong development is seen as a solution to labor market problems by politicians and policymakers. In this paper, we investigate how policy instruments are used to increase participation in lifelong development and on which behavioral principles policy is based. Digitization, automation, and an aging population change society and the labor market accordingly. Skills that were once most sought after in the workforce can become abundantly present. For people to remain relevant in the working population, they need to continue adapting new skills useful in the current labor market. Many reports have been written that focus on the role of lifelong development in this changing society and how lifelong development can help keep people adapt and stay relevant. Inspired by these reports, governments have implemented a broad range of policies to support participation in lifelong development. The question we ask ourselves is how government policies promote participation in lifelong development. This stems from a complex interplay of policy instruments and learning. Regulation, economic and soft instruments can be combined to promote lifelong development, and different types of education further complex policies on lifelong development. Literature suggests that different stages in people’s lives might warrant different methods of learning. Governments could anticipate this in their policies. In order to influence people’s behavior, the government can tap into a broad range of sociological, psychological, and (behavioral) economic principles. The traditional economic assumption that behavior is rational is known to be only partially true, and the government can use many biases in human behavior to stimulate participation in lifelong development. In this paper, we also try to find which biases the government taps into to promote participation if they tap into any of these biases. The goal of this paper is to analyze government policies intended to promote participation in lifelong development. To do this, we develop a framework to analyze the policies on lifelong development. We specifically incorporate the role of learning and the behavioral principles underlying policy instruments in the framework. We apply this framework to the case of the Netherlands, where we examine a set of policy documents. We single out the policies the government has put in place and how they are vertically and horizontally related. Afterward, we apply the framework and classify the individual policies by policy instrument and by type of learning. We find that the Dutch government focuses on formal and non-formal learning in their policy instruments. However, the literature suggests that learning at a later age is mainly done in an informal manner through experiences.

Keywords: learning, lifelong development, policy analysis, policy instruments

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511 Differential Proteomics Expression in Purple Rice Supplemented Type 2 Diabetic Rats’ Skeletal Muscle

Authors: Ei Ei Hlaing, Narissara Lailerd, Sittiruk Roytrakul, Pichapat Piamrojanaphat

Abstract:

Type 2 diabetes is one of the most common metabolic diseases all over the world. The pathogenesis of type 2 diabetes is not the only dysfunction of pancreatic beta cells but also insulin resistance in muscle, liver and adipose tissue. High levels of circulating free fatty acids, an increased lipid content of muscle cells, impaired insulin-mediated glucose uptake and diminished mitochondrial functioning are pathophysiological hallmarks of diabetic skeletal muscles. Purple rice (Oryza sativa L. indica) has been shown to have antidiabetic effects. However, the underlying mechanism(s) of antidiabetic activity of purple rice is still unraveled. In this research, to explore in-depth cellular mechanism(s), proteomic profile of purple rice supplemented type 2 diabetic rats’ skeletal muscle were analyzed contract with non-supplemented rats. Diabetic rats were induced high-fat diet combined with streptozotocin injection. By using one- dimensional gel electrophoresis (1-DE) and LC-MS/MS quantitative proteomic method, we analyzed proteomic profiles in skeletal muscle of normal rats, normal rats with purple rice supplementation, type 2 diabetic rats, and type 2 diabetic rats with purple rice supplementation. Total 2676 polypeptide expressions were identified. Among them, 24 peptides were only expressed in type 2 diabetic rats, and 24 peptides were unique peptides in type 2 diabetic rats with purple rice supplementation. Acetyl CoA carboxylase 1 (ACACA) found as unique protein in type 2 diabetic rats which is the major enzyme in lipid synthesis and metabolism. Interestingly, DNA damage response protein, heterogeneous nuclear ribonucleoprotein K [Mus musculus] (Hnrnpk), was upregulated in type 2 diabetic rats’ skeletal muscle. Meanwhile, unique proteins of type 2 diabetic rats with purple rice supplementation (bone morphogenetic 7 protein preproprotein, BMP7; and forkhead box protein NX4, Foxn4) involved with muscle cells growth through the regulation of TGF-β/Smad signaling network. Moreover, BMP7 may effect on insulin signaling through the downstream signaling of protein kinase B (Akt) which acts in protein synthesis, glucose uptake, and glycogen synthesis. In conclusion, our study supports that type 2 diabetes impairs muscular lipid metabolism. In addition, purple rice might recover the muscle cells growth and insulin signaling.

Keywords: proteomics, purple rice bran, skeletal muscle, type 2 diabetic rats

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510 CFD Modeling of Stripper Ash Cooler of Circulating Fluidized Bed

Authors: Ravi Inder Singh

Abstract:

Due to high heat transfer rate, high carbon utilizing efficiency, fuel flexibilities and other advantages numerous circulating fluidized bed boilers have grown up in India in last decade. Many companies like BHEL, ISGEC, Thermax, Cethar Limited, Enmas GB Power Systems Projects Limited are making CFBC and installing the units throughout the India. Due to complexity many problems exists in CFBC units and only few have been reported. Agglomeration i.e clinker formation in riser, loop seal leg and stripper ash coolers is one of problem industry is facing. Proper documentation is rarely found in the literature. Circulating fluidized bed (CFB) boiler bottom ash contains large amounts of physical heat. While the boiler combusts the low-calorie fuel, the ash content is normally more than 40% and the physical heat loss is approximately 3% if the bottom ash is discharged without cooling. In addition, the red-hot bottom ash is bad for mechanized handling and transportation, as the upper limit temperature of the ash handling machinery is 200 °C. Therefore, a bottom ash cooler (BAC) is often used to treat the high temperature bottom ash to reclaim heat, and to have the ash easily handled and transported. As a key auxiliary device of CFB boilers, the BAC has a direct influence on the secure and economic operation of the boiler. There are many kinds of BACs equipped for large-scale CFB boilers with the continuous development and improvement of the CFB boiler. These ash coolers are water cooled ash cooling screw, rolling-cylinder ash cooler (RAC), fluidized bed ash cooler (FBAC).In this study prototype of a novel stripper ash cooler is studied. The Circulating Fluidized bed Ash Coolers (CFBAC) combined the major technical features of spouted bed and bubbling bed, and could achieve the selective discharge on the bottom ash. The novel stripper ash cooler is bubbling bed and it is visible cold test rig. The reason for choosing cold test is that high temperature is difficult to maintain and create in laboratory level. The aim of study to know the flow pattern inside the stripper ash cooler. The cold rig prototype is similar to stripper ash cooler used industry and it was made after scaling down to some parameter. The performance of a fluidized bed ash cooler is studied using a cold experiment bench. The air flow rate, particle size of the solids and air distributor type are considered to be the key parameters of the operation of a fluidized bed ash cooler (FBAC) are studied in this.

Keywords: CFD, Eulerian-Eulerian, Eulerian-Lagraingian model, parallel simulations

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