Search results for: models synthesis

Authors: Diteboho Xaba, Kolentino Mpeta, Tlotliso Qejoe

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This paper assesses the in-sample forecasting of the South African exchange rates comparing a linear ARIMA model and a SETAR model. The study uses a monthly adjusted data of South African exchange rates with 420 observations. Akaike information criterion (AIC) and the Schwarz information criteria (SIC) are used for model selection. Mean absolute error (MAE), root mean squared error (RMSE) and mean absolute percentage error (MAPE) are error metrics used to evaluate forecast capability of the models. The Diebold –Mariano (DM) test is employed in the study to check forecast accuracy in order to distinguish the forecasting performance between the two models (ARIMA and SETAR). The results indicate that both models perform well when modelling and forecasting the exchange rates, but SETAR seemed to outperform ARIMA.

Keywords: ARIMA, error metrices, model selection, SETAR

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Authors: H. Taylan Selamlar, I. Yavuz, G. Yapar

Abstract:

It is difficult to make predictions especially about the future and making accurate predictions is not always easy. However, better predictions remain the foundation of all science therefore the development of accurate, robust and reliable forecasting methods is very important. Numerous number of forecasting methods have been proposed and studied in the literature. There are still two dominant major forecasting methods: Box-Jenkins ARIMA and Exponential Smoothing (ES), and still new methods are derived or inspired from them. After more than 50 years of widespread use, exponential smoothing is still one of the most practically relevant forecasting methods available due to their simplicity, robustness and accuracy as automatic forecasting procedures especially in the famous M-Competitions. Despite its success and widespread use in many areas, ES models have some shortcomings that negatively affect the accuracy of forecasts. Therefore, a new forecasting method in this study will be proposed to cope with these shortcomings and it will be called ATA method. This new method is obtained from traditional ES models by modifying the smoothing parameters therefore both methods have similar structural forms and ATA can be easily adapted to all of the individual ES models however ATA has many advantages due to its innovative new weighting scheme. In this paper, the focus is on modeling the trend component and handling seasonality patterns by utilizing classical decomposition. Therefore, ATA method is expanded to higher order ES methods for additive, multiplicative, additive damped and multiplicative damped trend components. The proposed models are called ATA trended models and their predictive performances are compared to their counter ES models on the M3 competition data set since it is still the most recent and comprehensive time-series data collection available. It is shown that the models outperform their counters on almost all settings and when a model selection is carried out amongst these trended models ATA outperforms all of the competitors in the M3- competition for both short term and long term forecasting horizons when the models’ forecasting accuracies are compared based on popular error metrics.

Keywords: accuracy, exponential smoothing, forecasting, initial value

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Authors: Sidique Fofanah

Abstract:

This paper explores the intersection of traditional communication theories and modern digital technologies, analyzing how established models adapt to contemporary communication platforms. It examines the evolving nature of interpersonal, group, and mass communication within digital environments, emphasizing the role of social media, AI-driven communication tools, and virtual reality in reshaping communication paradigms. The paper also discusses the implications for future research and practice in communication studies, proposing an integrated framework that accommodates both classical and emerging theories.

Keywords: communication, traditional models, emerging platforms, digital media

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

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Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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Authors: Zahid Ahmad, Nosheen Imran, Nauman Ali, Farah Amir

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The objective of the study is to forecast the US Dollar and Pak Rupee exchange rate by using time series models. For this purpose, daily exchange rates of US and Pakistan for the period of January 01, 2007 - June 2, 2017, are employed. The data set is divided into in sample and out of sample data set where in-sample data are used to estimate as well as forecast the models, whereas out-of-sample data set is exercised to forecast the exchange rate. The ADF test and PP test are used to make the time series stationary. To forecast the exchange rate ARIMA model and GARCH model are applied. Among the different Autoregressive Integrated Moving Average (ARIMA) models best model is selected on the basis of selection criteria. Due to the volatility clustering and ARCH effect the GARCH (1, 1) is also applied. Results of analysis showed that ARIMA (0, 1, 1 ) and GARCH (1, 1) are the most suitable models to forecast the future exchange rate. Further the GARCH (1,1) model provided the volatility with non-constant conditional variance in the exchange rate with good forecasting performance. This study is very useful for researchers, policymakers, and businesses for making decisions through accurate and timely forecasting of the exchange rate and helps them in devising their policies.

Keywords: exchange rate, ARIMA, GARCH, PAK/USD

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Authors: Cheng-Hao Jiang, Mu-Xuan Tao

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The rigid diaphragm model may cause errors in the calculation of internal forces due to neglecting the in-plane deformation of the diaphragm. This paper thus studies the effects of different diaphragm in-plane models (including in-plane rigid model and in-plane flexible model) on the seismic performance of structures. Taking an actual industrial plant as an example, the seismic performance of the structure is predicted using different floor diaphragm models, and the analysis errors caused by different diaphragm in-plane models including deformation error and internal force error are calculated. Furthermore, the influence of the aspect ratio on the analysis errors is investigated. Finally, the code rationality is evaluated by assessing the analysis errors of the structure models whose floors were determined as rigid according to the code’s criterion. It is found that different floor models may cause great differences in the distribution of structural internal forces, and the current code may underestimate the influence of the floor in-plane effect.

Keywords: industrial plant, diaphragm, calculating error, code rationality

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Authors: Yemane Tadesse Gebreslassie, Fisseha Guesh Gebremeskel

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Nanotechnology has made remarkable advancements in recent years, revolutionizing various scientific fields, industries, and research institutions through the utilization of metal and metal oxide nanoparticles. Among these nanoparticles, copper oxide nanoparticles (CuO NPs) have garnered significant attention due to their versatile properties and wide-range applications, particularly, as effective antimicrobial and anticancer agents. CuO NPs can be synthesized using different methods, including physical, chemical, and biological approaches. However, conventional chemical and physical approaches are expensive, resource-intensive, and involve the use of hazardous chemicals, which can pose risks to human health and the environment. In contrast, biological synthesis provides a sustainable and cost-effective alternative by eliminating chemical pollutants and allowing for the production of CuO NPs of tailored sizes and shapes. This comprehensive review focused on the green synthesis of CuO NPs using various biological resources, such as plants, microorganisms, and other biological derivatives. Current knowledge and recent trends in green synthesis methods for CuO NPs are discussed, with a specific emphasis on their biomedical applications, particularly in combating cancer and microbial infections. This review highlights the significant potential of CuO NPs in addressing these diseases. By capitalizing on the advantages of biological synthesis, such as environmental safety and the ability to customize nanoparticle characteristics, CuO NPs have emerged as promising therapeutic agents for a wide range of conditions. This review presents compelling findings, demonstrating the remarkable achievements of biologically synthesized CuO NPs as therapeutic agents. Their unique properties and mechanisms enable effective combating against cancer cells and various harmful microbial infections. CuO NPs exhibit potent anticancer activity through diverse mechanisms, including induction of apoptosis, inhibition of angiogenesis, and modulation of signaling pathways. Additionally, their antimicrobial activity manifests through various mechanisms, such as disrupting microbial membranes, generating reactive oxygen species, and interfering with microbial enzymes. This review offers valuable insights into the substantial potential of biologically synthesized CuO NPs as an alternative approach for future therapeutic interventions against cancer and microbial infections.

Keywords: copper oxide nanoparticles, green synthesis, nanotechnology, microbial infection

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Authors: Akintayo Emmanuel Temitope, Akintayo Cecilia Olufunke, Ziegler Thomas

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Bio-polyols are important components in polyurethane industries. The preliminary studies into the synthesis of bio-polyol products (epoxy-polyol and epoxyl-polyurethanes) from Jatropha curcas were investigated. The reactions were followed by both infrared and nuclear magnetic resonance. Physico-chemical characterisation of the samples for iodine value (IV), acid value (AV), saponification value (SV) and hydroxyl value (HV) were carried out. Thermal transitions of the products were studied by heating 5 mg of the sample from 20ºC to 800ºC and then cooling down to -500ºC on a differential scanning calorimeter (DSC). The preparation of epoxylpolyol and polyurethane from Jatropha curcas oil was smooth and efficient. Results of film and solubility properties revealed that coatings of Jatropha curcas epoxy-polyurethanes performed better with increased loading of toluylene 2, 4-diisocyanate (TDI) up to 2 wt% while their solvent resistance decreased beyond a TDI loading of 1.2 wt%. DSC analysis shows the epoxy-polyurethane to be less stable compared to the epoxy-polyol.

Keywords: synthesis, epoxy-polyol, epoxy-polyurethane, jatropha curcas oil

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Authors: Bowen Ding, Yihao Kuang

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In recent years, large-scale pre-trained language models have achieved state-of-the-art performance on a variety of natural language processing tasks. The word vectors produced by these language models can be viewed as dense encoded presentations of natural language that in text form. However, it is unknown how much linguistic information is encoded and how. In this paper, we construct several corresponding probing tasks for multiple linguistic information to clarify the encoding capabilities of different language models and performed a visual display. We firstly obtain word presentations in vector form from different language models, including BERT, ELMo, RoBERTa and GPT. Classifiers with a small scale of parameters and unsupervised tasks are then applied on these word vectors to discriminate their capability to encode corresponding linguistic information. The constructed probe tasks contain both semantic and syntactic aspects. The semantic aspect includes the ability of the model to understand semantic entities such as numbers, time, and characters, and the grammatical aspect includes the ability of the language model to understand grammatical structures such as dependency relationships and reference relationships. We also compare encoding capabilities of different layers in the same language model to infer how linguistic information is encoded in the model.

Keywords: language models, probing task, text presentation, linguistic information

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Authors: Idrissa Kayijuka

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The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

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The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

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Authors: Agnieszka Fryźlewicz, Jowita Kras, Mikołaj Sadowski, Agnieszka Łapczuk-Krygier, Agnieszka Kącka-Zych Radomir Jasiński

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Nicotines are a group of compounds containing conjugated pyridine and pyrrolidine molecular segments. They are widely applied in medicine, pharmacy, and agriculture. Namely as researched treatment of Alzheimer, depression, Parkinson's, Tourette syndrome, general nervous and mental disorders. Furthermore, nicotine itself is used as a stimulant, animal repellent and was widely applied as an insecticide. In our work, we obtained nicotine analogues with possible applications in agriculture. The synthesis employed [3+2] cycloaddition (32CA) reactions, occurring between pirydyl-functionalised nitrones and conjugated nitroalkenes, that allowed us to fully regio- and stereoselectively obtain product. Moreover, cycloaddition reaction realizes rapidly in mild conditions with the full atomic economy, thus fitting into “green chemistry” trends.

Keywords: nicotine, isoxazolidine, 1-3-dipolar cycloaddition, green chemistry, biological and pharmacological activity

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Authors: R. Sarada Jayalakshmi Devi B. Bhaskar, S. Khayum Ahammed, T. N. V. K. V. Prasad

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Use of bioagents and biofungicides is safe to manage the plant diseases and to avoid human health hazards which improves food security. Myconanotechnology is the study of nanoparticles synthesis using fungi and their applications. The present work reports on preparation, characterization and antifungal activity of biogenic silver nanoparticles produced by the fungus Trichoderma sp. which was collected from groundnut rhizosphere. The culture filtrate of Trichoderma sp. was used for the reduction of silver ions (Ag+) in AgNO3 solution to the silver (Ag0) nanoparticles. The different ages (4 days, 6 days, 8 days, 12 days, and 15 days) of culture filtrates were screened for the synthesis of silver nanoparticles. Synthesized silver nanoparticles were characterized using UV-Vis spectrophotometer, particle size and zeta potential analyzer, Fourier Transform Infrared Spectrophotometer (FTIR) and Transmission Electron Microscopy. Among all the treatments the silver nitrate solution treated with six days aged culture filtrate of Trichoderma sp. showed the UV absorption peak at 440 nm with maximum intensity (0.59) after 24 hrs incubation. The TEM micrographs showed the spherical shaped silver nanoparticles with an average size of 30 nm. The antifungal activity of silver nanoparticles against Aspergillus niger causing collar rot disease in groundnut and aspergillosis in humans showed the highest per cent inhibition at 100 ppm concentration (74.8%). The results points to the usage of these mycogenic AgNPs in agriculture to control plant diseases.

Keywords: groundnut rhizosphere, Trichoderma sp., silver nanoparticles synthesis, antifungal activity

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Authors: Kamran Jawed, Anu Jose Mattam, Zia Fatma, Saima Wajid, Malik Z. Abdin, Syed Shams Yazdani

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Worldwide demand of natural and sustainable fuels and chemicals have encouraged researchers to develop microbial platform for synthesis of short chain fatty acids as they are useful precursors to replace petroleum-based fuels and chemicals. In this study, we evaluated the role of fatty acid synthesis and β-oxidation cycle of Escherichia coli to produce butyric acid, a 4-carbon short chain fatty acid, with the help of three thioesterases, i.e., TesAT from Anaerococcus tetradius, TesBF from Bryantella formatexigens and TesBT from Bacteroides thetaiotaomicron. We found that E. coli strain transformed with gene for TesBT and grown in presence of 8 g/L glucose produced maximum butyric acid titer at 1.46 g/L, followed by that of TesBF at 0.85 g/L and TesAT at 0.12 g/L, indicating that these thioesterases were efficiently converting short chain fatty acyl-ACP intermediate of fatty acid synthesis pathway into the corresponding acid. The titer of butyric acid varied significantly depending upon the plasmid copy number and strain genotype. Deletion of genes for fatty acyl-CoA synthetase and acyl-CoA dehydrogenase, which are involved in initiating the fatty acid degradation cycle, and overexpression of FadR, which is a dual transcriptional regulator and exerts negative control over fatty acid degradation pathway, reduced up to 30% of butyric acid titer. This observation suggested that β-oxidation pathway is working synergistically with fatty acid synthesis pathway in production of butyric acid. Moreover, accelerating the fatty acid elongation cycle by overexpressing acetyl-CoA carboxyltransferase (Acc) and 3-hydroxy-acyl-ACP dehydratase (FabZ) or by deleting FabR, the transcription suppressor of elongation, did not improve the butyric acid titer, rather favored the long chain fatty acid production. Finally, a balance between cell growth and butyric acid production was achieved with the use of phosphorous limited growth medium and 14.3 g/L butyric acid, and 17.5 g/L total free fatty acids (FFAs) titer was achieved during fed-batch cultivation. We have engineered an E. coli strain which utilizes the intermediate of both fatty acid synthesis and degradation pathway, i.e. butyryl-ACP and -CoA, to produce butyric acid from glucose. The strategy used in this study resulted in highest reported titers of butyric acid and FFAs in engineered E. coli.

Keywords: butenoic acid, butyric acid, Escherichia coli, fed-batch fermentation, short chain fatty acids, thioesterase

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Authors: Susmita Panda, Arnab Banerjee, Ajinkya Baxy, Bappaditya Manna

Abstract:

The design of short to medium-span high-speed bridges in critical locations is an essential aspect of vehicle-bridge interaction. Due to dynamic interaction between moving load and bridge, mathematical models or finite element modeling computations become time-consuming. Thus, to reduce the computational effort, a universal approximator using an artificial neural network (ANN) has been used to evaluate the dynamic response of the bridge. The data set generation and training of surrogate models have been conducted over the results obtained from mathematical modeling. Further, the robustness of the surrogate model has been investigated, which showed an error percentage of less than 10% with conventional methods. Additionally, the dependency of the dynamic response of the bridge on various load and bridge parameters has been highlighted through a parametric study.

Keywords: artificial neural network, mode superposition method, moving load analysis, surrogate models

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Authors: Yemane Tadesse Gebreslassie, Fisseha Guesh Gebremeskel

Abstract:

Nanotechnology has made remarkable advancements in recent years, revolutionizing various scientific fields, industries, and research institutions through the utilization of metal and metal oxide nanoparticles. Among these nanoparticles, copper oxide nanoparticles (CuO NPs) have garnered significant attention due to their versatile properties and wide-range applications, particularly, as effective antimicrobial and anticancer agents. CuO NPs can be synthesized using different methods, including physical, chemical, and biological approaches. However, conventional chemical and physical approaches are expensive, resource-intensive, and involve the use of hazardous chemicals, which can pose risks to human health and the environment. In contrast, biological synthesis provides a sustainable and cost-effective alternative by eliminating chemical pollutants and allowing for the production of CuO NPs of tailored sizes and shapes. This comprehensive review focused on the green synthesis of CuO NPs using various biological resources, such as plants, microorganisms, and other biological derivatives. Current knowledge and recent trends in green synthesis methods for CuO NPs are discussed, with a specific emphasis on their biomedical applications, particularly in combating cancer and microbial infections. This review highlights the significant potential of CuO NPs in addressing these diseases. By capitalizing on the advantages of biological synthesis, such as environmental safety and the ability to customize nanoparticle characteristics, CuO NPs have emerged as promising therapeutic agents for a wide range of conditions. This review presents compelling findings, demonstrating the remarkable achievements of biologically synthesized CuO NPs as therapeutic agents. Their unique properties and mechanisms enable effective combating against cancer cells and various harmful microbial infections. CuO NPs exhibit potent anticancer activity through diverse mechanisms, including induction of apoptosis, inhibition of angiogenesis, and modulation of signaling pathways. Additionally, their antimicrobial activity manifests through various mechanisms, such as disrupting microbial membranes, generating reactive oxygen species, and interfering with microbial enzymes. This review offers valuable insights into the substantial potential of biologically synthesized CuO NPs as an alternative approach for future therapeutic interventions against cancer and microbial infections.

Keywords: biological synthesis, copper oxide nanoparticles, microbial infection, nanotechnology

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Authors: Animish Jain

Abstract:

This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

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Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

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The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models. These results are part of the CMST COST Action No. CM1306 "Understanding Movement and Mechanism in Molecular Machines".

Keywords: Antibacterial, benzimidazoles, chemometric, QSAR.

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Authors: H. Benaldjia, N. Habib, F. Djefaflia, A. Nait-Merzoug, A. Harat, J. El-Haskouri, O. Guellati

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Currently, the technology has attracted knowledge of energy storage sources similar to batteries, capacitors and super-capacitors because of its very different applications in many fields with major social and economic challenges. Moreover, hydroxides have attracted much attention as a promising and active material choice in large-scale applications such as molecular adsorption/storage and separation for the environment, ion exchange, nanotechnology, supercapacitor for energy storage and conversion, electro-biosensing, and catalysts, due to their unique properties which are strongly influenced by their composition, microstructure, and synthesis method. In this context, we report in this study the synthesis of hydroxide-based nanomaterials precisely based on Ni and Fe using a simple hydrothermal method with mono and bi precursors at optimized growth conditions (6h-120°C). The obtained products were characterized using different techniques, such as XRD, FTIR, FESEM and BET, as well as electrochemical measurements.

Keywords: energy storage, Supercapacitors, nanocomposites, nanohybride, electro-active materials.

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Authors: T. Bielewicz, S. Dogan, C. Klinke

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Two-dimensional, solution-processable semiconductor materials are interesting for low-cost electronic applications [1]. We demonstrate the synthesis of lead sulfide nanosheets and how their size, shape and height can be tuned by varying concentrations of pre-cursors, ligands and by varying the reaction temperature. Especially, the charge carrier confinement in the nanosheets’ height adjustable from 2 to 20 nm has a decisive impact on their electronic properties. This is demonstrated by their use as conduction channel in a field effect transistor [2]. Recently we also showed that especially thin nanosheets show a high carrier multiplication (CM) efficiency [3] which could make them, through the confinement induced band gap and high photoconductivity, very attractive for application in photovoltaic devices. We are already able to manufacture photovoltaic devices out of single nanosheets which show promising results.

Keywords: physical sciences, chemistry, materials, chemistry, colloids, physics, condensed-matter physics, semiconductors, two-dimensional materials

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Authors: Anna Piasek, Anna Szymkiewicz, Gabriela Wiktor, Jolanta Pulit-Prociak, Marcin Banach

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Carbon dots (CDs) have great potential for application in many fields of science. They are characterized by fluorescent properties that can be manipulated. The nanomaterial has many advantages in addition to its unique properties. CDs may be obtained easily, and they undergo surface functionalization in a simple way. In addition, there is a wide range of raw materials that can be used for their synthesis. An interesting possibility is the use of numerous waste materials of natural origin. In the research presented here, the synthesis of CDs was carried out according to the principles of Green chemistry. Beet molasses was used as a natural raw material. It has a high sugar content. This makes it an excellent high-carbon precursor for obtaining CDs. To increase the fluorescence effect, we modified the surface of CDs with silver (Ag-CDs) nanoparticles. The process of obtaining CQD was based on the hydrothermal method by applying microwave radiation. Silver nanoparticles were formed via the chemical reduction method. The synthesis plans were performed on the Design of the Experimental method (DoE). Variable process parameters such as concentration of beet molasses, temperature and concentration of nanosilver were used in these syntheses. They affected the obtained properties and particle parameters. The Ag-CDs were analyzed by UV-vis spectroscopy. The fluorescence properties and selection of the appropriate excitation light wavelength were performed by spectrofluorimetry. Particle sizes were checked using the DLS method. The influence of the input parameters on the obtained results was also studied.

Keywords: fluorescence, modification, nanosilver, molasses, Green chemistry, carbon dots

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Authors: Bright Kwakye-Awuah, Elizabeth Von-Kiti, Isaac Nkrumah, Baah Sefa-Ntiri, Craig D. Williams

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Bauxite and kaolin from Ghana Bauxite Company mine site were used to synthesize zeolites. Bauxite served as the alumina source and kaolin the silica source. Synthesis variations include variation of aging time at constant crystallization time and variation of crystallization times at constant aging time. Characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDX) and Fourier transform infrared spectroscopy (FTIR) were employed in the characterization of the raw samples as well as the synthesized samples. The results obtained showed that the transformations that occurred and the phase of the resulting products were coordinated by the aging time, crystallization time, alkaline concentration and Si/Al ratio of the system. Zeolites A, X, Y, analcime, Sodalite, and ZK-14 were some of the phases achieved. Zeolite LTA was achieved with short crystallization times of 3, 5, 18 and 24 hours and a maximum aging of 24 hours. Zeolite LSX was synthesized with 24 hr aging followed with 24 hr hydrothermal treatment whilst zeolite Y crystallized after 48 hr of aging and 24 hr crystallization. Prolonged crystallization time produced a mixed phased product. Prolonged aging times, on the other hand, did not yield any zeolite as the sample was amorphous. Increasing the alkaline content of the reaction mixture above 5M introduced sodalite phase in the final product. The properties of the final products were comparable to zeolites synthesized from pure chemical reagents.

Keywords: bauxite, kaolin, aging, crystallization, zeolites

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Authors: Ahmed F. Elaksher, Islam Omar

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In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Mustafa Mhawesh, Reza Langari

Abstract:

This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-Of-Freedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint.

Keywords: higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis

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Authors: Mohammed Saleh Rezk, Reza Kashani

Abstract:

Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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Authors: S. Gordon

Abstract:

Dual language immersion is growing fast in language teaching today. This study provides an overview and evaluation of the different models of Dual language immersion programs in US K-12 schools. First, the paper provides a brief current literature review on the theory of Dual Language Immersion (DLI) in Second Language Acquisition (SLA) studies. Second, examples of several types of DLI language teaching models in US K-12 public schools are presented (including 50/50 models, 90/10 models, etc.). Third, we focus on the unique example of DLI education in the state of Utah, a successful, growing program in K-12 schools that includes: French, Chinese, Spanish, and Portuguese. The project investigates the theory and practice particularly of the case of public elementary and secondary school children that study half their school day in the L1 and the other half in the chosen L2, from kindergarten (age 5-6) through high school (age 17-18). Finally, the project takes the observations of Utah French DLI elementary through secondary programs as a case study. To conclude, we look at the principal challenges, pedagogical objectives and outcomes, and important implications for other US states and other countries (such as France currently) that are in the process of developing similar language learning programs.

Keywords: dual language immersion, second language acquisition, language teaching, pedagogy, teaching, French

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Authors: Lazhar mouloud, Chemat Zoubida, Ouhoumna Faiza

Abstract:

The main objective of this study, concerns the modeling of breakthrough curves obtained in the adsorption column of malachite green into alginate-encapsulated aluminium pillared clay in fixed bed according to various operating parameters such as the initial concentration, the feed rate and the height fixed bed, applying mathematical models namely: the model of Bohart and Adams, Wolborska, Bed Depth Service Time, Clark and Yoon-Nelson. These models allow us to express the different parameters controlling the performance of the dynamic adsorption system. The results have shown that all models were found suitable for describing the whole or a definite part of the dynamic behavior of the column with respect to the flow rate, the inlet dye concentration and the height of fixed bed.

Keywords: adsorption column, malachite green, pillared clays, alginate, modeling, mathematic models, encapsulation.

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Authors: Sameh M. Osman, El-Refaie Kenawy, Zeid A. Al-Othman, Mohamed H. El-Newehy, El-Saied A. Aly, Sherine N. Khattab, Ayman El-Faham

Abstract:

Recently, there has been a huge interest in using cyanuric chloride in a wide range of functional group transformations, as Cyanuric chloride has temperature-dependent differential reactivity for displacement of chlorides with various nucleophiles In the present work, some copolymers based on s-triazine Unit were prepared by microwave-assisted synthesis. For comparison study, the copolymers were synthesized by the conventional method. Synthesized Copolymers were characterized by MP, IR, TGA, DSC and GPC. The result indicated that copolymers are thermally stable and in good in composition and yield. Further studies that involve the test for selected removal of transition elements such as Cu (II), Zn (II) and Mn (II). Moreover, the effects of the polymeric triazine derivatives containing different functional groups which expected to have a good thermal stability and char formation ability on thermal degradation and flame retardancy.

Keywords: flame retardants, heavy metals, microwave-assisted synthesis, s-triazine

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Authors: Nasser R. El-Brollosy, Roberta Loddo

Abstract:

6-Benzyl-1-(ethoxymethyl)-5-isopropyluracil (Emivirine) and its corresponding 1-benzyloxymethyl analogue (TNK-651) showed high activity against HIV-1. The present study describes synthesis of novel emivirine analogues by reaction of chloromethyl ethyl ether with uracils having 5-ethyl / isopropyl and 6-(3,5-dimethoxybenzyl) substituents. A series of new TNK-651 analogues substituted at N-1 with phenoxyethoxymethyl moiety was prepared on treatment of the corresponding uracils with bis(phenoxyethoxy) methane. The newly synthesized non-nucleosides were tested for biological activity against wild type HIV-1 IIIB as well as the resistant strains N119 (Y181C), A17 (K103N + Y181C), and the triple mutant EFVR (K103R + V179D + P225H) in MT-4 cells. Some of the tested compounds showed good activities. Among them 6-(3,5-dimethylbenzyl)-5-ethyl-1-[2-(phenoxyethyl) oxymethyl]uracil which showed inhibitory potency higher than emivirine against both wild type HIV-1 and the tested mutant strains.

Keywords: Emivirine, HIV, non-nucleoside reverse transcriptase, uracils

Procedia PDF Downloads 266