Search results for: mixed effects models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18744

Search results for: mixed effects models

16854 The Effect of Three-Dimensional Morphology on Vulnerability Assessment of Atherosclerotic Plaque

Authors: M. Zareh, H. Mohammadi, B. Naser

Abstract:

Atherosclerotic plaque rupture is the main trigger of heart attack and brain stroke which are the leading cause of death in developed countries. Better understanding of rupture-prone plaque can help clinicians detect vulnerable plaques- rupture prone or instable plaques- and apply immediate medical treatment to prevent these life-threatening cardiovascular events. Therefore, there are plenty of studies addressing disclosure of vulnerable plaques properties. Necrotic core and fibrous tissue are two major tissues constituting atherosclerotic plaque; using histopathological and numerical approaches, many studies have demonstrated that plaque rupture is strongly associated with a large necrotic core and a thin fibrous cap, two morphological characteristic which can be acquired by two-dimensional imaging of atherosclerotic plaque present in coronary and carotid arteries. Plaque rupture is widely considered as a mechanical failure inside plaque tissue; this failure occurs when the stress within plaque excesses the strength of tissue material; hence, finite element method, a strong numerical approach, has been extensively applied to estimate stress distribution within plaques with different compositions which is then used for assessment of various vulnerability characteristics including plaque morphology, material properties and blood pressure. This study aims to evaluate significance of three-dimensional morphology on vulnerability degree of atherosclerotic plaque. To reach this end, different two-dimensional geometrical models of atherosclerotic plaques are considered based on available data and named Main 2D Models (M2M). Then, for each of these M2Ms, two three-dimensional idealistic models are created. These two 3D models represent two possible three-dimensional morphologies which might exist for a plaque with similar 2D morphology to one of M2Ms. Finite element method is employed to estimate stress, von-Mises stress, within each 3D models. Results indicate that for each M2Ms stress can significantly varies due to possible 3D morphological changes in that plaque. Also, our results show that an atherosclerotic plaque with thick cap may experience rupture if it has a critical 3D morphology. This study highlights the effect of 3D geometry of plaque on its instability degree and suggests that 3D morphology of plaque might be necessary to more effectively and accurately assess atherosclerotic plaque vulnerability.

Keywords: atherosclerotic plaque, plaque rupture, finite element method, 3D model

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16853 Rural Development as a Strategy to Deter Migration in India - Re-Examining the Ideology of Cluster Development

Authors: Nandini Mohan, Thiruvengadam R. B.

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Mahatma Gandhi advocated that the true indicator of modern India lay in the development of its villages. This has been proven with the recent outbreak of the Coronavirus pandemic and the surfacing predicament of our urban centers. Developed on the Industrialization model, the current state of the metropolis is of rampant overcrowding, high rates of unemployment, inadequate infrastructure, and resources to cater to the growing population. A majority of each city’s strength composes of the migrant population, demonstrated through the migrant crisis, a direct repercussion of COVID-19. This paper explores the ideology of how rural development can act as a tactic to counter the high rates of rural-urban migration. It establishes the need for a rural push, as India is predominantly an agrarian economy, with a vast disparity between the urban and rural centers due to its urban bias. It seeks to define development in holistic terms. It studies the models of ‘cluster’ as conceptualized by V.K.R.V. Rao, and detailed by Architect Charles Correa in his book, The New Landscape. The paper reexamines the theory of cluster development through existing models proposed by the government of India. Namely, PURA (Provision of Urban Amenities in Rural Areas), DRI (Deendayal Research Institute), and Rurban under Shyama Prasad Mukharjee Rurban Mission. It analyses the models, their strengths, weaknesses, and reasons for their failure and success to derive parameters for the ideation of an archetype model. A model of rural development that talks of the simultaneous development of existing adjacent villages, by the introduction of set unique functions, that may turn into self-sustaining clusters or agglomerations in the future, which could serve as the next step for Indian village development based on the cluster ideology.

Keywords: counter migration, models of rural development, cluster development theory, India

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16852 Optimizing Inanda Dam Using Water Resources Models

Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno

Abstract:

The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective and management

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16851 Using Music in the Classroom to Help Syrian Refugees Deal with Post-War Trauma

Authors: Vartan Agopian

Abstract:

Millions of Syrian families have been displaced since the beginning of the Syrian war, and the negative effects of post-war trauma have shown detrimental effects on the mental health of refugee children. While educational strategies have focused on vocational training and academic achievement, little has been done to include music in the school curriculum to help these children improve their mental health. The literature of music education and psychology, on the other hand, shows the positive effects of music on traumatized children, especially when it comes to dealing with stress. This paper presents a brief literature review of trauma, music therapy, and music in the classroom, after having introduced the Syrian war and refugee situation. Furthermore, the paper highlights the benefits of using music with traumatized children from the literature and offers strategies for teachers (such as singing, playing an instrument, songwriting, and others) to include music in their classrooms to help Syrian refugee children deal with post-war trauma.

Keywords: children, music, refugees, Syria, war

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16850 Steam Reforming of Acetic Acid over Microwave-Synthesized Ce0.75Zr0.25O2 Supported Ni Catalysts

Authors: Panumard Kaewmora, Thirasak Rirksomboon, Vissanu Meeyoo

Abstract:

Due to the globally growing demands of petroleum fuel and fossil fuels, the scarcity or even depletion of fossil fuel sources could be inevitable. Alternatively, the utilization of renewable sources, such as biomass, has become attractive to the community. Biomass can be converted into bio-oil by fast pyrolysis. In water phase of bio-oil, acetic acid which is one of its main components can be converted to hydrogen with high selectivity over effective catalysts in steam reforming process. Steam reforming of acetic acid as model compound has been intensively investigated for hydrogen production using various metal oxide supported nickel catalysts and yet they seem to be rapidly deactivated depending on the support utilized. A catalyst support such as Ce1-xZrxO2 mixed oxide was proposed for alleviating this problem with the anticipation of enhancing hydrogen yield. However, catalyst preparation methods play a significant role in catalytic activity and performance of the catalysts. In this work, Ce0.75Zr0.25O2 mixed oxide solid solution support was prepared by urea hydrolysis using microwave as heat source. After that nickel metal was incorporated at 15 wt% by incipient wetness impregnation method. The catalysts were characterized by several techniques including BET, XRD, H2-TPR, XRF, SEM, and TEM as well as tested for the steam reforming of acetic acid at various operating conditions. Preliminary results showed that a hydrogen yield of ca. 32% with a relatively high acetic conversion was attained at 650°C.

Keywords: acetic acid, steam reforming, microwave, nickel, ceria, zirconia

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16849 Modeling of Masonry In-Filled R/C Frame to Evaluate Seismic Performance of Existing Building

Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

Abstract:

This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: masonry infill, framed structures, RC buildings, non-structural elements

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16848 Through Seligman’s Lenses: Creating a Culture of Well-Being in Higher-Education

Authors: Neeru Deep, Kimberly McAlister

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Mental health issues have been increasing worldwide for many decades, but the COVID-19 pandemic has brought mental health issues into the spotlight. Within higher education, promoting the well-being of students has dramatically increased in focus. The Northwestern State University of Louisiana opened the Center for Positivity, Well-being, and Hope using the action research process of reflecting, planning, acting, and observing. The study’s purpose is two-fold: First, it highlights how to create a collaborative team to reflect, plan, and act to develop a well-being culture in higher education institutions. Second, it investigates the efficacy of the center through Seligman’s lenses. The researchers shared their experience in the first three phases of the action research process and then applied an identical concurrent mixed methods design. A purposive sample evaluated the efficacy of the center through Seligman’s lenses. The researcher administered PERMA-Profiler Measure, the PERMA-Profiler Measure overview, the CoPWH Evaluation I, and the CoPWH Evaluation II questionnaires to collect qualitative and quantitative data. The thematic analysis for qualitative and descriptive statistics for quantitative data concluded that the center creates a well-being culture and promotes well-being in college students. In conclusion, this action research shares the successful implementation of the cyclic process of research in promoting a well-being culture in higher education with the implications for promoting a well-being culture in various educational settings, workplaces, and communities.

Keywords: action research, mixed methods research design, Seligman, well-being.

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16847 Impact of the Electricity Market Prices during the COVID-19 Pandemic on Energy Storage Operation

Authors: Marin Mandić, Elis Sutlović, Tonći Modrić, Luka Stanić

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With the restructuring and deregulation of the power system, storage owners, generation companies or private producers can offer their multiple services on various power markets and earn income in different types of markets, such as the day-ahead, real-time, ancillary services market, etc. During the COVID-19 pandemic, electricity prices, as well as ancillary services prices, increased significantly. The optimization of the energy storage operation was performed using a suitable model for simulating the operation of a pumped storage hydropower plant under market conditions. The objective function maximizes the income earned through energy arbitration, regulation-up, regulation-down and spinning reserve services. The optimization technique used for solving the objective function is mixed integer linear programming (MILP). In numerical examples, the pumped storage hydropower plant operation has been optimized considering the already achieved hourly electricity market prices from Nord Pool for the pre-pandemic (2019) and the pandemic (2020 and 2021) years. The impact of the electricity market prices during the COVID-19 pandemic on energy storage operation is shown through the analysis of income, operating hours, reserved capacity and consumed energy for each service. The results indicate the role of energy storage during a significant fluctuation in electricity and services prices.

Keywords: electrical market prices, electricity market, energy storage optimization, mixed integer linear programming (MILP) optimization

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16846 2D Point Clouds Features from Radar for Helicopter Classification

Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

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This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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16845 Speed Breaker/Pothole Detection Using Hidden Markov Models: A Deep Learning Approach

Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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16844 Two Concurrent Convolution Neural Networks TC*CNN Model for Face Recognition Using Edge

Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

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16843 The Effects of Key Factors in Traffic-Oriented Road Alignment Adjustment for Low Emissions Profile: A Case Study in Norway

Authors: Gaylord K. Booto, Marinelli Giuseppe, Helge Brattebø, Rolf A. Bohne

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Emissions reduction has emerged among the principal targets in the process of planning and designing road alignments today. Intelligent road design methods that can result in optimized alignment constitute concrete and innovative responses towards better alternatives and more sustainable road infrastructures. As the largest amount of emissions of road infrastructures occur in the operation stage, it becomes very important to consider traffic weight and distribution in alignment design process. This study analyzes the effects of four traffic factors (i.e. operating speed, vehicle category, technology and fuel type) on adjusting the vertical alignment of a given road, using optimization techniques. Further, factors’ effects are assessed qualitatively and quantitatively, and the emission profiles of resulting alignment alternatives are compared.

Keywords: alignment adjustment, emissions reduction, optimization, traffic-oriented

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16842 Predicting Recessions with Bivariate Dynamic Probit Model: The Czech and German Case

Authors: Lukas Reznak, Maria Reznakova

Abstract:

Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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16841 The Concepts of Ibn Taymiyyah in Halal and Haram and Their Relevance to Contemporary Issues

Authors: Muhammad Fakhrul Arrazi

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Ibn Taymiyyah is a great figure in Islam. His works have become the reference for many Muslims in implementing the fiqh of Ibadah and Muamalat. This article reviews the concepts that Ibn Taymiyyah has initiated in Halal and Haram, long before the books on Halal and Haram are written by contemporary scholars. There are at least four concepts of Halal and Haram ever spawned by Ibn Taymiyyah. First, the belief of a jurist (Faqih) in a matter that is Haram does not necessarily make the matter Haram. Haram arises from the Quran, Sunnah, Ijma’ and Qiyas as the tarjih. Due to the different opinions among the ulama, we should revisit this concept. Second, if a Muslim involves in a transaction (Muamalat), believes it permissible and gets money from such transaction, then it is legal for other Muslims to transact with the property of this Muslim brother, even if he does not believe that the transactions made by his Muslims brother are permissible. Third, Haram is divided into two; first is Haram because of the nature of an object, such as carrion, blood, and pork. If it is mixed with water or food and alters their taste, color, and smell, the food and water become Haram. Second is Haram because of the way it is obtained such as a stolen item and a broken aqad. If it is mixed with the halal property, the property does not automatically become Haram. Fourth, a treasure whose owners cannot be traced back then it is used for the benefit of the ummah. This study used the secondary data from the classics books by Ibn Taymiyyah, particularly those entailing his views on Halal and Haram. The data were then analyzed by using thematic and comparative approach. It is found that most of the concepts proposed by Ibn Taymiyyah in Halal and Haram correspond the majority’s views in the schools. However, some of his concepts are also in contrary to other scholars. His concepts will benefit the ummah, should it be applied to the contemporary issues.

Keywords: fiqh Muamalat, halal, haram, Ibn Taymiyyah

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16840 Teaching: Using Co-teaching as an Instructional Model

Authors: Beverley Gallimore

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The Individuals with Disabilities Education Act of 2004 (IDEA) has helped to improve outcomes for students with special education needs. Through IDEA, students with Special Education Needs (SEN) have opportunities for more equitable education within the General Education classroom. However, students with disabilities lack access to instructions that can help them to maximize their fullest learning potential. Recently, educational stakeholders have emphasized Integrated Co-teaching as a tool to increase engagement and learning outcomes for students with disabilities in general education classrooms. As a result of this new approach, general and special education teachers are working collaboratively to teach students with disabilities. However, co-teaching models are not properly designed and structured to effectively benefit students with disabilities. Teachers must be oriented correctly in the co-teaching models if it is to be beneficial for students.

Keywords: CO-teaching, differentiation, equitable, collaborative

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16839 Development of an Automatic Computational Machine Learning Pipeline to Process Confocal Fluorescence Images for Virtual Cell Generation

Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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16838 Adsorption of Lead and Zinc Ions Onto Chemical Activated Millet Husk: Equilibrium and Kinetics Studies

Authors: Hilary Rutto, Linda Sibali

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In this study, the adsorption of lead and zinc ions from aqueous solutions by modified millet husk has been investigated. The effects of different parameters, such as pH, adsorbent dosage, concentration, temperature, and contact time, have been investigated. The results of the experiments showed that the adsorption of both metal ions increased by increasing pH values up to 11. Adsorption process was initially fast. The adsorption rate decreased then until it reached to equilibrium time of 120 min for both lead and zinc ions. The Langmuir, Freundlich, Dubinin-Radushkevich (D-R), and thermodynamic models (Gibbs free energy) were used to determine the isotherm parameters associated with the adsorption process. The positive values of Gibbs free energy change indicated that reaction is not spontaneous. Experimental data were also evaluated in terms of kinetic characteristics of adsorption, and it was found that adsorption process for both metal ions followed pseudo-first order for zinc and pseudo-second-order for lead.

Keywords: zinc, lead, adsorption, millet husks

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16837 Using Complete Soil Particle Size Distributions for More Precise Predictions of Soil Physical and Hydraulic Properties

Authors: Habib Khodaverdiloo, Fatemeh Afrasiabi, Farrokh Asadzadeh, Martinus Th. Van Genuchten

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The soil particle-size distribution (PSD) is known to affect a broad range of soil physical, mechanical and hydraulic properties. Complete descriptions of a PSD curve should provide more information about these properties as opposed to having only information about soil textural class or the soil sand, silt and clay (SSC) fractions. We compared the accuracy of 19 different models of the cumulative PSD in terms of fitting observed data from a large number of Iranian soils. Parameters of the six most promising models were correlated with measured values of the field saturated hydraulic conductivity (Kfs), the mean weight diameter of soil aggregates (MWD), bulk density (ρb), and porosity (∅). These same soil properties were correlated also with conventional PSD parameters (SSC fractions), selected geometric PSD parameters (notably the mean diameter dg and its standard deviation σg), and several other PSD parameters (D50 and D60). The objective was to find the best predictions of several soil physical quality indices and the soil hydraulic properties. Neither SSC nor dg, σg, D50 and D60 were found to have a significant correlation with both Kfs or logKfs, However, the parameters of several cumulative PSD models showed statistically significant correlation with Kfs and/or logKfs (|r| = 0.42 to 0.65; p ≤ 0.05). The correlation between MWD and the model parameters was generally also higher than either with SSC fraction and dg, or with D50 and D60. Porosity (∅) and the bulk density (ρb) also showed significant correlation with several PSD model parameters, with ρb additionally correlating significantly with various geometric (dg), mechanical (D50 and D60), and agronomic (clay and sand) representations of the PSD. The fitted parameters of selected PSD models furthermore showed statistically significant correlations with Kfs,, MWD and soil porosity, which may be viewed as soil quality indices. Results of this study are promising for developing more accurate pedotransfer functions.

Keywords: particle size distribution, soil texture, hydraulic conductivity, pedotransfer functions

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16836 Measuring the Economic Impact of Cultural Heritage: Comparative Analysis of the Multiplier Approach and the Value Chain Approach

Authors: Nina Ponikvar, Katja Zajc Kejžar

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While the positive impacts of heritage on a broad societal spectrum have long been recognized and measured, the economic effects of the heritage sector are often less visible and frequently underestimated. At macro level, economic effects are usually studied based on one of the two mainstream approach, i.e. either the multiplier approach or the value chain approach. Consequently, there is limited comparability of the empirical results due to the use of different methodological approach in the literature. Furthermore, it is also not clear on which criteria the used approach was selected. Our aim is to bring the attention to the difference in the scope of effects that are encompassed by the two most frequent methodological approaches to valuation of economic effects of cultural heritage on macroeconomic level, i.e. the multiplier approach and the value chain approach. We show that while the multiplier approach provides a systematic, theory-based view of economic impacts but requires more data and analysis, the value chain approach has less solid theoretical foundations and depends on the availability of appropriate data to identify the contribution of cultural heritage to other sectors. We conclude that the multiplier approach underestimates the economic impact of cultural heritage, mainly due to the narrow definition of cultural heritage in the statistical classification and the inability to identify part of the contribution of cultural heritage that is hidden in other sectors. Yet it is not possible to clearly determine whether the value chain method overestimates or underestimates the actual economic impact of cultural heritage since there is a risk that the direct effects are overestimated and double counted, but not all indirect and induced effects are considered. Accordingly, these two approaches are not substitutes but rather complementary. Consequently, a direct comparison of the estimated impacts is not possible and should not be done due to the different scope. To illustrate the difference of the impact assessment of the cultural heritage, we apply both approaches to the case of Slovenia in the 2015-2022 period and measure the economic impact of cultural heritage sector in terms of turnover, gross value added and employment. The empirical results clearly show that the estimation of the economic impact of a sector using the multiplier approach is more conservative, while the estimates based on value added capture a much broader range of impacts. According to the multiplier approach, each euro in cultural heritage sector generates an additional 0.14 euros in indirect effects and an additional 0.44 euros in induced effects. Based on the value-added approach, the indirect economic effect of the “narrow” heritage sectors is amplified by the impact of cultural heritage activities on other sectors. Accordingly, every euro of sales and every euro of gross value added in the cultural heritage sector generates approximately 6 euros of sales and 4 to 5 euros of value added in other sectors. In addition, each employee in the cultural heritage sector is linked to 4 to 5 jobs in other sectors.

Keywords: economic value of cultural heritage, multiplier approach, value chain approach, indirect effects, slovenia

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16835 Examining the Dynamics of FDI Inflows in Both BRICS and G7 Economies: Dissecting the Influence of Geopolitical Risk versus Economic Policy Uncertainty

Authors: Adelakun O. Johnson

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The quest to mitigate the probable adverse effects of geopolitical risk on FDI inflows tends to result in more frequent changes in economic policies and, as a result, heightened policy uncertainty. In this regard, we extend the literature on the dynamics of FDI inflows to include the hypothesis of the possibility of geopolitical risk escalating the adverse effects of economic policy uncertainty on FDI inflows. To test the robustness of this hypothesis, we use the cases of different economic groups characterized by different levels of economic development and varying degrees of FDI confidence. Employing an ARDL-based dynamic panel data model that accounts for both non-stationarity and heterogeneity effects, we show result that suggests GPR and EPU retard the inflows of FDI in both economies but mainly in the short-run situation. In the long run, however, higher EPU not attributed to GPR is likely to boost the inflows of FDI rather than retarding, at least in the case of the G7 economy.

Keywords: FDI inflows, geopolitical risk, economic policy uncertainty, panel ARDL model

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16834 Modeling Geogenic Groundwater Contamination Risk with the Groundwater Assessment Platform (GAP)

Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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16833 A Dual-Mode Infinite Horizon Predictive Control Algorithm for Load Tracking in PUSPATI TRIGA Reactor

Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

Abstract:

The PUSPATI TRIGA Reactor (RTP), Malaysia reached its first criticality on June 28, 1982, with power capacity 1MW thermal. The Feedback Control Algorithm (FCA) which is conventional Proportional-Integral (PI) controller, was used for present power control method to control fission process in RTP. It is important to ensure the core power always stable and follows load tracking within acceptable steady-state error and minimum settling time to reach steady-state power. At this time, the system could be considered not well-posed with power tracking performance. However, there is still potential to improve current performance by developing next generation of a novel design nuclear core power control. In this paper, the dual-mode predictions which are proposed in modelling Optimal Model Predictive Control (OMPC), is presented in a state-space model to control the core power. The model for core power control was based on mathematical models of the reactor core, OMPC, and control rods selection algorithm. The mathematical models of the reactor core were based on neutronic models, thermal hydraulic models, and reactivity models. The dual-mode prediction in OMPC for transient and terminal modes was based on the implementation of a Linear Quadratic Regulator (LQR) in designing the core power control. The combination of dual-mode prediction and Lyapunov which deal with summations in cost function over an infinite horizon is intended to eliminate some of the fundamental weaknesses related to MPC. This paper shows the behaviour of OMPC to deal with tracking, regulation problem, disturbance rejection and caters for parameter uncertainty. The comparison of both tracking and regulating performance is analysed between the conventional controller and OMPC by numerical simulations. In conclusion, the proposed OMPC has shown significant performance in load tracking and regulating core power for nuclear reactor with guarantee stabilising in the closed-loop.

Keywords: core power control, dual-mode prediction, load tracking, optimal model predictive control

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16832 The Effects of a Thin Liquid Layer on the Hydrodynamic Machine Rotor

Authors: Jaroslav Krutil, František Pochylý, Simona Fialová, Vladimír Habán

Abstract:

A mathematical model of the additional effects of the liquid in the hydrodynamic gap is presented in the paper. An in-compressible viscous fluid is considered. Based on computational modeling are determined the matrices of mass, stiffness and damping. The mathematical model is experimentally verified.

Keywords: computational modeling, mathematical model, hydrodynamic gap, matrices of mass, stiffness and damping

Procedia PDF Downloads 557
16831 Basket Option Pricing under Jump Diffusion Models

Authors: Ali Safdari-Vaighani

Abstract:

Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.

Keywords: basket option, jump diffusion, ‎radial basis function, RBF-PUM

Procedia PDF Downloads 354
16830 An Analysis of Innovative Cloud Model as Bridging the Gap between Physical and Virtualized Business Environments: The Customer Perspective

Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike Lloyd-Williams

Abstract:

This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: innovation, virtualization, cloud computing, organizational flexibility

Procedia PDF Downloads 384
16829 Interlanguage Pragmatics Instruction: Evidence from EFL Teachers

Authors: Asma Ben Abdallah

Abstract:

Interlanguage Pragmatics (ILP) Instruction has brought a lot of enlightenment for Foreign Language Teaching and has secured itself a deserved position in SLA research. In the Tunisian context, ILP instruction remains less explored for academics and educational practitioners. In our experience as teachers, both at secondary school and at university levels, the instruction and assessment of pragmatics seem to be contentious. This paper firstly introduces the theoretical models of Interlanguage pragmatics Instruction and focuses on their implications for foreign language teaching. This study builds on the work of Ben Abdallah (2015) that investigated the effects of pragmatic Instruction on Tunisian EFL Learners where pragmatic Instruction has been approached from the perspective of students and their learning strategies. The data for the present study, however, come from Tunisian EFL teachers by investigating their pragmatics practices and their perceptions of pragmatic instruction. The findings indicated that EFL teachers have pragmatic awareness; yet, their reflections revealed that their awareness was mostly on theoretical pragmatic knowledge, and not explicitly brought into practical pragmatic applications. The paper concludes by promoting pragmatics instruction with the suggestion that EFL teachers should teach pragmatics in class.

Keywords: interlanguage pragmatics theory, pragmatics, pragmatic instruction, SLA

Procedia PDF Downloads 281
16828 Social Business Models: When Profits and Impacts Are Not at Odds

Authors: Elisa Pautasso, Matteo Castagno, Michele Osella

Abstract:

In the last decade, the emergence of new social needs as an effect of the economic crisis has stimulated the flourishing of business endeavours characterised by explicit social goals. Social start-ups, social enterprises or Corporate Social Responsibility operations carried out by traditional companies are quintessential examples in this regard. This paper analyses these kinds of initiatives in order to discover the main characteristics of social business models and to provide insights to social entrepreneurs for developing or improving their strategies. The research is conducted through the integration of literature review and case study analysis and, thanks to the recognition of the importance of both profits and social impacts as the key success factors for a social business model, proposes a framework for identifying indicators suitable for measuring the social impacts generated.

Keywords: business model, case study, impacts, social business

Procedia PDF Downloads 349
16827 Antistress Effects of Hydrangeae Dulcis Folium on Net Handing Stress-Induced Anxiety-Like Behavior in Zebrafish: Possible Mechanism of Action of Adrenocorticotropin Hormone (ACTH) Receptor

Authors: Lee Seungheon, Kim Ba-Ro

Abstract:

In this study, the anti-stress effects of the ethanolic extract of Hydrangeae Dulcis Folium (EHDF) were investigated. To determine the effects of EHDF on physical stress, changes in the whole-body cortisol level and behaviour were monitored in zebrafish. To induce physical stress, we used the net handling stress (NHS). Fish were treated with EHDF for 6 min before they were exposed to stress, and the fish were either evaluated via behavioural tests, including a novel tank test and an open field test or sacrificed to collect body fluid from the whole body. The results indicate that increased anxiety-like behaviours in the novel tank test and open field test under stress were recovered by treatment with EHDF at 5, 10 and 20 mg/L (P < 0.05). Moreover, compared with the normal group, which was not treated with NHS, the whole-body cortisol level was significantly increased by treatment with NHS in the control group. Compared with the control group, pre-treatment with EHDF at concentrations of 5, 10 and 20 mg/L for 6 min significantly prevented the increase in the whole-body cortisol level induced by NHS (P < 0.05). In addition, adrenocorticotropin hormone (ACTH) challenge studies showed that EHDF completely blocked the effects of ACTH (0.2 IU/g, IP) on cortisol secretion. These results suggest that EHDF may be a good anti-stress candidate and that its mechanism of action may be related to its positive effects on cortisol release.

Keywords: net handling stress, zebrafish, hydrangeae dulcis folium, whole-body cortisol, novel tank test, open field test

Procedia PDF Downloads 299
16826 Chemical Oxygen Demand Fractionation of Primary Wastewater Effluent for Process Optimization and Modelling

Authors: Thandeka Y. S. Jwara, Paul Musonge

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Traditionally, the complexity associated with implementing and controlling biological nutrient removal (BNR) in wastewater works (WWW) has been primarily in terms of balancing competing requirements for nitrogen and phosphorus removal, particularly with respect to the use of influent chemical oxygen demand (COD) as a carbon source for the microorganisms. Successful BNR optimization and modelling using WEST (Worldwide Engine for Simulation and Training) depend largely on the accurate fractionation of the influent COD. The different COD fractions have differing effects on the BNR process, and therefore, the influent characteristics need to be well understood. This study presents the fractionation results of primary wastewater effluent COD at one of South Africa’s wastewater works treating 65ML/day of mixed industrial and domestic effluent. The method used for COD fractionation was the oxygen uptake rate/respirometry method. The breakdown of the results of the analysis is as follows: 70.5% biodegradable COD (bCOD) and 29.5% of non-biodegradable COD (iCOD) in terms of the total COD. Further fractionation led to a readily biodegradable soluble fraction (SS) of 75%, a slowly degradable particulate fraction (XS) of 24%, a particulate non-biodegradable fraction (XI) of 50.8% and a non-biodegradable soluble fraction (SI) of 49.2%. The fractionation results demonstrate that the primary effluent has good COD characteristics, as shown by the high level of the bCOD fraction with Ss being higher than Xs. This means that the microorganisms have sufficient substrate for the BNR process and that these components can now serve as inputs to the WEST Model for the plant under study.

Keywords: chemical oxygen demand, COD fractionation, wastewater modelling, wastewater optimization

Procedia PDF Downloads 143
16825 Deficits and Solutions in the Development of Modular Factory Systems

Authors: Achim Kampker, Peter Burggräf, Moritz Krunke, Hanno Voet

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As a reaction to current challenges in factory planning, many companies think about introducing factory standards to lower planning times and decrease planning costs. If these factory standards are set-up with a high level of modularity, they are defined as modular factory systems. This paper deals with the main current problems in the application of modular factory systems in practice and presents a solution approach with its basic models. The methodology is based on methods from factory planning but also uses the tools of other disciplines like product development or technology management to deal with the high complexity, which the development of modular factory systems implies. The four basic models that such a methodology has to contain are introduced and pointed out.

Keywords: factory planning, modular factory systems, factory standards, cost-benefit analysis

Procedia PDF Downloads 595