Search results for: protein tertiary structure prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12203

Search results for: protein tertiary structure prediction

10793 Prediction of Dubai Financial Market Stocks Movement Using K-Nearest Neighbor and Support Vector Regression

Authors: Abdulla D. Alblooshi

Abstract:

The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

Procedia PDF Downloads 161
10792 Identification of Nutrient Sensitive Signaling Pathways via Analysis of O-GlcNAcylation

Authors: Michael P. Mannino, Gerald W. Hart

Abstract:

The majority of glucose metabolism proceeds through glycolytic pathways such as glycolysis or pentose phosphate pathway, however, about 5% is shunted through the hexosamine biosynthetic pathway, producing uridine diphosphate N-acetyl glucosamine (UDP-GlcNAc). This precursor can then be incorporated into complex oligosaccharides decorating the cell surface or remain as an intracellular post-translational-modification (PTM) of serine/threonine residues (O-GlcNAcylation, OGN), which has been identified on over 4,000 cytosolic or nuclear proteins. Intracellular OGN has major implications on cellularprocesses, typically by modulating protein localization, protein-protein interactions, protein degradation, and gene expression. Additionally, OGN is known to have an extensive cross-talk with phosphorylation, be in a competitive or cooperative manner. Unlike other PTMs there are only two cycling enzymes that are capable of adding or removing the GlcNAc moiety, O-linked N-aceytl glucosamine Transferase (OGT) and O-linked N-acetyl glucoamidase (OGA), respectively. The activity of OGT has been shown to be sensitive to cellular UDP-GlcNAc levels, even changing substrate affinity. Owing to this and that the concentration of UDP-GlcNAc is related to the metabolisms of glucose, amino acid, fatty acid, and nucleotides, O-GlcNAc is often referred to as a nutrient sensing rheostat. Indeed OGN is known to regulate several signaling pathways as a result of nutrient levels, such as insulin signaling. Dysregulation of OGN is associated with several disease states such as cancer, diabetes, and neurodegeneration. Improvements in glycomics over the past 10-15 years has significantly increased the OGT substrate pool, suggesting O-GlcNAc’s involvement in a wide variety of signaling pathways. However, O-GlcNAc’s role at the receptor level has only been identified in a case-by-case basis of known pathways. Examining the OGN of the plasma membrane (PM) may better focus our understanding of O-GlcNAc-effected signaling pathways. In this current study, PM fractions were isolated from several cell types via ultracentrifugation, followed by purification and MS/MS analysis in several cell lines. This process was repeated with or without OGT/OGA inhibitors or with increased/decreased glucose levels in media to ascertain the importance of OGN. Various pathways are followed up on in more detailed studies employing methods to localize OGN at the PM specifically.

Keywords: GlcNAc, nutrient sensitive, post-translational-modification, receptor

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10791 The Effect of Fermentation and Germination on the Nutrient and Antinutrient Composition of Lima Bean (Phaseolus lunatus) Flour

Authors: P. N. Okeke

Abstract:

Fermentation and germination of legumes have been an ancient practice. In this study, the influence of fermentation and germination on the chemical properties of Lima bean (Phaseolus lunatus) flour were evaluated. The flours were analyzed for their proximate and mineral composition, using the standard assay methods. The result showed that fermentation and germination increased the moisture, protein and ash content of the flours while fiber, fat and carbohydrate were decreased. The protein level of fermented and germinated lima bean increased from 21.06–26.60%. The minerals: iron, copper, zinc, and phosphorous increased due to germination and fermentation. The phytate and tannin levels were drastically reduced in both the fermented and germinated flours. The result of this study revealed that fermentation and germination makes the nutrient in lima beans more accessible as it reduces the anti-nutrients. It is therefore recommended that lima bean be process accordingly for richer and more bio-availability of the nutrients.

Keywords: nutrient, anti-nutrient, fermented, germinated, lima bean flour

Procedia PDF Downloads 375
10790 Attribute Index and Classification Method of Earthquake Damage Photographs of Engineering Structure

Authors: Ming Lu, Xiaojun Li, Bodi Lu, Juehui Xing

Abstract:

Earthquake damage phenomenon of each large earthquake gives comprehensive and profound real test to the dynamic performance and failure mechanism of different engineering structures. Cognitive engineering structure characteristics through seismic damage phenomenon are often far superior to expensive shaking table experiments. After the earthquake, people will record a variety of different types of engineering damage photos. However, a large number of earthquake damage photographs lack sufficient information and reduce their using value. To improve the research value and the use efficiency of engineering seismic damage photographs, this paper objects to explore and show seismic damage background information, which includes the earthquake magnitude, earthquake intensity, and the damaged structure characteristics. From the research requirement in earthquake engineering field, the authors use the 2008 China Wenchuan M8.0 earthquake photographs, and provide four kinds of attribute indexes and classification, which are seismic information, structure types, earthquake damage parts and disaster causation factors. The final object is to set up an engineering structural seismic damage database based on these four attribute indicators and classification, and eventually build a website providing seismic damage photographs.

Keywords: attribute index, classification method, earthquake damage picture, engineering structure

Procedia PDF Downloads 756
10789 Fault Tree Analysis and Bayesian Network for Fire and Explosion of Crude Oil Tanks: Case Study

Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia

Abstract:

In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.

Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety

Procedia PDF Downloads 650
10788 The Effect of Mechanical Stress on the Magnetic Structure and Properties of Ferromagnetic Microwires in Glass Insulation

Authors: N. N. Orlova, A. S. Aronin, Yu. P. Kabanov, S. I. Bozhko, V. S. Gornakov

Abstract:

We have investigated the change of the magnetic structure and the hysteresis properties of iron-based microwires after decreasing levels of internal mechanical stresses. The magnetic structure was investigated by the method of magneto-optical indicator film and the method of magnetic force microscopy. The hysteresis properties were studied by the vibrating sample magnetometer. The stresses were decreased by removing the glass coat and/or by low-temperature isothermal annealing. Previously, the authors carried out experimentally investigation of the magnetic structure of Fe-based microwire using these methods. According to the obtained results the domain structure of a microwire with a positive magnetostriction is composed of the inner cylindrical domains with the magnetization along the wire axis and the surface layer of the ring shape domains with the radial direction of magnetization. Surface ring domains with opposite magnetization direction (i.e., to the axis or from the axis) alternate with each other. For the first time the size of magnetic domains was determined experimentally. In this study it was found that in the iron-based microwires the value of the coercive force can be reduce more than twice by decreasing levels of internal mechanical stresses. Decrease of the internal stress value by the relaxation annealing influence on the magnetic structure. So in the as-prepared microwires observed local deviations of the magnetization of the magnetic core domains from the axis of the wire. After low-temperature annealing the local deviations of magnetization is not observed.

Keywords: amorphous microwire, magnetic structure, internal stress, hysteresis properties, ferromagnetic

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10787 Identification of Significant Genes in Rheumatoid Arthritis, Melanoma Metastasis, Ulcerative Colitis and Crohn’s Disease

Authors: Krishna Pal Singh, Shailendra Kumar Gupta, Olaf Wolkenhauer

Abstract:

Background: Our study aimed to identify common genes and potential targets across the four diseases, which include rheumatoid arthritis, melanoma metastasis, ulcerative colitis, and Crohn’s disease. We used a network and systems biology approach to identify the hub gene, which can act as a potential target for all four disease conditions. The regulatory network was extracted from the PPI using the MCODE module present in Cytoscape. Our objective was to investigate the significance of hub genes in these diseases using gene ontology and KEGG pathway enrichment analysis. Methods: Our methodology involved collecting disease gene-related information from DisGeNET databases and performing protein-protein interaction (PPI) network and core genes screening. We then conducted gene ontology and KEGG pathway enrichment analysis. Results: We found that IL6 plays a critical role in all disease conditions and in different pathways that can be associated with the development of all four diseases. Conclusions: The theoretical importance of our research is that we employed various systems and structural biology techniques to identify a crucial protein that could serve as a promising target for treating multiple diseases. Our data collection and analysis procedures involved rigorous scrutiny, ensuring high-quality results. Our conclusion is that IL6 plays a significant role in all four diseases, and it can act as a potential target for treating them. Our findings may have important implications for the development of novel therapeutic interventions for these diseases.

Keywords: melanoma metastasis, rheumatoid arthritis, inflammatory bowel diseases, integrated bioinformatics analysis

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10786 Features of the Functional and Spatial Organization of Railway Hubs as a Part of the Urban Nodal Area

Authors: Khayrullina Yulia Sergeevna, Tokareva Goulsine Shavkatovna

Abstract:

The article analyzes the modern major railway hubs as a main part of the Urban Nodal Area (UNA). The term was introduced into the theory of urban planning at the end of the XX century. Tokareva G.S. jointly with Gutnov A.E. investigated the structure-forming elements of the city. UNA is the basic unit, the "cell" of the city structure. Specialization is depending on the position in the frame or the fabric of the city. This is related to feature of its organization. Spatial and functional features of UNA proposed to investigate in this paper. The base object for researching are railway hubs as connective nodes of inner and extern-city communications. Research used a stratified sampling type with the selection of typical objects. Research is being conducted on the 14 railway hubs of the native and foreign experience of the largest cities with a population over 1 million people located in one and close to the Russian climate zones. Features of the organization identified in the complex research of functional and spatial characteristics based on the hypothesis of the existence of dual characteristics of the organization of urban nodes. According to the analysis, there is using the approximation method that enable general conclusions of a representative selection of the entire population of railway hubs and it development’s area. Results of the research show specific ratio of functional and spatial organization of UNA based on railway hubs. Based on it there proposed typology of spaces and urban nodal areas. Identification of spatial diversity and functional organization’s features of the greatest railway hubs and it development’s area gives an indication of the different evolutionary stages of formation approaches. It help to identify new patterns for the complex and effective design as a prediction of the native hub’s development direction.

Keywords: urban nodal area, railway hubs, features of structural, functional organization

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10785 Chemotactic Behaviour of Human Mesenchymal Stem Cells in Response to Silicate Substituted Hydroxyapatite

Authors: Dinara Ikramova, Karin A. Hing, Simon C. F. Rawlinson

Abstract:

Silicate-substituted hydroxyapatite (SiHA) has been shown to enhance bone regeneration in vivo compared with phase pure stoichiometric hydroxyapatite. Evidence suggests that substrate chemistry dependent formation of a permissive protein layer on the surface of synthetic bone graft substitute materials is key for bioactivity and cell attachment. However, little information is available on whether the substrate chemistry may affect cell migration and recruitment. The aim of this study is to investigate whether or not human Mesenchymal Stem Cells (hMSCs) exhibit a chemotactic response to SiHA porous granules and if it can be linked to either the ion exchange or protein sequestering and enrichment on the surface of the material. 150mg of SiHA granules with 80% total porosity and 20% strut porosity were incubated in 1ml of either Serum Free Media (SFM) or 10% Serum Containing Media (SCM) under static cell culture conditions (37°C, 5% CO2) in absence of cells. Protein sequestering and exchange of calcium, phosphate and silicate ions were analysed at 0.5, 1, 2, 4, 8, 16 and 24 hours with n=12 per time point. Migration of hMSCs in the presence of 150mg of SiHA granules was assessed over 24 hours using a modified transwell migration system in either SFM or SCM (n=6) with 30% serum containing media acting as a positive control. At 24 hours protein sequestering and ionic exchange were analysed, and the number of cells was quantified using a high throughput confocal microscope (IN Cell Analyser 6000). In acellular condition, both calcium and phosphate ion concentrations in media showed a decrease at 24 hours which was greater in SFM than in SCM. This suggests possible formation and precipitation of a bone like apatite on the surface of SiHA. Reduction in this activity observed in SCM indicates that the presence of serum proteins is interfering with the ion exchange at the material and media interface. Adsorbed protein levels showed fluctuation over time followed by sharp decrease at 24 hours, suggesting a possible protein rearrangement on the surface of the material. The ion analysis performed on SFM and SCM after 24-hour incubation with cells in the presence of granules showed a greater reduction in phosphate concentration in both SFM and SCM compared to phosphate levels in acellular condition. Silicate concentration in SCM increased from 1.6mM (absence of cells) to 5.1mM (presence of cells). This indicates that the cells are promoting the uptake of phosphate and release of silicate ions. No significant change was seen in levels of adsorbed proteins in the presence and absence of cells. Further analysis is required to determine whether the species of these proteins change over time. The analysis of cell migration after 24-hour incubation showed more cells migrating towards the granules, 12.7% in SFM and 8.3% in SCM, than in positive control, 4.5% in SFM and 3.6% in SCM respectively. These results suggest that SiHA has a chemotactic activity independent of serum proteins. A property which has not previously been demonstrated for a synthetic bone graft material.

Keywords: cell migration, hMSCs, SiHA, transwell migration system

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10784 Application of Microparticulated Whey Proteins in Reduced-Fat Yogurt through Hot-Extrusion: Influence on Physicochemical and Sensory Properties

Authors: M. K. Hossain, J. Keidel, O. Hensel, M. Diakite

Abstract:

Fat reduced dairy products are holding a potential market due to health reason. Due to less creamy, and pleasantness, reduced and/or low-fat dairy products are getting less consumer acceptance whereas the fat molecule provides smooth, creamy and a pleasant mouthfeel in dairy products especially yogurt & ice cream. This study was aimed to investigate whether the application of microparticulated whey proteins (MWPs) processed by extrusion cooking, the reduced fat yogurt can achieve similar or higher creaminess compared to whole milk (3.8% fat) and skimmed milk (0.5% fat) yogurt. Full cream and skimmed milk were used to prepare natural stirred yogurt, as well as the dry matter content, also adjusted up to 16% with skimmed milk powder. Whey protein concentrates (WPC80) were used to produce MWPs in particle size of d50 > 5 µm, d50 3<5 µm and d50 < 3 µm through the hot-extrusion process with a screw speed of 400, 600 and 1000 rpm respectively. Furthermore, the commercially available microparticulated whey protein called Simplesse® was also applied in order to compare with extruded MWPs. The rheological and sensory properties of yogurt were assessed, and data were analyzed statistically. The applications of extruded MWPs with 600 and 1000 rpm were achieved significantly (p < 0.05) higher creaminess and preference compared to the whole and skimmed milk yogurt whereas, 400 rpm got lower preference. On the other hand, Simplesse® obtained the lowest creaminess and preference compared to other yogurts, although the contribution of dry matter in yogurt was same as extruded MWPs. The creaminess and viscosities were strongly (r = 0.62) correlated, furthermore, the viscosity from sensory evaluation and the dynamic viscosity of yogurt was also significantly (r = 0.72) correlated which clarifies that the performance of sensory panelists as well as the quality of the products.

Keywords: microparticulation, hot-extrusion, reduced-fat yogurt, whey protein concentrate

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10783 A Ground Structure Method to Minimize the Total Installed Cost of Steel Frame Structures

Authors: Filippo Ranalli, Forest Flager, Martin Fischer

Abstract:

This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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10782 Neuronal Networks for the Study of the Effects of Cosmic Rays on Climate Variations

Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

Abstract:

The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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10781 Structural Health Monitoring and Damage Structural Identification Using Dynamic Response

Authors: Reza Behboodian

Abstract:

Monitoring the structural health and diagnosing their damage in the early stages has always been one of the topics of concern. Nowadays, research on structural damage detection methods based on vibration analysis is very extensive. Moreover, these methods can be used as methods of permanent and timely inspection of structures and prevent further damage to structures. Non-destructive methods are the low-cost and economical methods for determining the damage of structures. In this research, a non-destructive method for detecting and identifying the failure location in structures based on dynamic responses resulting from time history analysis is proposed. When the structure is damaged due to the reduction of stiffness, and due to the applied loads, the displacements in different parts of the structure were increased. In the proposed method, the damage position is determined based on the calculation of the strain energy difference in each member of the damaged structure and the healthy structure at any time. Defective members of the structure are indicated by the amount of strain energy relative to the healthy state. The results indicated that the proper accuracy and performance of the proposed method for identifying failure in structures.

Keywords: failure, time history analysis, dynamic response, strain energy

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10780 A Wall Law for Two-Phase Turbulent Boundary Layers

Authors: Dhahri Maher, Aouinet Hana

Abstract:

The presence of bubbles in the boundary layer introduces corrections into the log law, which must be taken into account. In this work, a logarithmic wall law was presented for bubbly two phase flows. The wall law presented in this work was based on the postulation of additional turbulent viscosity associated with bubble wakes in the boundary layer. The presented wall law contained empirical constant accounting both for shear induced turbulence interaction and for non-linearity of bubble. This constant was deduced from experimental data. The wall friction prediction achieved with the wall law was compared to the experimental data, in the case of a turbulent boundary layer developing on a vertical flat plate in the presence of millimetric bubbles. A very good agreement between experimental and numerical wall friction prediction was verified. The agreement was especially noticeable for the low void fraction when bubble induced turbulence plays a significant role.

Keywords: bubbly flows, log law, boundary layer, CFD

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10779 Learning Dynamic Representations of Nodes in Temporally Variant Graphs

Authors: Sandra Mitrovic, Gaurav Singh

Abstract:

In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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10778 Investigation of the Effect of Lecturers' Attributes on Students' Interest in Learning Statistic Ghanaian Tertiary Institutions

Authors: Samuel Asiedu-Addo, Jonathan Annan, Yarhands Dissou Arthur

Abstract:

The study aims to explore the relational effect of lecturers’ personal attribute on student’s interest in statistics. In this study personal attributes of lecturers’ such as lecturer’s dynamism, communication strategies and rapport in the classroom as well as applied knowledge during lecture were examined. Here, exploratory research design was used to establish the effect of lecturer’s personal attributes on student’s interest. Data were analyzed by means of confirmatory factor analysis and structural equation modeling (SEM) using the SmartPLS 3 program. The study recruited 376 students from the faculty of technical and vocational education of the University of Education Winneba Kumasi campus, and Ghana Technology University College as well as Kwame Nkrumah University of science and Technology. The results revealed that personal attributes of an effective lecturer were lecturer’s dynamism, rapport, communication and applied knowledge contribute (52.9%) in explaining students interest in statistics. Our regression analysis and structural equation modeling confirm that lecturers personal attribute contribute effectively by predicting student’s interest of 52.9% and 53.7% respectively. The paper concludes that the total effect of a lecturer’s attribute on student’s interest is moderate and significant. While a lecturer’s communication and dynamism were found to contribute positively to students’ interest, they were insignificant in predicting students’ interest. We further showed that a lecturer’s personal attributes such as applied knowledge and rapport have positive and significant effect on tertiary student’s interest in statistic, whilst lecturers’ communication and dynamism do not significantly affect student interest in statistics; though positively related.

Keywords: student interest, effective teacher, personal attributes, regression and SEM

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10777 Artificial Intelligence Methods in Estimating the Minimum Miscibility Pressure Required for Gas Flooding

Authors: Emad A. Mohammed

Abstract:

Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

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10776 Acoustic Induced Vibration Response Analysis of Honeycomb Panel

Authors: Po-Yuan Tung, Jen-Chueh Kuo, Chia-Ray Chen, Chien-Hsing Li, Kuo-Liang Pan

Abstract:

The main-body structure of satellite is mainly constructed by lightweight material, it should be able to withstand certain vibration load during launches. Since various kinds of change possibility in the space, it is an extremely important work to study the random vibration response of satellite structure. This paper based on the reciprocity relationship between sound and structure response and it will try to evaluate the dynamic response of satellite main body under random acoustic load excitation. This paper will study the technical process and verify the feasibility of sonic-borne vibration analysis. One simple plate exposed to the uniform acoustic field is utilized to take some important parameters and to validate the acoustics field model of the reverberation chamber. Then import both structure and acoustic field chamber models into the vibro-acoustic coupling analysis software to predict the structure response. During the modeling process, experiment verification is performed to make sure the quality of numerical models. Finally, the surface vibration level can be calculated through the modal participation factor, and the analysis results are presented in PSD spectrum.

Keywords: vibration, acoustic, modal, honeycomb panel

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10775 A Low-Power Comparator Structure with Arbitrary Pre-Amplification Delay

Authors: Ata Khorami, Mohammad Sharifkhani

Abstract:

In the dynamic comparators, the pre-amplifier amplifies the input differential voltage and when the output Vcm of the pre-amplifier becomes larger than Vth of the latch input transistors, the latch is activated and finalizes the comparison. As a result, the pre-amplification delay is fixed to a value and cannot be set at the minimum required delay, thus, significant power and delay are imposed. In this paper, a novel structure is proposed through which the pre-amplification delay can be set at any low value saving power and time. Simulations show that using the proposed structure, by setting the pre-amplification delay at the minimum required value the power and comparison delay can be reduced by 55% and 100ps respectively.

Keywords: dynamic comparator, low power comparator, analog to digital converter, pre-amplification delay

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10774 Potential of Grass Silage as a Source of Nutrients in Poultry Production

Authors: Hamim Abbas, Jean Luc-Hornick, Isabelle Dufrasne

Abstract:

Feed costs constitute over 60% of total expenses in organic layer poultry production, with feed protein supply being a significant concern. Alfalfa-based dehydrated silage pellets are mainly diets composed of leaves (ABSP), which are non-conventional protein sources that could enhance profits by reducing feed costs and ensuring consistent availability. This experiment studied the effects on the performances of Novogen Brown light layers of a commercial control diet replaced with 10% ABSP. After a 21-day trial, this diet (ABSP) has improved the laying rate, yolk color of eggs, feed conversion rate, ω−3 (PUFAs) and ω−6/ω−3 ratio (P<0.05) while the body weight and egg weight were degraded with the substitution of the ABSP in the diet(P>0.05). The laying rate showed a tendency to increase (P=0.06). These findings suggest that ABSP can replace at least 10% of the feed in organic layer diets without compromising production parameters negatively.

Keywords: alfalfa, silage, pellet, organic layers

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10773 EGF Serum Level in Diagnosis and Prediction of Mood Disorder in Adolescents and Young Adults

Authors: Monika Dmitrzak-Weglarz, Aleksandra Rajewska-Rager, Maria Skibinska, Natalia Lepczynska, Piotr Sibilski, Joanna Pawlak, Pawel Kapelski, Joanna Hauser

Abstract:

Epidermal growth factor (EGF) is a well-known neurotrophic factor that involves in neuronal growth and synaptic plasticity. The proteomic research provided in order to identify novel candidate biological markers for mood disorders focused on elevated EGF serum level in patients during depression episode. However, the EGF association with mood disorder spectrum among adolescents and young adults has not been studied extensively. In this study, we aim to investigate the serum levels of EGF in adolescents and young adults during hypo/manic, depressive episodes and in remission compared to healthy control group. In our study, we involved 80 patients aged 12-24 years in 2-year follow-up study with a primary diagnosis of mood disorder spectrum, and 35 healthy volunteers matched by age and gender. Diagnoses were established according to DSM-IV-TR criteria using structured clinical interviews: K-SADS for child and adolescents, and SCID for young adults. Clinical and biological evaluations were made at baseline and euthymic mood (at 3th or 6th month of treatment and after 1 and 2 years). The Young Mania Rating Scale and Hamilton Rating Scale for Depression were used for assessment. The study protocols were approved by the relevant ethics committee. Serum protein concentration was determined by Enzyme-Linked Immunosorbent Assays (ELISA) method. Human EGF (cat. no DY 236) DuoSet ELISA kit was used (R&D Systems). Serum EGF levels were analysed with following variables: age, age under 18 and above 18 years old, sex, family history of affective disorders, drug-free vs. medicated. Shapiro-Wilk test was used to test the normality of the data. The homogeneity of variance was calculated with Levene’s test. EGF levels showed non-normal distribution and the homogeneity of variance was violated. Non-parametric tests: Mann-Whitney U test, Kruskall-Wallis ANOVA, Friedman’s ANOVA, Wilcoxon signed rank test, Spearman correlation coefficient was applied in the analyses The statistical significance level was set at p<0.05. Elevated EGF level at baseline (p=0.001) and at month 24 (p=0.02) was detected in study subjects compared with controls. Increased EGF level in women at month 12 (p=0.02) compared to men in study group have been observed. Using Wilcoxon signed rank test differences in EGF levels were detected: decrease from baseline to month 3 (p=0.014) and increase comparing: month 3 vs. 24 (p=0.013); month 6 vs. 12 (p=0.021) and vs. 24 (p=0.008). EGF level at baseline was negatively correlated with depression and mania occurrence at 24 months. EGF level at 24 months was positively correlated with depression and mania occurrence at 12 months. No other correlations of EGF levels with clinical and demographical variables have been detected. The findings of the present study indicate that EGF serum level is significantly elevated in the study group of patients compared to the controls. We also observed fluctuations in EGF levels during two years of disease observation. EGF seems to be useful as an early marker for prediction of diagnosis, course of illness and treatment response in young patients during first episode od mood disorders, which requires further investigation. Grant was founded by National Science Center in Poland no 2011/03/D/NZ5/06146.

Keywords: biological marker, epidermal growth factor, mood disorders, prediction

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10772 Biodistribution of Fluorescence-Labelled Epidermal Growth Factor Protein from Slow Release Nanozolid Depots in Mouse

Authors: Stefan Gruden, Charlott Brunmark, Bo Holmqvist, Erwin D. Brenndorfer, Martin Johansson, Jian Liu, Ying Zhao, Niklas Axen, Moustapha Hassan

Abstract:

Aim: The study was designed to evaluate the ability of the calcium sulfate-based NanoZolid® drug delivery technology to locally release the epidermal growth factor (EGF) protein while maintaining its biological activity. Methods: NanoZolid-formulated EGF protein labelled with a near-infrared dye (EGF-NIR) depots or EGF-NIR dissolved in PBS were injected subcutaneously into mice bearing EGF receptor (EGFR) positive human A549 lung cancer tumors inoculated subcutaneously. The release and biodistribution of the EGF-NIR were investigated in vivo longitudinally up to 96 hours post-administration, utilizing whole-body fluorescence imaging. In order to confirm the in vivo findings, histological analysis of tumor cryosections was performed to investigate EGF-NIR fluorescent signal and EGFR expression level by immunofluorescence labelling. Results: The in vivo fluorescence imaging showed a controlled release profile of the EGF-NIR loaded in the NanoZolid depots compared to free EGF-NIR. Histological analysis of the tumors further demonstrated a prevailing distribution of EGF-NIR in regions with high levels of EGFR expression. Conclusion: Calcium sulfate based depots can be used to formulate EGF while maintaining its biological activity, e.g., receptor binding capability. This may have good clinical potential for local delivery of biomolecules to enhance treatment efficacy and minimize systemic adverse effects.

Keywords: bioresorbable, calcium sulfate, controlled release, NanoZolid

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10771 The Transition from National Policy to Institutional Practice of Vietnamese English Language Teacher Education

Authors: Thi Phuong Lan Nguyen

Abstract:

The English Language Teacher Education (ELTE) in Vietnam is rapidly changing to address the new requirements of the globalization and socialization era. Although there has been a range of investments and innovation in policy and curriculum, tertiary educators and learners do not engage in the enactment. It is vital to understand the practices at the tertiary education level. The study is to understand the higher education curriculum development policy, both in theory and in practice across four representatives of ELTE institutions in the North of Vietnam. The lecturers’ perceptions about the extent to which the enacted curriculum is aligned with national standards will be explored. Nineteen policy documents, seventy surveys, and twelve interviews with lecturers and instructional leaders across these four Vietnamese Northern ELTE institutions have been analyzed to investigate how the policy shape the practice. The two most significant findings are (i) a low level of alignment between curriculum and soft-skills standards of the graduates required by the Vietnamese Ministry of Education and Training (MOET) and (ii) incoherence between current national policy and these institutions’ implementation. In order to address these gaps, it is strongly recommended that curriculum needs to be further developed, focusing more on the institutional outcomes, MOET’s standards, and the social demands in times of globalization. More importantly, professional development in ELTE is vital for a range of curriculum and educational policy stakeholders. The study helps to develop the English teaching profession in Vietnam in a systematic way, from policymakers to implementers, and from instructors to learners. Its significance lies in its relevance to English teaching careers, particularly within the researcher’s specific context, yet also remains relevant to ELTE in other parts of Vietnam and in other EFL (English as a Foreign Language) countries.

Keywords: curriculum, English language teaching education, policy implementation, standard, teaching practice

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10770 Foreign Language Faculty Mentorship in Vietnam: An Interpretive Qualitative Study

Authors: Hung Tran

Abstract:

This interpretive qualitative study employed three theoretical lenses: Bronfenbrenner’s (1979) Ecological System of Human Development, Vygotsky’s (1978) Sociocultural Theory of Development, and Knowles’s (1970) Adult Learning Theory as the theoretical framework in connection with the constructivist research paradigm to investigate into positive and negative aspects of the extant English as a Foreign Language (EFL) faculty mentoring programs at four higher education institutions (HEIs) in the Mekong River Delta (MRD) of Vietnam. Four apprentice faculty members (mentees), four experienced faculty members (mentors), and two associate deans (administrators) from these HEIs participated in two tape-recorded individual interviews in the Vietnamese language. Twenty interviews were transcribed verbatim and translated into English with verification. The initial analysis of data reveals that the mentoring program, which is mandated by Vietnam’s Ministry of Education and Training, has been implemented differently at these HEIs due to a lack of officially-documented mentoring guidance. Other general themes emerging from the data include essentials of the mentoring program, approaches of the mentoring practice, the mentee – mentor relationship, and lifelong learning beyond the mentoring program. Practically, this study offers stakeholders in the mentoring cycle description of benefits and best practices of tertiary EFL mentorship and a suggested mentoring program that is metaphorically depicted as “a lifebuoy” for its current and potential administrators and mentors to help their mentees survive in the first years of teaching. Theoretically, this study contributes to the world’s growing knowledge of post-secondary mentorship by enriching the modest literature on Asian tertiary EFL mentorship.

Keywords: faculty mentorship, mentees, mentors, administrator, the MRD, Vietnam

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10769 A Secreted Protein Can Attenuate High Fat Diet Induced Obesity and Metabolic Syndrome in Mice

Authors: Abdul Soofi, Katherine Wolf, Egon Ranghini, Gregory Dressler

Abstract:

Obesity and its associated complications, such as insulin resistance and non-alcoholic fatty liver disease, are reaching epidemic proportions. In mice, the TGF-β superfamily is implicated in the regulation of white and brown adipose tissues differentiation. The Kielin/Chordin-like Protein (KCP) is a secreted regulator of the TGF-β superfamily pathways that can inhibit both TGF-β and Activin signals while enhancing the Bone Morphogenetic protein (BMP) signaling. However, the effects of KCP on metabolism and obesity have not been studied in animal models. Thus, we examined the effects of KCP loss or gain of function in mice that were maintained on either a regular or a high fat diet. Loss of KCP sensitized mice to obesity and associated complications such as hepatic steatosis and glucose intolerance. In contrast, transgenic mice that expressed KCP in the kidney, liver and adipose tissues were resistant to developing high fat diet induced obesity and had significantly reduced white adipose tissue. KCP over-expression was able to shift the pattern of Smad signaling in vivo, to increase the levels of P-Smad1 and decrease P-Smad3, resulting in resistance to high fat diet induced hepatic steatosis and glucose intolerance. In aging mice, loss of KCP promoted liver pathology even when mice were fed a normal diet. The data demonstrate that shifting the TGF-β superfamily signaling with a secreted inhibitor or enhancer can alter the physiology of adipose tissue to reduce obesity and can inhibit the initiation and progression of hepatic steatosis to significantly reduce the effects of high fat diet induced metabolic disease.

Keywords: adipose tissue, KCP, obesity, TGF-β, BMP, hepatic steatosis, metabolic syndrome

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10768 Time Series Modelling and Prediction of River Runoff: Case Study of Karkheh River, Iran

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R2) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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10767 Ensemble-Based SVM Classification Approach for miRNA Prediction

Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam

Abstract:

In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.

Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data

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10766 Implementation of Sensor Fusion Structure of 9-Axis Sensors on the Multipoint Control Unit

Authors: Jun Gil Ahn, Jong Tae Kim

Abstract:

In this paper, we study the sensor fusion structure on the multipoint control unit (MCU). Sensor fusion using Kalman filter for 9-axis sensors is considered. The 9-axis inertial sensor is the combination of 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We implement the sensor fusion structure among the sensor hubs in MCU and measure the execution time, power consumptions, and total energy. Experiments with real data from 9-axis sensor in 20Mhz show that the average power consumptions are 44mW and 48mW on Cortx-M0 and Cortex-M3 MCU, respectively. Execution times are 613.03 us and 305.6 us respectively.

Keywords: 9-axis sensor, Kalman filter, MCU, sensor fusion

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10765 A Study on Golden Ratio (ф) and Its Implications on Seismic Design Using ETABS

Authors: Vishal A. S. Salelkar, Sumitra S. Kandolkar

Abstract:

Golden ratio (ф) or Golden mean or Golden section, as it is often referred to, is a proportion or a mean, which is often used by architects while conceiving the aesthetics of a structure. Golden Ratio (ф) is an irrational number that can be roughly rounded to 1.618 and is derived out of quadratic equation x2-x-1=0. The use of Golden Ratio (ф) can be observed throughout history, as far as ancient Egyptians, which later peaked during the Greek golden age. The use of this design technique is very much prevalent. At present, architects around the world prefer this as one of the primary techniques to decide aesthetics. In this study, an analysis has been performed to investigate whether the use of the golden ratio while planning a structure has any effects on the seismic behavior of the structure. The structure is modeled and analyzed on ETABS (by Computers and Structures, Inc.) for Seismic requirements equivalent to Zone III (Region: Goa-India) as per Indian Standard Code IS-1893. The results were compared to that of an identical structure modeled along the lines of normal design philosophy, not using the Golden Ratio tools. The results were then compared for Story Shear, Story Drift, and Story Displacement Readings. Improvement in performance, although slight, but was observed. Similar improvements were also observed in subsequent iterations, performed using time-acceleration data of previous major earthquakes matched to Zone III as per IS-1893.

Keywords: ETABS, golden ratio, seismic design, structural behavior

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10764 Study of the Use of Artificial Neural Networks in Islamic Finance

Authors: Kaoutar Abbahaddou, Mohammed Salah Chiadmi

Abstract:

The need to find a relevant way to predict the next-day price of a stock index is a real concern for many financial stakeholders and researchers. We have known across years the proliferation of several methods. Nevertheless, among all these methods, the most controversial one is a machine learning algorithm that claims to be reliable, namely neural networks. Thus, the purpose of this article is to study the prediction power of neural networks in the particular case of Islamic finance as it is an under-looked area. In this article, we will first briefly present a review of the literature regarding neural networks and Islamic finance. Next, we present the architecture and principles of artificial neural networks most commonly used in finance. Then, we will show its empirical application on two Islamic stock indexes. The accuracy rate would be used to measure the performance of the algorithm in predicting the right price the next day. As a result, we can conclude that artificial neural networks are a reliable method to predict the next-day price for Islamic indices as it is claimed for conventional ones.

Keywords: Islamic finance, stock price prediction, artificial neural networks, machine learning

Procedia PDF Downloads 220