Search results for: linear induction motor
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4861

Search results for: linear induction motor

901 Reading Comprehension in Profound Deaf Readers

Authors: S. Raghibdoust, E. Kamari

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Research show that reduced functional hearing has a detrimental influence on the ability of an individual to establish proper phonological representations of words, since the phonological representations are claimed to mediate the conceptual processing of written words. Word processing efficiency is expected to decrease with a decrease in functional hearing. In other words, it is predicted that hearing individuals would be more capable of word processing than individuals with hearing loss, as their functional hearing works normally. Studies also demonstrate that the quality of the functional hearing affects reading comprehension via its effect on their word processing skills. In other words, better hearing facilitates the development of phonological knowledge, and can promote enhanced strategies for the recognition of written words, which in turn positively affect higher-order processes underlying reading comprehension. The aims of this study were to investigate and compare the effect of deafness on the participants’ abilities to process written words at the lexical and sentence levels through using two online and one offline reading comprehension tests. The performance of a group of 8 deaf male students (ages 8-12) was compared with that of a control group of normal hearing male students. All the participants had normal IQ and visual status, and came from an average socioeconomic background. None were diagnosed with a particular learning or motor disability. The language spoken in the homes of all participants was Persian. Two tests of word processing were developed and presented to the participants using OpenSesame software, in order to measure the speed and accuracy of their performance at the two perceptual and conceptual levels. In the third offline test of reading comprehension which comprised of semantically plausible and semantically implausible subject relative clauses, the participants had to select the correct answer out of two choices. The data derived from the statistical analysis using SPSS software indicated that hearing and deaf participants had a similar word processing performance both in terms of speed and accuracy of their responses. The results also showed that there was no significant difference between the performance of the deaf and hearing participants in comprehending semantically plausible sentences (p > 0/05). However, a significant difference between the performances of the two groups was observed with respect to their comprehension of semantically implausible sentences (p < 0/05). In sum, the findings revealed that the seriously impoverished sentence reading ability characterizing the profound deaf subjects of the present research, exhibited their reliance on reading strategies that are based on insufficient or deviant structural knowledge, in particular in processing semantically implausible sentences, rather than a failure to efficiently process written words at the lexical level. This conclusion, of course, does not mean to say that deaf individuals may never experience deficits at the word processing level, deficits that impede their understanding of written texts. However, as stated in previous researches, it sounds reasonable to assume that the more deaf individuals get familiar with written words, the better they can recognize them, despite having a profound phonological weakness.

Keywords: deafness, reading comprehension, reading strategy, word processing, subject and object relative sentences

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900 An Explanatory Study Approach Using Artificial Intelligence to Forecast Solar Energy Outcome

Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

Procedia PDF Downloads 157
899 Assessment and Evaluation Resilience of Urban Neighborhoods in Coping with Natural Disasters in in the Metropolis of Tabriz (Case Study: Region 6 of Tabriz)

Authors: Ali panahi-Kosar Khosravi

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Earthquake resilience is one of the most important theoretical and practical concepts in crisis management. Over the past few decades, the rapid growth of urban areas and developing lower urban areas (especially in developing countries) have made them more vulnerable to human and natural crises. Therefore, the resilience of urban communities, especially low-income and unhealthy neighborhoods, is of particular importance. The present study seeks to assess and evaluate the resilience of neighborhoods in the center of district 6 of Tabriz in terms of awareness, knowledge and personal skills, social and psychological capital, managerial-institutional, and the ability to return to appropriate and sustainable conditions. The research method in this research is descriptive-analytical. The authors used library and survey methods to collect information and a questionnaire to assess resilience. The statistical population of this study is the total households living in the four neighborhoods of Shanb Ghazan, Khatib, Gharamalek, and Abuzar alley. Three hundred eighty-four families from four neighborhoods were selected based on the Cochran formula using a simple random sampling method. A one-sample t-test, simple linear regression, and structural equations were used to test the research hypotheses. Findings showed that only two social and psychological awareness and capital indicators in district 6 of Tabriz had a favorable and approved status. Therefore, considering the multidimensional concept of resilience, district 6 of Tabriz is in an unfavorable resilience situation. Also, the findings based on the analysis of variance indicated no significant difference between the neighborhoods of district 6 in terms of resilience, and most neighborhoods are in an unfavorable situation.

Keywords: resilience, statistical analysis, earthquake, district 6 of tabriz

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898 Bio-Functionalized Silk Nanofibers for Peripheral Nerve Regeneration

Authors: Kayla Belanger, Pascale Vigneron, Guy Schlatter, Bernard Devauchelle, Christophe Egles

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A severe injury to a peripheral nerve leads to its degeneration and the loss of sensory and motor function. To this day, there still lacks a more effective alternative to the autograft which has long been considered the gold standard for nerve repair. In order to overcome the numerous drawbacks of the autograft, tissue engineered biomaterials may be effective alternatives. Silk fibroin is a favorable biomaterial due to its many advantageous properties such as its biocompatibility, its biodegradability, and its robust mechanical properties. In this study, bio-mimicking multi-channeled nerve guidance conduits made of aligned nanofibers achieved by electrospinning were functionalized with signaling biomolecules and were tested in vitro and in vivo for nerve regeneration support. Silk fibroin (SF) extracted directly from silkworm cocoons was put in solution at a concentration of 10wt%. Poly(ethylene oxide) (PEO) was added to the resulting SF solution to increase solution viscosity and the following three electrospinning solutions were made: (1) SF/PEO solution, (2) SF/PEO solution with nerve growth factor and ciliary neurotrophic factor, and (3) SF/PEO solution with nerve growth factor and neurotrophin-3. Each of these solutions was electrospun into a multi-layer architecture to obtain mechanically optimized aligned nanofibrous mats. For in vitro studies, aligned fibers were treated to induce β-sheet formation and thoroughly rinsed to eliminate presence of PEO. Each material was tested using rat embryo neuron cultures to evaluate neurite extension and the interaction with bio-functionalized or non-functionalized aligned fibers. For in vivo studies, the mats were rolled into 5mm long multi-, micro-channeled conduits then treated and thoroughly rinsed. The conduits were each subsequently implanted between a severed rat sciatic nerve. The effectiveness of nerve repair over a period of 8 months was extensively evaluated by cross-referencing electrophysiological, histological, and movement analysis results to comprehensively evaluate the progression of nerve repair. In vitro results show a more favorable interaction between growing neurons and bio-functionalized silk fibers compared to pure silk fibers. Neurites can also be seen having extended unidirectionally along the alignment of the nanofibers which confirms a guidance factor for the electrospun material. The in vivo study has produced positive results for the regeneration of the sciatic nerve over the length of the study, showing contrasts between the bio-functionalized material and the non-functionalized material along with comparisons to the experimental control. Nerve regeneration has been evaluated not only by histological analysis, but also by electrophysiological assessment and motion analysis of two separate natural movements. By studying these three components in parallel, the most comprehensive evaluation of nerve repair for the conduit designs can be made which can, therefore, more accurately depict their overall effectiveness. This work was supported by La Région Picardie and FEDER.

Keywords: electrospinning, nerve guidance conduit, peripheral nerve regeneration, silk fibroin

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897 A Case Report on Cognitive-Communication Intervention in Traumatic Brain Injury

Authors: Nikitha Francis, Anjana Hoode, Vinitha George, Jayashree S. Bhat

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The interaction between cognition and language, referred as cognitive-communication, is very intricate, involving several mental processes such as perception, memory, attention, lexical retrieval, decision making, motor planning, self-monitoring and knowledge. Cognitive-communication disorders are difficulties in communicative competencies that result from underlying cognitive impairments of attention, memory, organization, information processing, problem solving, and executive functions. Traumatic brain injury (TBI) is an acquired, non - progressive condition, resulting in distinct deficits of cognitive communication abilities such as naming, word-finding, self-monitoring, auditory recognition, attention, perception and memory. Cognitive-communication intervention in TBI is individualized, in order to enhance the person’s ability to process and interpret information for better functioning in their family and community life. The present case report illustrates the cognitive-communicative behaviors and the intervention outcomes of an adult with TBI, who was brought to the Department of Audiology and Speech Language Pathology, with cognitive and communicative disturbances, consequent to road traffic accident. On a detailed assessment, she showed naming deficits along with perseverations and had severe difficulty in recalling the details of the accident, her house address, places she had visited earlier, names of people known to her, as well as the activities she did each day, leading to severe breakdowns in her communicative abilities. She had difficulty in initiating, maintaining and following a conversation. She also lacked orientation to time and place. On administration of the Manipal Manual of Cognitive Linguistic Abilities (MMCLA), she exhibited poor performance on tasks related to visual and auditory perception, short term memory, working memory and executive functions. She attended 20 sessions of cognitive-communication intervention which followed a domain-general, adaptive training paradigm, with tasks relevant to everyday cognitive-communication skills. Compensatory strategies such as maintaining a dairy with reminders of her daily routine, names of people, date, time and place was also recommended. MMCLA was re-administered and her performance in the tasks showed significant improvements. Occurrence of perseverations and word retrieval difficulties reduced. She developed interests to initiate her day-to-day activities at home independently, as well as involve herself in conversations with her family members. Though she lacked awareness about her deficits, she actively involved herself in all the therapy activities. Rehabilitation of moderate to severe head injury patients can be done effectively through a holistic cognitive retraining with a focus on different cognitive-linguistic domains. Selection of goals and activities should have relevance to the functional needs of each individual with TBI, as highlighted in the present case report.

Keywords: cognitive-communication, executive functions, memory, traumatic brain injury

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896 Major Sucking Pests of Rose and Their Seasonal Abundance in Bangladesh

Authors: Md Ruhul Amin

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This study was conducted in the experimental field of the Department of Entomology, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh during November 2017 to May 2018 with a view to understanding the seasonal abundance of the major sucking pests namely thrips, aphid and red spider mite on rose. The findings showed that the thrips started to build up their population from the middle of January with abundance 1.0 leaf⁻¹, increased continuously, reached to the peak level (2.6 leaf⁻¹) in the middle of February and then declined. Aphid started to build up their population from the second week of November with abundance 6.0 leaf⁻¹, increased continuously, reached to the peak level (8.4 leaf⁻¹) in the last week of December and then declined. Mite started to build up their population from the first week of December with abundance 0.8 leaf⁻¹, increased continuously, reached to the peak level (8.2 leaf⁻¹) in the second week of March and then declined. Thrips and mite prevailed until the last week of April, and aphid showed their abundance till last week of May. The daily mean temperature, relative humidity, and rainfall had an insignificant negative correlation with thrips and significant negative correlation with aphid abundance. The daily mean temperature had significant positive, relative humidity had an insignificant positive, and rainfall had an insignificant negative correlation with mite abundance. The multiple linear regression analysis showed that the weather parameters together contributed 38.1, 41.0 and 8.9% abundance on thrips, aphid and mite on rose, respectively and the equations were insignificant.

Keywords: aphid, mite, thrips, weather factors

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895 Bismuth Telluride Topological Insulator: Physical Vapor Transport vs Molecular Beam Epitaxy

Authors: Omar Concepcion, Osvaldo De Melo, Arturo Escobosa

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Topological insulator (TI) materials are insulating in the bulk and conducting in the surface. The unique electronic properties associated with these surface states make them strong candidates for exploring innovative quantum phenomena and as practical applications for quantum computing, spintronic and nanodevices. Many materials, including Bi₂Te₃, have been proposed as TIs and, in some cases, it has been demonstrated experimentally by angle-resolved photoemission spectroscopy (ARPES), scanning tunneling spectroscopy (STM) and/or magnetotransport measurements. A clean surface is necessary in order to make any of this measurements. Several techniques have been used to produce films and different kinds of nanostructures. Growth and characterization in situ is usually the best option although cleaving the films can be an alternative to have a suitable surface. In the present work, we report a comparison of Bi₂Te₃ grown by physical vapor transport (PVT) and molecular beam epitaxy (MBE). The samples were characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and ARPES. The Bi₂Te₃ samples grown by PVT, were cleaved in the ultra-high vacuum in order to obtain a surface free of contaminants. In both cases, the XRD shows a c-axis orientation and the pole diagrams proved the epitaxial relationship between film and substrate. The ARPES image shows the linear dispersion characteristic of the surface states of the TI materials. The samples grown by PVT, a relatively simple and cost-effective technique shows the same high quality and TI properties than the grown by MBE.

Keywords: Bismuth telluride, molecular beam epitaxy, physical vapor transport, topological insulator

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894 Alterations of Molecular Characteristics of Polyethylene under the Influence of External Effects

Authors: Vigen Barkhudaryan

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The influence of external effects (γ-, UV–radiations, high temperature) in presence of air oxygen on structural transformations of low-density polyethylene (LDPE) have been investigated dependent on the polymers’ thickness, the intensity and the dose of external actions. The methods of viscosimetry, light scattering, turbidimetry and gelation measuring were used for this purpose. The comparison of influence of external effects on LDPE shows, that the destruction and cross-linking processes of macromolecules proceed simultaneously with all kinds of external effects. A remarkable growth of average molecular mass of LDPE along with the irradiation doses and heat treatment exposure growth was established. It was linear for the mass average molecular mass and at the initial doses is mainly the result of the increase of the macromolecular branching. As a result, the macromolecular hydrodynamic volumes have been changed, and therefore the dependence of viscosity average molecular mass on the doses was going through the minimum at initial doses. A significant change of molecular mass, sizes and shape of macromolecules of LDPE occurs under the influence of external effects. The influence is limited only by diffusion of oxygen during -irradiation and heat treatment. At UV–irradiation the influence is limited both by diffusion of oxygen and penetration of radiation. Consequently, the molecular transformations are deeper and evident in case of -irradiation, as soon as the polymer is transformed in a whole volume. It was also established, that the mechanism of molecular transformations in polymers from the surface layer distinctly differs from those of the sample deeper layer. A comparison of the results of these investigations allows us to conclude, that the mechanisms of influence of investigated external effects on polyethylene are similar.

Keywords: cross-linking, destruction, high temperature, LDPE, γ-radiations, UV-radiations

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893 Application of a Universal Distortion Correction Method in Stereo-Based Digital Image Correlation Measurement

Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

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892 Performance Evaluation of a Fuel Cell Membrane Electrode Assembly Prepared from a Reinforced Proton Exchange Membrane

Authors: Yingjeng James Li, Yun Jyun Ou, Chih Chi Hsu, Chiao-Chih Hu

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A fuel cell is a device that produces electric power by reacting fuel and oxidant electrochemically. There is no pollution produced from a fuel cell if hydrogen is employed as the fuel. Therefore, a fuel cell is considered as a zero emission device and is a source of green power. A membrane electrode assembly (MEA) is the key component of a fuel cell. It is, therefore, beneficial to develop MEAs with high performance. In this study, an MEA for proton exchange membrane fuel cell (PEMFC) was prepared from a 15-micron thick reinforced PEM. The active area of such MEA is 25 cm2. Carbon supported platinum (Pt/C) was employed as the catalyst for both anode and cathode. The platinum loading is 0.6 mg/cm2 based on the sum of anode and cathode. Commercially available carbon papers coated with a micro porous layer (MPL) serve as gas diffusion layers (GDLs). The original thickness of the GDL is 250 μm. It was compressed down to 163 μm when assembled into the single cell test fixture. Polarization curves were taken by using eight different test conditions. At our standard test condition (cell: 70 °C; anode: pure hydrogen, 100%RH, 1.2 stoic, ambient pressure; cathode: air, 100%RH, 3.0 stoic, ambient pressure), the cell current density is 1250 mA/cm2 at 0.6 V, and 2400 mA/cm2 at 0.4 V. At self-humidified condition and cell temperature of 55 °C, the cell current density is 1050 mA/cm2 at 0.6 V, and 2250 mA/cm2 at 0.4 V. Hydrogen crossover rate of the MEA is 0.0108 mL/min*cm2 according to linear sweep voltammetry experiments. According to the MEA’s Pt loading and the cyclic voltammetry experiments, the Pt electrochemical surface area is 60 m2/g. The ohmic part of the impedance spectroscopy results shows that the membrane resistance is about 60 mΩ*cm2 when the MEA is operated at 0.6 V.

Keywords: fuel cell, membrane electrode assembly, proton exchange membrane, reinforced

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891 Location Choice: The Effects of Network Configuration upon the Distribution of Economic Activities in the Chinese City of Nanning

Authors: Chuan Yang, Jing Bie, Zhong Wang, Panagiotis Psimoulis

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Contemporary studies investigating the association between the spatial configuration of the urban network and economic activities at the street level were mostly conducted within space syntax conceptual framework. These findings supported the theory of 'movement economy' and demonstrated the impact of street configuration on the distribution of pedestrian movement and land-use shaping, especially retail activities. However, the effects varied between different urban contexts. In this paper, the relationship between economic activity distribution and the urban configurational characters was examined at the segment level. In the study area, three kinds of neighbourhood types, urban, suburban, and rural neighbourhood, were included. And among all neighbourhoods, three kinds of urban network form, 'tree-like', grid, and organic pattern, were recognised. To investigate the nested effects of urban configuration measured by space syntax approach and urban context, multilevel zero-inflated negative binomial (ZINB) regression models were constructed. Additionally, considering the spatial autocorrelation, spatial lag was also concluded in the model as an independent variable. The random effect ZINB model shows superiority over the ZINB model or multilevel linear (ML) model in the explanation of economic activities pattern shaping over the urban environment. And after adjusting for the neighbourhood type and network form effects, connectivity and syntax centrality significantly affect economic activities clustering. The comparison between accumulative and new established economic activities illustrated the different preferences for economic activity location choice.

Keywords: space syntax, economic activities, multilevel model, Chinese city

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890 2D Convolutional Networks for Automatic Segmentation of Knee Cartilage in 3D MRI

Authors: Ananya Ananya, Karthik Rao

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Accurate segmentation of knee cartilage in 3-D magnetic resonance (MR) images for quantitative assessment of volume is crucial for studying and diagnosing osteoarthritis (OA) of the knee, one of the major causes of disability in elderly people. Radiologists generally perform this task in slice-by-slice manner taking 15-20 minutes per 3D image, and lead to high inter and intra observer variability. Hence automatic methods for knee cartilage segmentation are desirable and are an active field of research. This paper presents design and experimental evaluation of 2D convolutional neural networks based fully automated methods for knee cartilage segmentation in 3D MRI. The architectures are validated based on 40 test images and 60 training images from SKI10 dataset. The proposed methods segment 2D slices one by one, which are then combined to give segmentation for whole 3D images. Proposed methods are modified versions of U-net and dilated convolutions, consisting of a single step that segments the given image to 5 labels: background, femoral cartilage, tibia cartilage, femoral bone and tibia bone; cartilages being the primary components of interest. U-net consists of a contracting path and an expanding path, to capture context and localization respectively. Dilated convolutions lead to an exponential expansion of receptive field with only a linear increase in a number of parameters. A combination of modified U-net and dilated convolutions has also been explored. These architectures segment one 3D image in 8 – 10 seconds giving average volumetric Dice Score Coefficients (DSC) of 0.950 - 0.962 for femoral cartilage and 0.951 - 0.966 for tibia cartilage, reference being the manual segmentation.

Keywords: convolutional neural networks, dilated convolutions, 3 dimensional, fully automated, knee cartilage, MRI, segmentation, U-net

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889 Electrical Conductivity as Pedotransfer Function in the Determination of Sodium Adsorption Ratio in Soil System in Managing Micro Level Farming Practices in India: An Effective Low Cost Technology

Authors: Usha Loganathan, Haresh Pandya

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Analysis and correlation of soil properties represent an important outset for precision agriculture and is currently promoted and implemented in the developed world. Establishing relationships among indices of soil salinity has always been a challenging task in salt affected soils necessitating unique approaches for their reclamation and management to sustain long term productivity of Soil. Soil salinity indices like Electrical Conductivity (EC) and Sodium Adsorption Ratio (SAR) are normally used to characterize soils as either sodic or saline sodic. Currently, Determination of Soil sodium adsorption ratio is a more accepted and reliable measure of soil salinity. However, it involves arduous and protracted laboratory investigations which demand evolving new and economical methods to determine SAR based on simple soil salinity index. A linear regression model to predict soil SAR from soil electrical conductivity has been developed and presented in this paper as per which, soil SAR could very well be worked out as a pedotransfer function of soil EC. The present study was carried out in Orathupalayam (11.09-11.11 N latitude and 74.54-77.59 E longitude) in the vicinity of Orathupalayam Reservoir of Noyyal River Basin, India, over a period of 3 consecutive years from September 2013 through February 2016 in different locations chosen randomly through different seasons. The research findings are discussed in the light of micro level farming practices in India and recommend determination of SAR as a low cost technology aiding in the effective management of salt affected agricultural land.

Keywords: electrical conductivity, orathupalayam, pedotranfer function, sodium adsorption ratio

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888 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction

Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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887 Innovative Predictive Modeling and Characterization of Composite Material Properties Using Machine Learning and Genetic Algorithms

Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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886 Effect of Islamic Finance on Jobs Generation in Punjab, Pakistan

Authors: B. Ashraf, A. M. Malik

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The study was accomplished at the Department of Economics and Agriculture Economics, Pir Mahar Ali Shah ARID Agriculture University, Punjab, Pakistan during 2013-16 with a purpose to discover the effect of Islamic finance/banking on employment in Punjab, Pakistan. Islamic banking system is sub-component of conventional banking system in various countries of the world; however, in Pakistan, it has been established as a separate Islamic banking system. The Islamic banking operates under the doctrine of Shariah. It is claimed that the referred banking is free of interest (Riba) and addresses the philosophy and basic values of Islam in finance that reduces the factors of uncertainty, risk and others speculative activities. Two Islamic bank’s; Meezan Bank Limited (Pakistan) and Al-Baraka Bank Limited (Pakistan) from North Punjab (Bahawalnagar) and central Punjab (Lahore) west Punjab (Gujrat), Pakistan were randomly selected for the conduct of research. A total of 206 samples were collected from the define areas and banks through questionnaire. The data was analyzed by using the Statistical Package for Social Sciences (SPSS) version 21.0. Multiple linear regressions were applied to prove the hypothesis. The results revealed that the assets formation had significant positive; whereas, the technology, length of business (experience) and bossiness size had significant negative impact with employment generation in Islamic finance/banking in Punjab, Pakistan. This concludes that the employment opportunities may be created in the country by extending the finance to business/firms to start new business and increase the Public awareness by the Islamic banks through intensive publicity. However; Islamic financial institutions may be encouraged by Government as it enhances the employment in the country.

Keywords: assets formation, borrowers, employment generation, Islamic banks, Islamic finance

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885 Numerical Investigation of the Integration of a Micro-Combustor with a Free Piston Stirling Engine in an Energy Recovery System

Authors: Ayodeji Sowale, Athanasios Kolios, Beatriz Fidalgo, Tosin Somorin, Aikaterini Anastasopoulou, Alison Parker, Leon Williams, Ewan McAdam, Sean Tyrrel

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Recently, energy recovery systems are thriving and raising attention in the power generation sector, due to the request for cleaner forms of energy that are friendly and safe for the environment. This has created an avenue for cogeneration, where Combined Heat and Power (CHP) technologies have been recognised for their feasibility, and use in homes and small-scale businesses. The efficiency of combustors and the advantages of the free piston Stirling engines over other conventional engines in terms of output power and efficiency, have been observed and considered. This study presents the numerical analysis of a micro-combustor with a free piston Stirling engine in an integrated model of a Nano Membrane Toilet (NMT) unit. The NMT unit will use the micro-combustor to produce waste heat of high energy content from the combustion of human waste and the heat generated will power the free piston Stirling engine which will be connected to a linear alternator for electricity production. The thermodynamic influence of the combustor on the free piston Stirling engine was observed, based on the heat transfer from the flue gas to working gas of the free piston Stirling engine. The results showed that with an input of 25 MJ/kg of faecal matter, and flue gas temperature of 773 K from the micro-combustor, the free piston Stirling engine generates a daily output power of 428 W, at thermal efficiency of 10.7% with engine speed of 1800 rpm. An experimental investigation into the integration of the micro-combustor and free piston Stirling engine with the NMT unit is currently underway.

Keywords: free piston stirling engine, micro-combustor, nano membrane toilet, thermodynamics

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884 Coupled Hydro-Geomechanical Modeling of Oil Reservoir Considering Non-Newtonian Fluid through a Fracture

Authors: Juan Huang, Hugo Ninanya

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Oil has been used as a source of energy and supply to make materials, such as asphalt or rubber for many years. This is the reason why new technologies have been implemented through time. However, research still needs to continue increasing due to new challenges engineers face every day, just like unconventional reservoirs. Various numerical methodologies have been applied in petroleum engineering as tools in order to optimize the production of reservoirs before drilling a wellbore, although not all of these have the same efficiency when talking about studying fracture propagation. Analytical methods like those based on linear elastic fractures mechanics fail to give a reasonable prediction when simulating fracture propagation in ductile materials whereas numerical methods based on the cohesive zone method (CZM) allow to represent the elastoplastic behavior in a reservoir based on a constitutive model; therefore, predictions in terms of displacements and pressure will be more reliable. In this work, a hydro-geomechanical coupled model of horizontal wells in fractured rock was developed using ABAQUS; both extended element method and cohesive elements were used to represent predefined fractures in a model (2-D). A power law for representing the rheological behavior of fluid (shear-thinning, power index <1) through fractures and leak-off rate permeating to the matrix was considered. Results have been showed in terms of aperture and length of the fracture, pressure within fracture and fluid loss. It was showed a high infiltration rate to the matrix as power index decreases. A sensitivity analysis is conclusively performed to identify the most influential factor of fluid loss.

Keywords: fracture, hydro-geomechanical model, non-Newtonian fluid, numerical analysis, sensitivity analysis

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883 Analysis of Factors Affecting the Number of Infant and Maternal Mortality in East Java with Geographically Weighted Bivariate Generalized Poisson Regression Method

Authors: Luh Eka Suryani, Purhadi

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Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

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882 Optimal Operation of Bakhtiari and Roudbar Dam Using Differential Evolution Algorithms

Authors: Ramin Mansouri

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Due to the contrast of rivers discharge regime with water demands, one of the best ways to use water resources is to regulate the natural flow of the rivers and supplying water needs to construct dams. Optimal utilization of reservoirs, consideration of multiple important goals together at the same is of very high importance. To study about analyzing this method, statistical data of Bakhtiari and Roudbar dam over 46 years (1955 until 2001) is used. Initially an appropriate objective function was specified and using DE algorithm, the rule curve was developed. In continue, operation policy using rule curves was compared to standard comparative operation policy. The proposed method distributed the lack to the whole year and lowest damage was inflicted to the system. The standard deviation of monthly shortfall of each year with the proposed algorithm was less deviated than the other two methods. The Results show that median values for the coefficients of F and Cr provide the optimum situation and cause DE algorithm not to be trapped in local optimum. The most optimal answer for coefficients are 0.6 and 0.5 for F and Cr coefficients, respectively. After finding the best combination of coefficients values F and CR, algorithms for solving the independent populations were examined. For this purpose, the population of 4, 25, 50, 100, 500 and 1000 members were studied in two generations (G=50 and 100). result indicates that the generation number 200 is suitable for optimizing. The increase in time per the number of population has almost a linear trend, which indicates the effect of population in the runtime algorithm. Hence specifying suitable population to obtain an optimal results is very important. Standard operation policy had better reversibility percentage, but inflicts severe vulnerability to the system. The results obtained in years of low rainfall had very good results compared to other comparative methods.

Keywords: reservoirs, differential evolution, dam, Optimal operation

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881 The Stem Cell Transcription Co-factor Znf521 Sustains Mll-af9 Fusion Protein In Acute Myeloid Leukemias By Altering The Gene Expression Landscape

Authors: Emanuela Chiarella, Annamaria Aloisio, Nisticò Clelia, Maria Mesuraca

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ZNF521 is a stem cell-associated transcription co-factor, that plays a crucial role in the homeostatic regulation of the stem cell compartment in the hematopoietic, osteo-adipogenic, and neural system. In normal hematopoiesis, primary human CD34+ hematopoietic stem cells display typically a high expression of ZNF521, while its mRNA levels rapidly decrease when these progenitors progress towards erythroid, granulocytic, or B-lymphoid differentiation. However, most acute myeloid leukemias (AMLs) and leukemia-initiating cells keep high ZNF521 expression. In particular, AMLs are often characterized by chromosomal translocations involving the Mixed Lineage Leukemia (MLL) gene, which MLL gene includes a variety of fusion oncogenes arisen from genes normally required during hematopoietic development; once they are fused, they promote epigenetic and transcription factor dysregulation. The chromosomal translocation t(9;11)(p21-22;q23), fusing the MLL gene with AF9 gene, results in a monocytic immune phenotype with an aggressive course, frequent relapses, and a short survival time. To better understand the dysfunctional transcriptional networks related to genetic aberrations, AML gene expression profile datasets were queried for ZNF521 expression and its correlations with specific gene rearrangements and mutations. The results showed that ZNF521 mRNA levels are associated with specific genetic aberrations: the highest expression levels were observed in AMLs involving t(11q23) MLL rearrangements in two distinct datasets (MILE and den Boer); elevated ZNF521 mRNA expression levels were also revealed in AMLs with t(7;12) or with internal rearrangements of chromosome 16. On the contrary, relatively low ZNF521 expression levels seemed to be associated with the t(8;21) translocation, that in turn is correlated with the AML1-ETO fusion gene or the t(15;17) translocation and in AMLs with FLT3-ITD, NPM1, or CEBPα double mutations. Invitro, we found that the enforced co-expression of ZNF521 in cord blood-derived CD34+ cells induced a significant proliferative advantage, improving MLL-AF9 effects on the induction of proliferation and the expansion of leukemic progenitor cells. Transcriptome profiling of CD34+ cells transduced with either MLL-AF9, ZNF521, or a combination of the two transgenes highlighted specific sets of up- or down-regulated genes that are involved in the leukemic phenotype, including those encoding transcription factors, epigenetic modulators, and cell cycle regulators as well as those engaged in the transport or uptake of nutrients. These data enhance the functional cooperation between ZNF521 and MA9, resulting in the development, maintenance, and clonal expansion of leukemic cells. Finally, silencing of ZNF521 in MLL-AF9-transformed primary CD34+ cells inhibited their proliferation and led to their extinction, as well as ZNF521 silencing in the MLL-AF9+ THP-1 cell line resulted in an impairment of their growth and clonogenicity. Taken together, our data highlight ZNF521 role in the control of self-renewal and in the immature compartment of malignant hematopoiesis, which, by altering the gene expression landscape, contributes to the development and/or maintenance of AML acting in concert with the MLL-AF9 fusion oncogene.

Keywords: AML, human zinc finger protein 521 (hZNF521), mixed lineage leukemia gene (MLL) AF9 (MLLT3 or LTG9), cord blood-derived hematopoietic stem cells (CB-CD34+)

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880 Exploring 1,2,4-Triazine-3(2H)-One Derivatives as Anticancer Agents for Breast Cancer: A QSAR, Molecular Docking, ADMET, and Molecular Dynamics

Authors: Said Belaaouad

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This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site.

Keywords: QSAR, molecular docking, ADMET, 1, 2, 4-triazin-3(2H)-ones, breast cancer, anticancer, molecular dynamic simulations, MMPBSA calculation

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879 Clay Hydrogel Nanocomposite for Controlled Small Molecule Release

Authors: Xiaolin Li, Terence Turney, John Forsythe, Bryce Feltis, Paul Wright, Vinh Truong, Will Gates

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Clay-hydrogel nanocomposites have attracted great attention recently, mainly because of their enhanced mechanical properties and ease of fabrication. Moreover, the unique platelet structure of clay nanoparticles enables the incorporation of bioactive molecules, such as proteins or drugs, through ion exchange, adsorption or intercalation. This study seeks to improve the mechanical and rheological properties of a novel hydrogel system, copolymerized from a tetrapodal polyethylene glycol (PEG) thiol and a linear, triblock PEG-PPG-PEG (PPG: polypropylene glycol) α,ω-bispropynoate polymer, with the simultaneous incorporation of various amounts of Na-saturated, montmorillonite clay (MMT) platelets (av. lateral dimension = 200 nm), to form a bioactive three-dimensional network. Although the parent hydrogel has controlled swelling ability and its PEG groups have good affinity for the clay platelets, it suffers from poor mechanical stability and is currently unsuitable for potential applications. Nanocomposite hydrogels containing 4wt% MMT showed a twelve-fold enhancement in compressive strength, reaching 0.75MPa, and also a three-fold acceleration in gelation time, when compared with the parent hydrogel. Interestingly, clay nanoplatelet incorporation into the hydrogel slowed down the rate of its dehydration in air. Preliminary results showed that protein binding by the MMT varied with the nature of the protein, as horseradish peroxidase (HRP) was more strongly bound than bovine serum albumin. The HRP was no longer active when bound, presumably as a result of extensive structural refolding. Further work is being undertaken to assess protein binding behaviour within the nanocomposite hydrogel for potential diabetic wound healing applications.

Keywords: hydrogel, nanocomposite, small molecule, wound healing

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878 Development and Evaluation of New Complementary Food from Maize, Soya Bean and Moringa for Young Children

Authors: Berhan Fikru

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The objective of this study was to develop new complementary food from maize, soybean and moringa for young children. The complementary foods were formulated with linear programming (LP Nutri-survey software) and Faffa (corn soya blend) use as control. Analysis were made for formulated blends and compared with the control and recommended daily intake (RDI). Three complementary foods composed of maize, soya bean, moringa and sugar with ratio of 65:20:15:0, 55:25:15:5 and 65:20:10:5 for blend 1, 2 and 3, respectively. The blends were formulated based on the protein, energy, mineral (iron, zinc an calcium) and vitamin (vitamin A and C) content of foods. The overall results indicated that nutrient content of faffa (control) was 16.32 % protein, 422.31 kcal energy, 64.47 mg calcium, 3.8 mg iron, 1.87mg zinc, 0.19 mg vitamin A and 1.19 vitamin C; blend 1 had 17.16 % protein, 429.84 kcal energy, 330.40 mg calcium, 6.19 mg iron, 1.62 mg zinc, 6.33 mg vitamin A and 4.05 mg vitamin C; blend 2 had 20.26 % protein, 418.79 kcal energy, 417.44 mg calcium, 9.26 mg iron, 2.16 mg zinc, 8.43 mg vitamin A and 4.19 mg vitamin C whereas blend 3 exhibited 16.44 % protein, 417.42 kcal energy, 242.4 mg calcium, 7.09 mg iron, 2.22 mg zinc, 3.69 mg vitamin A and 4.72 mg vitamin C, respectively. The difference was found between all means statically significance (P < 0.05). Sensory evaluation showed that the faffa control and blend 3 were preferred by semi-trained panelists. Blend 3 had better in terms of its mineral and vitamin content than FAFFA corn soya blend and comparable with WFP proprietary products CSB+, CSB++ and fulfills the WHO recommendation for protein, energy and calcium. The suggested formulation with Moringa powder can therefore be used as a complementary food to improve the nutritional status and also help solve problems associated with protein energy and micronutrient malnutrition for young children in developing countries, particularly in Ethiopia.

Keywords: corn soya blend, proximate composition, micronutrient, mineral chelating agents, complementary foods

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877 Effective Health Promotion Interventions Help Young Children to Maximize Their Future Well-Being by Early Childhood Development

Authors: Nadeesha Sewwandi, Dilini Shashikala, R. Kanapathy, S. Viyasan, R. M. S. Kumara, Duminda Guruge

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Early childhood development is important to the emotional, social, and physical development of young children and it has a direct effect on their overall development and on the adult they become. Play is so important to optimal child developments including skill development, social development, imagination, creativity and it fulfills a baby’s inborn need to learn. So, health promotion approach empowers people about the development of early childhood. Play area is a new concept and this study focus how this play areas helps to the development of early childhood of children in rural villages in Sri Lanka. This study was conducted with a children society in a rural village called Welankulama in Sri Lanka. Survey was conducted with children society about emotional, social and physical development of young children (Under age eight) in this village using questionnaires. It described most children under eight years age have poor level of emotional, social and physical development in this village. Then children society wanted to find determinants for this problem and among them they prioritized determinants like parental interactions, learning environment and social interaction and address them using an innovative concept called play area. In this village there is a common place as play area under a big tamarind tree. It consists of a playhouse, innovative playing toys, mobile library, etc. Twice a week children, parents, grandparents gather to this nice place. Collective feeding takes place in this area once a week and it was conducted by several mothers groups in this village. Mostly grandparents taught about handicrafts and this is a very nice place to share their experiences with all. Healthy competitions were conducted in this place through playing to motivate the children. Happy calendar (mood of the children) was marked by children before and after coming to the play area. In terms of results qualitative changes got significant place in this study. By learning about colors and counting through playing the thinking and reasoning skills got developed among children. Children were widening their imagination by means of storytelling. We observed there were good developments of fine and gross motor skills of two differently abled children in this village. Children learn to empathize with other people, sharing, collaboration, team work and following of rules. And also children gain knowledge about fairness, through role playing, obtained insight on the right ways of displaying emotions such as stress, fear, anger, frustration, and develops knowledge of how they can manage their feelings. The reading and writing ability of the children got improved by 83% because of the mobile library. The weight of children got increased by 81% in the village. Happiness was increased by 76% among children in the society. Playing is very important for learning during early childhood period of a person. Health promotion interventions play a major role to the development of early childhood and it help children to adjust to the school setting and even to enhance children’s learning readiness, learning behaviors and problem solving skills.

Keywords: early childhood development, health promotion approach, play and learning, working with children

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876 Studying Second Language Development from a Complex Dynamic Systems Perspective

Authors: L. Freeborn

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This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

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875 Simultaneous Determination of Bisphenol a, Phtalates and Its Metabolites in Human Urine, by Tandem SPE Coupled to GC-MS

Authors: L. Correia-Sá, S. Norberto, Conceição Calhau, C. Delerue-Matos, V. F. Domingues

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Endocrine disruptor chemicals (EDCs) are synthetic compounds that even though being initially designed for a specific function are now being linked with a wide range of side effects. The list of possible EDCs is growing and includes phthalates and bisphenol A (BPA). Phthalates are one of the most widely used plasticizers to improve the extensibility, elasticity and workability of polyvinyl chloride (PVC), polyvinyl acetates, etc. Considered non-toxic and harmless additives for polymers, they were used unrestrainedly all over the world for several decades. However, recent studies have indicated that some phthalates and their metabolic products are reproductive and developmental toxicants in animals and suspected endocrine disruptors in humans. BPA (2,2-bis(4-hydroxyphenyl)propane) is a high production volume chemical mainly used in the production of polycarbonate plastics and epoxy resins. Although BPA was initially considered to be a weak environmental estrogen, nowadays it is known that this compound can stimulate several cellular responses at very low levels of concentrations. The aim of this study was to develop a method based on tandem SPE to evaluate the presence of phthalates, metabolites and BPA in human urine samples. The analyzed compounds included: dibutyl phthalate (DBP) and di-2-ethylhexyl phthalate (DEHP), BPA, mono-isobutyl phthalate (MiBP), monobutyl phthalate (MBP) and. mono-(2-ethyl-5-oxohexyl) (MEOHP). Two SPE cartridges were applied both from Phenomenex, the strata X polymeric reversed phase and the strata X A (Strong anion). Chromatographic analyses were carried out in a Thermo GC ULTRA GC-MS/MS. Good recoveries and linear calibration curves were obtained. After validation, the methodology was applied to human urine samples for phthalates, metabolites and BPA evaluation.

Keywords: Bisphenol A (BPA), gas chromatography, metabolites, phtalates, SPE, tandem mode

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874 Hemodynamics of a Cerebral Aneurysm under Rest and Exercise Conditions

Authors: Shivam Patel, Abdullah Y. Usmani

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Physiological flow under rest and exercise conditions in patient-specific cerebral aneurysm models is numerically investigated. A finite-volume based code with BiCGStab as the linear equation solver is used to simulate unsteady three-dimensional flow field through the incompressible Navier-Stokes equations. Flow characteristics are first established in a healthy cerebral artery for both physiological conditions. The effect of saccular aneurysm on cerebral hemodynamics is then explored through a comparative analysis of the velocity distribution, nature of flow patterns, wall pressure and wall shear stress (WSS) against the reference configuration. The efficacy of coil embolization as a potential strategy of surgical intervention is also examined by modelling coil as a homogeneous and isotropic porous medium where the extended Darcy’s law, including Forchheimer and Brinkman terms, is applicable. The Carreau-Yasuda non-Newtonian blood model is incorporated to capture the shear thinning behavior of blood. Rest and exercise conditions correspond to normotensive and hypertensive blood pressures respectively. The results indicate that the fluid impingement on the outer wall of the arterial bend leads to abnormality in the distribution of wall pressure and WSS, which is expected to be the primary cause of the localized aneurysm. Exercise correlates with elevated flow velocity, vortex strength, wall pressure and WSS inside the aneurysm sac. With the insertion of coils in the aneurysm cavity, the flow bypasses the dilatation, leading to a decline in flow velocities and WSS. Particle residence time is observed to be lower under exercise conditions, a factor favorable for arresting plaque deposition and combating atherosclerosis.

Keywords: 3D FVM, Cerebral aneurysm, hypertension, coil embolization, non-Newtonian fluid

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873 Parameter Selection and Monitoring for Water-Powered Percussive Drilling in Green-Fields Mineral Exploration

Authors: S. J. Addinell, T. Richard, B. Evans

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The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising downhole water powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barron cover. This system has shown superior rates of penetration in water-rich hard rock formations at depths exceeding 500 meters. Several key challenges exist regarding the deployment and use of these bottom hole assemblies for mineral exploration, and this paper discusses some of the key technical challenges. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process is presented and shows a strong power law relationship for particle size distributions. Several percussive drilling parameters such as RPM, applied fluid pressure and weight on bit have been shown to influence the particle size distributions of the cuttings generated. This has direct influence on other drilling parameters such as flow loop performance, cuttings dewatering, and solids control. Real-time, accurate knowledge of percussive system operating parameters will assist the driller in maximising the efficiency of the drilling process. The applied fluid flow, fluid pressure, and rock properties are known to influence the natural oscillating frequency of the percussive hammer, but this paper also shows that drill bit design, drill bit wear and the applied weight on bit can also influence the oscillation frequency. Due to the changing drilling conditions and therefore changing operating parameters, real-time understanding of the natural operating frequency is paramount to achieving system optimisation. Several techniques to understand the oscillating frequency have been investigated and presented. With a conventional top drive drilling rig, spectral analysis of applied fluid pressure, hydraulic feed force pressure, hold back pressure and drill string vibrations have shown the presence of the operating frequency of the bottom hole tooling. Unfortunately, however, with the implementation of a coiled tubing drilling rig, implementing a positive displacement downhole motor to provide drill bit rotation, these signals are not available for interrogation at the surface and therefore another method must be considered. The investigation and analysis of ground vibrations using geophone sensors, similar to seismic-while-drilling techniques have indicated the presence of the natural oscillating frequency of the percussive hammer. This method is shown to provide a robust technique for the determination of the downhole percussive oscillation frequency when used with a coiled tubing drill rig.

Keywords: cuttings characterization, drilling optimization, oscillation frequency, percussive drilling, spectral analysis

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872 Engineering a Band Gap Opening in Dirac Cones on Graphene/Tellurium Heterostructures

Authors: Beatriz Muñiz Cano, J. Ripoll Sau, D. Pacile, P. M. Sheverdyaeva, P. Moras, J. Camarero, R. Miranda, M. Garnica, M. A. Valbuena

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Graphene, in its pristine state, is a semiconductor with a zero band gap and massless Dirac fermions carriers, which conducts electrons like a metal. Nevertheless, the absence of a bandgap makes it impossible to control the material’s electrons, something that is essential to perform on-off switching operations in transistors. Therefore, it is necessary to generate a finite gap in the energy dispersion at the Dirac point. Intense research has been developed to engineer band gaps while preserving the exceptional properties of graphene, and different strategies have been proposed, among them, quantum confinement of 1D nanoribbons or the introduction of super periodic potential in graphene. Besides, in the context of developing new 2D materials and Van der Waals heterostructures, with new exciting emerging properties, as 2D transition metal chalcogenides monolayers, it is fundamental to know any possible interaction between chalcogenide atoms and graphene-supporting substrates. In this work, we report on a combined Scanning Tunneling Microscopy (STM), Low Energy Electron Diffraction (LEED), and Angle-Resolved Photoemission Spectroscopy (ARPES) study on a new superstructure when Te is evaporated (and intercalated) onto graphene over Ir(111). This new superstructure leads to the electronic doping of the Dirac cone while the linear dispersion of massless Dirac fermions is preserved. Very interestingly, our ARPES measurements evidence a large band gap (~400 meV) at the Dirac point of graphene Dirac cones below but close to the Fermi level. We have also observed signatures of the Dirac point binding energy being tuned (upwards or downwards) as a function of Te coverage.

Keywords: angle resolved photoemission spectroscopy, ARPES, graphene, spintronics, spin-orbitronics, 2D materials, transition metal dichalcogenides, TMDCs, TMDs, LEED, STM, quantum materials

Procedia PDF Downloads 79