Search results for: wee hour.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 173

Search results for: wee hour.

173 A Flipped Classroom Approach for Non-Science Majors

Authors: Nidhi Gadura

Abstract:

To ensure student success in a non-majors biology course, a flipped classroom pedagogical approach was developed and implemented. All students were assigned online lectures to listen to before they come to class. A three hour lecture was split into one hour of online component, one hour of in class lecture and one hour of worksheets done by students in the classroom. This deviation from a traditional 3 hour in class lecture has resulted in increased student interest in science as well as better understanding of difficult scientific concepts. A pre and post survey was given to measure the interest in the subject and grades were used to measure the success rates. While the overall grade average did not change dramatically, students reported a much better appreciation of biology. Also, students overwhelmingly like the use of worksheets in class to help them understand the concepts. They liked the fact that they could listen to lectures at their own pace on line and even repeat if needed. The flipped classroom approach turned out to work really well our non-science majors and the author is ready to implement this in other classrooms.

Keywords: Flipped classroom, non-science majors, pedagogy, technological pedagogical model.

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172 Characterization of Ajebo Kaolinite Clay for Production of Natural Pozzolan

Authors: Gbenga M. Ayininuola, Olasunkanmi A. Adekitan

Abstract:

Calcined kaolinite clay (CKC) is a pozzolanic material that is current drawing research attention. This work investigates the conditions for the best performance of a CKC from a kaolinite clay source in Ajebo, Abeokuta (southwest Nigeria) known for its commercial availability. Samples from this source were subjected to X-ray diffractometry (XRD) and differential scanning calorimetry (DSC). XRD shows that kaolinite is the main mineral in the clay source. This mineral is responsible for the pozzolanic behavior of CKC. DSC indicates that the transformation from the clay to CKC occurred between 550 and 750 oC. Using this temperature range, clay samples were milled and different CKC samples were produced in an electric muffle furnace using temperatures of 550, 600, 650, 700, 750 and 800 oC respectively for 1 hour each. This was also repeated for 2 hours. The degree of de-hydroxylation (dtg) and strength activity index (SAI) were also determined for each of the CKC samples. The dtg and SAI tests were repeated two more times for each sample and averages were taken. Results showed that peak dtg occurred at 750 oC for 1 hour calcining combination (94.27%) whereas marginal differences were recorded at some lower temperatures (90.97% for 650 oC for 2 hours; 91.05% for 700 oC for 1 hour and 92.77% for 700 oC for 2 hours). Optimum SAI was reported at 700 oC for 1 hour (99.05%). Rating SAI as a better parameter than dtg, 700 oC for 1 hour combination was adopted as the best calcining condition. The paper recommends the adoption of this clay source for pozzolan production by adopting the calcining conditions established in this work.

Keywords: Calcined kaolinite clay, calcination, optimum-calcining conditions, pozzolanity.

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171 Safety Practices among Bus Operators during Wee Hour Operations

Authors: M.R. Osman, F. Abas, M.S. Noh, A. Mohamad Suffian, O. Ilhamah, H.Z. Zarir, A.B. Wahida, P. Noor Faradila, M.F. Siti Atiqah

Abstract:

Safety Health and Environment Code of Practice (SHE COP) was developed to help road transportation operators to manage its operation in a systematic and safe manner. A study was conducted to determine the effectiveness of SHE COP implementation during non-OPS period. The objective of the study is to evaluate the implementations of SHE COP among bus operators during wee hour operations. The data was collected by completing a set of checklist after observing the activities during pre departure, during the trip, and upon arrival. The results show that there are seven widely practiced SHE COP elements. 22% of the buses have average speed exceeding the maximum permissible speed on the highways (90 km/h), with 13% of the buses were travelling at the speed of more than 100 km/h. The statistical analysis shows that there is only one significant association which relates speeding with prior presence of enforcement officers.

Keywords: Safety practices, speeding, wee hour.

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170 Elasticity Model for Easing Peak Hour Demand for Metrorail Transport System

Authors: P. K. Sarkar, Amit Kumar Jain

Abstract:

The demand for Urban transportation is characterised by a large scale temporal and spatial variations which causes heavy congestion inside metro trains in peak hours near Centre Business District (CBD) of the city. The conventional approach to address peak hour congestion, metro trains has been to increase the supply by way of introduction of more trains, increasing the length of the trains, optimising the time table to increase the capacity of the system. However, there is a limitation of supply side measures determined by the design capacity of the systems beyond which any addition in the capacity requires huge capital investments. The demand side interventions are essentially required to actually spread the demand across the time and space. In this study, an attempt has been made to identify the potential Transport Demand Management tools applicable to Urban Rail Transportation systems with a special focus on differential pricing. A conceptual price elasticity model has been developed to analyse the effect of various combinations of peak and nonpeak hoursfares on demands. The elasticity values for peak hour, nonpeak hour and cross elasticity have been assumed from the relevant literature available in the field. The conceptual price elasticity model so developed is based on assumptions which need to be validated with actual values of elasticities for different segments of passengers. Once validated, the model can be used to determine the peak and nonpeak hour fares with an objective to increase overall ridership, revenue, demand levelling and optimal utilisation of assets.

Keywords: Congestion, differential pricing, elasticity, transport demand management, urban transportation.

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169 A Preliminary Study on the Suitability of Data Driven Approach for Continuous Water Level Modeling

Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

Abstract:

Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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168 Potential of Solar Energy in Zarqa Region

Authors: Ali M. Jawarneh, Ahmad S. AL-Shyyab

Abstract:

The purpose of this work is to present the potential of solar energy in Zarqa region. The solar radiation along year 2009 was obtained from Pyranometer which measures the global radiation over horizontal surfaces. Solar data in several different forms, over period of 5 minutes, hour-by-hour, daily and monthly data radiation have been presented. Briefly, the yearly global solar radiation in Zarqa is 7297.5 MJ/m2 (2027 kWh/m²) and the average annual solar radiation per day is 20 MJ/m2 (5.5 Kwh/m2). More specifically, the average annual solar radiation per day is 12.9 MJ/m2 (3.57 Kwh/m2) in winter and 25 MJ/m2 (7 Kwh/m2) in summer.

Keywords: Solar Energy, Pyranometer, Zarqa Region

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167 Zinc Contaminate on Urban Roadside in Rush Hour, Bangkok, Thailand

Authors: Sivapan Choo-In

Abstract:

This research aims to study the Zinc (Zn) concentration in fine particulate matter on Rajchawithee roadside in rush hour. 30 Samples were collected in Jun to August 2013 by 8 stage non-avaible cascade impactor. Each samples (filter paper) were digest with nitric acid and analyed by atomic absorption spectrophotometer for Zinc determination. The highest value for the mean fraction (18.00 ± 9.28%) is the size 9.0 – 110.0 micron follow by the range 3.3 – 4.7 micron (14.77 ± 14.66 %) and 1.1 – 2.1 micron (14.01 ± 11.77 %). The concentration of Zn in the particulate matter of range 0.43 – 0.7mm, 0.7 – 1.1 mm, 1.1 – 2.1 mm, 2.1 – 3.3 mm, 3.3 – 4.7 mm, 4.7 – 5.8 mm, 5.8 – 9.0 mm, 9.0 – 10.0 mm, were 41.56 – 217.62 mg/m3 (175.86 ±32.25 mg/m3), 152.60 – 217.24 mg/m3 (187.71 ± 17.42 mg/m3), 142.90 – 214.67 mg/m3(180.95 ± 18.71 mg/m3), 155.48 – 218.19 mg/m3(183.22 ± 19.94 mg/m3), 151.72 – 217.39 mg/m3(181.85 ± 17.57 mg/m3), 133.86 – 220.17 mg/m3 (178.78 ± 23.45 mg/m3), 160.00 – 220.35 mg/m3 (182.58 ± 18.08 mg/m3), 153.30 – 226.70 mg/m3 (181.52 ± 20.05 mg/m3), respectively. The Zn concentration in each size of particulate matter was not statistically significant different (p > .005)

Keywords: Air Pollution, Air Quality, Pollution and monitoring.

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166 Integrating the Theory of Constraints and Six Sigma in Manufacturing Process Improvement

Authors: Kai Jin, Hyder Abdul-Razzak, Yousri Elkassabgi, Hong Zhou, Aaron Herrera

Abstract:

Six Sigma is a well known discipline that reduces variation using complex statistical tools and the DMAIC model. By integrating Goldratts-s Theory of Constraints, the Five Focusing Points and System Thinking tools, Six Sigma projects can be selected where it can cause more impact in the company. This research defines an integrated model of six sigma and constraint management that shows a step-by-step guide using the original methodologies from each discipline and is evaluated in a case study from the production line of a Automobile engine monoblock V8, resulting in an increase in the line capacity from 18.7 pieces per hour to 22.4 pieces per hour, a reduction of 60% of Work-In-Process and a variation decrease of 0.73%.

Keywords: Constraint Management, Manufacturing Process Improvement, Six Sigma, System Thinking.

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165 Estimating the Traffic Impacts of Green Light Optimal Speed Advisory Systems Using Microsimulation

Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

Abstract:

Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: Connected vehicles, GLOSA, intelligent transportation systems, infrastructure-to-vehicle communication.

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164 Adjusted LOLE and EENS Indices for the Consideration of Load Excess Transfer in Power Systems Adequacy Studies

Authors: F. Vallée, J-F. Toubeau, Z. De Grève, J. Lobry

Abstract:

When evaluating the capacity of a generation park to cover the load in transmission systems, traditional Loss of Load Expectation (LOLE) and Expected Energy not Served (EENS) indices can be used. If those indices allow computing the annual duration and severity of load non covering situations, they do not take into account the fact that the load excess is generally shifted from one penury state (hour or quarter of an hour) to the following one. In this paper, a sequential Monte Carlo framework is introduced in order to compute adjusted LOLE and EENS indices. Practically, those adapted indices permit to consider the effect of load excess transfer on the global adequacy of a generation park, providing thus a more accurate evaluation of this quantity.

Keywords: Expected Energy not Served, Loss of Load Expectation, Monte Carlo simulation, reliability, wind generation.

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163 Estimation of the Spent Fuel Pool Water Temperature at a Loss-of-Pool-Cooling Accident

Authors: Chan Hee Park, Arim Lee, Jung Min Lee, Joo Hyun Moon

Abstract:

Accident in spent fuel pool (SFP) of Fukushima Daiichi Unit 4 showed the importance of continuous monitoring of the key environmental parameters such as water temperature, water level, and radiation level in the SFP at accident conditions. Because the SFP water temperature is one of the key parameters indicating SFP conditions, its behavior at accident conditions shall be understood to prepare appropriate measures. This study estimated temporal change in the SFP water temperature at Kori Unit 1 with 587 MWe for 1 hour after initiation of a loss-of-pool-cooling accident. For the estimation, ANSYS CFX 13.0 code was used. The estimation showed that the increasing rate of the water temperature was 3.90C per hour and the SFP water temperature could reach 1000C in 25.6 hours after the initiation of loss-of-pool-cooling accident.

Keywords: Spent fuel pool, water temperature, Kori Unit 1, a loss-of-pool-cooling accident.

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162 Neural Network Ensemble-based Solar Power Generation Short-Term Forecasting

Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka

Abstract:

This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.

Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study

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161 Inadequacy of Macronutrient and Micronutrient Intake in Children Aged 12-23 Months Old: An Urban Study in Central Jakarta, Indonesia

Authors: Dewi Fatmaningrum, Ade Wiradnyani

Abstract:

Optimal feeding, including optimal micronutrient intake, becomes one of the ways to overcome the long-term consequences of undernutrition. Macronutrient and micronutrient intake were important to a rapid growth and development of young children. The study objective was to assess macro and micronutrient intake and its adequacy in children aged 12-23 months. This survey was a cross-sectional study, involving 83 caregivers with children aged 12-23 months old in Senen Sub-district, Central Jakarta selected through simple random sampling. Data on nutrient intake was obtained through interview using single 24-hour recall. Repeated 24- hour recall to sub-sample was done to estimate the proportion of nutrient inadequacy. The highest prevalence of nutrient inadequacy was iron (52.4%), followed by vitamin C (30.9%) and zinc (28.8%). Almost 12% children had inadequate energy intake. More than half of children (62.6%) were anemic (25.3% were severely anemic). Micronutrient inadequacy, especially iron, was more problematic than macronutrient inadequacy in the study area.

Keywords: Micronutrient, macronutrient, children under five, urban setting.

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160 One Hour Ahead Load Forecasting Using Artificial Neural Network for the Western Area of Saudi Arabia

Authors: A. J. Al-Shareef, E. A. Mohamed, E. Al-Judaibi

Abstract:

Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Keywords: Artificial neural networks, short-term load forecasting, back propagation.

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159 Application of Neural Networks for 24-Hour-Ahead Load Forecasting

Authors: Fatemeh Mosalman Yazdi

Abstract:

One of the most important requirements for the operation and planning activities of an electrical utility is the prediction of load for the next hour to several days out, known as short term load forecasting. This paper presents the development of an artificial neural network based short-term load forecasting model. The model can forecast daily load profiles with a load time of one day for next 24 hours. In this method can divide days of year with using average temperature. Groups make according linearity rate of curve. Ultimate forecast for each group obtain with considering weekday and weekend. This paper investigates effects of temperature and humidity on consuming curve. For forecasting load curve of holidays at first forecast pick and valley and then the neural network forecast is re-shaped with the new data. The ANN-based load models are trained using hourly historical. Load data and daily historical max/min temperature and humidity data. The results of testing the system on data from Yazd utility are reported.

Keywords: Artificial neural network, Holiday forecasting, pickand valley load forecasting, Short-term load-forecasting.

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158 Influence of Flood Detention Capability in Flood Prevention for Flood Disaster of Depression Area

Authors: Chia Lin Chan, Yi Ju Yang, Chih Chin Yang

Abstract:

Rainfall records of rainfall station including the rainfall potential per hour and rainfall mass of five heavy storms are explored, respectively from 2001 to 2010. The rationalization formula is to investigate the capability of flood peak duration of flood detention pond in different rainfall conditions. The stable flood detention model is also proposed by using system dynamic control theory to get the message of flood detention pond in this research. When rainfall frequency of one hour rainfall duration is more than 100-year frequency which exceeds the flood detention standard of 20-year frequency for the flood detention pond, the flood peak duration of flood detention pond is 1.7 hours at most even though the flood detention pond with maximum drainage potential about 15.0 m3/s of pumping system is constructed. If the rainfall peak current is more than maximum drainage potential, the flood peak duration of flood detention pond is about 1.9 hours at most. The flood detention pond is the key factor of stable drainage control and flood prevention. The critical factors of flood disaster is not only rainfall mass, but also rainfall frequency of heavy storm in different rainfall duration and flood detention frequency of flood detention system.

Keywords: Rainfall frequency, Rainfall duration, Rainfallintensity, Flood detention capability

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157 Forecasting 24-Hour Ahead Electricity Load Using Time Series Models

Authors: Ramin Vafadary, Maryam Khanbaghi

Abstract:

Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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156 Optimization and Feasibility Analysis of PV/Wind/ Battery Hybrid Energy Conversion

Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

Abstract:

In this paper, the optimum design for renewable energy system powered an aquaculture pond was determined. Hybrid Optimization Model for Electric Renewable (HOMER) software program, which is developed by U.S National Renewable Energy Laboratory (NREL), is used for analyzing the feasibility of the stand alone and hybrid system in this study. HOMER program determines whether renewable energy resources satisfy hourly electric demand or not. The program calculates energy balance for every 8760 hours in a year to simulate operation of the system. This optimization compares the demand for the electrical energy for each hour of the year with the energy supplied by the system for that hour and calculates the relevant energy flow for each component in the model. The essential principle is to minimize the total system cost while HOMER ensures control of the system. Moreover the feasibility analysis of the energy system is also studied. Wind speed, solar irradiance, interest rate and capacity shortage are the parameters which are taken into consideration. The simulation results indicate that the hybrid system is the best choice in this study, yielding lower net present cost. Thus, it provides higher system performance than PV or wind stand alone systems.

Keywords: Wind stand-alone system, Photovoltaic stand-alone system, Hybrid system, Optimum system sizing, feasibility, Cost analysis.

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155 Arduino Pressure Sensor Cushion for Tracking and Improving Sitting Posture

Authors: Andrew Hwang

Abstract:

The average American worker sits for thirteen hours a day, often with poor posture and infrequent breaks, which can lead to health issues and back problems. The Smart Cushion was created to alert individuals of their poor postures, and may potentially alleviate back problems and correct poor posture. The Smart Cushion is a portable, rectangular, foam cushion, with five strategically placed pressure sensors, that utilizes an Arduino Uno circuit board and specifically designed software, allowing it to collect data from the five pressure sensors and store the data on an SD card. The data is then compiled into graphs and compared to controlled postures. Before volunteers sat on the cushion, their levels of back pain were recorded on a scale from 1-10. Data was recorded for an hour during sitting, and then a new, corrected posture was suggested. After using the suggested posture for an hour, the volunteers described their level of discomfort on a scale from 1-10. Different patterns of sitting postures were generated that were able to serve as early warnings of potential back problems. By using the Smart Cushion, the areas where different volunteers were applying the most pressure while sitting could be identified, and the sitting postures could be corrected. Further studies regarding the relationships between posture and specific regions of the body are necessary to better understand the origins of back pain; however, the Smart Cushion is sufficient for correcting sitting posture and preventing the development of additional back pain.

Keywords: Arduino Sketch Algorithm, biomedical technology, pressure sensors, Smart Cushion.

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154 Gastroprotective Activity of Swietenia Mahagoni Seed Extract on Ethanol-Induced Gastric Mucosal Injury in Rats

Authors: Salma Saleh Alrdahe, Mahmood Ameen Abdulla, Shaharudin Abul Razak, Farkaad Abdul Kadir, Pouya Hassandarvish

Abstract:

Swietenia mahagoni have been used in traditional medicine for treatment of different diseases. Present study was performed to evaluate anti-ulcerogenic activity of ethanol seed extract against ethanol induced gastric mucosal injury in rats. Six groups of rats were orally pre-treated respectively with carboxymethyl cellulose, omeprazole 20 mg/kg, 50, 100, 200 and 400 mg/kg plant extract one hour before oral administration of absolute ethanol to generate gastric mucosal injury. After additional hour, rats were sacrificed and ulcer areas of gastric walls were determined. Grossly, carboxymethyl cellulose group exhibited severe mucosal injury, whereas pre-treatment with plant extract exhibited significant protection of gastric mucosa. Histology, carboxymethyl cellulose group exhibited severe damage of gastric mucosa; edema and leucocytes infiltration of sub mucosa compared to plant extract which showed gastric protection. Acute toxicity study did not manifest any toxicological signs in rats. Conclusions, results suggest that S. mahagoni promotes ulcer protection as ascertained grossly and histologically.

Keywords: Cytoprotection, Gastric ulcer, Histology, Swieteniamahagoni seed.

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153 Formation of Protective Aluminum-Oxide Layer on the Surface of Fe-Cr-Al Sintered-Metal-Fibers via Multi-Stage Thermal Oxidation

Authors: Loai Ben Naji, Osama M. Ibrahim, Khaled J. Al-Fadhalah

Abstract:

The objective of this paper is to investigate the formation and adhesion of a protective aluminum-oxide (Al2O3, alumina) layer on the surface of Iron-Chromium-Aluminum Alloy (Fe-Cr-Al) sintered-metal-fibers. The oxide-scale layer was developed via multi-stage thermal oxidation at 930 oC for 1 hour, followed by 1 hour at 960 oC, and finally at 990 oC for 2 hours. Scanning Electron Microscope (SEM) images show that the multi-stage thermal oxidation resulted in the formation of predominantly Al2O3 platelets-like and whiskers. SEM images also reveal non-uniform oxide-scale growth on the surface of the fibers. Furthermore, peeling/spalling of the alumina protective layer occurred after minimum handling, which indicates weak adhesion forces between the protective layer and the base metal alloy.  Energy Dispersive Spectroscopy (EDS) analysis of the heat-treated Fe-Cr-Al sintered-metal-fibers confirmed the high aluminum content on the surface of the protective layer, and the low aluminum content on the exposed base metal alloy surface. In conclusion, the failure of the oxide-scale protective layer exposes the base metal alloy to further oxidation, and the fragile non-uniform oxide-scale is not suitable as a support for catalysts.

Keywords: High-temperature oxidation, alumina protective layer, iron-chromium-aluminum alloy, sintered-metal-fibers.

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152 Carcass Characteristics and Qualities of Philippine White Mallard (Anas boschas L.) and Pekin (Anas platyrhynchos L.) Duck

Authors: Jerico M. Consolacion, Maria Cynthia R. Oliveros

Abstract:

The Philippine White Mallard duck was compared with Pekin duck for potential meat production. A total of 50 ducklings were randomly assigned to five (5) pens per treatment after one month of brooding. Each pen containing five (5) ducks was considered as a replicate. The ducks were raised until 12 weeks of age and slaughtered at the end of the growing period. Meat from both breeds was analyzed. The data were subjected to the Independent-Sample T-test at 5% level of confidence. Results showed that post-mortem pH (0, 20 minutes, 50 minutes, 1 hour and 20 minutes, 1 hour and 50 minutes, and 24 hours ) did not differ significantly (P>0.05) between breeds. However, Pekin ducks (89.84±0.71) had a significantly higher water-holding capacity than Philippine White Mallard ducks (87.93±0.63) (P<0.05). Also, meat color (CIE L, a, b) revealed that no significant differences among the lightness, redness, and yellowness of the skin (breast) in both breeds (P>0.05) except for the yellowness of the lean muscles of the Pekin duck breast. Pekin duck meat (1.15±0.04) had significantly higher crude fat content than Philippine White Mallard (0.47±0.58). The study clearly showed that breed is a factor and provided some pronounced effects among the parameters. However, these results are considered as preliminary information on the meat quality of Philippine White Mallard duck. Hence, further studies are needed to understand and fully utilize it for meat production and develop different meat products from this breed.

Keywords: Crude fat, meat quality, water-holding capacity.

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151 Evaluating Emission Reduction Due to a Proposed Light Rail Service: A Micro-Level Analysis

Authors: Saeid Eshghi, Neeraj Saxena, Abdulmajeed Alsultan

Abstract:

Carbon dioxide (CO2) alongside other gas emissions in the atmosphere cause a greenhouse effect, resulting in an increase of the average temperature of the planet. Transportation vehicles are among the main contributors of CO2 emission. Stationary vehicles with initiated motors produce more emissions than mobile ones. Intersections with traffic lights that force the vehicles to become stationary for a period of time produce more CO2 pollution than other parts of the road. This paper focuses on analyzing the CO2 produced by the traffic flow at Anzac Parade Road - Barker Street intersection in Sydney, Australia, before and after the implementation of Light rail transport (LRT). The data are gathered during the construction phase of the LRT by collecting the number of vehicles on each path of the intersection for 15 minutes during the evening rush hour of 1 week (6-7 pm, July 04-31, 2018) and then multiplied by 4 to calculate the flow of vehicles in 1 hour. For analyzing the data, the microscopic simulation software “VISSIM” has been used. Through the analysis, the traffic flow was processed in three stages: before and after implementation of light rail train, and one during the construction phase. Finally, the traffic results were input into another software called “EnViVer”, to calculate the amount of CO2 during 1 h. The results showed that after the implementation of the light rail, CO2 will drop by a minimum of 13%. This finding provides an evidence that light rail is a sustainable mode of transport.

Keywords: Carbon dioxide, emission modeling, light rail, microscopic model, traffic flow.

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150 Long-term Monitor of Seawater by using TiO2:Ru Sensing Electrode for Hard Clam Cultivation

Authors: Jung-Chuan Chou, Cheng-Wei Chen

Abstract:

The hard clam (meretrix lusoria) cultivated industry has been developed vigorously for recent years in Taiwan, and seawater quality determines the cultivated environment. The pH concentration variation affects survival rate of meretrix lusoria immediately. In order to monitor seawater quality, solid-state sensing electrode of ruthenium-doped titanium dioxide (TiO2:Ru) is developed to measure hydrogen ion concentration in different cultivated solutions. Because the TiO2:Ru sensing electrode has high chemical stability and superior sensing characteristics, thus it is applied as a pH sensor. Response voltages of TiO2:Ru sensing electrode are readout by instrument amplifier in different sample solutions. Mean sensitivity and linearity of TiO2:Ru sensing electrode are 55.20 mV/pH and 0.999 from pH1 to pH13, respectively. We expect that the TiO2:Ru sensing electrode can be applied to real environment measurement, therefore we collect two sample solutions by different meretrix lusoria cultivated ponds in the Yunlin, Taiwan. The two sample solutions are both measured for 200 seconds after calibration of standard pH buffer solutions (pH7, pH8 and pH 9). Mean response voltages of sample 1 and sample 2 are -178.758 mV (Standard deviation=0.427 mV) and -180.206 mV (Standard deviation =0.399 mV), respectively. Response voltages of the two sample solutions are between pH 8 and pH 9 which conform to weak alkali range and suitable meretrix lusoria growth. For long-term monitoring, drift of cultivated solutions (sample 1 and sample 2) are 1.16 mV/hour and 1.03 mV/hour, respectively.

Keywords: Co-sputtering system, Hard clam (meretrix lusoria), Ruthenium-doped titanium dioxide, Solid-state sensing electrode.

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149 Perceptual and Ultrasound Articulatory Training Effects on English L2 Vowels Production by Italian Learners

Authors: I. Sonia d’Apolito, Bianca Sisinni, Mirko Grimaldi, Barbara Gili Fivela

Abstract:

The American English contrast /ɑ-ʌ/ (cop-cup) is difficult to be produced by Italian learners since they realize L2-/ɑ-ʌ/ as L1-/ɔ-a/ respectively, due to differences in phonetic-phonological systems and also in grapheme-to-phoneme conversion rules. In this paper, we try to answer the following research questions: Can a short training improve the production of English /ɑ-ʌ/ by Italian learners? Is a perceptual training better than an articulatory (ultrasound - US) training? Thus, we compare a perceptual training with an US articulatory one to observe: 1) the effects of short trainings on L2-/ɑ-ʌ/ productions; 2) if the US articulatory training improves the pronunciation better than the perceptual training. In this pilot study, 9 Salento-Italian monolingual adults participated: 3 subjects performed a 1-hour perceptual training (ES-P); 3 subjects performed a 1-hour US training (ES-US); and 3 control subjects did not receive any training (CS). Verbal instructions about the phonetic properties of L2-/ɑ-ʌ/ and L1-/ɔ-a/ and their differences (representation on F1-F2 plane) were provided during both trainings. After these instructions, the ES-P group performed an identification training based on the High Variability Phonetic Training procedure, while the ES-US group performed the articulatory training, by means of US video of tongue gestures in L2-/ɑ-ʌ/ production and dynamic view of their own tongue movements and position using a probe under their chin. The acoustic data were analyzed and the first three formants were calculated. Independent t-tests were run to compare: 1) /ɑ-ʌ/ in pre- vs. post-test respectively; /ɑ-ʌ/ in pre- and post-test vs. L1-/a-ɔ/ respectively. Results show that in the pre-test all speakers realize L2-/ɑ-ʌ/ as L1-/ɔ-a/ respectively. Contrary to CS and ES-P groups, the ES-US group in the post-test differentiates the L2 vowels from those produced in the pre-test as well as from the L1 vowels, although only one ES-US subject produces both L2 vowels accurately. The articulatory training seems more effective than the perceptual one since it favors the production of vowels in the correct direction of L2 vowels and differently from the similar L1 vowels.

Keywords: L2 vowel production, perceptual training, articulatory training, ultrasound.

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148 Biodiesel Production from Waste Chicken Fatbased Sources

Authors: Kambiz Tahvildari A., Narges Davari B., Mohammadreza Allahgholi Ghasri C, MasoomehBehrourzinavid D

Abstract:

Chicken fat was employed as a feedstock for producing of biodiesel by trasesterification reaction with methanol and alkali catalyst (KOH). In this study chicken fat biodiesel with 1.4% free fatty acid, methanol and various amount of potassium hydroxide for 2 hour were studied. The progression of reaction and conversion of triglycerides to methyl ester were checked by IR spectrum method.

Keywords: Alkali catalyst, biodiesel, chicken fat, transesterification reaction

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147 Heart Rate Variability Analysis for Early Stage Prediction of Sudden Cardiac Death

Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

Abstract:

In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: Early stage prediction, heart rate variability, linear and non linear analysis, sudden cardiac death.

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146 Green Building and Energy Saving

Authors: Nahed Ayedh Al-Hajeri

Abstract:

In a world of climate change and limited fossil fuel resources, renewable energy sources are playing an increasingly important role. Due to industrializations and population growth our economy and technologies today largely depend upon natural resources, which are not replaceable. Approximately 90% of our energy consumption comes from fossil fuels (viz. coal, oil and natural gas). The irony is that these resources are depleting. Also, the huge consumption of fossil fuels has caused visible damage to the environment in various forms viz. global warming, acid rains etc.

Keywords: Kilo watt, kilo watt hour, carbon di-oxide, photovoltaic, environmental protection agency, Kwaiti dinar.

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145 Mucus Secretion Responses to Various Sublethal Copper (II) Concentrations in the Mussel Perna perna

Authors: Kamleshan Pillay

Abstract:

The purpose of this study was to evaluate the use of mucus production as a biomarker. This was done by exposing the mussel Perna perna to various sublethal concentrations of Cu. Mussels are effective as a bioindicator species as they accumulate Cu in their tissues. Differences in mucus production rates were evaluated at different Cu concentrations. The findings of this study indicate that increasing Cu concentrations had a significant effect on the mucus production rates over a 24 hour exposure. There were also significant differences between the mucus production rates at different Cu concentrations (p < 0.05). Thus, mucus is an essential detoxification mechanism.

Keywords: Copper, Mucus, Depuration, Perna perna.

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144 Investigation of Utilization Possibility of Fluid Gas Desulfurization Waste for Industrial Waste Water Treatment

Authors: S. Kızıltas Demir, A. S. Kipcak, E. Moroydor Derun, N. Tugrul, S. Piskin

Abstract:

Flue gas desulfurization gypsum (FGD) is a waste material arouse from coal power plants. Hydroxyapatite (HAP) is a biomaterial with porous structure. In this study, FGD gypsum which retrieved from coal power plant in Turkey was characterized and HAP particles which can be used as an adsorbent in wastewater treatment application were synthesized from the FGD gypsum. The raw materials are characterized by using X Ray Diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) techniques and produced HAP are characterized by using XRD. As a result, HAP particles were synthesized at the molar ratio of 5:10, 5:15, 5:20, 5:24, at room temperature, in alkaline medium (pH=11) and in 1 hour-reaction time. Among these conditions, 5:20 had the best result.

Keywords: FGD wastes, HAP, gypsum, wastewater.

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