Search results for: single subject experimental designs.

Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: Academic performance prediction system, prediction model, educational data mining, dominant factors, feature selection methods, student performance.

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Authors: M. Ishak, K. Yamasaki, K. Maekawa

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Magnesium alloys have gained increased attention in recent years in automotive, electronics, and medical industry. This because of magnesium alloys have better properties than aluminum alloys and steels in respects of their low density and high strength to weight ratio. However, the main problems of magnesium alloy welding are the crack formation and the appearance of porosity during the solidification. This paper proposes a unique technique to weld two thin sheets of AZ31B magnesium alloy using a paste containing Ag nanoparticles. The paste containing Ag nanoparticles of 5 nm in average diameter and an organic solvent was used to coat the surface of AZ31B thin sheet. The coated sheet was heated at 100 °C for 60 s to evaporate the solvent. The dried sheet was set as a lower AZ31B sheet on the jig, and then lap fillet welding was carried out by using a pulsed Nd:YAG laser in a closed box filled with argon gas. The characteristics of the microstructure and the corrosion behavior of the joints were analyzed by opticalmicroscopy (OM), energy dispersive spectrometry (EDS), electron probe micro-analyzer (EPMA), scanning electron microscopy (SEM), and immersion corrosion test. The experimental results show that the wrought AZ31B magnesium alloy can be joined successfully using Ag nanoparticles. Ag nanoparticles insert promote grain refinement, narrower the HAZ width and wider bond width compared to weld without and insert. Corrosion rate of welded AZ31B with Ag nanoparticles reduced up to 44 % compared to base metal. The improvement of corrosion resistance of welded AZ31B with Ag nanoparticles due to finer grains and large grain boundaries area which consist of high Al content. β-phase Mg17Al12 could serve as effective barrier and suppressed further propagation of corrosion. Furthermore, Ag distribution in fusion zone provide much more finer grains and may stabilize the magnesium solid solution making it less soluble or less anodic in aqueous

Keywords: Laser welding, magnesium alloys, nanoparticles, mechanical property

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Authors: K. A. Weidenmann, M. Grigo, B. Brylka, P. Elsner, T. Böhlke

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In order to reduce fuel consumption, the weight of automobiles has to be reduced. Fiber reinforced polymers offer the potential to reach this aim because of their high stiffness to weight ratio. Additionally, the use of fiber reinforced polymers in automotive applications has to allow for an economic large-scale production. In this regard, long fiber reinforced thermoplastics made by direct processing offer both mechanical performance and processability in injection moulding and compression moulding. The work presented in this contribution deals with long glass fiber reinforced polypropylene directly processed in compression moulding (D-LFT). For the use in automotive applications both the temperature and the time dependency of the materials properties have to be investigated to fulfill performance requirements during crash or the demands of service temperatures ranging from -40 °C to 80 °C. To consider both the influence of temperature and time, quasistatic tensile tests have been carried out at different temperatures. These tests have been complemented by high speed tensile tests at different strain rates. As expected, the increase in strain rate results in an increase of the elastic modulus which correlates to an increase of the stiffness with decreasing service temperature. The results are in good accordance with results determined by dynamic mechanical analysis within the range of 0.1 to 100 Hz. The experimental results from different testing methods were grouped and interpreted by using different time temperature shift approaches. In this regard, Williams-Landel-Ferry and Arrhenius approach based on kinetics have been used. As the theoretical shift factor follows an arctan function, an empirical approach was also taken into consideration. It could be shown that this approach describes best the time and temperature superposition for glass fiber reinforced polypropylene manufactured by D-LFT processing.

Keywords: Composite, long fiber reinforced thermoplastics, mechanical properties, dynamic mechanical analysis, time temperature superposition.

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: Data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index.

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Authors: Maksudur Rahman Khan, Kar Min Chan, Huei Ruey Ong, Chin Kui Cheng, Wasikur Rahman

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Microbial fuel cells (MFCs) represent a promising technology for simultaneous bioelectricity generation and wastewater treatment. Catalysts are significant portions of the cost of microbial fuel cell cathodes. Many materials have been tested as aqueous cathodes, but air-cathodes are needed to avoid energy demands for water aeration. The sluggish oxygen reduction reaction (ORR) rate at air cathode necessitates efficient electrocatalyst such as carbon supported platinum catalyst (Pt/C) which is very costly. Manganese oxide (MnO2) was a representative metal oxide which has been studied as a promising alternative electrocatalyst for ORR and has been tested in air-cathode MFCs. However the single MnO2 has poor electric conductivity and low stability. In the present work, the MnO2 catalyst has been modified by doping Pt nanoparticle. The goal of the work was to improve the performance of the MFC with minimum Pt loading. MnO2 and Pt nanoparticles were prepared by hydrothermal and sol gel methods, respectively. Wet impregnation method was used to synthesize Pt/MnO2 catalyst. The catalysts were further used as cathode catalysts in air-cathode cubic MFCs, in which anaerobic sludge was inoculated as biocatalysts and palm oil mill effluent (POME) was used as the substrate in the anode chamber. The asprepared Pt/MnO2 was characterized comprehensively through field emission scanning electron microscope (FESEM), X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and cyclic voltammetry (CV) where its surface morphology, crystallinity, oxidation state and electrochemical activity were examined, respectively. XPS revealed Mn (IV) oxidation state and Pt (0) nanoparticle metal, indicating the presence of MnO2 and Pt. Morphology of Pt/MnO2 observed from FESEM shows that the doping of Pt did not cause change in needle-like shape of MnO2 which provides large contacting surface area. The electrochemical active area of the Pt/MnO2 catalysts has been increased from 276 to 617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The CV results in O2 saturated neutral Na2SO4 solution showed that MnO2 and Pt/MnO2 catalysts could catalyze ORR with different catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode catalyst generates a maximum power density of 165 mW/m3, which is higher than that of MFC with MnO2 catalyst (95 mW/m3). The open circuit voltage (OCV) of the MFC operated with MnO2 cathode gradually decreased during 14 days of operation, whereas the MFC with Pt/MnO2 cathode remained almost constant throughout the operation suggesting the higher stability of the Pt/MnO2 catalyst. Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced performance.

Keywords: Microbial fuel cell, oxygen reduction reaction, Pt/MnO2, palm oil mill effluent, polarization curve.

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Authors: Pravesh Chandra Shukla, Kunal Ghosh

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Over 90% of the world trade is carried by the international shipping industry. As most of the countries are developing, seaborne trade continues to expand to bring benefits for consumers across the world. Studies show that world trade will increase 70-80% through shipping in the next 15-20 years. Present global fleet of 70000 commercial ships consumes approximately 200 million tonnes of diesel fuel a year and it is expected that it will be around 350 million tonnes a year by 2020. It will increase the demand for fuel and also increase the concentration of CO2 in the atmosphere. So, it-s essential to control this massive fuel consumption and CO2 emission. The idea is to utilize a diesel-wind hybrid system for ship propulsion. Use of wind energy by installing modern wing-sails in ships can drastically reduce the consumption of diesel fuel. A huge amount of wind energy is available in oceans. Whenever wind is available the wing-sails would be deployed and the diesel engine would be throttled down and still the same forward speed would be maintained. Wind direction in a particular shipping route is not same throughout; it changes depending upon the global wind pattern which depends on the latitude. So, the wing-sail orientation should be such that it optimizes the use of wind energy. We have made a computer programme in which by feeding the data regarding wind velocity, wind direction, ship-motion direction; we can find out the best wing-sail position and fuel saving for commercial ships. We have calculated net fuel saving in certain international shipping routes, for instance, from Mumbai in India to Durban in South Africa. Our estimates show that about 8.3% diesel fuel can be saved by utilizing the wind. We are also developing an experimental model of the ship employing airfoils (small scale wingsail) and going to test it in National Wind Tunnel Facility in IIT Kanpur in order to develop a control mechanism for a system of airfoils.

Keywords: Commercial ships, Wind diesel hybrid system, Wing-sail, Wind direction, Wind velocity.

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Authors: Khosro Mohammadi, Amir Ghalavand, Majid Aghaalikhani

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In order to Study the efficacy application of green manure as chickpea pre plant, field experiments were carried out in 2007 and 2008 growing seasons. In this research the effects of different strategies for soil fertilization were investigated on grain yield and yield component, minerals, organic compounds and cooking time of chickpea. Experimental units were arranged in splitsplit plots based on randomized complete blocks with three replications. Main plots consisted of (G1): establishing a mixed vegetation of Vicia panunica and Hordeum vulgare and (G2): control, as green manure levels. Also, five strategies for obtaining the base fertilizer requirement including (N1): 20 t.ha-1 farmyard manure; (N2): 10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate; (N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1 triple super phosphate were considered in sub plots. Furthermoree four levels of biofertilizers consisted of (B1): Bacillus lentus + Pseudomonas putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus + Pseudomonas putida + Trichoderma harzianum; and (B4): control (without biofertilizers) were arranged in sub-sub plots. Results showed that integrating biofertilizers (B3) and green manure (G1) produced the highest grain yield. The highest amounts of yield were obtained in G1×N5 interaction. Comparison of all 2-way and 3-way interactions showed that G1N5B3 was determined as the superior treatment. Significant increasing of N, P2O5, K2O, Fe and Mg content in leaves and grains emphasized on superiority of mentioned treatment because each one of these nutrients has an approved role in chlorophyll synthesis and photosynthesis abilities of the crops. The combined application of compost, farmyard manure and chemical phosphorus (N5) in addition to having the highest yield, had the best grain quality due to high protein, starch and total sugar contents, low crude fiber and reduced cooking time.

Keywords: chickpea, biofertilizer, nitrogen fixation.

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Authors: H. Alabed, K. Abuzayan, J. Waterhouse

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The Muslim faith requires individuals to fast between the hours of sunrise and sunset during the month of Ramadan. Our recent work has concentrated on some of the changes that take place during the daytime when fasting. A questionnaire was developed to assess subjective estimates of physical, mental and social activities, and fatigue. Four days were studied: in the weeks before and after Ramadan (control days) and during the first and last weeks of Ramadan (experimental days). On each of these four days, this questionnaire was given several times during the daytime and once after the fast had been broken and just before individuals retired at night. During Ramadan, daytime mental, physical and social activities all decreased below control values but then increased to abovecontrol values in the evening. The desires to perform physical and mental activities showed very similar patterns. That is, individuals tried to conserve energy during the daytime in preparation for the evenings when they ate and drank, often with friends. During Ramadan also, individuals were more fatigued in the daytime and napped more often than on control days. This extra fatigue probably reflected decreased sleep, individuals often having risen earlier (before sunrise, to prepare for fasting) and retired later (to enable recovery from the fast). Some physiological measures and objective measures of performance (including the response to a bout of exercise) have also been investigated. Urine osmolality fell during the daytime on control days as subjects drank, but rose in Ramadan to reach values at sunset indicative of dehydration. Exercise performance was also compromised, particularly late in the afternoon when the fast had lasted several hours. Self-chosen exercise work-rates fell and a set amount of exercise felt more arduous. There were also changes in heart rate and lactate accumulation in the blood, indicative of greater cardiovascular and metabolic stress caused by the exercise in subjects who had been fasting. Daytime fasting in Ramadan produces widespread effects which probably reflect combined effects of sleep loss and restrictions to intakes of water and food.

Keywords: Drinking, Eating, Mental Performance, Physical Performance, Social Activity, Sleepiness.

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Authors: Randy Gomez, Keisuke Nakamura, Kazuhiro Nakadai

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Distant-talking voice-based HCI system suffers from performance degradation due to mismatch between the acoustic speech (runtime) and the acoustic model (training). Mismatch is caused by the change in the power of the speech signal as observed at the microphones. This change is greatly influenced by the change in distance, affecting speech dynamics inside the room before reaching the microphones. Moreover, as the speech signal is reflected, its acoustical characteristic is also altered by the room properties. In general, power mismatch due to distance is a complex problem. This paper presents a novel approach in dealing with distance-induced mismatch by intelligently sensing instantaneous voice power variation and compensating model parameters. First, the distant-talking speech signal is processed through microphone array processing, and the corresponding distance information is extracted. Distance-sensitive Gaussian Mixture Models (GMMs), pre-trained to capture both speech power and room property are used to predict the optimal distance of the speech source. Consequently, pre-computed statistic priors corresponding to the optimal distance is selected to correct the statistics of the generic model which was frozen during training. Thus, model combinatorics are post-conditioned to match the power of instantaneous speech acoustics at runtime. This results to an improved likelihood in predicting the correct speech command at farther distances. We experiment using real data recorded inside two rooms. Experimental evaluation shows voice recognition performance using our method is more robust to the change in distance compared to the conventional approach. In our experiment, under the most acoustically challenging environment (i.e., Room 2: 2.5 meters), our method achieved 24.2% improvement in recognition performance against the best-performing conventional method.

Keywords: Human Machine Interaction, Human Computer Interaction, Voice Recognition, Acoustic Model Compensation, Acoustic Speech Enhancement.

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Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain

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This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.

Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: Subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing.

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Authors: Jaka Suyana, Komariah, Masateru Senge

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This research was aimed at determining the impact of conservation techniques including bench terrace, stone terrace, mulching, grass strip and intercropping on soil erosion at tobacco-based farming system at Progo Hulu subwatershed, Central Java, Indonesia. Research was conducted from September 2007 to September 2009, located at Progo Hulu subwatershed, Central Java, Indonesia. Research site divided into 27 land units, and experimental fields were grouped based on the soil type and slope, ie: 30%, 45% and 70%, with the following treatments: 1) ST0= stone terrace (control); 2) ST1= stone terrace + Setaria spacelata grass strip on a 5 cm height dike at terrace lips + tobacco stem mulch with dose of 50% (7 ton/ ha); 3) ST2= stone terrace + Setaria spacelata grass strip on a 5 cm height dike at terrace lips + tobacco stem mulch with dose of 100% (14 ton/ ha); 4) ST3= stone terrace + tobacco and red bean intercropping + tobacco stem mulch with dose of 50% (7 ton/ ha). 5) BT0= bench terrace (control); 6) BT1= bench terrace + Setaria spacelata grass strip at terrace lips + tobacco stem mulch with dose of 50% (7 ton/ ha); 7) BT2= bench terrace + Setaria spacelata grass strip at terrace lips + tobacco stem mulch with dose of 100% (14 ton/ ha); 8) BT3= bench terrace + tobacco and red bean intercropping + tobacco stem mulch with dose of 50% (7 ton/ ha). The results showed that the actual erosion rates of research site were higher than that of tolerance erosion with mean value 89.08 ton/ha/year and 33.40 ton/ha/year, respectively. These resulted in 69% of total research site (5,119.15 ha) highly degraded. Conservation technique of ST2 was the most effective in suppressing soil erosion, by 42.87%, following with BT2 as much 30.63%. Others suppressed erosion only less than 21%.

Keywords: Steep land, subwatershed, conservation terrace, tolerance erosion.

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Authors: W. Thongwat, B. Terakulsatit

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The study area is Kham Sakaesaeng District in Nakhon Ratchasima Province, the south section of Northeastern Thailand, located in the Lower Khorat-Ubol Basin. This region is the one of saline soil area, located in a dry plateau and regularly experience standing with periods of floods and alternating with periods of drought. Especially, the drought in the summer season causes the major saline soil and saline water problems of this region. The general cause of dry land salting resulted from salting on irrigated land, and an excess of water leading to the rising water table in the aquifer. The purpose of this study is to determine the relationship of physical and chemical properties between the soil and groundwater. The soil and groundwater samples were collected in both rainy and summer seasons. The content of pH, electrical conductivity (EC), total dissolved solids (TDS), chloride and salinity were investigated. The experimental result of soil and groundwater samples show the slightly pH less than 7, EC (186 to 8,156 us/cm and 960 to 10,712 us/cm), TDS (93 to 3,940 ppm and 480 to 5,356 ppm), chloride content (45.58 to 4,177,015 mg/l and 227.90 to 9,216,736 mg/l), and salinity (0.07 to 4.82 ppt and 0.24 to 14.46 ppt) in the rainy and summer seasons, respectively. The distribution of chloride content and salinity content were interpolated and displayed as a map by using ArcMap 10.3 program, according to the season. The result of saline soil and brined groundwater in the study area were related to the low-lying topography, drought area, and salt-source exposure. Especially, the Rock Salt Member of Maha Sarakham Formation was exposed or lies near the ground surface in this study area. During the rainy season, salt was eroded or weathered from the salt-source rock formation and transported by surface flow or leached into the groundwater. In the dry season, the ground surface is dry enough resulting salt precipitates from the brined surface water or rises from the brined groundwater influencing the increasing content of chloride and salinity in the ground surface and groundwater.

Keywords: Environmental geology, soil salinity, geochemistry, groundwater hydrology.

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Authors: Saranya Chularee, Tawa Chularee

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Successful intelligence (SI) is the integrated set of the ability needed to attain success in life, within individual-s sociocultural context. People are successfully intelligent by recognizing their strengths and weaknesses. They will find ways to strengthen their weakness and maintain their strength or even improve it. SI people can shape, select, and adapt to the environments by using balance of higher-ordered thinking abilities including; critical, creative, and applicative. Aims: The purposes of this study were to; 1) develop curriculum that promotes SI for nursing students, and 2) study the effectiveness of the curriculum development. Method: Research and Development was a method used for this study. The design was divided into two phases; 1) the curriculum development which composed of three steps (needs assessment, curriculum development and curriculum field trail), and 2) the curriculum implementation. In this phase, a pre-experimental research design (one group pretest-posttest design) was conducted. The sample composed of 49 sophomore nursing students of Boromarajonani College of Nursing, Surin, Thailand who enrolled in Nursing care of Health problem course I in 2011 academic year. Data were carefully collected using 4 instruments; 1) Modified essay questions test (MEQ) 2) Nursing Care Plan evaluation form 3) Group processing observation form (α = 0.74) and 4) Satisfied evaluation form of learning (α = 0.82). Data were analyzed using descriptive statistics and content analysis. Results: The results revealed that the sample had post-test average score of SI higher than pre-test average score (mean difference was 5.03, S.D. = 2.84). Fifty seven percentages of the sample passed the MEQ posttest at the criteria of 60 percentages. Students demonstrated the strategies of how to develop nursing care plan. Overall, students- satisfaction on teaching performance was at high level (mean = 4.35, S.D. = 0.46). Conclusion: This curriculum can promote the attribute of characteristic of SI person and was highly required to be continued.

Keywords: Curriculum Development, Nursing Education, Successful Intelligence, Thinking ability.

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Authors: Hanaa M. M. El-Khayat, Hoda Abdel-Hamid, Kadria M. A. Mahmoud, Hanan S. Gaber, Hoda, M. A. Abu Taleb, Hassan E. Flefel

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Snails are considered as suitable diagnostic organisms for heavy metal–contaminated sites. Biomphalaria alexandrina snails are used in this work as pollution bioindicators after exposure to chemical mixtures consisted of heavy metals (HM); zinc (Zn), copper (Cu) and lead (Pb); and persistent organic pollutants; Decabromodiphenyl ether 98% (D) and Aroclor 1254 (A). The impacts of these tested chemicals, individual and mixtures, on liver and kidney functions, antioxidant enzymes, complete blood picture, and tissue histology were studied. Results showed that Cu was proved to be the highly toxic against snails than Zn and Pb where LC₅₀ values were 1.362, 213.198 and 277.396 ppm, respectively. Also, B. alexandrina snails exposed to the mixture of HM (¼ LC₅ Cu, Pb and Zn) showed the highest bioaccumulation of Cu and Zn in their whole tissue, the most significant increase in AST, ALT & ALP activities and the highest significant levels of total protein, albumin and globulin. Results showed significant alterations in CAT activity in snail tissue extracts while snail samples exposed to most experimental tests showed significant increase in GST activity. Snail samples that exposed to HM mixtures showed a significant decrease in total hemocytes count while snail samples that exposed to mixtures containing A & D showed a significant increase in total hemocytes and Hyalinocytes. Histopathological alterations in snail samples exposed to individual HM and their mixtures for 4 weeks showed degeneration, edema, hyper trophy and vaculation in head-foot muscle, degeneration and necrotic changes in the digestive gland and accumulation in most tested organs. Also, the hermaphrodite gland showed mature ova with irregular shape and reduction in sperm number. In conclusion, the resulted damage and alterations in B. alexandrina studied parameters can be used as bioindicators to the presence of pollutants in its habitats.

Keywords: Biomphalaria, Zn, Cu, Pb, AST, ALT, ALP, total protein albumin, globulin, CAT and Histopathology.

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Authors: E. Cenderelli, E. Bruno, G. Iacoviello, A. Lazzini

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The financial sector is exposed to the risk of cyber-attacks like any other industrial sector. Furthermore, the topic of CybeRisk (cyber risk) has become particularly relevant given that Information Technology (IT) attacks have increased drastically in recent years, and cannot be stopped by single organizations requiring a response at international and national level. IT risk is never a matter purely for the IT manager, although he clearly plays a key role. A bank's risk management function requires a thorough understanding of the evolving risks as well as the tools and practical techniques available to address them. Upon the request of European and national legislation regarding CybeRisk in the financial system, banks are therefore called upon to strengthen the operational model for CybeRisk management. This will require an important change with a more intense collaboration with the structures that deal with information security for the development of an ad hoc system for the evaluation and control of this type of risk. The aim of the work is to propose a framework for the management and control of CybeRisk that will bridge the gap in the literature regarding the understanding and consideration of CybeRisk as an integral part of business management. The IT function has a strong relevance in the management of CybeRisk, which is perceived mainly as operational risk, but with a positive tendency on the part of risk management to the identification of CybeRisk assessment methods that are increasingly complete, quantitative and able to better describe the possible impacts on the business. The paper provides answers to the research questions: Is it possible to define a CybeRisk governance structure able to support the comparison between risk and security? How can the relationships between IT assets be integrated into a cyberisk assessment framework to guarantee a system of protection and risks control? From a methodological point of view, this research uses a case study approach. The choice of “Monte dei Paschi di Siena” was determined by the specific features of one of Italy’s biggest lenders. It is chosen to use an intensive research strategy: an in-depth study of reality. The case study methodology is an empirical approach to explore a complex and current phenomenon that develops over time. The use of cases has also the advantage of allowing the deepening of aspects concerning the "how" and "why" of contemporary events, on which the scholar has little control. The research bases on quantitative data and qualitative information obtained through semi-structured interviews of an open-ended nature and questionnaires to directors, members of the audit committee, risk, IT and compliance managers, and those responsible for internal audit function and anti-money laundering. The added value of the paper can be seen in the development of a framework based on a mapping of IT assets from which it is possible to identify their relationships for purposes of a more effective management and control of cyber risk.

Keywords: Bank, CybeRisk, information technology, risk management.

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Authors: Wolfram Irsa, Lorenz Boruch

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Innovative solutions in additive manufacturing applying material extrusion for functional parts necessitates innovative filaments with persistent quality. Uniform homogeneity and consistent dispersion of particles embedded in filaments generally require multiple cycles of extrusion or well-prepared primal matter by injection molding, kneader machines, or mixing equipment. These technologies commit to dedicated equipment that are rarely at disposal in production laboratories unfamiliar with research in polymer materials. This stands in contrast to laboratories which investigate on complex material topics and technology science to leverage on the potential of 3-D printing. Consequently, scientific studies in labs are often constrained to compositions and concentrations of fillers offered from the market. Therefore, we present a prototypal laboratory methodology scalable to tailored primal matter for extruding ceramic composite filaments with fused filament fabrication (FFF) technology. A desktop single-screw extruder serves as core device for the experiments. Custom-made filament encapsulates the ceramic fillers and serves with polylactide (PLA), which is a thermoplastic polyester, as primal matter and is processed in the melting area of the extruder preserving the defined concentration of the fillers. Validated results demonstrate that this approach enables continuously produced and uniform composite filaments with consistent homogeneity. It is 3-D printable with controllable dimensions, which is a prerequisite for any scalable application. Additionally, digital microscopy confirms steady dispersion of the ceramic particles in the composite filament. This permits a 2D reconstruction of the planar distribution of the embedded ceramic particles in the PLA matrices. The innovation of the introduced method lies in the smart simplicity of preparing the composite primal matter. It circumvents the inconvenience of numerous extrusion operations and expensive laboratory equipment. Nevertheless, it delivers consistent filaments of controlled, predictable, and reproducible filler concentration, which is the prerequisite for any industrial application. The introduced prototypal laboratory methodology seems capable for other polymer matrices and suitable to further utilitarian particle types, beyond and above of ceramic fillers. This inaugurates a roadmap for supplementary laboratory development of peculiar composite filaments, providing value for industries and societies. This low-threshold entry of sophisticated preparation of composite filaments - enabling businesses creating their own dedicated filaments - will support the mutual efforts for establishing 3D printing to new functional devices.

Keywords: Additive manufacturing, ceramic composites, complex filament, industrial application.

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Authors: Shima Fasahat

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This research is an experimental research which was done about microbial fuel cells in order to study them for electricity generating and wastewater treatment. These days, it is very important to find new, clean and sustainable ways for energy supplying. Because of this reason there are many researchers around the world who are studying about new and sustainable energies. There are different ways to produce these kind of energies like: solar cells, wind turbines, geothermal energy, fuel cells and many other ways. Fuel cells have different types one of these types is microbial fuel cell. In this research, an MFC was built in order to study how it can be used for electricity generating and wastewater treatment. The microbial fuel cell which was used in this research is a reactor that has two tanks with a catalyst solution. The chemical reaction in microbial fuel cells is a redox reaction. The microbial fuel cell in this research is a two chamber MFC. Anode chamber is an anaerobic one (ABR reactor) and the other chamber is a cathode chamber. Anode chamber consists of stabilized sludge which is the source of microorganisms that do redox reaction. The main microorganisms here are: Propionibacterium and Clostridium. The electrodes of anode chamber are graphite pages. Cathode chamber consists of graphite page electrodes and catalysts like: O₂, KMnO₄ and C₆N₆FeK₄. The membrane which separates the chambers is Nafion117. The reason of choosing this membrane is explained in the complete paper. The main goal of this research is to generate electricity and treating wastewater. It was found that when you use electron receptor compounds like: O_2, MnO₄, C₆N₆FeK₄ the velocity of electron receiving speeds up and in a less time more current will be achieved. It was found that the best compounds for this purpose are compounds which have iron in their chemical formula. It is also important to pay attention to the amount of nutrients which enters to bacteria chamber. By adding extra nutrients in some cases the result will be reverse.  By using ABR the amount of chemical oxidation demand reduces per day till it arrives to a stable amount.

Keywords: Anaerobic baffled reactor, bioenergy, electrode, energy efficient, microbial fuel cell, renewable chemicals, sustainable.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Surajit Debnath, Soma Addya

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Human genome is not only the evolutionary summation of all advantageous events, but also houses lesions of deleterious foot prints. A single gene mutation sometimes may express multiple consequences in numerous tissues and a linear relationship of the genotype and the phenotype may often be obscure. ß Thalassemia minor, a transfusion independent mild anaemia, coupled with environment among other factors may articulate into phenotypic pleotropy with Hypocholesterolemia, Vitamin D deficiency, Tissue hypoxia, Hyper-parathyroidism and Psychological alterations. Occurrence of Pancreatic insufficiency, resultant steatorrhoea, Vitamin-D (25-OH) deficiency (13.86 ngm/ml) with Hypocholesterolemia (85mg/dl) in a 30 years old male ß Thal-minor patient (Hemoglobin 11mg/dl with Fetal Hemoglobin 2.10%, Hb A2 4.60% and Hb Adult 84.80% and altered Hemogram) with increased Para thyroid hormone (62 pg/ml) & moderate Serum Ca+2 (9.5mg/ml) indicate towards a cascade of phenotypic pleotropy where the ß Thalassemia mutation ,be it in the 5’ cap site of the mRNA , differential splicing etc in heterozygous state is effecting several metabolic pathways. Compensatory extramedulary hematopoiesis may not coped up well with the stressful life style of the young individual and increased erythropoietic stress with high demand for cholesterol for RBC membrane synthesis may have resulted in Hypocholesterolemia.Oxidative stress and tissue hypoxia may have caused the pancreatic insufficiency, leading to Vitamin D deficiency. This may in turn have caused the secondary hyperparathyroidism to sustain serum Calcium level. Irritability and stress intolerance of the patient was a cumulative effect of the vicious cycle of metabolic compromises. From these findings we propose that the metabolic deficiencies in the ß Thalassemia mutations may be considered as the phenotypic display of the pleotropy to explain the genetic epidemiology. According to the recommendations from the NIH Workshop on Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model, study design of observations should be informed by gene-environment hypotheses and results of a study (genetic diseases) should be published to inform future hypotheses. Variety of approaches is needed to capture data on all possible aspects, each of which is likely to contribute to the etiology of disease. Speakers also agreed that there is a need for development of new statistical methods and measurement tools to appraise information that may be missed out by conventional method where large sample size is needed to segregate considerable effect. A meta analytic cohort study in future may bring about significant insight on to the title comment.

Keywords: Genetic disease, Genetic epidemiology, Heterozygous, Phenotype, Pleotropy, ß Thalassemia minor, Metabolic compromises.

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Authors: U. Pangnakorn, S. Chuenchooklin

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Acute and chronic effects of biopesticide from entomopathogenic nematode (Steinernema thailandensis n. sp.), bacteria ISR (Pseudomonas fluorescens), wood vinegar and fermented organic substances from plants: (neem Azadirachta indica + citronella grass Cymbopogon nardus Rendle + bitter bush Chromolaena odorata L.) were tested on culantro (Eryngium foetidum L.). The biopesticide was investigated for infestation reduction of the major insect pest whitefly (Bemisia tabaci (Gennadius)). The experimental plots were located at a farm in Nakhon Sawan Province, Thailand. This study was undertaken during the drought season (late November to May). Effectiveness of the treatment was evaluated in terms of acute and chronic effect. The populations of whitefly were observed and recorded every hour up to 3 hours with insect nets and yellow sticky traps after the treatments were applied for the acute effect. The results showed that bacteria ISR had the highest effectiveness for controlling whitefly infestation on culantro; the whitefly numbers on insect nets were 12.5, 10.0 and 7.5 after 1 hr, 2 hr, and 3 hr, respectively while the whitefly on yellow sticky traps showed 15.0, 10.0 and 10.0 after 1 hr, 2 hr, and 3 hr, respectively. For chronic effect, the whitefly was continuously collected and recorded at weekly intervals; the result showed that treatment of bacteria ISR found the average whitefly numbers only 8.06 and 11.0 on insect nets and sticky traps respectively, followed by treatment of nematode where the average whitefly was 9.87 and 11.43 on the insect nets and sticky traps, respectively. In addition, the minor insect pests were also observed and collected. The biopesticide influenced the reduction number of minor insect pests (red spider mites, beet armyworm, short-horned grasshopper, pygmy locusts, etc.) with only a few found on the culantro cultivation.

Keywords: Whitefly (Bemisia tabaci Gennadius), Culantro (Eryngium foetidum L.), Entomopathogenic nematode (Steinernema thailandensis n. sp.), Bacteria ISR (Pseudomonas fluorescens), wood vinegar, fermented organic substances.

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Authors: S. Grace Sahaya Sheba, R. Omegala Priakumari

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Polyethylene glycol (PEG) is a condensation polymer of ethylene oxide and water. It is soluble in water and in many organic solvents. PEG is used to make emulsifying agents, detergents, soaps, plasticizers, ointments etc. Ethanol (C₂H₅OH) also known as ethyl alcohol is a well-known organic compound and has wide applications in chemical industry as it is used as a solvent for paint, varnish, in preserving biological specimens, used as a fuel mixed with petrol etc. Though their chemical and physical properties are already studied, still because of their uses in day to day life the authors thought it is better to study some more of their physical properties like ultrasonic velocity and hence adiabatic compressibility, free length, etc. A detailed study of such properties and some excess parameters like excess adiabatic compressibility, excess free volume and few more in the liquid mixtures of these two compounds with PEG as a solute and Ethanol as a solvent at various mole fractions may throw some light on deeper understanding of molecular interaction between the solute and the solvent supported by NMR, IR etc. Hence the present research work is on ultrasonics/allied studies on these two liquid mixtures. Ultrasonic velocity (U), density (ρ) and viscosity (η) at room temperature and at different mole fraction from 0 to 0.055 of ethanol in PEG have been experimentally carried out by the authors. Acoustical parameters such as adiabatic compressibility (β), free volume (V_f), acoustic impedance (Z), internal pressure (π_i), intermolecular free length (L_f) and relaxation time (τ) were calculated from the experimental data. We have calculated excess parameters like excess adiabatic compressibility (β^E), excess internal pressure (π_i^E) free length (L_f^E) and excess acoustic impedance (Z^E) etc for these two chosen liquid mixtures. The excess compressibility is positive and maximum around a mole fraction 0.007 and excess internal pressure is negative and maximum at the same mole fraction and longer free length. The results are analyzed and it may be concluded that the molecular interactions between the solute and the solvent is not strong and it may be weak. Appropriate graphs are drawn.

Keywords: Adiabatic Compressibility, Binary mixture, Induce dipole, Polarizability, Ultrasonic.

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Authors: Victor Maldonado

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Recent concerns of the growing impact of aviation on climate change has prompted the emergence of a field referred to as Sustainable or “Green” Aviation dedicated to mitigating the harmful impact of aviation related CO2 emissions and noise pollution on the environment. In the current paper, a unique “green” business jet aircraft called the TransAtlantic was designed (using analytical formulation common in conceptual design) in order to show the feasibility for transatlantic passenger air travel with an aircraft weighing less than 10,000 pounds takeoff weight. Such an advance in fuel efficiency will require development and integration of advanced and emerging aerospace technologies. The TransAtlantic design is intended to serve as a research platform for the development of technologies such as active flow control. Recent advances in the field of active flow control and how this technology can be integrated on a sub-scale flight demonstrator are discussed in this paper. Flow control is a technique to modify the behavior of coherent structures in wall-bounded flows (over aerodynamic surfaces such as wings and turbine nozzles) resulting in improved aerodynamic cruise and flight control efficiency. One of the key challenges to application in manned aircraft is development of a robust high-momentum actuator that can penetrate the boundary layer flowing over aerodynamic surfaces. These deficiencies may be overcome in the current development and testing of a novel electromagnetic synthetic jet actuator which replaces piezoelectric materials as the driving diaphragm. One of the overarching goals of the TranAtlantic research platform include fostering national and international collaboration to demonstrate (in numerical and experimental models) reduced CO2/ noise pollution via development and integration of technologies and methodologies in design optimization, fluid dynamics, structures/ composites, propulsion, and controls.

Keywords: Aircraft Design, Sustainable “Green” Aviation, Active Flow Control, Aerodynamics.

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Authors: Anna Słupik, Anna Mosiołek, Sebastian Wójtowicz, Dariusz Białoszewski

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Introduction: Whole-Body Vibration (WBV) uses high frequency mechanical stimuli generated by a vibration plate and transmitted through bone, muscle and connective tissues to the whole body. Research has shown that long-term vibration-plate training improves neuromuscular facilitation, especially in afferent neural pathways, responsible for the conduction of vibration and proprioceptive stimuli, muscle function, balance and proprioception. Some researchers suggest that the vibration stimulus briefly inhibits the conduction of afferent signals from proprioceptors and can interfere with the maintenance of body balance. The aim of this study was to evaluate the influence of a single set of exercises associated with whole-body vibration on the joint position sense and body balance. Material and methods: The study enrolled 55 people aged 19-24 years. These individuals were randomly divided into a test group (30 persons) and a control group (25 persons). Both groups performed the same set of exercises on a vibration plate. The following vibration parameters: frequency of 20Hz and amplitude of 3mm, were used in the test group. The control group performed exercises on the vibration plate while it was off. All participants were instructed to perform six dynamic exercises lasting 30 seconds each with a 60-second period of rest between them. The exercises involved large muscle groups of the trunk, pelvis and lower limbs. Measurements were carried out before and immediately after exercise. Joint position sense (JPS) was measured in the knee joint for the starting position at 45° in an open kinematic chain. JPS error was measured using a digital inclinometer. Balance was assessed in a standing position with both feet on the ground with the eyes open and closed (each test lasting 30 sec). Balance was assessed using Matscan with FootMat 7.0 SAM software. The surface of the ellipse of confidence and front-back as well as right-left swing were measured to assess balance. Statistical analysis was performed using Statistica 10.0 PL software. Results: There were no significant differences between the groups, both before and after the exercise (p> 0.05). JPS did not change in both the test (10.7° vs. 8.4°) and control groups (9.0° vs. 8.4°). No significant differences were shown in any of the test parameters during balance tests with the eyes open or closed in both the test and control groups (p> 0.05). Conclusions: 1. Deterioration in proprioception or balance was not observed immediately after the vibration stimulus. This suggests that vibrationinduced blockage of proprioceptive stimuli conduction can have only a short-lasting effect that occurs only as long as a vibration stimulus is present. 2. Short-term use of vibration in treatment does not impair proprioception and seems to be safe for patients with proprioceptive impairment. 3. These results need to be supplemented with an assessment of proprioception during the application of vibration stimuli. Additionally, the impact of vibration parameters used in the exercises should be evaluated.

Keywords: Balance, joint position sense, proprioception, whole body vibration.

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Large Neural Network, Short-Term Load Forecasting, Particle Swarm Optimization.

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Authors: S. V. Ukwungwu, A. J. Abbas, G. G. Nasr

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The increasing high price of natural gas and oil with attendant increase in energy demand on world markets in recent years has stimulated interest in recovering residual oil saturation across the globe. In order to meet the energy security, efforts have been made in developing new technologies of enhancing the recovery of oil and gas, utilizing techniques like CO₂ flooding, water injection, hydraulic fracturing, surfactant flooding etc. Surfactant flooding however optimizes production but poses risk to the environment due to their toxic nature. Amongst proven records that have utilized other type of bacterial in producing biosurfactants for enhancing oil recovery, this research uses a technique to combine biosurfactants that will achieve a scale of EOR through lowering interfacial tension/contact angle. In this study, three biosurfactants were produced from three Bacillus species from freeze dried cultures using sucrose 3 % (w/v) as their carbon source. Two of these produced biosurfactants were screened with the TEMCO Pendant Drop Image Analysis for reduction in IFT and contact angle. Interfacial tension was greatly reduced from 56.95 mN.m^-1 to 1.41 mN.m^-1 when biosurfactants in cell-free culture (Bacillus licheniformis) were used compared to 4. 83mN.m^-1 cell-free culture of Bacillus subtilis. As a result, cell-free culture of (Bacillus licheniformis) changes the wettability of the biosurfactant treatment for contact angle measurement to more water-wet as the angle decreased from 130.75^o to 65.17^o. The influence of microbial treatment on crushed rock samples was also observed by qualitative wettability experiments. Treated samples with biosurfactants remained in the aqueous phase, indicating a water-wet system. These results could prove that biosurfactants can effectively change the chemistry of the wetting conditions against diverse surfaces, providing a desirable condition for efficient oil transport in this way serving as a mechanism for EOR. The environmental friendly effect of biosurfactants applications for industrial purposes play important advantages over chemically synthesized surfactants, with various possible structures, low toxicity, eco-friendly and biodegradability.

Keywords: Bacillus, biosurfactant, enhanced oil recovery, residual oil, wettability.

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Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

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Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm.

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Authors: Fariba Tadayon, Elmira Hassanlou, Hasan Bagheri, Mostafa Jafarian

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Heavy metals are released into water, plants, soil, and food by natural and human activities. Lead has toxic roles in the human body and may cause serious problems even in low concentrations, since it may have several adverse effects on human. Therefore, determination of lead in different samples is an important procedure in the studies of environmental pollution. In this work, an ultrasonic assisted-ionic liquid based-liquid-liquid microextraction (UA-IL-DLLME) procedure for the determination of lead in zucchini, pomegranate, and lettuce has been established and developed by using flame atomic absorption spectrometer (FAAS). For UA-IL-DLLME procedure, 10 mL of the sample solution containing Pb2+ was adjusted to pH=5 in a glass test tube with a conical bottom; then, 120 μL of 1-Hexyl-3-methylimidazolium hexafluoro phosphate (CMIM)(PF6) was rapidly injected into the sample solution with a microsyringe. After that, the resulting cloudy mixture was treated by ultrasonic for 5 min, then the separation of two phases was obtained by centrifugation for 5 min at 3000 rpm and IL-phase diluted with 1 cc ethanol, and the analytes were determined by FAAS. The effect of different experimental parameters in the extraction step including: ionic liquid volume, sonication time and pH was studied and optimized simultaneously by using Response Surface Methodology (RSM) employing a central composite design (CCD). The optimal conditions were determined to be an ionic liquid volume of 120 μL, sonication time of 5 min, and pH=5. The linear ranges of the calibration curve for the determination by FAAS of lead were 0.1-4 ppm with R2=0.992. Under optimized conditions, the limit of detection (LOD) for lead was 0.062 μg.mL-1, the enrichment factor (EF) was 93, and the relative standard deviation (RSD) for lead was calculated as 2.29%. The levels of lead for pomegranate, zucchini, and lettuce were calculated as 2.88 μg.g-1, 1.54 μg.g-1, 2.18 μg.g-1, respectively. Therefore, this method has been successfully applied for the analysis of the content of lead in different food samples by FAAS.

Keywords: Dispersive liquid-liquid microextraction, Central composite design, Food samples, Flame atomic absorption spectrometry.

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Authors: Mário Silva, Filipa Gomes, Filipa Oliveira, Simone Morais, Cristina Delerue-Matos

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Brown seaweeds are abundant in Portuguese coastline and represent an almost unexploited marine economic resource. One of the most common species, easily available for harvesting in the northwest coast, is Saccorhiza polyschides grows in the lowest shore and costal rocky reefs. It is almost exclusively used by local farmers as natural fertilizer, but contains a substantial amount of valuable compounds, particularly alginates, natural biopolymers of high interest for many industrial applications. Alginates are natural polysaccharides present in cell walls of brown seaweed, highly biocompatible, with particular properties that make them of high interest for the food, biotechnology, cosmetics and pharmaceutical industries. Conventional extraction processes are based on thermal treatment. They are lengthy and consume high amounts of energy and solvents. In recent years, microwave-assisted extraction (MAE) has shown enormous potential to overcome major drawbacks that outcome from conventional plant material extraction (thermal and/or solvent based) techniques, being also successfully applied to the extraction of agar, fucoidans and alginates. In the present study, acid pretreatment of brown seaweed Saccorhiza polyschides for subsequent microwave-assisted extraction (MAE) of alginate was optimized. Seaweeds were collected in Northwest Portuguese coastal waters of the Atlantic Ocean between May and August, 2014. Experimental design was used to assess the effect of temperature and acid pretreatment time in alginate extraction. Response surface methodology allowed the determination of the optimum MAE conditions: 40 mL of HCl 0.1 M per g of dried seaweed with constant stirring at 20ºC during 14h. Optimal acid pretreatment conditions have enhanced significantly MAE of alginates from Saccorhiza polyschides, thus contributing for the development of a viable, more environmental friendly alternative to conventional processes.

Keywords: Acid pretreatment, Alginate, Brown seaweed, Microwave-assisted extraction, Response surface methodology.

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Authors: Abdullah Faqihi, John Hedley

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Biosensors play a significant role in the healthcare sectors, scientific and technological progress. Developing electrodes that are easy to manufacture and deliver better electrochemical performance is advantageous for diagnostics and biosensing. They can be implemented extensively in various analytical tasks such as drug discovery, food safety, medical diagnostics, process controls, security and defence, in addition to environmental monitoring. Development of biosensors aims to create high-performance electrochemical electrodes for diagnostics and biosensing. A biosensor is a device that inspects the biological and chemical reactions generated by the biological sample. A biosensor carries out biological detection via a linked transducer and transmits the biological response into an electrical signal; stability, selectivity, and sensitivity are the dynamic and static characteristics that affect and dictate the quality and performance of biosensors. In this research, a developed experimental study for laser scribing technique for graphene oxide inside a vacuum chamber for processing of graphene oxide is presented. The processing of graphene oxide (GO) was achieved using the laser scribing technique. The effect of the laser scribing on the reduction of GO was investigated under two conditions: atmosphere and vacuum. GO solvent was coated onto a LightScribe DVD. The laser scribing technique was applied to reduce GO layers to generate rGO. The micro-details for the morphological structures of rGO and GO were visualised using scanning electron microscopy (SEM) and Raman spectroscopy so that they could be examined. The first electrode was a traditional graphene-based electrode model, made under normal atmospheric conditions, whereas the second model was a developed graphene electrode fabricated under a vacuum state using a vacuum chamber. The purpose was to control the vacuum conditions, such as the air pressure and the temperature during the fabrication process. The parameters to be assessed include the layer thickness and the continuous environment. Results presented show high accuracy and repeatability achieving low cost productivity.

Keywords: Laser scribing, LightScribe DVD, graphene oxide, scanning electron microscopy.

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