Search results for: food composition data

Authors: Douglas Shabe

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The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Automotive interior material consisting of several material layers has the sound-absorbing function. It is difficult to predict sound absorbing coefficient because of several material layers. So, many experimental tunings are required to achieve the target of sound absorption. Therefore, while the car interior materials are developed, so much time and money is spent. In this study, we present a method to predict the sound absorbing performance of the material with multi-layer using physical properties of each material. The properties are predicted by Foam-X software using the sound absorption coefficient data measured by impedance tube. Then, we will compare and analyze the predicted sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If the method is used instead of experimental tuning in the development of car interior material, the time and money can be saved, and then, the development effort can be reduced because it can be optimized by simulation.

Keywords: multi-layer nonwoven, sound absorption coefficient, scaled reverberation chamber, impedance tubes

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Authors: Yaa Asuaba Duopah, Lisa Moran, Khalifa Elmusharaf, Dervla Kelly

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Background: Research has identified a strong link between stress and drug use behaviours. Also, it has been established that the prolonged use of crack cocaine stimulates emotional, cognitive, neurological, and social changes. This paper examines the psychosocial stressors associated with crack cocaine use. Methodology: The study is qualitative and adopts a critical realist approach. Data was collected through 26 face-to-face, in-depth, semi-structured interviews with people who use crack cocaine. Study participants were recruited through two addiction services using purposive. Participants consisted of 15 males and 11 females between the ages of 24-57 years. Data were analysed using thematic analysis. Results: Cravings, financial hardship, family breakdown, and emotional stimulation were revealed as psychosocial stressors associated with crack cocaine use. Conclusion: Addressing the psychosocial stressors identified in this paper through targeted interventions and supportive policies is crucial for improving the well-being of persons who use crack cocaine. Collaboration between addiction, mental health, and support services is recommended to develop and deliver these interventions.

Keywords: psychological stress, substance misuse disorder, mental health, coping

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Authors: Bahattin Kanal, Nursel Akçam

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Data transmission size and frequency requirements are increasing rapidly in electronic communication protocols. Increasing data transmission speeds have made the design of printed circuit boards much more important. It is important to carefully examine the requirements and make analyses before and after the design of the digital electronic circuit board. It delves into impedance matching techniques, signal trace routing considerations, and the impact of layer stacking on signal performance. The paper extensively explores techniques for minimizing crosstalk issues and interference, presenting a holistic perspective on design strategies to optimize the quality of high-speed signals. Through a comprehensive review of these design methodologies, this study aims to provide insights into achieving reliable and high-performance printed circuit board layouts for these signals. In this study, the effect of different design methods on Ethernet signals was examined from the type of S parameters. Siemens company HyperLynx software tool was used for the analyses.

Keywords: HyperLynx, printed circuit board, s parameters, ethernet

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Authors: Ismene Ithai Bras-Ruiz

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Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.

Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)

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Authors: Dorian Audot, Isobel Margaret Thompson, Dominic Hudson, Joseph Banks, Martin Warner

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In competitive swimming, after dives and turns, athletes perform underwater undulatory swimming (UUS), copying marine mammals’ method of locomotion. The body, performing this wave-like motion, accelerates the fluid downstream in its vicinity, generating propulsion with minimal resistance. Through this technique, swimmers can maintain greater speeds than surface swimming and take advantage of the overspeed granted by the dive (or push-off). Almost all previous work has considered UUS when performed at maximum effort. Critical parameters to maximize UUS speed are frequently discussed; however, this does not apply to most races. In only 3 out of the 16 individual competitive swimming events are athletes likely to attempt to perform UUS with the greatest speed, without thinking of the cost of locomotion. In the other cases, athletes will want to control the speed of their underwater swimming, attempting to maximise speed whilst considering energy expenditure appropriate to the duration of the event. Hence, there is a need to understand how swimmers adapt their underwater strategies to optimize the speed within the allocated energetic cost. This paper develops a consistent methodology that enables different sets of UUS kinematics to be investigated. These may have different propulsive efficiencies and force generation mechanisms (e.g.: force distribution along with the body and force magnitude). The developed methodology, therefore, needs to: (i) provide an understanding of the UUS propulsive mechanisms at different speeds, (ii) investigate the key performance parameters when UUS is not performed solely for maximizing speed; (iii) consistently determine the propulsive efficiency of a UUS technique. The methodology is separated into two distinct parts: kinematic data acquisition and computational fluid dynamics (CFD) analysis. For the kinematic acquisition, the position of several joints along the body and their sequencing were either obtained by video digitization or by underwater motion capture (Qualisys system). During data acquisition, the swimmers were asked to perform UUS at a constant depth in a prone position (facing the bottom of the pool) at different speeds: maximum effort, 100m pace, 200m pace and 400m pace. The kinematic data were input to a CFD algorithm employing a two-dimensional Large Eddy Simulation (LES). The algorithm adopted was specifically developed in order to perform quick unsteady simulations of deforming bodies and is therefore suitable for swimmers performing UUS. Despite its approximations, the algorithm is applied such that simulations are performed with the inflow velocity updated at every time step. It also enables calculations of the resistive forces (total and applied to each segment) and the power input of the modeled swimmer. Validation of the methodology is achieved by comparing the data obtained from the computations with the original data (e.g.: sustained swimming speed). This method is applied to the different kinematic datasets and provides data on swimmers’ natural responses to pacing instructions. The results show how kinematics affect force generation mechanisms and hence how the propulsive efficiency of UUS varies for different race strategies.

Keywords: CFD, efficiency, human swimming, hydrodynamics, underwater undulatory swimming

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Authors: Hanan Al-Khalaifah, Afaf Al-Nasser

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Probiotics and prebiotics claimed to serve as effective alternatives to antibiotics in the poultry. This study aims to investigate the effect of different probiotics and prebiotics on the economic impact analysis of the use of probiotics and prebiotics in broiler feed. The study involved four broiler cycles, two during winter and two during summer. In the first two cycles (summer and winter), different types of prebiotics and probiotics were used. The probiotics were Bacillus coagulans (1 g/kg dried culture) and Lactobacillus (1 g/kg dried culture of 12 commercial strains), and prebiotics included fructo-oligosaccharides (FOS) (5 g/kg) and mannan-oligosaccharide (MOS) derived from Saccharomyces cerevisiae (5 g/kg). Based on the results obtained, the best treatment was chosen to be FOS, from which different ratios were used in the last two cycles during winter and summer. The levels of FOS chosen were 0.3, 0.5, and 0.7% of the diet. From an economic point of view, it was generally concluded that in all dietary treatments, food was consumed less in cycle 1 than in cycle 2, the total body weight gain was more in cycle 1 than cycle 2, and the average feed efficiency was less in cycle l than cycle 2. This indicates that the weather condition affected better in cycle 1. Also, there were very small differences between the dietary treatments in each cycle. In cycle 1, the best total feed consumption was for the FOS treatment, the highest total body weight gain and average feed efficiency were for B. coagulans. In cycle 2, all performance was better in FOS treatment. FOS significantly reduced the Salmonella sp. counts in the intestine, where the environment was driven towards acidity. FOS was the best on the average taste panel study of the produced meat. Accordingly, FOS prebiotic was chosen to be the best treatment to be used in cycles 3 and 4. The economic impact analysis generally revealed that there were no big differences between the treatments in all of the studied indicators, but there was a difference between the cycles.

Keywords: antibiotic, economic impact, prebiotic, probiotic, broiler

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Authors: Alexander B. Barker, Megan Parkin, Shreesh Sinha, Emma Wilson, Rachael L. Murray

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Objectives: Exposure to HFSS imagery is associated with consumption of foods high in fat, sugar, or salt (HFSS), and subsequently obesity, among young people. We report and compare the results of two content analyses, one of two popular terrestrial children’s television channels in the UK and the other of a selection of children’s programs available on video-on-demand (VOD) streaming sites. Design: Content analysis of three days’ worth of programs (including advertisements) on two popular children’s television channels broadcast on UK television (CBeebies and Milkshake) as well as a sample of 40 highest-rated children’s programs available on the VOD platforms, Netflix and Amazon Prime, using 1-minute interval coding. Setting: United Kingdom, Participants: None. Results: HFSS content was seen in 181 broadcasts (36%) and in 417 intervals (13%) on terrestrial television, ‘Milkshake’ had a significantly higher proportion of programs/adverts which contained HFSS content than ‘CBeebies’. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programs containing HFSS content between Netflix and Amazon Prime. Conclusions: This study demonstrates that HFSS content is common in both popular UK children’s television channels and children's programs on VOD services. Since previous research has shown that HFSS content in the media has an effect on HFSS consumption, children’s television programs broadcast either on TV or VOD services are likely having an effect on HFSS consumption in children and legislative opportunities to prevent this exposure are being missed.

Keywords: public health, epidemiology, obesity, content analysis

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Authors: Bello, A., Muhammed Ibrahim Abba., Abdullahi, M., Dauda, Sabo, & Shittu, A. T.

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This study investigated the Predictors of Lecturers Knowledge Sharing Acceptance on Open Educational Resources (OER) in North-East Nigerian in Universities. The study population comprised of 632 lecturers of Federal Universities in North-east Nigeria. The study sample covered 338 lecturers who were selected purposively from Adamawa, Bauchi and Borno State Federal Universities in Nigeria. The study adopted a prediction correlational research design. The instruments used for data collection was the questionnaire. Experts in the field of educational technology validated the instrument and tested it for reliability checks using Cronbach’s alpha. The constructs on lecturers’ acceptance to share OER yielded a reliability coefficient of; α = .956 for Performance Expectancy, α = .925; for Effort Expectancy, α = .955; for Social Influence, α = .879; for Facilitating Conditions and α = .948 for acceptance to share OER. the researchers contacted the Deanery of faculties of education and enlisted local coordinators to facilitate the data collection process at each university. The data was analysed using multiple sequential regression statistic at a significance level of 0.05 using SPSS version 23.0. The findings of the study revealed that performance expectancy (β = 0.658; t = 16.001; p = 0.000), effort expectancy (β = 0.194; t = 3.802; p = 0.000), social influence (β = 0.306; t = 5.246; p = 0.000), collectively indicated that the variables have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. However, the finding revealed that facilitating conditions (β = .053; t = .899; p = 0.369), does not have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. Based on these findings, the study recommends among others that the university management should consider adjusting OER policy to be centered around actualizing lecturers career progression.

Keywords: acceptance, lecturers, open educational resources, knowledge sharing

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Authors: Dominic Wentworth-Linton, Shian Gao

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This project was aimed at investigating the effect of velocity stacks on the intakes of internal combustion engines for motorsport applications. The intake systems in motorsport are predominantly fuel injection with a plate mounted for the stacks. Using Computational Fluid Dynamics software, the relationship between the stack length and power and torque delivery across the engine’s rev range was investigated and the results were used to choose the best option for its intended motorsport discipline. The test results are expected to vary with engine geometry and its natural manufacturer characteristics. The test was also relevant in bridging between computational data and real simulation as the results show flow, pressure and velocity readings but the behaviour of the engine is inferred from the nature of each test. The results of the data analysis were tested in a real-life simulation on a dynamometer to prove the theory of stack length on power and torque delivery, which helps determine the most suitable stack for the Vauxhall engine for rallying in the Caribbean.

Keywords: CFD simulation, Internal combustion engine, Intake system, Dynamometer test

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Authors: Roya Pournaghi

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Measuring the extent of daily use of the libraries study space is of utmost significance in order to develop, re-organize and maintain the efficiency of the study space. The current study aimed to employ GIS in analyzing the study halls space of the document center and central library of Tehran University and determine the extent of use of the study chairs and desks by the students-intended users. This combination of survey methods - descriptive design system. In order to collect the required data and a description of the method, To implement and entering data into ArcGIS software. It also analyzes the data and displays the results on the library floor map design method were used. And spatial database design and plan has been done at the Central Library of Tehran University through the amount of space used by members of the Library and Information halls plans. Results showed that Biruni's hall is allocated the highest occupancy rate to tables and chairs compared to other halls. In the Hall of Science and Technology, with an average occupancy rate of 0.39 in the tables represents the lowest users and Rashid al-Dins hall, and Science and Technology’s hall with an average occupancy rate (0.40) represents the lowest users of seats. In this study, the comparison of the space is occupied at different period as a study’s hall in the morning, evenings, afternoons, and several months was performed through GIS. This system analyzed the space relationship effectively and efficiently. The output of this study can be used by administrators and librarians to determine the exact amount of using the Equipment of study halls and librarians can use the output map to design more efficient space at the library.

Keywords: geospatial information system, spatial analysis, reading room, academic libraries, library’s user, central library of Tehran university

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Authors: Mompi Sharma, Labananda Choudhury, Anjana M. Saikia

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Background: The period life table is entirely based on the assumption that the mortality patterns of the population existing in the given period will persist throughout their lives. However, it has been observed that the mortality rate continues to decline. As such, if the rates of change of probabilities of death are considered in a life table then we get a dynamic life table. Although, mortality has been declining in all parts of India, one may be interested to know whether these declines had appeared more in an urban area of underdeveloped regions like North-Eastern India. So, attempt has been made to know the mortality pattern and the life expectancy under dynamic scenario in Guwahati, the biggest city of North Eastern India. Further, if the probabilities of death changes then there is a possibility that its different constituent probabilities will also change. Since cardiovascular disease (CVD) is the leading cause of death in Guwahati. Therefore, an attempt has also been made to formulate dynamic cause specific death ratio and probabilities of death due to CVD. Objectives: To construct dynamic life table for Guwahati for the year 2011 based on the rates of change of probabilities of death over the previous 10 and 25 years (i.e.,2001 and 1986) and to compute corresponding dynamic cause specific death ratio and probabilities of death due to CVD. Methodology and Data: The study uses the method proposed by Denton and Spencer (2011) to construct dynamic life table for Guwahati. So, the data from the Office of the Birth and Death, Guwahati Municipal Corporation for the years 1986, 2001 and 2011 are taken. The population based data are taken from 2001 and 2011 census (India). However, the population data for 1986 has been estimated. Also, the cause of death ratio and probabilities of death due to CVD are computed for the aforementioned years and then extended to dynamic set up for the year 2011 by considering the rates of change of those probabilities over the previous 10 and 25 years. Findings: The dynamic life expectancy at birth (LEB) for Guwahati is found to be higher than the corresponding values in the period table by 3.28 (5.65) years for males and 8.30 (6.37) years for females during the period of 10 (25) years. The life expectancies under dynamic consideration in all the other age groups are also seen higher than the usual life expectancies, which may be possible due to gradual decline in probabilities of death since 1986-2011. Further, a continuous decline has also been observed in death ratio due to CVD along with cause specific probabilities of death for both sexes. As a consequence, dynamic cause of death probability due to CVD is found to be less in comparison to usual procedure. Conclusion: Since incorporation of changing mortality rates in period life table for Guwahati resulted in higher life expectancies and lower probabilities of death due to CVD, this would possibly bring out the real situation of deaths prevailing in the city.

Keywords: cause specific death ratio, cause specific probabilities of death, dynamic, life expectancy

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Authors: Athena Pedro, Carushca de Beer, Erin Cupido, Tarryn Johnson, Tawana Keneilwe, Crystal Stoffels, Carinne Annfred Lorraine Petersen, Kuan Michael Truskey

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The early experiences of children during their first 1000 days of life are the main determining factor of their development. Therefore, the aim of this study was to explore mothers' understanding of an attachment bond and the role that it plays in early childhood. A qualitative exploratory research design guided this study. Ethics approval was granted by appropriate ethics committees. Data were gathered through the use of semi-structured interviews with 15 participants within the Cape Town area, South Africa. Participants completed informed consents and were informed of confidentiality, anonymity, their rights, and voluntary participation. Thematically analysed data revealed that many participants were unaware of the term ‘the first 1000 days of a child’s life’; however, they were aware of the methods to be used for forming an attachment bond with their children. There is a need for more awareness on the subject matter within South Africa.

Keywords: awareness, children, first 1000 days, milestones, South Africa, understanding

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Eleanor L. Kutschera

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This study explores the possible impact that QR codes play in helping individuals make more sustainable choices regarding apparel consumption. Data was collected via an online survey to ascertain individuals’ knowledge, attitudes, and behaviors with regard to QR codes and how this impacts their decisions to purchase apparel. Results from 250 participants provide both qualitative and quantitative data that provide valuable information regarding consumers’ use of QR codes and more sustainable purchases. Specifically, results indicate that QR codes are currently under-utilized in the apparel industry but have the potential to generate more environmentally conscious purchases. Also, results posit that while the cost of the item is the most influential factor in purchasing sustainable garments, other factors such as how, where, and what it is made of are in the middle, along with the company’s story/inspiration for creation have an impact. Moreover, participants posit the use of QR codes could make them more informed and empowered consumers, and they would be more likely to make purchases that are better for the environment. Participants’ qualitative responses provide useful incentives that could increase their future sustainable purchases. Finally, this study touches on the study’s limitations, implications, and future direction of research.

Keywords: digital ID, QR codes, environmental consciousness, sustainability, fashion industry, apparel consumption

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Authors: E. Bal Beşikçi, O. Arslan

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Fuel saving has become one of the most important issue for shipping in terms of fuel economy and environmental impact. Lowering fuel consumption is possible for both new ships and existing ships through enhanced energy efficiency measures, technical and operational respectively. The limitations of applying technical measures due to the long payback duration raise the potential of operational changes for energy efficient ship operations. This study identifies operational energy efficiency measures related voyage performance management. We use ‘noon’ data to examine the correlation between fuel consumption and operational parameters- revolutions per minute (RPM), draft, trim, (beaufort number) BN and relative wind direction, which are used as measures of ship energy efficiency. The results of this study reveal that speed optimization is the most efficient method as fuel consumption depends heavily on RPM. In conclusion, this study will provide ship operators with the strategic approach for evaluating the priority of the operational energy efficiency measures against high fuel prices and carbon emissions.

Keywords: ship, voyage related operational energy Efficiency measures, fuel consumption, pearson's correlation coefficient

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Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Usriatur Rohma, Adji Achmad Rinaldo Fernandes

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Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best nonparametric truncated spline path function between linear and quadratic polynomial degrees with 1, 2, and 3-knot points and to determine the significance of estimating the best nonparametric truncated spline path function in the model of the effect of population migration and agricultural economic growth on rural poverty through the variable unemployment rate using the t-test statistic at the jackknife resampling stage. The data used in this study are secondary data obtained from statistical publications. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3-knot points. In addition, the significance of the best-truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables.

Keywords: nonparametric path analysis, truncated spline, linear, quadratic, rural poverty, jackknife resampling

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Authors: Ahlem Nefzi, Rania Aydi Ben Abdallah, Hayfa Jabnoun-Khiareddine, Nawaim Ammar, Sined Medimagh-Saidana, Mejda Daami-Remadi

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In the present study, leaf, stem, and fruit aqueous extracts of native wild Solanum linnaeanum L. were screened for their ability to suppress Fusarium Crown and Root Rot disease and to enhance tomato (Solanum lycopersicum L.) growth under greenhouse conditions. Leaf extract used at 30% w/v was the most effective in reducing leaf and root damage index by 92.3% and the extent of vascular discoloration by 97.56% compared to Fusarium oxyxporum f. sp radicis lycopersici -inoculated and untreated control. A significant promotion of growth parameters (root length, shoot height, root and shoot biomass and stem diameter) was recorded on tomato cv. Rio Grande seedlings by 40.3-94.1% as compared to FORL inoculated control and by 9.6-88.8% over pathogen-free control. All S. linnaeanum aqueous extracts tested significantly stimulated the germination by 10.2 to 80.1% relative to the untreated control. FORL mycelial growth, assessed using the poisoned food technique, varied depending on plant organs, extracts, and concentrations used. Butanolic extracts were the most active, leading to 60.81% decrease in FORL mycelial growth. HPLC analysis of butanolic extract revealed the presence of thirteen phenolic compounds. Thus, S. linnaeanum can be explored as a potential natural source of antifungal and biofertilizing compounds.

Keywords: antifungal activity, HPLC-MS analysis, Fusarium oxysporum f. sp. radicis-lycopersici, tomato growth

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Authors: Cajethan U. Ugwuoke

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Agriculture is taught in secondary schools to develop skills in students which will empower them to contribute to national economic development. Unfortunately, our educational system emphasizes the application of conventional teaching methods in delivering instructions, which fails to produce students competent enough to carry out agricultural production. This study was therefore aimed at examining the application of digital technologies as tools for transformative instructional delivery. Four specific purposes, research questions and hypotheses guided the study. The study adopted a descriptive survey research design where 80 subjects representing 64 teachers of agriculture and 16 principals in the Udenu local government area of Enugu State, Nigeria, participated in the study. A structured questionnaire was used to collect data. The assumption of normality was ascertained by subjecting the data collected to a normality test. Data collected were later subjected to mean, Pearson product-moment correlation, ANOVA and t-test to answer the research questions and test the hypotheses at a 5% significant level. The result shows that the application of digital technologies helps to reduce learners’ boredom (3.52.75), improves learners’ performance (3.63.51), and is used as a visual aid for learners (3.56.61), among others. There was a positive, strong and significant relationship between the application of digital technologies and effective instructional delivery (+.895, p=.001<.05, F=17.73), competency of teachers to the application of digital technologies and effective instructional delivery (+998, p=.001<0.5, F=16263.45), and frequency of the application of digital technologies and effective instructional delivery (+.999, p=.001<.05, F=31436.14). There was no evidence of autocorrelation and multicollinearity in the regression models between the application of digital technologies and effective instructional delivery (2.03, Tolerance=1.00, VIF=1.00), competency of teachers in the application of digital technologies and effective instructional delivery (2.38, Tolerance=1.00, VIF=1.00) and frequency of the application of digital technologies and effective instructional delivery (2.00, Tolerance=1.00, VIF=1.00). Digital technologies should be therefore applied in teaching to facilitate effective instructional delivery in agriculture.

Keywords: agricultural science, digital technologies, instructional delivery, learning

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Authors: Dada. O.Akinola, Uche. I. Ebele, Bamiro .A.Rafatu, Akinbami A. Akinsegun, Dada O. Adeyemi, Adeyemi. O. Ibukun, Okunowo O.Bolanle, Abdulateef O. Kareem, Ibrahim.N. Ismaila, Dosu Rihanat

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Background: Hyperglycaemia alters qualitatively and quantitatively all the full blood count parameters. The alterations among other factors are responsible for the macrovascular and microvascular complications associated with diabetes mellitus (DM). This study is aimed at correlating haematological parameters in DM subjects with their fasting blood glucose (FBG) and anthropometric parameters. Materials and Methods: This was a cross-sectional study of participants attending DM clinic of Lagos State University Teaching Hospital (LASUTH), Ikeja. The study recruited one hundred and two (102) DM subjects and one hundred (100) non-DM controls. Venous blood samples were collected for full blood count (FBC) assay while FBG was done, structured questionnaires were administered, and anthropometric measurements of all participants were done. Data were analyzed with Statistical Package for Social Science (SPSS) version 23. P was set at ≤0.05. Results: The mean age of DM patients was 64.32± 11.31 years. Using a haemoglobin concentration cut-off of 11g/dl, 39.2%, and 13% DM and control participants respectively had values lower than 11g/dl. A total of 22.5% and 3% of DM and controls respectively gave a history of previous blood transfusion.White blood cells count and platelet count means were (6.12±1.60 and 5.30±7.52,p=0.59) and (213.31±73.58 and 228.91±73.21,p = 0.26) *109/L in DM subjects and controls respectively. FBG and all the anthropometric data in DM subjects were significantly higher than in controls. Conclusions: The prevalence of anaemia in DM subjects was three times higher than in controls. The white blood cell count was higher but not statistically significant in DM compared with controls. But platelet count was higher but not statistically significant in controls compared with DM subjects.

Keywords: haematological profile, diabetes mellitus, anthropometric data, fasting blood glucose

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Ben Tappin, Ryan McKay

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The political left and right appear to disagree not only over questions of value but, also, over questions of fact—over what is true “out there” in society and the world. Alarmingly, a large body of survey data collected during the past decade suggests that this disagreement tends to be greatest among the most educated and most cognitively sophisticated opposing partisans. In other words, the data show that these individuals display the widest political polarization in their reported factual beliefs. Explanations of this polarization pattern draw heavily on cultural and political factors; yet, the large majority of the evidence originates from one cultural and political context—the United States, a country with a rather unique cultural and political history. One consequence is that widening political polarization conditional on education and cognitive sophistication may be due to idiosyncratic cultural, political or historical factors endogenous to US society—rather than a more general, international phenomenon. We examined widening political polarization conditional on education across Europe, over a topic that is culturally and politically contested; immigration. To do so, we analyzed data from the European Social Survey, a premier survey of countries in and around the European area conducted biennially since 2002. Our main results are threefold. First, we see widening political polarization conditional on education over beliefs about the economic impact of immigration. The foremost countries showing this pattern are the most influential in Europe: Germany and France. However, we also see heterogeneity across countries, with some—such as Belgium—showing no evidence of such polarization. Second, we find that widening political polarization conditional on education is a product of sorting. That is, highly educated partisans exhibit stronger within-group consensus in their beliefs about immigration—the data do not support the view that the more educated partisans are more polarized simply because the less educated fail to adopt a position on the question. Third, and finally, we find some evidence that shocks to the political climate of countries in the European area—for example, the “refugee crisis” of summer 2015—were associated with a subsequent increase in political polarization over immigration conditional on education. The largest increase was observed in Germany, which was at the centre of the so-called refugee crisis in 2015. These results reveal numerous insights: they show that widening political polarization conditional on education is not restricted to the US or native English-speaking culture; that such polarization emerges in the domain of immigration; that it is a product of within-group consensus among the more educated; and, finally, that exogenous shocks to the political climate may be associated with subsequent increases in political polarization conditional on education.

Keywords: beliefs, Europe, immigration, political polarization

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Authors: Ambreen Aslam, Tahira Aziz Mughal, Skye R. Thomas-Hall, Peer M. Schenk

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Biodiesel is an alternative to petroleum-derived fuel mainly composed of fatty acid from oleaginous microalgae feedstock. Microalgae produced fatty acid methyl esters (FAMEs) as they can store high levels of lipids without competing for food productivity. After lipid extraction and esterification, fatty acid profile from algae feedstock possessed the abundance of fatty acids with carbon chain length specifically C16 and C18. The qualitative analysis of FAME was done by cultivating mix microalgae consortia under three different CO₂ concentrations (1%, 3%, and 5.5%) from a coal fired flue gas. FAME content (280.3 µg/mL) and productivity (18.69 µg/mL/D) was higher under 1% CO₂ (flue gas) as compare to other treatments. Whereas, Mixed C. (F) supplemented with 5.5% CO₂ (50% flue gas) had higher SFA (36.28%) and UFA (63.72%) which improve the oxidative stability of biodiesel. Subsequently, low Iodine value (136.3 gI₂/100g) and higher Cetane number (52) of Mixed C.+P (F) were found to be in accordance with European (EN 14214) standard under 5.5% CO₂ along with 50mM phosphate buffer. Experimental results revealed that sufficient phosphate reduced FAME productivity but significantly enhance biodiesel quality. This research aimed to develop an integrated approach of utilizing flue gas (as CO₂ source) for significant improvement in biodiesel quality under surplus phosphorus. CO₂ sequestration from industrial flue gas not only reduce greenhouse gases (GHG) emissions but also ensure sustainability and eco-friendliness of the biodiesel production process through microalgae.

Keywords: biodiesel analysis, carbon dioxide, coal fired flue gas, FAME productivity, fatty acid profile, fuel properties, lipid content, mixed culture microalgae

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Authors: Andreia Guimaraes Farnese, Mateus Fernandes Reu Urban, Leandro Procopio, Renato Zangaro, Regiane Albertini

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Senescence changes include postural balance, inferring the risk of falls, and can lead to fractures, bedridden, and the risk of death. Physical activity, e.g., cardiovascular exercises, is notable for improving balance due to brain cell stimulations, but fine coordination exercises also elevate cell brain metabolism. This study aimed to verify whether the elderly person who performs fine motor activity has a balance similar to that of those who practice physical activity. The subjects were divided into three groups according to the activity practice: control group (CG) with seven participants for the sedentary individuals, motor coordination group (MCG) with six participants, and activity practitioner group (PAG) with eight participants. Data comparisons were from the Berg balance scale, Time up and Go test, and stabilometric analysis. Descriptive statistical and ANOVA analyses were performed for data analysis. The results reveal that including fine motor activities can improve the balance of the elderly and indirectly decrease the risk of falls.

Keywords: balance, barapodometer, coordination, elderly

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Authors: Maria C. Proença, Maria T. Rebelo, Maria J. Alves, Sofia Cunha

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Vector-borne diseases are transmitted to humans by mosquitos, sandflies, bugs, ticks, and other vectors. Some are re-transmitted between vectors, if the infected human has a new contact when his levels of infection are high. The vector is infected for lifetime and can transmit infectious diseases not only between humans but also from animals to humans. Some vector borne diseases are very disabling and globally account for more than one million deaths worldwide. The mosquitoes from the complex Culex pipiens sl. are the most abundant in Portugal, and we dispose in this moment of a data set from the surveillance program that has been carried on since 2006 across the country. All mosquitos’ species are included, but the large coverage of Culex pipiens sl. and its importance for public health make this vector an interesting candidate to assess risk of disease amplification. This work focus on ports and airports identified as key areas of high density of vectors. Mosquitoes being ectothermic organisms, the main factor for vector survival and pathogen development is temperature. Minima and maxima local air temperatures for each area of interest are averaged by month from data gathered on a daily basis at the national network of meteorological stations, and interpolated in a geographic information system (GIS). The range of temperatures ideal for several pathogens are known and this work shows how to use it with the meteorological data in each port and airport facility, to focus an efficient implementation of countermeasures and reduce simultaneously risk transmission and mitigation costs. The results show an increased alert with decreasing latitude, which corresponds to higher minimum and maximum temperatures and a lower amplitude range of the daily temperature.

Keywords: human health, risk assessment, risk management, vector-borne diseases

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Authors: Amritansh Agarwal, Tejaswi Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

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Authors: Yasufumi Yoshimoto, Enkhjargal Tserenochir, Eiji Kinoshita, Takeshi Otaka

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Next generation bio-alcohols produced from non-food based sources like cellulosic biomass are promising renewable energy sources. The present study investigates engine performance, combustion characteristics, and emissions of a small single cylinder direct injection diesel engine fueled by four kinds of next generation bio-alcohol isomer and diesel fuel blends with a constant blending ratio of 3:7 (mass). The tested bio-alcohol isomers here are n-butanol and iso-butanol (C₄ alcohol), and n-pentanol and iso-pentanol (C₅ alcohol). To obtain simultaneous reductions in NOx and smoke emissions, the experiments employed supercharging combined with EGR (Exhaust Gas Recirculation). The boost pressures were fixed at two conditions, 100 kPa (naturally aspirated operation) and 120 kPa (supercharged operation) provided with a roots blower type supercharger. The EGR rates were varied from 0 to 25% using a cooled EGR technique. The results showed that both with and without supercharging, all the bio-alcohol blended diesel fuels improved the trade-off relation between NOx and smoke emissions at all EGR rates while maintaining good engine performance, when compared with diesel fuel operation. It was also found that regardless of boost pressure and EGR rate, the ignition delays of the tested bio-alcohol isomer blends are in the order of iso-butanol > n-butanol > iso-pentanol > n-pentanol. Overall, it was concluded that, except for the changes in the ignition delays the influence of bio-alcohol isomer blends on the engine performance, combustion characteristics, and emissions are relatively small.

Keywords: alternative fuel, butanol, diesel engine, EGR (Exhaust Gas Recirculation), next generation bio-alcohol isomer blended fuel, pentanol, supercharging

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Authors: Tumelo Jaquiline Ntsopi

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This study explored the academic writing challenges of first-year students who use English as an Additional Language (EAL) registered in the EAW101 module at an ODeL institution. Research shows that academic writing is a challenge for EAL teaching and learning contexts across the globe in higher education institutions (HEIs). Academic writing is an important aspect of academic literacy in any institution of higher learning, more so in an ODeL institution. This has probed research that shows that academic writing is and continues to pose challenges for EAL teaching and learning contexts in higher education institutions. This study stems from the researcher’s experience in teaching academic writing to first-year students in the EAW101 module. The motivation for this study emerged from the fact that EAW101 is a writing module that has a high number of students in the Department of English Studies with an average of between 50-80 percent pass rate. These statistics elaborate on the argument that most students registered in this module struggle with academic writing, and they need intervention to assist and support them in achieving competence in the module. This study is underpinned by Community of Inquiry (CoI) framework and Transactional distance theory. This study adopted a qualitative research methodology and utilised a case study approach as a research design. Furthermore, the study gathered data from first year students and the EAW101 module’s student support initiatives. To collect data, focus group discussions, structured open-ended evaluation questions, and an observation schedule were used to gather data. The study is vital towards exploring academic writing challenges that first-year students in EAW101 encounter so that lecturers in the module may consider re-evaluating their methods of teaching to improve EAL students’ academic writing skills. This study may help lecturers towards enhancing academic writing in a ODeL context by assisting first year students through using student support interventions.

Keywords: academic writing, academic writing challenge, ODeL, EAL

Procedia PDF Downloads 83