Search results for: sequential patterns

Authors: Barbara Papp

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Purpose: This article aims to rethink the relationship between the trauma and the choice of professions. By studying a homogenous sample of respondents, it seeks answers to the following question: how did personal losses that were caused by historical upheavals motivate people to enter the helping professions. By becoming helping professionals, the respondents of the survey sought to handle both historical representation and self-representation. How did psychotherapists working in the second half of the 20th century (Kádár-era in Hungary) shape their course of life? How did their family members respond to their choice of career? What forces supported or hindered them? How did they become professional helpers? Methodology: When interviewing 40 psychotherapists, the interviewer used the oral history technique. In-depth interviews were made with a focus on motivation. First, the collected material was examined using traditional content analysis tools: searching for content patterns, applying a word frequency analysis, and identifying the connections between key events and key persons. Second, a narrative psychological content analysis (NarrCat) was made. Findings: Interconnections were established between attachment, family and historical traumas and career choices. The history of the mid-20th-century period was traumatic and full of losses for the families of most of the psychotherapists concerned. Those experiences may have considerably influenced their choice of career. Working as helping therapists, they could get the opportunity to revise their losses. Conclusion: The results revealed core components that play a role in the psychotherapists’ choice of career, and also emphasized the importance of post-traumatic growth.

Keywords: biography, identity, narrative psychological content analysis, psychotherapists, trauma

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Authors: Diego Moya, Juan Paredes, Clay Aldas, Ramiro Tite, Prasad Kaparaju

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Globally, energy policy for geothermal development is addressed in different forms, depending on the economy, resources, country-development, environment aspects and technology access. Although some countries have established strong regulations and standards for geothermal exploration, exploitation and sustainable use at the policy level (government departments and institutions), others have discussed geothermal laws at legal levels (congress – a national legislative body of a country). Appropriate regulations are needed not only to meet local and international funding requirements but also to avoid speculation in the use of the geothermal resource. In this regards, this paper presents the results of a systematic, qualitative and critical literature review of geothermal energy policy worldwide addressing two scenarios: policy and legal levels. At first, literature is collected and classified from scientific and government sources regarding geothermal energy policy of the most advanced geothermal producing countries, including Iceland, New Zealand, Mexico, the USA, Central America, Italy, Japan, Philippines, Indonesia, Kenia, and Australia. This is followed by a systematic review of the literature aiming to know the best geothermal practices and what remains uncertain regarding geothermal policy implementation. This analysis is made considering the stages of geothermal production. Furthermore, a qualitative analysis is conducted comparing the findings across geothermal policies in the countries mentioned above. Then, a critical review aims to identify significant items in the field to be applied in countries with geothermal potential but with no or weak geothermal policies. Finally, patterns and relationships are detected, and conclusions are drawn.

Keywords: assessment, geothermal, energy policy, worldwide

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Authors: Edgar Mauricio Ruiz Osuna, Claudia Yaneth Herrera Bolivar, Sandra Liliana Gomez Vasquez

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The increasing needs of professionals with skills in software development in industry are incremental, therefore, the relevance of an educational process in line with the strengthening of these competencies, are part of the responsibilities of universities with careers related to the area of Informatics and Systems. In this sense, it is important to consider that in the National Science, Technology and Innovation Plan for the development of the Electronics, Information Technologies and Communications (2013) sectors, it is established as a weakness in the SWOT Analysis of the Software sector and Services, Deficiencies in training and professional training. Accordingly, UNIMINUTO's Computer Technology Program has addressed the analysis of students' performance in software development, identifying various problems such as dropout in programming subjects, academic averages, as well as deficiencies in strategies and competencies developed in the area of programming. As a result of this analysis, it was determined to design a collaborative learning platform in basic programming using heat maps as a tool to support didactic feedback. The pilot phase allows to evaluate in a programming course the ALGORINFO platform as a didactic resource, through an interactive and collaborative environment where students can develop basic programming practices and in turn, are fed back through the analysis of time patterns and difficulties frequent in certain segments or program cycles, by means of heat maps. The result allows the teacher to have tools to reinforce and advise critical points generated on the map, so that students and graduates improve their skills as software developers.

Keywords: collaborative platform, learning, feedback, programming, heat maps

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

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Authors: Dewi Liesnoor Setyowati, Puji Hardati, Tri Marhaeni Puji Astuti, Muhammad Amin

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Universitas Negeri Semarang (UNNES) is a university with a vision of conservation. The impact of the UNNES conservation is the existence of a positive response from the community for the effort of greening the campus and the planting of conservation value in the academic community. But in reality,  energy consumption in UNNES campus tends to increase. The objectives of the study were to analyze the energy consumption in the campus area, to analyze the absorption of emissions by trees and the awareness of UNNES citizens in reducing emissions. Research focuses on energy consumption, carbon emissions, and awareness of citizens in reducing emissions. Research subjects in this study are UNNES citizens (lecturers, students and employees). The research area covers 6 faculties and one administrative center building. Data collection is done by observation, interview and documentation. The research used a quantitative descriptive method to analyze the data. The number of trees in UNNES is 10,264. Total emission on campus UNNES is 7.862.281.56 kg/year, the tree absorption is 6,289,250.38 kg/year. In UNNES campus area there are still 1,575,031.18 kg/year of emissions, not yet absorbed by trees. There are only two areas of the faculty whose trees are capable of absorbing emissions. The awareness of UNNES citizens in reducing energy consumption is seen in change the habit of: using energy-saving equipment (65%); reduce energy consumption per unit (68%); do energy literacy for UNNES citizens (74%). UNNES leaders always provide motivation to the citizens of UNNES, to reduce and change patterns of energy consumption.

Keywords: energy consumption, carbon emission absorption, emission reduction, energy literation

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Authors: Niveen M. Hassan-Abbas

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The COVID-19 pandemic created a range of stressors, among them difficulties related to work conditions, financial changes, lack of childcare, and confinement or isolation due to social distancing. Among families and married individuals, these stressors were often expressed in additional daily hassles, with an influence on mental health. This study examined two moderated mediation models based on Bodenmann’s systemic-transactional stress model. Specifically, the models tested the hypothesis that intra-dyadic stress mediates the association between extra-dyadic stress and mental health, while two measures of family functioning, cohesion, and flexibility, moderate the relationship between extra and intra-dyadic stress. Participants were 480 heterosexual married Palestinians from Israel who completed self-report questionnaires. The results showed partial mediation patterns supporting both models, indicating that family cohesion and flexibility weakened the mediating effect of intra-dyadic stress on the relationship between extra-dyadic stress and mental health. These findings increase our understanding of the variables that affected mental health during the pandemic and suggested that when faced with extra-dyadic stress, married individuals with good family environments are less likely to experience high levels of intra-dyadic stress, which is in turn associated with preserved mental health. Limitations and implications for planning interventions for couples and families during the pandemic are discussed.

Keywords: Palestinian families in Israel, COVID-19 pandemic, family cohesion and flexibility, extra-dyadic stress, intra-dyadic stress, mental health

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Authors: In Hee Shim, Dong Sik Bae

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Introduction: Obesity and unfavorable lipid profile may be linked to depressive disorders. This study compared the levels of obesity, lipid profiles and depression severity of patients with depressive disorders. Methods: This study included 156 patients diagnosed with a depressive disorder who were hospitalized between March 2012 and February 2016. The patients were categorized into mild to moderate and severe depressive groups, based on Hamilton Depression Rating Scale scores (Mild to moderate depression 8-23 vs. severe depression ≥ 24). The charts of the patients were reviewed to evaluate body mass index and lipid profiles, including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG), confounding factors, such as other general medical disorders (hypertension, diabetes mellitus, and dyslipidemia), except smoking status (insufficient data). Demographic and clinical characteristics, such as age, sex, comorbidities, family history of mood disorders, psychotic features, and prescription patterns were also assessed. Results: Compared to the mild to the moderate depressive group, patients with severe depression had significantly lower rate of male and comorbidity. The patients with severe depression had a significantly lower TG than patients in the mild to moderate depressive group. After adjustment for the sex and comorbidity, there were no significant differences between the two groups in terms of the obesity and lipid profiles, including TG. Conclusion: These results did not show a significant difference in the association between obesity, lipid profiles and the depression severity. The role of obesity and lipid profiles in the pathophysiology of depression remains to be clarified.

Keywords: depression, HAM-D, lipid profiles, obesity

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Authors: Jukka Heinonen

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Higher density reduces distances, private car dependency and thus reduces greenhouse gas emissions (GHGs). As a result, increased density has been given a central role among urban development targets. However, it is not just travel behavior that changes along with density. Rather, the consumption patterns, or overall lifestyles, change along with changing urban structure, particularly with changing housing types and consumption opportunities. Furthermore, elevated consumption of services, more frequent flying and less intra-household sharing have been shown to potentially outweigh the gains from reduced driving in more dense urban settlements. In this study, the geography of carbon footprints (CFs) in California is analyzed paying close attention to the household size differences and the resulting economies-of-scale advantages and disadvantages. A hybrid life cycle assessment (LCA) framework is employed together with consumer expenditure data to assess the CFs. According to the study, small urban households have the highest CFs in California. Their transport related emissions are significantly lower than those of the residents of less urbanized areas, but higher emissions from other consumption categories, together with the low degree of sharing of goods, overweigh the gains. Two functional units, per capita and per household, are used to analyze the CFs and to demonstrate the importance of household size. The lifestyle impacts visible through the consumption data are also discussed. The study suggests that there are still significant gaps in our understanding of the premises of low-carbon human settlements.

Keywords: carbon footprint, life cycle assessment, lifestyle, household size, consumption, economies-of-scale

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Authors: M. F. Miah, K. M. A. Zinnah, M. J. Raihan, H. Ali, M. N. Naser

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As genetic diversity is most important for existing, breeding and production of any fish; this study was undertaken for investigating genetic diversity of freshwater mud eel, Monopterus cuchia at population level where three ecological populations such as flooded area of Sylhet (P1), open water of Moulvibazar (P2) and open water of Sunamganj (P3) districts of Bangladesh were considered. Four arbitrary RAPD primers (OPB-12, C0-4, B-03 and OPB-08) were screened and RAPD banding patterns were analyzed among the populations considering 15 individuals of each population. In total 174, 138 and 149 bands were detected in the populations of P1, P2 and P3 respectively; however, each primer revealed less number of bands in each population. 100% polymorphic loci were recorded in P2 and P3 whereas only one monomorphic locus was observed in P1, recorded 97.5% polymorphism. Different genetic parameters such as inter-individual pairwise similarity, genetic distance, Nei genetic similarity, linkage distances, cluster analysis and allelic information, etc. were considered for measuring genetic diversity. The average inter-individual pairwise similarity was recorded 2.98, 1.47 and 1.35 in P1, P2 and P3 respectively. Considering genetic distance analysis, the highest distance 1 was recorded in P2 and P3 and the lowest genetic distance 0.444 was found in P2. The average Nei genetic similarity was observed 0.19, 0.16 and 0.13 in P1, P2 and P3, respectively; however, the average linkage distance was recorded 24.92, 17.14 and 15.28 in P1, P3 and P2 respectively. Based on linkage distance, genetic clusters were generated in three populations where 6 clades and 7 clusters were found in P1, 3 clades and 5 clusters were observed in P2 and 4 clades and 7 clusters were detected in P3. In addition, allelic information was observed where the frequency of p and q alleles were observed 0.093 and 0.907 in P1, 0.076 and 0.924 in P2, 0.074 and 0.926 in P3 respectively. The average gene diversity was observed highest in P2 (0.132) followed by P3 (0.131) and P1 (0.121) respectively.

Keywords: genetic diversity, Monopterus cuchia, population, RAPD, Bangladesh

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: S. H. Atef

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Background: The most common chromosomal abnormalities identified at birth are aneuploidies of chromosome 21, 18, 13, X and Y. Prenatal diagnosis of fetal aneuploidies is routinely done by traditional cytogenetic culture, a major drawback of this technique is the long period of time required to reach a diagnosis. In this study, we evaluated the QF-PCR as a rapid technique for prenatal diagnosis of common aneuploidies. Method:This work was carried out on Sixty amniotic fluid samples taken from patients with one or more of the following indications: Advanced maternal age (3 case), abnormal biochemical markers (6 cases), abnormal ultrasound (12 cases) or previous history of abnormal child (39 cases).Each sample was tested by QF-PCR and traditional cytogenetic. Aneuploidy screenings were performed amplifying four STRs on chromosomes 21, 18, 13, two pseudoautosomal,one X linked, as well as the AMXY and SRY; markers were distributed in two multiplex QFPCR assays (S1 and S2) in order to reduce the risk of sample mishandling. Results: All the QF-PCR results were successful, while there was two culture failures, only one of them was repeated. No discrepancy was seen between the results of both techniques. Fifty six samples showed normal patterns, three sample showed trisomy 21, successfully detected by both techniques and one sample showed normal pattern by QF-PCR but could not be compared to the cytogenetics due to culture failure, the pregnancy outcome of this case was a normal baby. Conclusion: Our study concluded that QF-PCR is a reliable technique for prenatal diagnosis of the common chromosomal aneuploidies. It has the advantages over the cytogenetic culture of being faster with the results appearing within 24-48 hours, simpler, doesn't need a highly qualified staff, less prone to failure and more cost effective.

Keywords: QF-PCR, traditional cytogenetic fetal aneuploidies, trisomy 21, prenatal diagnosis

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Authors: Bernard Moeketsi Hlalele

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Drought is a complicated natural phenomenon that creates significant economic, social, and environmental problems. An analysis of paleoclimatic data indicates that severe and extended droughts are inevitable part of natural climatic circle. This study characterised drought in Lejweleputswa using both Standardised Precipitation Index (SPI) and neural networks (NN) to quantify and predict respectively. Monthly 37-year long time series precipitation data were obtained from online NASA database. Prior to the final analysis, this dataset was checked for outliers using SPSS. Outliers were removed and replaced by Expectation Maximum algorithm from SPSS. This was followed by both homogeneity and stationarity tests to ensure non-spurious results. A non-parametric Mann Kendall's test was used to detect monotonic trends present in the dataset. Two temporal scales SPI-3 and SPI-12 corresponding to agricultural and hydrological drought events showed statistically decreasing trends with p-value = 0.0006 and 4.9 x 10⁻⁷, respectively. The study area has been plagued with severe drought events on SPI-3, while on SPI-12, it showed approximately a 20-year circle. The concluded the analyses with a seasonal analysis that showed no significant trend patterns, and as such NN was used to predict possible SPI-3 for the last season of 2018/2019 and four seasons for 2020. The predicted drought intensities ranged from mild to extreme drought events to come. It is therefore recommended that farmers, agri-business owners, and other relevant stakeholders' resort to drought resistant crops as means of adaption.

Keywords: drought, risk, neural networks, agri-businesses, project, Lejweleputswa

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Authors: A. Al-Wandi, A. Al-Ali, R. Dali, Y. Al-Karaghouli

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Background: Non-communicable diseases (NCDs) have become an alarming health problem across the globe. The risk of developing those diseases begins in childhood and develops gradually under the influence of risk factors including obesity, hypertension, dyslipidemia, cigarette smoking and decreased physical activity. Therefore, this study aims to determine the level of knowledge, attitudes, and practices of the risk factors of lifestyle induced chronic diseases (non-communicable diseases) among secondary school students in Sharjah city. Methods: Five hundred and ninety-one school children, from grades 10 to 12, formed the study sample, using the multistage stratified cluster sampling method. Four governmental schools were chosen, for each gender. Data was collected through a pretested, close-ended questionnaire consisting of five sections; demographics, physical activity, diet, smoking and sleeping patterns. Frequencies and descriptive statistics were used to analyze data through SPSS 23. Results: The data showed 64.6% of students had low knowledge of risk factors of non-communicable diseases. Concerning physical activity, 58.2 % were physically inactive and females being less active than males. More than 2/3 of students didn’t fulfill the recommended daily intake of fruits and vegetables (75.9%). 8% reported to be smokers with cigarettes being the most encountered tobacco product. Conclusion: Our study has demonstrated a low level of knowledge and practices yet, positive attitudes towards risk factors of chronic diseases. We recommend implementation of thorough awareness campaigns through public health education about the risk factors of non-communicable diseases.

Keywords: non-communicable diseases, physical activity, diet, knowledge, attitudes, practices, smoking

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Authors: Felix Platzer, Eric Fimbinger

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In Discrete Element Method (DEM) simulations, the breakage behavior of particles can be simulated based on different principles. In the case of large, complex-shaped particles that show various breakage patterns depending on the scenario leading to the failure and often only break locally instead of fracturing completely, some of these principles do not lead to realistic results. The reason for this is that in said cases, the methods in question, such as the Particle Replacement Method (PRM) or Voronoi Fracture, replace the initial particle (that is intended to break) into several sub-particles when certain breakage criteria are reached, such as exceeding the fracture energy. That is why those methods are commonly used for the simulation of materials that fracture completely instead of breaking locally. That being the case, when simulating local failure, it is advisable to pre-build the initial particle from sub-particles that are bonded together. The dimensions of these sub-particles consequently define the minimum size of the fracture results. This structure of bonded sub-particles enables the initial particle to break at the location of the highest local loads – due to the failure of the bonds in those areas – with several sub-particle clusters being the result of the fracture, which can again also break locally. In this project, different methods for the generation and calibration of complex-shaped particle conglomerates using bonded particle modeling (BPM) to enable the ability to depict more realistic fracture behavior were evaluated based on the example of filter cake. The method that proved suitable for this purpose and which furthermore allows efficient and realistic simulation of breakage behavior of complex-shaped particles applicable to industrial-sized simulations is presented in this paper.

Keywords: bonded particle model, DEM, filter cake, particle breakage

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Authors: Csilla Marianna Szabó

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In Hungary, the society has changes a lot for the past 25 years, and these changes could be detected in educational situations as well. The number and the intensity of conflicts have been increased in most fields of life, as well as at schools. Teachers have difficulties to be able to handle school conflicts. What is more, the new net generation, generation Z has values and behavioural patterns different from those of the previous one, which might generate more serious conflicts at school, especially with teachers who were mainly socialising in a traditional teacher – student relationships. In Hungary, the bill CCIV, 2011 declared the foundation of Institutes of Teacher Training in higher education institutes. One of the tasks of the Institutes is to survey the competences and needs of teachers working in public education and to provide further trainings and services for them according to their needs and requirements. This job is supported by the Social Renewal Operative Programs 4.1.2.B. The Institute of Teacher Training at the College of Dunaújváros, Hungary carried out a questionnaire and surveyed the needs and the requirements of teachers working in the Central Transdanubian region. Based on the results, the professors of the Institute of Teacher Training decided to meet the requirements of teachers and launch short courses in spring 2015. One of the courses is going to focus on school conflict management through mediation. The aim of the pilot course is to provide conflict management techniques for teachers presenting different mediation techniques to them. The theoretical part of the course (5 hours) will enable participants to understand the main points and the advantages of mediation, while the practical part (10 hours) will involve teachers in role plays to learn how to cope with conflict situations applying mediation. We hope if conflicts could be reduced, it would influence school atmosphere in a positive way and the teaching – learning process could be more successful and effective.

Keywords: conflict resolution, generation Z, mediation, teacher training

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Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Rogelio Omar Corona-Núñez, Alma Mendoza-Ponce

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The Tropical Dry Forest not only is one of the most important tropical ecosystems in terms of area, but also it is one of the most degraded ecosystems. However, little is known about the degradation impacts on carbon stocks, therefore in carbon emissions. There are different studies which explain its deforestation dynamics, but there is still a lack of understanding of how they correlate to carbon losses. Recently different authors have built current biomass maps for the tropics and Mexico. However, it is not clear how well they predict at the local scale, and how they can be used to estimate carbon emissions. This study quantifies the forest net carbon losses by comparing the potential carbon stocks and the different current biomass maps in the Southern Pacific coast in Oaxaca, Mexico. The results show important differences in the current biomass estimates with not a clear agreement. However, by the aggregation of the information, it is possible to infer the general patterns of biomass distribution and it can identify the driving forces of the carbon emissions. This study estimated that currently ~44% of the potential carbon stock estimated for the region is still present. A total of 6,764 GgC has been emitted due to deforestation and degradation of the forest at a rate of above ground biomass loss of 66.4 Mg ha-1. Which, ~62% of the total carbon emissions can be regarded as being due to forest degradation. Most of carbon losses were identified in places suitable for agriculture, close to rural areas and to roads while the lowest losses were accounted in places with high water stress and within the boundaries of the National Protected Area. Moreover, places not suitable for agriculture, but close to the coast showed carbon losses as a result of urban settlements.

Keywords: above ground biomass, deforestation, degradation, driving forces, tropical deciduous forest

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Authors: Hedi Dghim, Ahmed El-Naggar, Istvan Erlich

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Power electronic converters are being introduced in low voltage (LV) grids at an increasingly rapid rate due to the growing adoption of power electronic-based home appliances in residential grid. Photovoltaic (PV) systems are considered one of the potential installed renewable energy sources in distribution power systems. This trend has led to high distortion in the supply voltage which consequently produces harmonic currents in the network and causes an inherent voltage unbalance. In order to investigate the effect of harmonic distortions, a case study of a typical LV grid configuration with high penetration of 3-phase and 1-phase rooftop mounted PV from southern Germany was first considered. Electromagnetic transient (EMT) simulations were then carried out under the MATLAB/Simulink environment which contain detailed models for power electronic-based loads, ohmic-based loads as well as 1- and 3-phase PV. Note that, the switching patterns of the power electronic circuits were considered in this study. Measurements were eventually performed to analyze the distortion levels when PV operating under different solar irradiance. The characteristics of the load-side harmonic impedances were analyzed, and their harmonic contributions were evaluated for different distortion levels. The effect of the high penetration of PV on the harmonic distortion of both positive and negative sequences was also investigated. The simulation results are presented based on case studies. The current distortion levels are in agreement with relevant standards, otherwise the Total Harmonic Distortion (THD) increases under low PV power generation due to its inverse relation with the fundamental current.

Keywords: harmonic distortion analysis, power quality, PV systems, residential distribution system

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Authors: Alireza Abdiardekani, Maryam Salimi, Shirin Sarejloo, Mehdi Bazrafshan, Amir Askarinejad, Amirhossein Salimi, Hanieh Bazrafshan, Salar Javanshir, Armin Attar, Shokoufeh Khanzadeh, Mohsen Esmaeili, Hamed Bazrafshan Drissi

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Background: Opium, after tobacco, is the most abused substance in the Middle East. The effects of opium use on coronary artery disease are indeed unclear. This study aimed to assess the association between opium use and angiographic findings in patients with acute coronary syndrome (ACS) diagnosis at Al-Zahra Heart Hospital, Shiraz, Iran. Methods: In this case-control study, 170 patients admitted for coronary angiography were enrolled from 2019 to 2020. They were categorized into two groups based on their history: "non-opium" and "opium." SPSS (Version 26) was used to investigate the correlation between opioid addiction and the severity of coronary artery disease. Results: The results of our study reveal that the mean age of the participants was 61.63±9.07. This study indicated that 49 (28.82%) patients were female, and 121 (71.17%) were male. Our findings revealed that three-vessel disease was more frequent in non-opium (40; 47.05%) and opium (45; 52.94%) groups. There was a significant correlation between the severity of the second diagonal artery(D2) and right coronary artery(RCA) involvement and opium consumption. There was a strong positive correlation between the location of the vascular lesion in the left circumflex artery and opium consumption. Conclusion: Opium, as an independent risk factor for cardiovascular diseases, can have specific effects on angiographic findings in patients with coronary artery disease. Public health officials and politicians should arrange several programs to increase the general population’s consciousness about opioid use and its consequences.

Keywords: acute coronary syndrome, opium, coronary artery disease, angiography

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Authors: Supannika Klangphukhiew, Roongnapa Srichana, Rina Patramanon

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Cortisol has been used as a well-known commercial stress biomarker. A homeostasis response to psychological stress is indicated by an increased level of cortisol produced in hypothalamus-pituitary-adrenal (HPA) axis. Chronic psychological stress contributing to the high level of cortisol relates to several health problems. In this study, the cortisol biosensor was fabricated that mimicked the natural receptors. The artificial antibodies were prepared using molecular imprinted polymer technique that can imitate the performance of natural anti-cortisol antibody with high stability. Cortisol-molecular imprinted polymer (cortisol-MIP) was obtained using the multi-step swelling and polymerization protocol with cortisol as a target molecule combining methacrylic acid:acrylamide (2:1) with bisacryloyl-1,2-dihydroxy-1,2-ethylenediamine and ethylenedioxy-N-methylamphetamine as cross-linkers. Cortisol-MIP was integrated to the sensor. It was coated on the disposable screen-printed carbon electrode (SPCE) for portable electrochemical analysis. The physical properties of Cortisol-MIP were characterized by means of electron microscope techniques. The binding characteristics were evaluated via covalent patterns changing in FTIR spectra which were related to voltammetry response. The performance of cortisol-MIP modified SPCE was investigated in terms of detection range, high selectivity with a detection limit of 1.28 ng/ml. The disposable cortisol biosensor represented an application of MIP technique to recognize steroids according to their structures with feasibility and cost-effectiveness that can be developed to use in point-of-care.

Keywords: stress biomarker, cortisol, molecular imprinted polymer, screen-printed carbon electrode

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Rajendra K. Meena, Maneesh S. Bhandari, Santan Barthwal, Harish S. Ginwal

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Microsatellite markers are the most valuable tools for the characterization of plant genetic resources or population genetic analysis. Since it is codominant and allelic markers, utilizing them in polyploid species remained doubtful. In such cases, the microsatellite marker is usually analyzed by treating them as a dominant marker. In the current study, it has been showed that despite losing the advantage of co-dominance, microsatellite markers are still a powerful tool for genotyping of polyploid species because of availability of large number of reproducible alleles per locus. It has been studied by genotyping of 19 subpopulations of Dendrocalamus hamiltonii (hexaploid bamboo species) with 17 polymorphic simple sequence repeat (SSR) primer pairs. Among these, ten primers gave typical banding pattern of microsatellite marker as expected in diploid species, but rest 7 gave an unusual pattern, i.e., more than two bands per locus per genotype. In such case, genotyping data are generally analyzed by considering as dominant markers. In the current study, data were analyzed in both ways as dominant and co-dominant. All the 17 primers were first scored as nonallelic data and analyzed; later, the ten primers giving standard banding patterns were analyzed as allelic data and the results were compared. The UPGMA clustering and genetic structure showed that results obtained with both the data sets are very similar with slight variation, and therefore the SSR marker could be utilized to characterize polyploid species by considering them as a dominant marker. The study is highly useful to widen the scope for SSR markers applications and beneficial to the researchers dealing with polyploid species.

Keywords: microsatellite markers, Dendrocalamus hamiltonii, dominant and codominant, polyploids

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Authors: Sung-Won Yoo, Chul-Hyeon Kang, Kyoung-Tae Park, Hae-Sik Woo

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Numerous studies were dedicated on the High Volume Fly-Ash (HVFA) concrete using high volume fly ash. The material properties of HVFA concrete have been the primordial topics of early studies, and interest shifted gradually toward the structural behavior of HVFA concrete such as elasticity modulus, stress-strain relationship, and structural behavior. However, structural studies consider small-scale members limited to the scope of reinforced concrete only. Therefore, in this paper, on the basis of recent studies on the structural behavior, 2 full-scale test members were manufactured with 7.5 m span length, fly ash replacement ratio of 50 % and concrete compressive strength of 50 MPa in order to evaluate the practicability of HVFA to real structures. In addition, 2 steel composite test members were also manufactured with span length of 3 m and using the same HVFA concrete for the same purpose. The test results of full-scale RC members showed that the practical use of HVFA on such structures is not hard despite small differences between test results and existing research results on the stress-strain relationship. The flexural test revealed very little difference between 50% fly ash concrete and general concrete in view of the similarity exhibited by the displacement and strain patterns. The experimental concrete shear strength being very close to that of design code, the existing design code can be applied. From the flexural test results of steel girder composite members, the composite behavior can be secured as much as that using normal concrete under the condition of sufficient arrangement of reinforcing bar.

Keywords: composite, fly ash, full-scale, high volume

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Authors: Nidhi Adhlakha, K. L. Yadav

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Three phase magnetoelectric (ME) composites (1-x)(0.7BiFeO3-0.3CoFe2O4)-xPbTiO3 (or equivalently written as (1-x)(0.7BFO-0.3CFO)-xPT) with x variations 0, 0.30, 0.35, 0.40, 0.45 and 1.0 were synthesized using hybrid processing route. The effects of PT addition on structural, multiferroic and optical properties have been subsequently investigated. A detailed Rietveld refinement analysis of X-ray diffraction patterns has been performed, which confirms the presence of structural phases of individual constituents in the composites. Field emission scanning electron microscopy (FESEM) images are taken for microstructural analysis and grain size determination. Transmission electron microscopy (TEM) analysis of 0.3CFO-0.7BFO reveals the average particle size to be lying in the window of 8-10 nm. The temperature dependent dielectric constant at various frequencies (1 kHz, 10 kHz, 50 kHz, 100 kHz and 500 kHz) has been studied and the dielectric study reveals that the increase of dielectric constant and decrease of average dielectric loss of composites with incorporation of PT content. The room temperature ferromagnetic behavior of composites is confirmed through the observation of Magnetization vs. Magnetic field (M-H) hysteresis loops. The variation of magnetization with temperature indicates the presence of spin glass behavior in composites. Magnetoelectric coupling is evidenced in the composites through the observation of the dependence of the dielectric constant on the magnetic field, and magnetodielectric response of 2.05 % is observed for 45 mol% addition of PT content. The fractional change of magnetic field induced dielectric constant can also be expressed as ∆ε_r~γM^2 and the value of γ is found to be ~1.08×10-2 (emu/g)-2 for composite with x=0.40. Fourier transformed infrared (FTIR) spectroscopy of samples is carried out to analyze various bonds formation in the composites.

Keywords: composite, X-ray diffraction, dielectric properties, optical properties

Procedia PDF Downloads 287

Authors: Sidika McNeil

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Borderline personality disorder (BPD) is a personality disorder that has been found to have strong origins in childhood trauma. One of the key symptoms of BPD is an association with irregular moods swings, as well as suicidal ideation (SI). Owing to the typically severe trauma patients experience during childhood, it is hard for them to control their emotions and thus makes it hard to emotionally regulate. It is then very common for those suffering from BPD to turn to unhealthy coping mechanisms, such as substance use, unhealthy relationships, and more, often unsuccessfully creating experiences that facilitate safety which leads to further negative experiences. With the high suicide rating among children, adolescents, and teens, and an ever-increasing number of children being diagnosed with BPD, it is very important that more research is done to find further treatments for patients who are currently suffering. Methods: Utilizing data found in prior studies, this paper will analyze the literature to focus on a comprehensive treatment plan for those with DBT. It is currently suggested that with the use of dialectical behavioral therapy (DBT), a therapy that focuses on changing negative thinking patterns and pushes for more positive ones is helpful for treatment for those with BPD. Though this therapy is not a cure to BPD, it does help mitigate the risk; this essay will explore other options that can further the treatment process, such as cognitive analytical therapy (CAT), which focuses on delving into the past to find the root causes of an issue to create coping strategies and harm reduction, a type of therapy used to aid patients in lowering the use of substances without complete cessation. Results: The research provides enough evidence to link between the treatment of BPD with the utilization of CAT.

Keywords: borderline personality disorder, cognitive analytical therapy, dialectical behavioral therapy, harm reduction, suicidal ideation

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Authors: Peng, Chun-Yi, Chen, Wei-Hsuan, Ueng, Shyh-Kuang

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Ayoub. El Bourtali, Abdessamed.Najine, Amrou Moussa. Benmoussa

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One of the main goals of river engineering is river training, which is defined as controlling and predicting the behavior of a river. It is taking effective measurements to eliminate all related risks and thus improve the river system. In some rivers, the riverbed continues to erode and degrade; therefore, equilibrium will never be reached. Generally, river geometric characteristics and riverbed erosion analysis are some of the most complex but critical topics in river engineering and sediment hydraulics; riverbank erosion is the second answering process in hydrodynamics, which has a major impact on the ecological chain and socio-economic process. This study aims to integrate the new computer technology that can analyze erosion and hydraulic problems through computer simulation and modeling. Choosing the right model remains a difficult and sensitive job for field engineers. This paper makes use of the 5.0.4 version of the HEC-RAS model. The river section is adopted according to the gauged station and the proximity of the adjustment. In this work, we will demonstrate how 2D hydraulic modeling helped clarify the design and cover visuals to set up depth and velocities at riverbanks and throughout advanced structures. The hydrologic engineering center's-river analysis system (HEC-RAS) 2D model was used to create a hydraulic study of the erosion model. The geometric data were generated from the 12.5-meter x 12.5-meter resolution digital elevation model. In addition to showing eroded or overturned river sections, the model output also shows patterns of riverbank changes, which can help us reduce problems caused by erosion.

Keywords: 2D hydraulics model, erosion, floodplain, hydrodynamic, HEC-RAS, riverbed erosion, river morphology, resolution digital data, sediment

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Authors: Sidharta Sahirman, Ardiansyah, Muhammad Rifan, Edy-Melmambessy

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Merauke district in Papua, Indonesia has a strategic position and natural potential for the development of agricultural industry. The development of agriculture in this region is being accelerated as part of Indonesian Government’s declaration announcing Merauke as one of future national food barns. Therefore, land-use suitability analysis for Merauke need to be performed. As a result, the mapping for future agriculture-based industries can be done optimally. In this research, a case study is carried out in Semangga sub district. The objective of this study is to determine the suitability of Merauke land for some food crops. A modified agro-ecological zoning is applied to reach the objective. In this research, land cover based on satellite imagery is combined with soil, water and climate survey results to come up with preliminary zoning. Considering the special characteristics of Merauke community, the agricultural zoning maps resulted based on those inputs will be combined with socio-economic information and culture to determine the final zoning map for agricultural industry in Merauke. Examples of culture are customary rights of local residents and the rights of local people and their own local food patterns. This paper presents the results of first year of the two-year research project funded by The Indonesian Government through MP3EI schema. It shares the findings of land cover studies, the distribution of soil physical and chemical parameters, as well as suitability analysis of Semangga sub-district for five different food plants.

Keywords: agriculture, agro-ecological, Merauke, zoning

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Authors: Yousef Sahari, Eisa Asiri

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Hollywood films are produced in an open and liberal context, and when subtitling for a more conservative and closed society such as an Arabic society, religious words can pose a thorny challenge for subtitlers. Using a corpus of 90 Hollywood films released between 2000 and 2018 and applying insights from Descriptive Translation Studies (Toury, 1995, 2012) and the dichotomy of domestication and foreignization, this paper investigates three main research questions: (1) What are the dominant religious terms and functions in the English subtitles? (2) What are the dominant translation strategies used in the translation of religious words? (3) Do these strategies tend to be SL-oriented or TL-oriented (domesticating or foreignising)? To answer the research questions above, a quantitative and qualitative analysis of the corpus is conducted, in which the researcher adopts a self-designed, parallel, aligned corpus of ninety films and their Arabic subtitles. A quantitative analysis is performed to compare the frequencies and distribution of religious words, their functions, and the translation strategies employed by the subtitlers of ninety films, with the aim of identifying similarities or differences in addition to identifying the impact of functions of religious terms on the use of subtitling strategies. Based on the quantitative analysis, a qualitative analysis is performed to identify any translational patterns in Arabic translations of religious words and the possible reasons for subtitlers’ choices. The results show that the function of religious words has a strong influence on the choice of subtitling strategies. Also, it is found that foreignization strategies are applied in about two-thirds of the total occurrences of religious words.

Keywords: religious terms, subtitling, audiovisual translation, modern standard arabic, subtitling strategies, english-arabic subtitling

Procedia PDF Downloads 135

Authors: E. A. Ojoko, G. B. Umbugadu

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This study aims at describing the expenditure pattern of households on millet, maize and sorghum across income groups in Nasarawa State. A multi-stage sampling technique was used to select a sample size of 316 respondents for the study. The Almost Ideal Demand System (AIDS) model was adopted in this study. Results from the study shows that the average household size was five persons with dependency ratio of 52 %, which plays an important role on the household’s expenditure pattern by increasing the household budget share. On the average 82 % were male headed households with an average age of 49 years and 13 years of formal education. Results on expenditure share show that maize has the highest expenditure share of 38 % across the three income groups and that most of the price effects are significantly different from zero at 5 % significant level. This shows that the low price of maize increased its demand as compared to other cereals. Household size and age of household members are major factors affecting the demand for cereals in the study. This agrees with the fact that increased household population (size) will bring about increase consumption. The results on factors influencing preferences for cereal grains reveals that cooking quality and appearance (65.7 %) were the most important factors affecting the demand for maize in the study area. This study recommends that cereal crop production should be prioritized in government policies and farming activities that help to boost food security and alleviate poverty should be subsidized.

Keywords: expenditure pattern, AIDS model, budget share, price cereal grains and consumption

Procedia PDF Downloads 176