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Readings as a Helping Tools for Economics Education: Animal Farm
No full textEconomic events have many social and political causes and consequences. Unfortunately, it becomes meaningless to explain these events using only mathematical methods as time goes by. In addition, the teaching methods of this comprehensive science to young generations have begun to be questioned. While the learning skills of generations change, there is no drastic change in methods in economics education. This study aims to analyze the advantages of using literary works in economics education in the sample of Animal Farm as in using different training methods. Firstly, the study examined the interactions between literature and economics briefly. Then, the plots of Animal Farm were revealed from the allegory of historical events using defamiliarization. Finally, the benefits of using Animal Farm in economics education were discussed. Using literary works like Animal Farm in economics education assists in raising future economists who can prick the bubble in the events, understand the effects, and create unique systems for societies more easily.Economic
Seaport Business Actions to Ensure Clean and Affordable Energy
No full textMany different sectors are obliged to implement the 17 goals established by the United Nations General Assembly, both for their own life cycles and for the future of our world. Each goal has its own goals and plans. Although different applications are made for these targets on a sectoral basis, a common language must be developed for each target. In this study, the 7th goal of the Sustainable Development Goals (SDGs), the goal of providing access to economic, sustainable and clean energy for everyone, was emphasized. In the study, the maritime transport sector, which has a large share in the logistics sector in terms of both economic and environmental damage, has been selected. In this context, the sustainability, environment, corporate social responsibility and annual reports of the 33 biggest European ports with a gross weight handling volume were examined in line with the SDG 7 target and a content analysis was made on these reports. According to the results of the analysis, the contribution and approach of Europe's largest ports to Clean and Affordable Energy, the 7th sustainable development goal of the United Nations, emerged.Green & Sustainable Science & Technology || Engineering, Environmental || Operations Research & Management Scienc
Machine Learning Implementations for Multi-class Cardiovascular Risk Prediction in Family Health Units
No full textCardiovascular disease (CVD) risk prediction plays a significant role in clinical research since it is the key to primary prevention. As family health units follow up on a specific group of patients, particularly in the middle-aged and elderly groups, CVD risk prediction has additional importance for them. In a retrospectively collected data set from a family health unit in Turkey in 2018, we evaluated the CVD risk levels of patients based on SCORE-Turkey. By identifying additional CVD risk factors for SCORE-Turkey and grouping the study patients into 3-classes low risk, moderate risk, and high risk patients, we proposed a machine learning implemented early warning system for CVD risk prediction in family health units. Body mass index, diastolic blood pressures, serum glucose, creatinine, urea, uric acid levels, and HbA1c were significant additional CVD risk factors to SCORE-Turkey. All of the five implemented algorithms, k-nearest neighbour (KNN), random forest (RF), decision tree (DT), logistic regression (LR), and support vector machines (SVM), had high prediction performances for both the K4 and K5 partitioning protocols. With 89.7% and 92.1% accuracies for K4 and K5 protocols, KNN outperformed the other algorithms. For the five ML algorithms, while for the low risk category, precision and recall measures varied between 95% to 100%, moderate risk, and high risk categories, these measures varied between 60% to 92%. Machine learning-based algorithms can be used in CVD risk prediction by enhancing prediction performances and combining various risk factors having complex relationships.Engineering, Multidisciplinary || Operations Research & Management Science || Mathematics, Applie
Factors Relating to Decision Delay in the Emergency Department: Effects of Diagnostic Tests and Consultations
No full textPurpose: The purpose of this study is to investigate the factors increasing waiting time (WT) and length of stay (LOS) in patients, which may cause delays in decision-making in the emergency departments (ED). Patients and Methods: Patients who arrived at a training hospital in the central region of Izmir City, Turkey, during the first quarter of 2020 were retrospectively analyzed. WT and LOS were the outcome variables of the study, and gender, age, arrival type, triage level determined based on the clinical acuity, diagnosis encoded based on International Classification of Diseases-10 (ICD-10), the existence of diagnostic tests or consultation status were the identified factors. The significance of the differences in WT and LOS values based on each level of these factors was analyzed using independent sample t-tests and ANOVA. Results: While patients for which no diagnostic testing or consultation was requested had a significantly higher WT in EDs, their LOS values were substantially lower than those for which at least one diagnostic test or consultation was ordered (p <= 0.001). Besides, elderly and red zone patients and those who arrived by ambulance had significantly lower WT and higher LOS values than other levels for all groups of patients for which laboratory-type or imaging-type diagnostic test or consultation was requested (p <= 0.001 for each comparison). Conclusion: Besides ordering diagnostic tests or consultation in EDs, different factors may extend patients' WT and LOS values and cause significant decision-making delays. Understanding the patient characteristics associated with longer waiting times and LOS values and, thus, delayed decisions will enable practitioners to improve operations management in EDs.Emergency Medicin
Oil rents and non-oil economic growth in CIS oil exporters. The role of financial development
No full textThe role of financial development is vital in long-run economic growth. Due to the windfall revenues it might have extra relevance in natural resource-rich developing economies. This study explores whether financial development, measured in the percentage share of the bank loans to the private sector in GDP, can facilitate the impact of oil rents on the development of the non-oil sector in Commonwealth of Independent States oil exporters: Azerbaijan, Kazakhstan, and Russia in the long run. It develops a combined framework where financial development acts as both a threshold variable and an interaction term for the impact of oil rents on non-oil GDP. We find a threshold effect of oil rents for the non-oil sector in Azerbaijan and Kazakhstan. It shows that the same magnitude of oil rents can create more non-oil growth if financial development exceeds 9.6% and 15.5% in Azerbaijan and Kazakhstan, respectively. For Russia, neither threshold nor interaction effects were found - oil rents have a linearly positive impact on non-oil economic development. Moreover, we find that institutional quality fosters non-oil development in Azerbaijan. It also positively affects non-oil development in Kazakhstan and Russia, albeit statistically insignificant. In the design of policies, authorities may wish to implement measures that would lead to the further development of the financial sector and institutional quality to make oil rents more beneficial for the development of the non-oil sector.Environmental Studie
Perceived expert and laypeople consensus predict belief in local conspiracy theories in a non-WEIRD culture: Evidence from Turkey
No full textPast research has shown that perceived scientific consensus (or lack thereof) on an issue predicts belief in misinformation. In the current study (N = 729), we investigated how perceived consensus among both experts and laypeople predicts beliefs in localized and specific conspiracy theories in Turkey, a non-WEIRD country. Participants in our study were found to overestimate consensus among both experts and laypeople regarding baseless conspiracy theories surrounding the alleged secret articles of the Lausanne Treaty and unused mining reserves in Turkey. Notably, conspiracy believers exhibited a higher tendency to overestimate consensus compared to non-believers. Furthermore, perceived expert consensus had a stronger association with conspiracy beliefs than perceived laypeople consensus. We also explored the correlates of conspiracy beliefs and perceived consensus, including socioeconomic factors, worldview, cognitive sophistication, and personality. The results further indicate that the correlations between belief and perceived consensus manifest with comparable magnitudes, irrespective of the specific conspiracy theories under consideration. These findings support the potential of perceived consensus as an important factor for understanding conspiracy beliefs.Psychology, Multidisciplinar
Environmental Sustainability Implications and Economic Prosperity of Integrated Renewable Solutions in Urban Development
No full textThe increasing urbanization and growth of cities worldwide have led to a significant increase in energy demand. As a transition to a low carbon environment occurs, the role of renewable and sustainable energy systems in urban areas is benefiting industry and the environment alike. From this perspective, the Sustainable Development Goals (SDGs) have a lot to offer to the energy industry, particularly the integration of renewable and sustainable energy systems for environmental protection in cities. This study presents a comprehensive view that integrates technological, economic, political, and social challenges confronted with the effective implementation of renewable and sustainable energy in urban cities and proposes a solution agenda to overcome these hurdles with the aid of the SDGs. The weights for the challenges of adopting renewable and sustainable energy systems were determined using the Fuzzy Best-Worst Method. The SDGs were then ranked using the fuzzy TOPSIS technique to overcome predetermined challenges. The originality of this study lies in finding solutions to the determined challenges by adopting SDGs, emphasizing the need for integrated solutions that address energy-related concerns, and highlighting the role and importance of SDGs in environmental protection. The study highlights the importance of SDGs in promoting renewable energy integration in urban areas, with SDG 11 being the most crucial to mitigate harmful environmental occurrences related to energy-related issues in urban areas, followed by SDG 7 and SDG 13.Energy & Fuel
Incremental Testing in Software Product Lines-An Event Based Approach
No full textOne way of developing fast, effective, and high-quality software products is to reuse previously developed software components and products. In the case of a product family, the software product line (SPL) approach can make reuse more effective. The goal of SPLs is faster development of low-cost and high-quality software products. This paper proposes an incremental model-based approach to test products in SPLs. The proposed approach utilizes event-based behavioral models of the SPL features. It reuses existing event-based feature models and event-based product models along with their test cases to generate test cases for each new product developed by adding a new feature to an existing product. Newly introduced featured event sequence graphs (FESGs) are used for behavioral feature and product modeling || thus, generated test cases are event sequences. The paper presents evaluations with three software product lines to validate the approach and analyze its characteristics by comparing it to the state-of-the-art ESG-based testing approach. Results show that the proposed incremental testing approach highly reuses the existing test sets as intended. Also, it is superior to the state-of-the-art approach in terms of fault detection effectiveness and test generation effort but inferior in terms of test set size and test execution effort.Computer Science, Information Systems || Engineering, Electrical & Electronic || Telecommunication
Investigating the role of knowledge-based supply chains for supply chain resilience by graph theory matrix approach
No full textNowadays, providing information flow at every phase of a knowledge-based supply chain with technologies has become a vital issue due to rapid population growth, globalisation, and increases in demand in the supply chain. Knowledge-based supply chains have a critical role in increasing resilience in supply chain processes with emerging technologies. Thus, it is necessary to determine the critical factors that increase SC resilience. Therefore, this study aims to determine SC resilience improvement factors in knowledge-based supply chains and investigate the importance level of determining factors using the Graph Theory Matrix Approach. The results suggest that the most important supply chain resilience improvement factor is Adaptive Capacity (F3), followed by Product Prioritization (F9) and Flexibility (F1), respectively. This study is expected to benefit managers and policymakers as it provides a better understanding of critical SC resilience improvement factors that play a role in knowledge-based supply chains. In order to increase resilience in the supply chain, system thinking and solutions should be encouraged by businesses to increase collaboration with stakeholders. Businesses and governments should provide collaborative long-term solutions for the uncertain environment to ensure a sustainable and resilient environment.Managemen
Meteorological Drought Assessment and Trend Analysis in Puntland Region of Somalia
No full textDrought assessment and trend analysis of precipitation and temperature time series are essential in the planning and management of water resources. Long-term precipitation and temperature historical records (monthly for 41 years, from 1980 to 2020) are used to investigate annual drought characteristics and trend analysis in Somalia's northern region. Six drought indices of the normal Standardized Precipitation Index (normal-SPI), the log normal Standardized Precipitation Index (log-SPI), the Standardized Precipitation Index using the gamma distribution (Gamma-SPI), the Percent of Normal Index (PNI), the Discrepancy Precipitation Index (DPI), and the Deciles Index (DI) are used in this study for the annual drought assessment. The log-SPI, the gamma-SPI, the PNI, and the DPI could capture historical extreme and severe droughts that occurred in the early 1980s and over the last two decades. The results indicate that Somalia has gone through extended drought periods over the past quarter century, exacerbating the existing humanitarian situation. The normal-SPI, gamma-SPI, and PNI indicate less and moderate drought conditions, whereas log-SPI, DPI, and DI accurately capture historical extreme and severe drought periods || thus, these methods are recommended as annual drought assessment tools in the studied region. Not only are the PNI and DPI less correlated to each other, but their correlation coefficient (CC) with SPI-based drought indices are not as high as SPI-based indices which are close to unity. For the purpose of the trend analysis, the Mann Kendall (MK) test, the Spearman's rho (SR) test, and the Sen test are used. Furthermore, the Pettitt test is implemented to detect the change points and the Thiel-Sen approach is used to estimate the magnitude of trend in the precipitation and temperature time series. The results indicate that there is overall warming in the region which has experienced a significant shift in trend direction since 2000. The trend analysis of annual precipitation data time series shows that Bossaso and Garowe stations have significant positive trends, while the Qardho station has no trend. In 1997 and 1998, respectively, abrupt changes in annual precipitation are detected at Qardho and Garowe stations. Due to the civil war of more than three decades in Somalia and the non-institutionalized governance to inform historical drought conditions in the country, determining the most appropriate meteorological drought index would help to develop a drought monitoring system for states and the entire country.Green & Sustainable Science & Technology || Environmental Sciences || Environmental Studie