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How To Activate Threat Perceptions in Behavior Research: a Simple Technique for Inducing Health and Resource Scarcity Threats
No full textIsler, Ozan/0000-0002-4638-2230Understanding our cognitive and behavioral reactions to large-scale collective problems involving health and resource scarcity threats, such as the COVID-19 pandemic, helps us be better prepared for future collective threats. However, existing studies on these threats tend to be restricted to correlational data, partly due to a lack of reliable experimental techniques for manipulating threat perceptions. In four preregistered experiments (N = 5152), we developed and validated an experimental technique that can separately activate perceptions of personal health threat or resource scarcity threat, either in the specific context of the COVID-19 pandemic or in general. We compared the threat manipulations to a relaxation manipulation designed to deactivate background threat perceptions as well as to a passive control condition. Confirmatory tests showed substantial activation of personal health and resource scarcity threat perceptions. This brief technique can be easily used in online experiments. Distress due to the threat manipulation was rarely reported and easily managed with a debriefing toolkit.H2020 European Research CouncilNo Statement AvailableSocial Science Citation Inde
A Hesitant Fuzzy Linguistic Terms Set-Based Ahp and Topsis Methodology for Fuel Coal Type Selection Problem of Industrial Facilities
No full textCoal is still used widely by both industrial facilities and coal fired power plants. Lignite, hard coal, coke, and imported coal are some alternatives. The coal has ash content, moisture content, heat rate, volatile matter, carbon content, sulphur content, and size that need to be considered as well as price. The suppliers provide coal products for each coal type, and the most appropriate coal product needs to be selected considering different parameters. Therefore, in this paper, a hesitant fuzzy linguistic term sets-based AHP (HFLTS-AHP) and TOPSIS method are used to select the best coal type alternative for industrial facilities. As the HFLTS-AHP is used to weight the evaluation criteria, TOPSIS is utilized to rank the fuel coal type alternatives. The proposed methodology offers an innovative and novel approach to help industrial facilities select the appropriate coal product while balancing the outputs, such as carbon, sulphur, ash content, and so on. In another point of view, the motivation of this research is to help industrial firms find out the ultimate fuel coal alternative based on their needs. This objective is realized using the proposed approach that integrates the HFLTS-AHP and TOPSIS approaches for the related problem, also utilizing group decision making. Moreover, this approach is concreted by an Excel template that provides an effective tool for firms to realize the evaluation process without many tiresome fuzzy comparisons and complex calculations. Furthermore, in the paper, a real-life case study in Turkish industrial facilities is presented to demonstrate the effectiveness and applicability of the proposed approach to readers and practitioners. In this case, seven coal type options are evaluated in terms of eight criteria by three decision makers, and the best coal type alternative is determined. © 2024 Old City Publishing, Inc.Science Citation Index Expande
In the Shadow of War and Empire: Industrialisation, Nation-Building, and Working-Class Politics in Turkey
No full textOzbek, Muge/0000-0003-2684-6891[No Abstract Available]Social Science Citation Inde
Nigeria's Fossil Fuel Energy Consumption-Gdp Relation and Its Effect on National Hdi:2005-2022
No full textThe correlation between energy usage and economic growth is widely acknowledged. The placement within the dynamics of Nigeria's economic growth and fossil fuel usage is evaluated in this paper. Retrieved and processed data from reliable databases, such as "Our World in Data"and THE WORLD BANK, covering the years 2005 to 2022, were used to analyze the following: percentage of total primary energy consumption (fossil fuel), percentage of consumption per capita, percentage of total Gross Domestic Product (GDP), percentage of GDP per capita, and overall Human Development Index (HDI). The results showed fluctuations in GDP growth rates in tandem with stable energy consumption, a continuous reliance on fossil fuels in the face of a slow but steady rise in the HDI, and economic difficulties in certain years in spite of stable energy consumption. In contrast to predictions, the country's HDI, which has been rising steadily over time, was mostly unaffected by the non-linear link between GDP and fossil fuel usage. The study also showed variations in Adjusted Net Savings, indicating the unpredictability of the country's energy sector in the face of political and economic unpredictability. Notwithstanding these obstacles, the HDI showed a slow but noticeable improvement, suggesting that the income and savings Nigeria's petroleum resources provide to its population are not very beneficial. Considering the findings, policy-based recommendations were also offered. © 2024 IEEE
Retraction: a Nano-Scale Design of a Multiply-Accumulate Unit for Digital Signal Processing Based on Quantum Computing
No full text[No Abstract Available]Science Citation Index Expande
Cognitive Flexibility and Depression: the Moderator Roles of Humor Styles
No full textHumor style, which involves both adaptive and maladaptive forms, refers to the ways people use humor in daily life. Maladaptive humor styles (self-defeating and aggressive) can be risk factors for various mental disorders, including depression and anxiety. In contrast, adaptive humor styles (affiliative and self-enhancing) are perceived as resilience factors and buffer the negative impact of other risk factors. Cognitive flexibility reflects a capacity to come up with alternative interpretations and resolutions to demanding situations while perceiving them as controllable. Although the connection of high cognitive flexibility with low depression levels has been consistently documented, its interaction with trait-like factors received limited attention. The current study aims to explore the moderator role of humor styles in the association of cognitive flexibility with depression. Data were gathered from 436 (320 women) participants aged 18 and 70 (M=35.4, SD=9.18) through scales assessing humor styles, cognitive flexibility, and depression. The results revealed that the interaction of affiliative humor style with cognitive flexibility was significantly linked to the individual differences in depression levels, highlighting that affiliative humor is functional if individuals have difficulty approaching problematic situations from different angles. However, a similar pattern was not observed for other humor styles.Scientific and Technological Research Council of Turkiye (TUBITAK)Open access funding provided by the Scientific and Technological Research Council of Turkiye (TUBITAK).Social Science Citation Inde
The Link Between Early Iconic Gesture Comprehension and Receptive Language
No full textAKTAN-ERCIYES, ASLI/0000-0002-6531-6140; Goksun, Tilbe/0000-0002-0190-7988; Ozer, Demet/0000-0003-3230-2874Children comprehend iconic gestures relatively later than deictic gestures. Previous research with English-learning children indicated that they could comprehend iconic gestures at 26 months, a pattern whose extension to other languages is not yet known. The present study examined Turkish-learning children's iconic gesture comprehension and its relation to their receptive vocabulary knowledge. Turkish-learning children between the ages of 22- and 30-month-olds (N = 92, M = 25.6 months, SD = 1.6; 51 girls) completed a gesture comprehension task in which they were asked to choose the correct picture that matched the experimenter's speech and iconic gestures. They were also administered a standardized receptive vocabulary test. Children's performance in the gesture comprehension task increased with age, which was also related to their receptive vocabulary knowledge. When children were categorized into younger and older age groups based on the median age (i.e., 26 months-the age at which iconic gesture comprehension was present for English-learning children), only the older group performed at chance level in the task. At the same time, receptive vocabulary was positively related to gesture comprehension for younger but not older children. These findings suggest a shift in iconic gesture comprehension at around 26 months and indicate a possible link between receptive vocabulary knowledge and iconic gesture comprehension, particularly for children younger than 26 months.James S. McDonnell Foundation [220020510]James S. McDonnell Foundation, Grant/Award Number: 220020510Social Science Citation Inde
The Flashbulb-Like Nature of Memory for the First Covid-19 Case and the Impact of the Emergency. a Cross-National Survey
No full textMarkostamou, Ioanna/0000-0001-7343-0122; Lanciano, Tiziana/0000-0001-6533-1052; Ergen, Irem/0000-0003-0703-111X; Alfeo, Federica/0000-0002-0306-2122; Watson, Lynn Ann/0000-0001-5150-1217; Barzykowski, Krystian/0000-0003-4016-3966; Oner, Sezin/0000-0001-8124-3554; Anthony, Kristine/0000-0001-6043-8192; Matias-Garcia, Jose Antonio/0000-0002-3832-3804; Decarolis, Diletta/0000-0002-5190-7425Flashbulb memories (FBMs) refer to vivid and long-lasting autobiographical memories for the circumstances in which people learned of a shocking and consequential public event. A cross-national study across eleven countries aimed to investigate FBM formation following the first COVID-19 case news in each country and test the effect of pandemic-related variables on FBM. Participants had detailed memories of the date and others present when they heard the news, and had partially detailed memories of the place, activity, and news source. China had the highest FBM specificity. All countries considered the COVID-19 emergency as highly significant at both the individual and global level. The Classification and Regression Tree Analysis revealed that FBM specificity might be influenced by participants' age, subjective severity (assessment of COVID-19 impact in each country and relative to others), residing in an area with stringent COVID-19 protection measures, and expecting the pandemic effects. Hierarchical regression models demonstrated that age and subjective severity negatively predicted FBM specificity, whereas sex, pandemic impact expectedness, and rehearsal showed positive associations in the total sample. Subjective severity negatively affected FBM specificity in Turkey, whereas pandemic impact expectedness positively influenced FBM specificity in China and negatively in Denmark.French Government ScholarshipNo Statement Availabl
Continuity and Change in Turkish Politics: Economic and Behavioural Explanations of Democratic Backsliding
No full textYıldırım, Kerem/0000-0002-2421-9109This paper introduces a special issue focusing on the intricacies of Turkey's party system and the evolution of Turkish party competition amid democratic challenges. The introduction provides a brief overview of each paper in this special issue, which delves into the relationship between economic factors and voter behavior, offering insights into the continued dominance of the ruling party. While doing so, the special issue specifically examines the 2023 Turkish General elections, presenting alternative perspectives on how the incumbent party maintains its electoral success
Mental Disorder and Suicidal Ideation Detection From Social Media Using Deep Neural Networks
No full textDehkharghani, Rahim/0000-0002-9619-8247Depression and suicidal ideation are global reasons for life-threatening injury and death. Mental disorders have increased especially among young people in recent years, and early detection of those cases can prevent suicide attempts. Social media platforms provide users with an anonymous space to interact with others, making them a secure environment to discuss their mental disorders. This paper proposes a solution to detect depression/suicidal ideation using natural language processing and deep learning techniques. We used Transformers and a unique model to train the proposed model and applied it to three different datasets: SuicideDetection, CEASEv2.0, and SWMH. The proposed model is evaluated using the accuracy, precision, recall, and ROC curve. The proposed model outperforms the state-of-the-art in the SuicideDetection and CEASEv2.0 datasets, achieving F1 scores of 0.97 and 0.75, respectively. However, in the SWMH data set, the proposed model is 4% points behind the state-of-the-art precision providing the F1 score of 0.68. In the real world, this project could help psychologists in the early detection of depression and suicidal ideation for a more efficient treatment. The proposed model achieves state-of-the-art performance in two of the three datasets, so they could be used to develop a screening tool that could be used by mental health professionals or individuals to assess their own risk of suicide. This could lead to early intervention and treatment, which could save lives.Scientific and Technological Research Council of Turkiye (TUBIdot;TAK)Open access funding provided by the Scientific and Technological Research Council of Turkiye (TUB & Idot;TAK).Emerging Sources Citation Inde