Scopus İndeksli Yayınlar Koleksiyonu

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Analyses of Chemical and Physical Egg Quality Parameters of Laying Hens Housed in Different Conditions in Turkey
(Sakarya University, 2023) Uysal Afacan, R.S.
The aim of the present study is to determine the content of chemical and physical quality parameters of hen eggs (liquid whole egg (LWE), liquid egg yolk (LEY), and liquid egg white (LEW)) produced for different housing and feeding conditions in Turkey. Chemical quality parameters (protein, lipid, and moisture) and physical quality parameters (total soluble solid (°Brix), pH, conductivity, and yolk:white ratio) were analyzed using different egg samples. Kjeldahl, wet ashing, and oven-drying official methods were used for the protein, total lipid, and moisture analyses of egg samples. The highest protein content in the LEY and LEW samples were found to be 19.0% and 15.13%, respectively for the tenth sample having fortified feeding (selenium+DHA) parameters. For LWE samples, it was also obtained 15.65% with the second sample having a not fortified feeding parameter. The highest total lipid content for LWE samples was determined as 10.43% for the seventh sample which housed under cage free conditions and fed with organic (omega3+EPA+DHA) fortifiers, while it was found with a value 25.7% for the second and third LEY samples possessing a not fortified feeding parameters. The highest moisture content was determined as 78.37%, 54.64%, and 89.11 for thirty-first LWE sample (with not fortified feeding), third LEY sample (with not fortified feeding) and sixth LEW sample (having cage free and organic parameters), respectively. As a result, the minimum, average, and maximum contents of the chemical and physical quality parameters were determined for laying hen eggs raised in several housing and feeding conditions in Turkey. © 2023, Sakarya University. All rights reserved.
Analyzing Cost Efficiency and Project Scope in Post-Disaster Housing: Reconstruction Cases of Toki in Türkiye
(MDPI, 2025) Geylani, Ozlem
The Mass Housing Administration of T & uuml;rkiye (TOKI) operates as the primary public organization responsible for delivering extensive affordable housing throughout T & uuml;rkiye while ensuring disaster resilience. The recent decades of earthquakes and environmental hazards in T & uuml;rkiye have necessitated extensive post-disaster reconstruction initiatives nationwide. In response, TOKI has completed numerous disaster housing projects across the country through an integrated infrastructure framework supporting community recovery. This study presents an extensive statistical evaluation of 664 disaster housing projects constructed by TOKI across 40 provinces. Specifically, a quantitative analysis is conducted on 434 disaster housing projects for which detailed financial data are available. This research examines differences in construction costs between urban mass housing developments and rural village settlements, particularly focusing on the integration of functional structures such as schools, mosques, commercial units, and barns. Although mass housing projects require significantly larger total budgets due to their extensive scale, statistical analysis reveals no significant difference in per-unit construction costs between mass housing and village housing projects. Regression analysis indicates that incorporating barns increased per-unit construction costs, while the presence of schools and mosques significantly decreases these expenses. The findings of this research provide critical insights into the economic and functional factors influencing disaster housing reconstruction in T & uuml;rkiye and offer practical recommendations for improved planning, resource management, and community reconstruction based on an evaluation of functional structures.
Applying Entropy Weighting and 2-Tuple Linguistic T-Spherical Fuzzy MCDM: A Case Study of Developing a Strategic Sustainability Plan for Istanbul Airport
(MDPI, 2024) Mizrak, Filiz; Polat, Levent; Tasar, Sezin Acik
This study presents a novel sustainability plan tailored for Istanbul Airport, leveraging advanced decision-making methodologies to address the urgent need for sustainable practices in aviation. By integrating the entropy weighting and 2-tuple linguistic T-spherical fuzzy multi-criteria decision-making (MCDM) models, the study offers a comprehensive approach to evaluating and prioritizing sustainability criteria based on expert input from 12 professionals. The novelty of this research lies in its unique combination of advanced MCDM techniques with cutting-edge technologies, including IoT-enabled monitoring systems, digital twin models, blockchain-based sustainability reporting, and carbon capture initiatives, tailored specifically for large-scale airport operations. The study develops a phased implementation roadmap comprising three stages: (1) a short-term focus on energy efficiency and renewable energy infrastructure, achieving significant cost reductions within a 3-7.5-year payback period; (2) medium-term initiatives integrating IoT and digital twins to enhance operational efficiency; and (3) long-term measures incorporating carbon capture and blockchain for transparency and compliance. Key implementation steps include upgrading energy systems, deploying IoT sensors, creating digital replicas of airport infrastructure, and establishing regulatory and stakeholder collaboration frameworks. This research contributes a replicable framework for airports worldwide, bridging theoretical models with actionable solutions.
Artificial Intelligence Technologies and Ethics in Educational Processes: Solution Suggestions and Results
(Univ Malaga, 2024) Kolemen, Cansu Sahin
Artificial intelligence is a technology used to imitate the human-like thinking and decision-making abilities of computer systems. This technology enables computers to perform complex tasks such as data analysis, learning, problem solving and decision making. It is used in the field of education as well as in every field. While the use of artificial intelligence in the field of education provides advantages such as providing personalized learning experiences to students, providing teachers with intuition about student performance and developing educational materials, the ethical dimension should not be ignored. Therefore, the aim of this study is to produce solutions to ethical problems in the teaching and evaluation processes of artificial intelligence technologies in education. Qualitative research method was used in this study. It has adopted the phenomenological research approach among qualitative research methods. The concept of phenomenon is also the ethics of artificial intelligence. The working group consists of teachers, educational technologists and academicians. When selecting the working group, it was taken into consideration that there were teachers who use artificial intelligence applications in education and academics and technologists working in this field. Document analysis and focus group interviews were used as data collection tools. Content analysis was performed on the data obtained. According to the results of the study, ethical problems encountered with the use of artificial intelligence in education were identified and solution suggestions were offered.
Authoritarian Neoliberalism and Resistance in Turkey: Construction, Consolidation, and Contestation
(Springer Nature, 2021) Borsuk, İ.; Dinç, P.; Kavak, S.; Sayan, P.
This book offers new clarity on three important political concepts: authoritarianism, neoliberalism, and resistance. While debates on authoritarian resurgence have been limited to the examination of political factors (e.g., polarisation, conflict) until recently, the rising literature on ‘authoritarian neoliberalism’ highlights how the neoliberal restructuring of political economy bolsters the authoritarian tendencies of elected governments both in the Global South and the Global North. This book will be an invaluable resource not only to scholars of Turkey and the Middle East but also to researchers into authoritarianism and neoliberalism around the world. Chapters 2 and 10 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
Beyond the Silicon Valley of the East: Exploring Portfolio Diversification with India and Mint Economies
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Ozdurak, C.; Hekim, D.
In the past few decades, India’s tech industry has boomed, making it a leader in the digital world. Today, India has many big tech companies, well-trained software developers, and cutting-edge technology like AI and cloud computing. This success shows India’s innovative spirit and makes the country a good example for other developing nations. However, global portfolio managers often overlook potential diversification opportunities beyond India’s dynamic stock market. This study investigates the viability of MINT (Mexico, Indonesia, Nigeria, and Turkey) as diversification targets, specifically analyzing spillover effects and volatility dynamics between their stock markets and that of India. Leveraging vector autoregressions (VARs) and dynamic conditional correlation (DCC)–GARCH models, we uncover intricate relationships. Further, DCC–GARCH analysis reveals varying degrees of volatility spillover, offering valuable insights for risk management. Our findings suggest that MINT economies, particularly Mexico and Turkey, hold promise for Indian portfolio diversification. By strategically incorporating these markets, investors can potentially mitigate India-specific risks and enhance portfolio returns. We urge global portfolio managers to consider Turkey as a viable diversification avenue, acknowledging the nuanced market growth dynamics highlighted in this study. © 2024 by the authors.
Binary Particle Swarm Optimization as a Detection Tool for Influential Subsets in Linear Regression
(Taylor & Francis Ltd, 2021) Deliorman, G.; Inan, D.
An influential observation is any point that has a huge effect on the coefficients of a regression line fitting the data. The presence of such observations in the data set reduces the sensitivity and validity of the statistical analysis. In the literature there are many methods used for identifying influential observations. However, many of those methods are highly influenced by masking and swamping effects and require distributional assumptions. Especially in the presence of influential subsets most of these methods are insufficient to detect these observations. This study aims to develop a new diagnostic tool for identifying influential observations using the meta-heuristic binary particle swarm optimization algorithm. This proposed approach does not require any distributional assumptions and also not affected by masking and swamping effects as the known methods. The performance of the proposed method is analyzed via simulations and real data set applications.
Borsa Istanbul as an Inflation Hedge: A Post-COVID Perspective
(Econjournals, 2025) Ozdurak, C.; Çipe, B.; Ertem, G.Y.; Bolgün, K.E.
This study delves into the intricate relationship between inflation and stock prices on Borsa Istanbul, with a particular focus on the turbulent post-COVID-19 era. While traditional assets like real estate have historically served as reliable inflation hedges, the emergence of Borsa Istanbul as a potential alternative warrants investigation, especially during the period 2019-2023. To assess the effectiveness of the Turkish stock market as an inflation hedge, we employ a rigorous econometric framework that extends beyond broad market indices to examine sector-specific responses. By adopting a Vector Autoregression (VAR) model, we capture the dynamic interplay between inflation and stock returns. Our analysis incorporates a comprehensive set of macroeconomic control variables spanning the period 2006Q1-2023Q4 and utilizes robust estimation techniques to account for potential structural breaks induced by the COVID-19 pandemic and unconventional economic policies. The primary objective of this study is to determine whether Borsa Istanbul stocks constitute an effective inflation hedge. In essence, our results suggest that the Turkish equity market has served as a safe haven for investors during inflationary periods. A deeper understanding of the relationship between inflation and equity markets is crucial for investors, policymakers, and financial market participants seeking to comprehend and manage inflation risks in emerging economies. In this context the study contributes to the existing literature by providing empirical evidence on the inflation hedging capabilities of Borsa Istanbul stocks, particularly in the context of recent economic and geopolitical upheavals. © 2025, Econjournals. All rights reserved.
Can Commercial Buildings Cope with Australian Bushfires? An IAQ Analysis
(Ubiquity Press Ltd, 2021) Brambilla, Arianna; Candido, Christhina; Sangiorgio, Marco filippo; Gocer, Ozgur; Gocer, Kenan
The Australian 2019/20 summer witnessed an extraordinary bushfire season characterised by unprecedented duration, geographical reach and impact. The aftermath of the bushfires includes increased health-related implications on people due to short and long exposure to poor air quality. The current advice from the Australian authorities in such events is to remain indoors, as it was assumed indoor air quality (IAQ) is healthy. This paper examined that assumption and presents the case study of an office building in Canberra subjected to the 2019/20 bushfires, responding to the need of understanding the ability of air-conditioning buildings to cope with such unprecedented and extreme weather events. Measured data for indoor concentration of CO2, PM10 and PM2.5 recorded a prolonged period of concerning levels, as well as extreme concentration peaks. This poses a significant risk to the occupants' health. The values showed peaks up to 12 times higher for PM10 and 24 times higher for PM2.5 than the recommended critical thresholds. The infiltration factor and protection performance analysis suggest that old filtering systems and low airtightness levels are not optimal in protecting the indoor environment from outdoor air pollutants.
Case Report: Physiological and Psychological Underpinnings of Muscle Dysmorphia Using EEG, GSR, and Eye-Tracking
(Frontiers Media SA, 2025) Cinaroglu, Metin; Ulker, Selami Varol; Yilmazer, Eda; Sayar, Goekben Hizli
Background Muscle dysmorphia (MD), a subtype of Body Dysmorphic Disorder (BDD), involves an obsessive preoccupation with perceived insufficient muscularity despite an objectively muscular physique. While its psychological features are well-documented, physiological and attentional underpinnings remain underexplored.Objective This exploratory, proof-of-concept case series examines the psychological, physiological, and attentional characteristics of individuals with varying experiences of MD using a multimodal approach combining electroencephalography (EEG), galvanic skin response (GSR), and eye-tracking technologies.Methods Three male participants were purposefully selected to represent distinct clinical profiles: one with active MD and steroid use, one in sustained remission from MD, and one with no MD history. Participants completed validated psychological scales (MDDI, BIDQ, STAI, RSES) and were exposed to personalized visual stimuli (past, current, and idealized body images). A triangulated recording protocol was used to capture EEG, GSR, and eye-tracking data during stimulus exposure.Results Participants with current and past MD showed elevated beta wave activity, increased skin conductance, and attentional biases toward muscular regions, corresponding with higher self-reported distress and anxiety. In contrast, the control participant exhibited stable physiological responses and emotionally neutral reactions. Triangulated data revealed coherent patterns across subjective and physiological domains, supporting the internal validity of the findings despite the small sample.Conclusion These findings illustrate the potential of multimodal assessment in identifying candidate psychophysiological markers of MD. While not generalizable, this case-series provides a valuable framework for future hypothesis-driven research and supports the need for gender-specific diagnostic and intervention strategies in muscle dysmorphia.
Causes of Intimate Partner Homicide: Gender Differences in Empathy, Psychopathy, and Perceived Social Support
(Kare Publishing, 2022) Topcu, A.L.; Görgülü, T.; Erden, G.
Objective: Intimate partner homicide (IPH) and attempted murder behaviors have increased in recent years. In addition, the causes of partner murder are affected by gender dynamics. This study aims to determine whether individuals who committed murder and attempted murder toward their partners differ in terms of empathy, psychopathy, and perceived social support and to determine the predictive variables of IPH toward their partners. Method: This study was carried out with a total of 123 participants (73 women and 50 men) from 10 different prisons. Demographic Information Form, Empathic Tendency Scale, Levenson Self-Report Psychopathy Scale, and Multidimensional Scale of Perceived Social Support were used. Results: A value of 82.19% of women and 60.97% of men were charged with killing their partners. Of these, 24% of women and 7% of men killed their partners by planning. The psychopathy scores of men (56.92±8.45) were found to be higher than women (52.73±8.98). The results of the logistic regression analysis indicate that the behaviors of women to kill and attempt to kill their partners are best predicted by physical violence from their partner, feelings of jealousy toward their partner, and perceived weak social support from a significant other and family. It was found that the best predictive variable for IPH in men was physical violence against their partners during their relationships. Conclusion: It has been evaluated that having insufficient social support and experiencing physical violence from their partners are associated with IPH among women. This result suggests that women use violence against their partners to protect themselves from violence. On the other hand, the physically violent behaviors of men toward their partners during their relationship are an important variable for IPH. © 2022 Yerkure Tanitim ve Yayincilik Hizmetleri A.S.. All rights reserved.
Changes in Anthocyanin Pigments, Trans-Resveratrol, and Colorimetric Characteristics of Fondillón Wine and Other “Monastrell” Wines During the Aging Period
(Springer Science and Business Media Deutschland GmbH, 2023) Uysal, R.S.; Issa-Issa, H.; Esther, E.; Carbonell-Barrachina, A.A.
The studied red wines, which are Fondillón, reserva, crianza, and young, are prepared from exclusive “Monastrell” grapes, and protected under the Alicante Denomination of Origin (Alicante, Spain). The objectives of the present study were (i) to show the effect of aging period on the amount of anthocyanin pigments, trans-resveratrol, and the colorimetric characteristics (color intensity, color density, and tonality) of Fondillón and other Monastrell wines (young, crianza, and reserva) which have different aging periods, and (ii) to propose a new traceability method for the determination of the Fondillón originality. Identification of anthocyanin compounds and determination of trans-resveratrol content were performed using LC–MS/MS. Correlation analysis was performed among anthocyanin compounds and color parameters. A sharp decrease in the anthocyanins content was observed in Fondillón wine. Besides, statistically significant changes were found in all colorimetric parameters between young and Fondillón samples. A significant change from red hue to brick red/yellow hue was observed between the colors of young and Fondillón wines, respectively. A significant decrease in the content of trans-resveratrol was also observed as a result of the aging period of these “Monastrell” wines. In this study, anthocyanin compounds of Fondillón wine were identified for the first time and their effects on the colorimetric parameters of the wine were revealed. Consequently, the authenticity of Fondillón wines can be determined by monitoring of anthocyanin compounds and trans-resveratrol. © 2023, The Author(s).
Cognitive Behavioral Therapy for Muscle Dysmorphia and Anabolic Steroid-Related Psychopathology: A Randomized Controlled Trial
(MDPI, 2025) Cinaroglu, Metin; Yilmazer, Eda; Ulker, Selami Varol; Sayar, Gokben Hizli
Background/Objectives: Muscle dysmorphia (MD), a subtype of body dysmorphic disorder, is prevalent among males who engage in the non-medical use of anabolic-androgenic steroids (AASs) and performance-enhancing drugs (PEDs). These individuals often experience severe psychopathology, including mood instability, compulsivity, and a distorted body image. Despite its clinical severity, no randomized controlled trials (RCTs) have evaluated structured psychological treatments in this subgroup. This study aimed to assess the efficacy of a manualized cognitive behavioral therapy (CBT) protocol in reducing MD symptoms and associated psychological distress among male steroid users. Results: Participants in the CBT group showed significant reductions in MD symptoms from the baseline to post-treatment (MDDI: p < 0.001, d = 1.12), with gains sustained at follow-up. Large effect sizes were also observed in secondary outcomes including depressive symptoms (PHQ-9: d = 0.98), psychological distress (K10: d = 0.93), disordered eating (EDE-Q: d = 0.74), and exercise addiction (EAI: d = 1.07). No significant changes were observed in the control group. Significant group x time interactions were found for all outcomes (all p < 0.01), indicating CBT's specific efficacy. Discussion: This study provides the first RCT evidence that CBT significantly reduces both core MD symptoms and steroid-related psychopathology in men engaged in AAS/PED misuse. Improvements extended to mood, body image perception, and compulsive exercise behaviors. These findings support CBT's transdiagnostic applicability in addressing both the cognitive-behavioral and affective dimensions of MD. Materials and Methods: In this parallel-group, open-label RCT, 59 male gym-goers with DSM-5-TR diagnoses of MD and a history of AAS/PED use were randomized to either a 12-week CBT intervention (n = 30) or a waitlist control group (n = 29). CBT sessions were delivered weekly online and targeted distorted muscularity beliefs, compulsive behaviors, and emotional dysregulation. Primary and secondary outcomes-Muscle Dysmorphic Disorder Inventory (MDDI), PHQ-9, K10, EDE-Q, EAI, and BIG-were assessed at the baseline, post-treatment, and 3-month follow-up. A repeated-measures ANOVA and paired t-tests were used to analyze time x group interactions. Conclusions: CBT offers an effective, scalable intervention for individuals with muscle dysmorphia complicated by anabolic steroid use. It promotes broad psychological improvement and may serve as a first-line treatment option in high-risk male fitness populations. Future studies should examine long-term outcomes and investigate implementation in diverse clinical and cultural contexts.
Comparative Efficacy of Brief Psychoanalytic Psychotherapy and Cognitive Behavioral Therapy for Generalized Anxiety Disorder: A Randomized Controlled Trial
(Multidisciplinary Digital Publishing Institute (MDPI), 2026) Çınaroğlu M.; Yılmazer E.; Ülker S.V.; Hızlı Sayar G.
Background: Cognitive behavioral therapy (CBT) is the most established psychological treatment for generalized anxiety disorder (GAD), yet many patients do not achieve full remission. Brief psychoanalytic psychotherapy represents a theoretically distinct alternative, but direct controlled comparisons remain limited. This study examined the short-term efficacy of brief psychoanalytic psychotherapy and CBT relative to a waitlist control in adults with GAD. Methods: In a three-arm randomized controlled trial, 60 adults with DSM-5-diagnosed GAD were allocated to brief psychoanalytic psychotherapy (12 weekly sessions), CBT (12 weekly sessions), or a waitlist control. Assessments were conducted at pre-treatment and post-treatment. The primary outcome was anxiety severity measured by the Beck Anxiety Inventory (BAI). Secondary outcomes included depressive symptoms (BDI-II), quality of life (WHOQOL-BREF), functional impairment (WHODAS 2.0), and therapeutic alliance (Working Alliance Inventory). Data were analyzed using mixed-design ANOVAs and effect size estimates. Results: Both active treatments produced significantly greater reductions in anxiety than the waitlist control, with large effect sizes. Mean BAI scores decreased by 14.5 points in the psychoanalytic group and 16.3 points in the CBT group, compared to minimal change in the waitlist condition. Similar patterns were observed for depressive symptoms, quality of life, and functional impairment, with both therapies outperforming waitlist controls on all secondary outcomes. No statistically significant differences were found between CBT and brief psychoanalytic psychotherapy on any outcome measure. Therapeutic alliance ratings were high and comparable across the two active treatments. Conclusions: Brief psychoanalytic psychotherapy and CBT were both effective short-term treatments for GAD and superior to no treatment, with no significant differences between the two modalities at post-treatment. These findings suggest that time-limited psychoanalytic psychotherapy may represent a promising short-term therapeutic option to CBT for GAD, expanding treatment options for patients and clinicians. © 2026 by the authors.
Comparison of Domino Transplantation with Two-Way Paired Exchange and Normal Transplantation: Acute Rejection, Surgical Complications, and 5-Year Survival Outcomes
(Springer, 2025) Huseynov, Amil; Cicek, Sevim Nuran Kuslu
Background Domino kidney paired donation and Two-Way Paired Exchange have emerged as vital strategies to expand the donor pool in renal transplantation, especially for patients facing ABO or HLA incompatibilities. Despite their potential benefits, concerns remain regarding immunological risks, infectious complications, and long-term graft survival. Methods In this retrospective cohort study conducted at Medicana Transplant Center, 980 adult kidney transplant recipients were categorized into three groups: Domino (n = 144), Two-Way Paired Exchange (n = 350), and Normal Transplant (n = 486). Baseline characteristics, acute rejection rates, and surgical or infectious complications were collected, alongside data on 1-year and 5-year patient and graft survival. Statistical analysis included Kaplan-Meier survival curves and Cox proportional hazards modeling for independent predictors of graft outcomes. Results The Domino group had the highest 1-year acute rejection rate (17.4%) compared to Two-Way Paired Exchange (4.3%) and Normal Transplant (3.7%), yet 1-year graft survival rates remained comparable (92%, 95%, and 96%, respectively; p = 0.271). Infectious complications were more frequent in the Domino group (25%) than in others (p < 0.01). Extended follow-up to 5 years indicated no statistically significant difference in overall graft or patient survival among the three groups (log-rank p = 0.197), despite a trend toward lower 5-year graft survival in the Domino group. Donor-specific antibodies and higher HLA mismatches independently predicted acute rejection. Conclusions Domino transplantation, while associated with higher immunologic challenges, achieves acceptable short-term and 5-year outcomes akin to Two-Way Paired Exchange and Normal Transplant. Careful immunosuppressive strategies, vigilant monitoring, and collaborative protocols are integral for optimizing long-term success in high-risk transplant scenarios.
Competitive Advantage and Clusters: What Can We Learn from Nine Turkish Clusters
(Boğaziçi University bjournal@boun.edu.tr, 2018) Mutlucan, N.Ç.
Many researchers have studied the ability of clusters to promote innovation, regional economic development, and national prosperity; however, these studies had been mostly conducted at the cluster level, not at the firm level. This study attempts to bring the cluster discourse back to the firm by answering the following research question: how do firms create and defend competitive advantages through clusters? The theoretical model presumes positive relationships between several constructs and firm performance, namely, business ties, support ties, entrepreneurial orientation and strategic learning capability. Furthermore, these relationships are supposed to be enhanced by the moderating effect of the cluster construct. The Partial Least Squares path model analysis of data from 160 surveyed firms located in nine Turkish clusters revealed that only entrepreneurial orientation and support ties contributed significantly and positively to firm performance. © 2018 The Trustees of Indiana University. All rights reserved.
Consolidating and Contesting Authoritarian Neoliberalism in Turkey: Towards a Framework
(Palgrave Macmillan, 2022) Borsuk, Imren; Dinc, Pinar; Kavak, Sinem; Sayan, Pinar
During the early years of the ruling Adalet ve Kalkinma Partisi (Justice and Development Party, AKP), Turkey was seen as a burgeoning democratic power propped up by economic prosperity in line with the reforms for European Union (EU) accession and International Monetary Fund (IMF) conditionality. However, 20 years later, it is considered an emblematic case of democratic backsliding in line with rising poverty and inequalities that have been amplified as a result of sweeping neoliberal reforms and authoritarian consolidation in the country. The recent literature has identified these concomitant and complementary modes of authoritarian governance and neoliberal policies in Turkey as 'authoritarian neoliberalism'. In this chapter, we discuss the dynamics of consolidation of authoritarian neoliberalism in Turkey as well as the acts of contention against it. Building mainly on the eight case studies presented in this volume, we put forward a framework that explains the consolidation of authoritarian neoliberalism in Turkey through the mechanisms of executive centralisation, autocratic legalism, cronyism, violence-fuelled rentier accumulation, criminalisation and stigmatisation, and contestations against authoritarian neoliberalism through strikes, protests, demonstrations, network building, litigation, everyday struggles, and armed acts of contention.
Current State and Future of Shipping and Logistics
(Elsevier Science Bv, 2013) Tuna, Okan; Duru, Okan
Desire and Absence in Rimini Protokoll's Conference of the Absent: A Lacanian Analysis of Audience Interviews
(John Wiley and Sons Ltd, 2026) Akıncı Ö.; Sümerkan H.H.
This paper explores the Conference of the Absent experience, a participatory theater piece produced by Rimini Protokoll, through a Lacanian psychoanalytic perspective. Drawing on semi-structured interviews with audience members who participated in the performance, it seeks to analyze the anxieties and resistances around performing, as well as how these experiences are retrospectively narrated and made sense of. Conference of the Absent is considered as a reconfiguration of the spectator-performer relation in a manner analogous to processes of subject formation in Lacanian psychoanalysis. The paper, thus, discusses how the performance destabilizes scopic mastery, repositions the voice as the central medium of subjectivation and situates the participants in a new system of meaning. Drawing from the audience interviews and analysis of the theatrical design, it is argued that the audience's engagement is less an act of personal agency than a pre-orchestrated response conditioned by the performance's dramaturgical design. This paper contributes to theater audience research by offering psychoanalytical theory as a methodological tool in understanding the workings of spectatorship in a participatory theater setting. © 2026 John Wiley & Sons Ltd.
Detection of Damaged Structures from Satellite Imagery Processed by Autoencoder with Boruta Feature Selection Method
(AVES, 2023) Muzoglu, Nedim; Adiguzel, Ertugrul; Akbacak, Enver; Karaslan, Melike Kaya
Many worldwide changing events, including meteorology, weather forecasting, disaster response, and environmental monitoring, are tracked by states or companies via satellite imagery. Early response to disasters is critical for human life. In these cases, artificial intelligence applications are also used to make rapid determinations about large geographical region. In this study, satellite images of flooded and undamaged structures in Hurricane Harvey were used. An autoencoder process has been applied to this dataset to reduce the noise in satellite imagery. AlexNet and VGG16 deep learning (DL) models are used to extract features from both datasets. The most effective features selected by the Boruta feature selection algorithm were classified with the support vector machine, and the highest classification accuracy of 99.35% was obtained. Since disasters involve the evaluation of very big datasets from large geographic areas, presenting the data with the smallest possible feature will facilitate the process. For this reason, by applying dimensionality reduction to the selected attributes, a 98.29% success was achieved in the classification with only 90 attributes. The proposed approach shows that DL and feature engineering are very effective methods to quickly respond to disaster areas using satellite imagery.

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