WoS
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Unpacking Women’s Worries about Leadership: The Interplay of Perceived Sexism and Organizational Support(SAGE Publications Inc, 2026) Metin Camgoz, Selin; Yilmaz, Berru Ayse; Metin-Orta, IremBackground Despite significant advancements in workplace equality, gender-based discrimination continues to hinder women's leadership aspirations and potential. In many non-Western societies, cultural and institutional structures intensify the influence of sexism on women's professional experiences.Objective This study explores how benevolent and hostile sexism, together with perceived organizational support, affect female employees' worries about leadership roles. It also examines whether organizational support moderates the relationship between sexism and leadership-related anxieties.Methods Data were collected from 201 full-time female employees working in various occupations in Türkiye. An online survey included the Worries about Leadership scale, the Perceived Organizational Support Scale, and the Perceived/Experienced Sexism Scale. Hypotheses were tested using moderation analysis via the PROCESS macro.Results Benevolent sexism and perceived organizational support were both negatively associated with worries about leadership. Perceived organizational support moderated the effect of benevolent sexism on leadership worries, such that higher support reduced its impact, demonstrating a crossover effect. Specifically, benevolent sexism was linked to fewer leadership worries when organizational support was low but associated with more worries when support was high. However, hostile sexism showed no main or interaction effect with POS on WAL.Conclusion This study highlights the complex role of benevolent sexism in shaping women's leadership concerns, showing both its potentially protective and harmful effects. It also emphasizes the need for culturally sensitive approaches that go beyond generic organizational support to actively challenge subtle sexism and promote gender-inclusive leadership readiness in non-Western contexts.Article The Prognostic Impact of 18F-FDG PET SUVmax in Patients with Non-Small Cell Lung Cancer(Bayrakol Medical Publisher, 2026) Gulcek, Ilham; Agar, Mehmet; Kalkan, Muhammed; Celik, Muhammet Reha; Ulutas, HakkiAim: The maximum standardized uptake value (SUVmax) of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) enhances clinical prediction in non-small cell lung cancers (NSCLC). This study aimed to investigate whether SUVmax could serve as a prognostic factor and improve clinical prognostication. Methods: This retrospective study included 86 patients with NSCLC who underwent surgical resection. Using receiver operating characteristic (ROC) analysis, the SUVmax cut-off value was 12.3. Patients with SUVmax values below 12.3 were classified as Group A, while those with values above 12.3 were designated as Group B. Survival analyses were performed using the Kaplan-Meier method. Overall survival was defined as the time from diagnosis to death. Confidence intervals were reported at 95%, and a p-value of <0.05 was considered statistically significant. The variables analyzed for survival included gender, age, surgical approach, histopathological subtype of lung cancer, cancer stage, T score, and N score. Results: Survival analyses revealed statistically significant associations between SUVmax and age (p=0.043), gender (p=0.060), surgical approach (p=0.037), and histopathological subtype (p=0.026). Due to insufficient sample size within subgroups, separate p-values were calculated for each stage, T score, and N score. Based on the obtained p-values, no statistically significant correlation was found between SUVmax and overall survival across different stages, T scores, or N scores, except for stage 1A and T1b. Conclusion: SUVmax contributes to determining appropriate diagnostic and treatment protocols and aids in predicting the prognosis of the disease.Article The Objects and Effects of the Restrictions by Object Under Art. 101(1) TFEU: Has the ECJ Solved the Riddle(Springer Heidelberg, 2026) Korkmaz Goka, EkinThe concept of by object infringements under Art. 101(1) of the TFEU has been a subject of ongoing controversy. Central to this debate are two primary issues: the interpretation of the term object and whether the effects or non-agreement elements in general should be considered when determining it. Should the latter question be answered affirmatively, further complications arise, particularly regarding the scope of the analysis in relation to the effects analysis and the allocation of the evidentiary burden between the parties. EU case law has significantly contributed to this debate, both in support and contradiction. The ECJ has, albeit implicitly, developed a system which seeks to strike a balance between competing interests while considering economic realities. However, the use of ambiguous terminology, inconsistencies in judicial rulings, and a lack of sufficiently clear explanations in certain cases have hindered the literature and national authorities from fully understanding the underlying system. This study aims to address this gap in the literature by providing a comprehensive legal analysis of the concept of by object infringements under Art. 101(1), in light of the framework established by the ECJ. The objective is to contribute to greater legal certainty in this area.Article Citation - WoS: 1The Evaluation of System Reliability Under Dependent Shock Magnitudes(Springer, 2026) Eryilmaz, SerkanThis paper studies shock models by assuming a certain kind of dependence among shock magnitudes. In particular, discrete time extreme and run shock models are investigated when the shock magnitudes follow discrete autoregressive process of order 1. Exact expressions are obtained for the reliability functions and mean time to failure values under both models. The method for deriving the reliability characteristics is based on the use of probability generating functions. Numerical results are presented when the shocks arrive according to a Binomial process.Article Citation - WoS: 30Citation - Scopus: 40Software Code Smell Prediction Model Using Shannon, Renyi and Tsallis Entropies(MDPI, 2018) Blazauskas, Tomas; Gupta, Aakanshi; Misra, Sanjay; Suri, Bharti; Kumar, Vijay; Damasevicius, RobertasThe current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Renyi and Tsallis entropy). By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE)). The values of model performance statistics (R-2, adjusted R-2, Mean Square Error (MSE) and standard error) also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.Article Simulation-Based Optimization of HVAC Systems in Aging Educational Facilities: Addressing IAQ Challenges Through Retrofitting(MDPI, 2026) Saleh, Yousif Abed Saleh; Turhan, Cihan; Turhan, BurcuIndoor air quality (IAQ) in educational buildings plays a critical role in the health, cognitive performance, and well-being of occupants. Aging university facilities often rely on outdated ventilation systems that are not designed to meet current demands or respond to dynamic occupancy levels. This study investigates the performance and feasibility of various advanced ventilation strategies in comparison to an existing balanced mechanical ventilation (BMV) system in a university classroom accommodating 100 students. Using a Dynamic Building Energy Simulation Program, simulations were conducted to evaluate IAQ (using CO2 levels), energy consumption, and thermal comfort under three retrofitting scenarios: BMV, demand-controlled ventilation (DCV), and hybrid ventilation combining natural and mechanical airflow. The simulations indicate that DCV cuts annual HVAC energy use by 33% relative to the baseline, while the hybrid strategy achieves the greatest reduction of 42% and maintains CO2 levels and thermal comfort within recommended limits. Although hybrid systems provide seasonal advantages, their complexity may limit applicability. In addition to technical analysis, this study also explores the financial and tax-related challenges associated with retrofitting ventilation systems in university buildings. Investment payback periods, operational costs, and potential tax incentives are discussed to evaluate economic viability. Overall, the endorse hybrid ventilation as the most cost-effective strategy where mixed-mode control is feasible, and DCV as a practical alternative for buildings unable to employ natural ventilation.Article Self-Efficacy as the Saviour: Defending Psychological Well-Being against the Destructive Power of Social Undermining(Inderscience Enterprises Ltd, 2026) Tosun, Burcu; Basim, Hamdullah Nejat; Kibaroglu, Gamze GunerEmployee psychological well-being is crucial for fostering a positive work environment and ensuring organisational success. Social undermining, which disrupts workplace relationships, often leads to stress, anxiety, and burnout. However, self-efficacy - the belief in one's ability to successfully perform tasks - can help mitigate these adverse effects. This study investigates the detrimental impact of social undermining on employees' psychological well-being and examines the protective role of self-efficacy. Data were collected from 582 employees in the fast-moving consumer goods sector. The findings underscore the importance of prioritising psychological well-being in the workplace and reveal how self-efficacy can act as a buffer against the harmful effects of social undermining. By exploring the interplay between social undermining, self-efficacy, and psychological well-being, this study provides valuable insights into their influence on employee outcomes. Furthermore, the research highlights strategies for minimising the negative impact of undermining behaviours by co-workers and supervisors, thereby fostering a healthier work environment.Article Citation - WoS: 20Citation - Scopus: 25Quantitative Quality Evaluation of Software Products by Considering Summary and Comments Entropy of a Reported Bug(MDPI, 2019) Misra, Sanjay; Kumari, Madhu; Misra, Ananya; Damasevicius, Robertas; Fernandez Sanz, Luis; Sanz, Luis Fernandez; Singh, V. B.A software bug is characterized by its attributes. Various prediction models have been developed using these attributes to enhance the quality of software products. The reporting of bugs leads to high irregular patterns. The repository size is also increasing with enormous rate, resulting in uncertainty and irregularities. These uncertainty and irregularities are termed as veracity in the context of big data. In order to quantify these irregular and uncertain patterns, the authors have appliedentropy-based measures of the terms reported in the summary and the comments submitted by the users. Both uncertainties and irregular patterns have been taken care of byentropy-based measures. In this paper, the authors considered that the bug fixing process does not only depend upon the calendar time, testing effort and testing coverage, but it also depends on the bug summary description and comments. The paper proposed bug dependency-based mathematical models by considering the summary description of bugs and comments submitted by users in terms of the entropy-based measures. The models were validated on different Eclipse project products. The models proposed in the literature have different types of growth curves. The models mainly follow exponential, S-shaped or mixtures of both types of curves. In this paper, the proposed models were compared with the modelsfollowingexponential, S-shaped and mixtures of both types of curves.Article Prognostic Value of the C-Reactive Protein-Albumin-Lymphocyte (CALLY) Index for 1-Year Mortality After Transcatheter Aortic Valve Implantation(MDPI, 2026) Guney, Murat Can; Suygun, Hakan; Turinay Ertop, Zeynep Seyma; Polat, Melike; Bozkurt, Engin; Ayhan, Huseyin; Keles, TelatObjectives: Systemic inflammation, malnutrition, and immune dysregulation have emerged as important determinants of long-term outcomes after transcatheter aortic valve implantation (TAVI). The C-reactive protein-albumin-lymphocyte (CALLY) index is a novel immunonutritional biomarker that integrates these pathophysiological domains; however, its prognostic value in TAVI patients has not yet been investigated. This study aimed to evaluate the association between the CALLY index and 1-year mortality after TAVI. Methods: This retrospective observational study included 532 consecutive patients who underwent TAVI at a tertiary-care center between 2014 and 2023. Baseline laboratory parameters were obtained before the procedure, and the CALLY index was calculated as (albumin & times; lymphocyte count)/(C-reactive protein & times; 10). The primary endpoint was 1-year mortality. Receiver operating characteristic (ROC) curve analysis was performed to assess the discriminative ability of the CALLY index and conventional surgical risk scores. Multivariable regression analyses were used to identify independent predictors of mortality. Results: During the 1-year follow-up period, 85 patients (15.9%) died. Patients who died had significantly lower baseline CALLY index values compared to survivors (p < 0.001). The CALLY index demonstrated good discriminative performance for 1-year mortality (AUC: 0.797), outperforming EuroSCORE II (AUC: 0.705) and the Society of Thoracic Surgeons (STS) score (AUC: 0.619). A CALLY cut-off value of 0.45, derived using Youden's index, was associated with a more than threefold increased risk of mortality. In multivariable analysis, the CALLY index remained independently associated with 1-year mortality, along with EuroSCORE II and more than mild mitral regurgitation. Conclusions: The CALLY index is a strong and independent predictor of 1-year mortality after TAVI and provides incremental prognostic value beyond conventional surgical risk scores. Given its simplicity and reliance on routinely available laboratory parameters, the CALLY index may serve as a practical tool for long-term risk stratification in patients undergoing TAVI.Article Post-Hoc Mixture Models to eBLUPs from Linear Mixed-Effects Models: A Tractable Approach for Clustering Irregular Longitudinal Data(Taylor & Francis Ltd, 2026) Balakrishnan, N.; Hossain, Md JobayerClustering longitudinal data with irregular and sparse measurement schedules has become important in analyzing many medical data and associated decision-making. These datasets often involve observation times that vary across individuals, making trajectory-based analysis essential for uncovering meaningful patterns. Mixture-based linear mixed-effects models, such as heterogeneous linear mixed-effects models and growth mixture modeling, are commonly used for this purpose. While theoretically powerful, these methods often suffer from convergence issues and computational inefficiency in large-scale applications. This study introduces a computationally efficient two-step approach that applies a post-hoc mixture model to empirical Best Linear Unbiased Predictors (eBLUPs), derived from a fitted (piecewise) linear mixed-effects model under homogeneity assumptions. The method is then demonstrated with real clinical data, in which it effectively identified distinct growth trajectories in early childhood data involving 3,365 children across 51,711 clinic visits. The optimal number of clusters is then selected using the BIC, likelihood ratio tests, and model-based validation, achieving the best balance of model fit, classification stability, and interpretability. Simulation studies have shown that eBLUPs preserve individual-level heterogeneity and that post-hoc mixture modeling outperforms HLME across varying separability. Overall, this approach offers a robust, interpretable, and scalable alternative to traditional clustering methods for irregular longitudinal data.