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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Comparative in Silico Investigation of Costunolide and Dehydrocostus Lactone as Potential PTEN Modulators: DFT, Molecular Docking and Molecular Dynamics Approaches(Taylor & Francis Ltd, 2026-05-05) Yonar, DilekThe phosphatase and tensin homolog (PTEN) is an important tumour suppressor that inhibits PI3 K/AKT/mTOR signalling pathway, which is generally dysregulated in malignancies. This study examined the potential regulatory effects of costunolide (COS) and dehydrocostus lactone (DEH) on PTEN through density functional theory (DFT), molecular docking, molecular dynamics (MD) simulations, and in silico pharmacokinetic analyses. DFT calculations revealed that both compounds possess strong electrophilic character, with COS showing higher chemical reactivity and DEH displaying greater stability. Molecular docking results indicated that both ligands bind favourably to PTEN active site. DEH has slightly stronger binding affinity (-7.6 kcal/mol) than COS (-7.3 kcal/mol). MD simulations demonstrated that PTEN-DEH complex maintained higher structural stability, compactness, and persistent hydrogen bonding compared to PTEN-COS complex, which exhibited greater fluctuations. However, MM/GBSA analysis revealed that COS had a better binding free energy (Delta G(bind) = -11.26 kcal/mol), suggesting a better balance between intermolecular interactions and solvation effects. ADME predictions confirmed favourable drug-likeness profiles and high gastrointestinal absorption for both ligands, adhering to Lipinski's rule of five. These findings suggest that both ligands are promising PTEN modulators; DEH exhibits superior structural stability, while COS displays more favourable binding energetics, providing a theoretical basis for further experimental validation in anticancer therapy.Article Citation - Scopus: 1Robust Inference for an Interval-Monitored Step-Stress Experiment under Proportional Hazards(Taylor & Francis Ltd, 2026-04-08) Balakrishnan, Narayanaswamy; Jaenada, María; Pardo, LeandroAccelerated life tests (ALTs) are widely used in reliability analysis to infer on product lifetimes under normal operating conditions from data collected at higher stress levels. In step-stress ALTs, the stress is increased at predetermined times and kept constant between changes, accelerating failures and reducing test duration and cost. While many ALT studies assume a specific lifetime distribution, some applications require a more flexible formulation satisfying the proportional hazards (PH) assumption, under which stress acts multiplicatively on the hazard rate. In this paper, we study step-stress ALTs under a PH framework with linear and quadratic baseline hazard functions. We focus on settings where continuous monitoring is impractical and failures are observed only at scheduled inspections, yielding interval-censored count data. To achieve robustness and efficiency in this context, we introduce a family of minimum density power divergence estimators (MDPDEs) for model parameters, device reliability, and lifetime measures such as the mean lifetime and distributional quantiles. We derive the corresponding asymptotic distributions and construct approximate confidence intervals. Monte Carlo simulations assess the estimators' efficiency and robustness, and real-data examples illustrate the practical value of the proposed model and inferential methods.Article Post-Hoc Mixture Models to eBLUPs from Linear Mixed-Effects Models: A Tractable Approach for Clustering Irregular Longitudinal Data(Taylor & Francis Ltd, 2026-03-13) 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.Article Distance-Based Estimation Under Progressive Type-I Interval Censoring(Taylor & Francis Ltd, 2026-01-12) Balakrishnan, N.; Castilla, E.Monte Carlo simulation is used to demonstrate improved estimation performance of proposed distance-type estimators for lifetime models under progressive Type-I interval censoring. We propose novel distance-based estimators for lifetime models under progressive Type-I interval censoring. These estimators minimize the discrepancy between observed and model-based conditional failure probabilities using either quadratic or Mahalanobis distances, providing natural alternatives to maximum likelihood estimators (MLEs). Through extensive Monte Carlo simulations, we demonstrate that the Mahalanobis estimator outperforms MLE, particularly under heavy censoring or sparse data. The quadratic estimator also yields competitive results, especially under model misspecification. Two real data examples illustrate the practical advantages of the proposed approach.Article Shanghai's High-Rise Buildings: Exploring Space Efficiency, Structural Systems, Forms, Materials and Core Designs(Taylor & Francis Ltd, 2026-01-22) Aktas, Kurt Orkun; Aslantamer, Ozlem Nur; Aktas, Gozen Guner; Ilgin, Huseyin EmreThis study examines the architectural and structural design considerations influencing space efficiency in Shanghai's high-rise buildings. Understanding space efficiency is significant because it directly affects land-use intensity, economic returns, and sustainability outcomes. The objective of this study is to quantify space efficiency ratios by analyzing the relationships between core types, function, form, and structural systems, and assess temporal and comparative benchmarks for Shanghai within the global context. The novelty lies in its combined focus on architectural and structural determinants of space efficiency, supported by data on 43 high-rise buildings in Shanghai. Methodologically, this study relies on quantitative analysis of Net Floor Area (NFA), Gross Floor Area (GFA), and core ratios, supplemented with comparative evaluation of building forms, materials, and structural systems. The key findings reveal: (1) average space efficiency at 75% with core-to-GFA ratios of 23%, varying between 52-93% and 5-33% respectively; (2) the dominance of prismatic forms supported by composite outriggered frame systems; (3) a decline in efficiency with increasing building height due to larger service cores. Practically, this research highlights opportunities for stakeholders - including architects, engineers, and policymakers - to adopt lightweight materials, prefabrication techniques, and smart building systems that improve space efficiency in future high-rise developments.Article Mixed Method Investigation of the Major Challenges to the Sustainable Deployment of the Electric Vehicle Charging Station Network in Türkiye(Taylor & Francis Ltd, 2026-01-05) Erol, Ismail; Oztel, Ahmet; Peker, Iskender; Ar, Ilker Murat; Benli, Tolga; Turan, IsmetCharging the increasing number of electric vehicles (EVs) in use requires the deployment of EV charging station networks (EVCSN). However, there are various challenges to deploying EVCSN in a sustainable manner. T & uuml;rkiye, a developing country, should also build a robust EVCSN to encourage future adoption of EVs as the country's market for EVs has been rapidly growing. The literature review concludes that no previous study has systematically explored challenges to the sustainable deployment of EVCSN. The goal of this study is, therefore, twofold: first, it identifies those challenges through the lenses of commonly used theories. Second, it explores them using a multi-criteria decision-making (MCDM) framework that incorporates a rough-derived interval-valued neutrosophic set (R-IVN)-based ISM into MICMAC. By deriving interval neutrosophic information from single-valued expert inputs using rough number operators, the proposed approach more accurately captures epistemic uncertainty and variability in expert judgments compared to conventional interval-based models. The method is further validated through a novel Dice-S & oslash;rensen similarity index-based simulation approach. The findings of this study suggest that developing government policies and regulations and addressing the existence of vertically integrated companies are the critical challenges with higher driving powers. These findings provide key responsibilities for stakeholders, including urban municipalities, in developing guidelines for EVCSN deployment.Article Reconfiguring Stoicism: Convergence of Self-Improvement and Masculinity on TikTok(Taylor & Francis Ltd, 2025-12-02) Agaoglu, ErhanThis research examines the multimodal representations of Stoic content within TikTok. The research aimed to explore the multifaceted structure of an emerging digital philosophy discourse and its implications for contemporary socio-cultural dynamics. It explores a fragmented version of Stoicism, focussing on the affordances of algorithm-driven platforms and modularity principles. For multimodal discourse analysis, 20 highly viewed (>300,000) videos under the hashtags of #stoic and #stoicism are selected through purposeful sampling. It identifies the emergence of a fragmented Stoicism, built upon platform affordances and audio-visual modularity. Emerging themes include self-improvement, being dangerous and traditional masculinity remarking a divergence from popular and classical interpretations of Stoicism. Through these key themes, construction of an arbitrary link between hegemonic masculinity, glorified individualism and Stoicism is explored. Employing elements of aggression, self-isolation and self-improvement, TikTok content creates a novel discourse of Stoicism which is elusive, abstract, and reliant on visually driven narratives.Article Citation - WoS: 3Citation - Scopus: 3Impact of Water Consumption on Structural Members in RC Frames Using Multi-Objective Metaheuristics Algorithm(Taylor & Francis Ltd, 2025-12-15) Nader Negarestani, Mohammad; Fatehi-Nobarian, Bahador; Alizadeh Tabrizi, SinaThe construction industry has a significant global water footprint because buildings incorporate large quantities of embedded materials, such as concrete and steel, whose production consumes substantial amounts of water throughout their life cycle. The grey wolf optimizer (GWO) is particularly suitable for this problem because it is a population-based metaheuristic with strong exploration and exploitation balance, which makes it effective in navigating large discrete search spaces such as structural design variables. GWO has demonstrated robustness in multi-objective problems by efficiently approximating Pareto fronts and avoiding local optima. A numerical structural analysis and design model was developed via an application programming interface. This study is indeed the first optimization of the weight of reinforced concrete (RC) structural elements considering virtual water, with the given structural specifications and using the proposed multi-objective metaheuristic methodology. Results showed the optimal structural weight to be 266 tons, with virtual water usage reaching approximately 253 m3. These findings provide actionable insights for sustainable structural design, guiding material selection and early-stage decision-making to minimize virtual water consumption in RC buildings. This study addresses the research gap by introducing virtual water, alongside structural weight, as a novel objective function within multi-objective metaheuristic optimization of RC frames.Article A Coupled Modelling and Simulation Approach to Electromagnetic Sheet Metal Forming(Taylor & Francis Ltd, 2025-08-13) Aslan, Ozgur; Kabakci, Gamze Cakir; Sait, Ferit; Camalan, Caner; Baranoglu, Besim; Bayraktar, Emin; Cakir Kabakci, GamzeThis study presents a coupled numerical and experimental investigation of electromagnetic forming (EMF) for aluminium sheets. A custom simulation framework is developed in ABAQUS/Standard using user-defined material (UMAT) and load (DLOAD) subroutines. The magnetic pressure exerted on the workpiece is computed through a finite difference-based solution of Maxwell's equations and applied to the mechanical solver. The mechanical response of the material is modelled using a strain-rate-sensitive plasticity law calibrated for aluminium 7075-O. Experimental forming trials are performed using a custom-built EMF setup, and the results are compared with numerical predictions to validate the model. The comparison shows strong agreement in deformation profiles, confirming the predictive capability of the proposed simulation strategy. This work offers a reliable computational tool for optimising EMF processes and provides insights into material behaviour under high strain rate electromagnetic loading.Article Citation - WoS: 1Citation - Scopus: 1Enhancing Machining Efficiency and Sustainability of Ti-6Al-4V Through Minimum Quantity Lubrication With Ester-Based Oils(Taylor & Francis Ltd, 2025-07-24) Namlu, Ramazan Hakki; Kavut, Kuebra; Tom, Hanife GulenTi-6Al-4 V is known as difficult-to-cut due to its low thermal conductivity and high chemical reactivity. While cutting fluids aid lubrication and reduce friction, Conventional Cutting Fluids (CCF) have high consumption, limited efficiency gains and negative environmental and health effects. Therefore, there is an ongoing search for more sustainable alternatives to CCF that do not adversely affect machining performance. Minimum Quantity Lubrication (MQL), which delivers compressed air - oil aerosol, has emerged as a promising solution by drastically reducing fluid use and associated risks. Selecting the right MQL fluid is key to optimising machining performance. This study evaluates MQL fluids based on polyol and polymeric esters for Ti-6Al-4 V machining and compares their performance with CCF. Cutting forces, surface roughness and topography are examined. Results show that MQL reduces cutting forces up to 21.7% and surface roughness up to 57.6% compared to CCF, with more uniform surface topography. Among MQL oils, polymeric esters perform better than polyol esters, with a reduction in cutting force up to 14.6% and surface roughness up to 47.7%. High viscosity indexed polymeric esters showed the best overall performance due to their thermal stability. Moreover, according to the sustainability assessment analysis polymeric esters were identified as the most sustainable option.