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Article Citation - WoS: 1Citation - Scopus: 1An Application of Spectral Theory of the Laplace Operator(Taylor & Francis Ltd, 2013) Guseinov, Gusein Sh.We describe the structure of arbitrary rapidly decreasing functions of the Laplace operator. Combining this with the spectral data of the periodic Laplace operator we develop a generalization of the classical Poisson summation formula.Article Reconfiguring Stoicism: Convergence of Self-Improvement and Masculinity on TikTok(Taylor & Francis Ltd, 2025) 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: 1Citation - Scopus: 1On the Eigenfunction Expansion of the Laplace-Beltrami Operator in Hyperbolic Space(Taylor & Francis Ltd, 2015) Guseinov, Gusein Sh.We describe the spectral projection of the Laplace-Beltrami operator in n-dimensional hyperbolic space by studying its resolvent as an analytic operator-valued function and applying the technique of contour integration. As a result an integral formula is established for the associated Legendre functionArticle Citation - WoS: 8Citation - Scopus: 9First-principles studies of Tin+1SiNn (n=1, 2, 3) MAX phase(Taylor & Francis Ltd, 2020) Surucu, Gokhan; Gullu, Hasan Huseyin; Candan, Abdullah; Yildiz, Bugra; Erkisi, AytacIn this study, the structural, electronic, mechanical, lattice dynamical and thermodynamic characteristics of ( 1, 2 and 3) phase compounds were investigated using the first principle calculations. These ternary nitride compounds were found to be stable and synthesisable, and the results on the stability nature of them were also evaluated for the possible and phases. -was found to be the most stable one among these new class of layered phases for which limited works are available in the literature. The band structures, that are essential for the electronic properties, were determined along with the partial density of states (PDOS) indicating the metallic behaviour of these compounds. The polycrystalline elastic moduli were calculated based on the single-crystal elastic constants and the mechanical stabilities were verified. Some basic physical parameters, such as bulk modulus, shear modulus, Young's modulus, Poisson's ratio, Debye temperature, and sound velocities, were also predicted. Furthermore, the anisotropic elastic properties were visualised in three dimensions (3D) for Young's modulus, linear compressibility, shear modulus and Poisson's ratio as well as with the calculation of the anisotropic factors. - phase showed the most isotropic characteristics with minimum deviations. These theoretical values were also used to identify the stiffness and ionic characteristics. The phonon dispersion curves and corresponding PDOS indicated that compounds were dynamically stable. Moreover, thermodynamic properties obtained from phonon dispersion curves were investigated in detail.Article Citation - WoS: 3Citation - Scopus: 4Predictive Rental Values Model for Low-Income Earners in Slums: the Case of Ijora, Nigeria(Taylor & Francis Ltd, 2023) Iroham, Chukwuemeka O.; Misra, Sanjay; Emebo, Onyeka C.; Okagbue, Hilary, IIt is well known most often that values of properties tend to hike at the effluxion of time. This has necessitated the adoption of predictive models in interpreting outcomes in the property market in the future. Earlier studies have been oblivious of such models' outcomes as it affects any focal group, particularly the vulnerable. This present study focuses on the low-income earners found in the slum. The Ijora community in Lagos was the highlight of this study, particularly Ijora Badia and Ijora Oloye, regarded as slums according to the UNDP report. The entire fifty-two (52) local agents in the Ijora community were surveyed in cross-sectional survey research that entailed the questionnaire's issuance. The nexus of data collection, pre-processing, data analysis, algorithm application, and model evaluation resulted in retrieving rental values within the years 2010 and 2019 on two predominant residential property types of self-contain and one-bedroom flats found within the community. Three selected algorithms, Artificial Neural Network (ANN), Support Vector Machine, and Logistic Regression, were essentially used as classifiers but trained to predict the continuous values. These algorithms were implemented through the use of Python's SciKit-learn Library and RapidMiner. The findings revealed that though all three models gave accurate predictions, Logistic Regression was the highest with low error values. It was recommended that Logistic Regression be applied but with much data set of property values of low-income earners over much more period. This study will contribute to the Sustainable development goals(SDG) 11(Sustainable cities and communities) of the United Nations to benefit developing countries, especially in sub-Saharan Africa.Review Citation - WoS: 18Citation - Scopus: 24A Literature Review on Mhe Selection Problem: Levels, Contexts, and Approaches(Taylor & Francis Ltd, 2015) Saputro, Thomy Eko; Masudin, Ilyas; Rouyendegh (Babek Erdebilli), Babak Daneshvar; Rouyendegh , Babak DaneshvarThis paper presents a review on selection problem of material handling equipment (MHE) and general equipment used in industry area. The issue on MHE is widely paid attention since MHE has contribution on material, good and product accomplishment. Few methods and softwares have been proposed and developed to select the most appropriate MHE for a complex selection problem. Today's high diverisity of MHE categories and types influence the generation of many possible choices which leads to the complexity. In this paper, a further discussion in terms of MHE and equipment including three major points namely level of selection, the context of selection problem and the approaches are served to highlight the complex MHE selection according to the number of possible choices provided, to analyse the consideration for the problem context, and to reveal the superior method for complex MHE selection. Forty-two papers collected from the past study are presented asscociating each point of the discussion.Article Mixed Method Investigation of the Major Challenges to the Sustainable Deployment of the Electric Vehicle Charging Station Network in Türkiye(Taylor & Francis Ltd, 2025) 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.Review Citation - WoS: 10Citation - Scopus: 10Latest Developments in Engineered Skeletal Muscle Tissues for Drug Discovery and Development(Taylor & Francis Ltd, 2023) Ostrovidov, Serge; Ramalingam, Murugan; Bae, Hojae; Orive, Gorka; Fujie, Toshinori; Shi, Xuetao; Kaji, HirokazuIntroductionWith the advances in skeletal muscle tissue engineering, new platforms have arisen with important applications in biology studies, disease modeling, and drug testing. Current developments highlight the quest for engineering skeletal muscle tissues with higher complexity . These new human skeletal muscle tissue models will be powerful tools for drug discovery and development and disease modeling.Areas coveredThe authors review the latest advances in in vitro models of engineered skeletal muscle tissues used for testing drugs with a focus on the use of four main cell culture techniques: Cell cultures in well plates, in microfluidics, in organoids, and in bioprinted constructs. Additional information is provided on the satellite cell niche.Expert opinionIn recent years, more sophisticated in vitro models of skeletal muscle tissues have been fabricated. Important developments have been made in stem cell research and in the engineering of human skeletal muscle tissue. Some platforms have already started to be used for drug testing, notably those based on the parameters of hypertrophy/atrophy and the contractibility of myotubes. More developments are expected through the use of multicellular types and multi-materials as matrices . The validation and use of these models in drug testing should now increase.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.Article Citation - WoS: 18Citation - Scopus: 18A New Outlier Detection Method Based on Convex Optimization: Application To Diagnosis of Parkinson's Disease(Taylor & Francis Ltd, 2021) Taylan, Pakize; Yerlikaya-Ozkurt, Fatma; Bilgic Ucak, Burcu; Weber, Gerhard-WilhelmNeuroscience is a combination of different scientific disciplines which investigate the nervous system for understanding of the biological basis. Recently, applications to the diagnosis of neurodegenerative diseases like Parkinson's disease have become very promising by considering different statistical regression models. However, well-known statistical regression models may give misleading results for the diagnosis of the neurodegenerative diseases when experimental data contain outlier observations that lie an abnormal distance from the other observation. The main achievements of this study consist of a novel mathematics-supported approach beside statistical regression models to identify and treat the outlier observations without direct elimination for a great and emerging challenge in humankind, such as neurodegenerative diseases. By this approach, a new method named as CMTMSOM is proposed with the contributions of the powerful convex and continuous optimization techniques referred to as conic quadratic programing. This method, based on the mean-shift outlier regression model, is developed by combining robustness of M-estimation and stability of Tikhonov regularization. We apply our method and other parametric models on Parkinson telemonitoring dataset which is a real-world dataset in Neuroscience. Then, we compare these methods by using well-known method-free performance measures. The results indicate that the CMTMSOM method performs better than current parametric models.
