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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Portfolio Optimization with Semi-Tsallis Entropy: Managing Flexible Downside Uncertainty in Uncertain Random Environments(Elsevier, 2026) Ahmadzade, Hamed; Li, Qiqi; Gao, Jinwu; Celik, Esref Ugur; Sheng, YuhongThis paper introduces semi-Tsallis entropy as a novel downside risk measure for uncertain random variables within the framework of chance theory. By integrating the parametric flexibility of Tsallis entropy with the asymmetric focus of semi-entropy, we develop a comprehensive framework that captures only unfavorable uncertainties while preserving the tuning capability of the deformation parameter q. We establish fundamental mathematical properties of semi-Tsallis entropy, including monotonicity and transformation rules, and derive closed-form expressions via inverse uncertainty distributions. A key theoretical contribution is the representation of partial semi-Tsallis entropy as an expectation, which enables efficient Monte Carlo simulation methods for practical implementation in complex optimization scenarios. The proposed measure addresses a critical gap in the literature: existing downside risk measures for uncertain random variables lack the parametric flexibility offered by Tsallis entropy formulations. Our framework fills this gap by providing a mathematically rigorous approach that combines the asymmetric focus of downside risk measurement with the adaptability of Tsallis entropy. The deformation parameter q facilitates custom-tailored risk assessment aligned with specific investor preferences and evolving market conditions, while the semi-entropy structure ensures concentrated measurement of unfavorable uncertainties. We formulate and solve portfolio optimization problems that integrate semi-Tsallis entropy as a downside risk constraint in uncertain random environments. The framework offers portfolio managers a flexible tool for tailoring risk assessment to hybrid markets characterized by both random fluctuations and epistemic uncertainty, where conventional symmetric measures often yield suboptimal risk management outcomes. The methodological contributions presented here establish a foundation for further advances in downside risk management and entropy-based optimization under uncertainty.Article Advances in Stabilizing Lipid-Based Nanoparticles: The Central Role of Lyophilization(Elsevier, 2026) Gallego, Idoia; Pedraz, José Luis; Bautista-Lopez, Irene; Enriquez-Rodriguez, Lucia; Maldonado, Iván; Lafuente-Merchan, Markel; Ramalingam, MuruganLipid-based nanoparticles (L-bNPs) have become a key platform in nanomedicine, enabling advances in drug delivery, gene therapy, and vaccine development. However, their widespread clinical application remains limited by their poor long-term stability, especially when stored in aqueous media. This review provides a comprehensive overview of long-term storage strategies for L-bNPs, with a particular focus on lyophilization (freeze-drying), which has emerged as the most widely adopted and effective stabilization method in the biopharmaceutical industry. The review begins with a classification of lipid-based nanoparticles and their medical applications, followed by an analysis of key storage challenges and a detailed exploration of freeze-drying processes, including critical parameters such as cryoprotectant selection, vial type, and the lipid composition of the formulation. Additionally, novel approaches such as spin freeze-drying are discussed for their potential to optimize solvent distribution and product morphology. Other long-term storage methods-including cryopreservation and atomization-based drying techniques such as spray-drying and supercritical fluid drying (SCFD)- are also examined for their potential benefits. Spray congealing, though still under development for L-bNPs, is highlighted for its promising performance in related lipid-based systems. While lyophilization remains the gold standard, the choice of method must be tailored to the physicochemical properties of the L-bNPs and their intended therapeutic use. Future perspectives highlight the need for more standardized protocols and advanced analytical tools to ensure stability and effectiveness across storage and transport conditions.Article Citation - Scopus: 1Machine Learning and Scenario-Based Forecasting of Türkiye’s Renewable Energy Transition toward Net-Zero 2053(Elsevier, 2026) Sutcu, Muhammed; Yildiz, Baris; Sahin, Nurettin; Almomany, Abedalmuhdi; Gulbahar, Ibrahim TumayThe issue of global warming has been identified as one of the most critical challenges of the 21st century, with the consumption of fossil fuels being identified as a major contributor to greenhouse gas emissions. In response to these challenges, countries worldwide are expediting their transition towards renewable energy sources to meet international climate commitments, such as the Paris Agreement, and to achieve long-term sustainability goals. Türkiye has established a target to achieve net-zero emissions by 2053. This objective is consistent with both the nation's domestic energy strategy and its international commitments. Nevertheless, the transition from fossil fuels to renewable energy sources is impeded by geographical, economic, and technological constraints. The present study aims to assess the capacity and efficiency of renewable energy in Türkiye with environmental protocols and future electricity demand projections. Electricity generation, transmission data, and national energy plans are used to identify future electricity generation and capacity trends. In the context of this study, a range of machine learning models is executed across diverse scenarios, yielding a series of outcomes. Consequently, the repercussions of regulatory measures and financial investments were examined, and prospective inferences were derived. The findings underscore the pivotal role of scenario-based modeling in formulating sustainable energy policies and directing investment decisions within the context of climate change mitigation.Article Catalyst-Free Synthesis of Thiourea-Linked Dumbbell-Shaped POSS for Ultrasensitive Determination of Prilocaine in Human Blood With Computational Insights(Elsevier, 2026) Bilge, Selva; Bayraktar, Ece Nur; Erkmen, Cem; Balci, Burcu; Abofoul, Anas; Ozkut, Merve Icli; Cihaner, AtillaAlthough various electrochemical sensors have been reported for the determination of local anesthetic drugs, most existing platforms suffer from limited sensitivity, insufficient surface stability, or inadequate electron-transfer efficiency, particularly when applied to complex biological matrices. Moreover, the potential of hybrid polyhedral oligomeric silsesquioxane (POSS)-based nanostructures combined with metal oxide nano-particles for improving electroanalytical performance has not yet been thoroughly explored. In this study, a high-sensitivity electrochemical nanosensor was developed for the determination of prilocaine (PC), an amide-type local anesthetic, using a glassy carbon (GC) electrode modified with POSS-titanium dioxide (TiO2) nano-particles (Nps). The combination of modifications provided a unique electrode surface by combining the high stability of POSS with the strong adsorption properties of TiO2 Nps, thereby increasing both surface loading and adsorption capacity. To elucidate the structure of the modification combination, 1H and 13C nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) spectroscopic techniques, as well as Brunauer-Emmett-Teller (BET), X-Ray diffraction (XRD), Electrochemical impedance spectroscopy (EIS), and high-resolution transmission electron microscopy (HRTEM) analysis techniques were used, respectively. The analytical performance of the developed nanosensor was systematically optimized using differential pulse voltammetry (DPV), adsorptive stripping differential pulse voltammetry (AdSDPV), square wave voltammetry (SWV), and adsorptive stripping square wave voltammetry (AdSSWV) techniques. As a result of the optimization studies, the lowest limit of detection (LOD) was 3.66 x 10-8 M with the AdSSWV technique. DFT results corroborated the mechanism, indicating ring-centered electron donation (HOMO) and adsorption-favored N/O regions (MEP). Low LOD values were also recorded with other techniques, demonstrating the method's high sensitivity in analyte detection. In real sample analysis tests, PC recovery value in human blood samples was determined to be 98.69% using the AdSDPV technique. Despite the matrix effect, the nanosensor demonstrated high accuracy and reproducibility. The results indicate that the developed POSS-TiO2 Nps modified GC electrode sensor offers a high-performance, reliable, and good electrochemical detection platform suitable for use in biological and clinical applications.Article Robust Divergence-Based Tests of Hypotheses for Simple Step-Stress Accelerated Life-Testing Under Gamma Lifetime Distributions(Elsevier, 2026) Balakrishnan, Narayanaswamy; Jaenada, Maria; Pardo, LeandroMany modern devices are highly reliable, with long lifetimes before their failure. Conducting reliability tests under actual use conditions may require therefore impractically long experimental times to gather sufficient data for developing accurate inference. To address this, Accelerated Life Tests (ALTs) are often used in industrial experiments to induce product degradation and eventual failure more quickly by increasing certain environmental stress factors. Data collected under such increased stress conditions are analyzed, and results are then extrapolated to normal operating conditions. These tests typically involve a small number of devices and so pose significant challenges, such as interval-censoring. As a result, the outcomes are particularly sensitive to outliers in the data. Additionally, a comprehensive analysis requires more than just point estimation; inferential methods such as confidence intervals and hypothesis testing are essential to fully assess the reliability behaviour of the product. This paper presents robust statistical methods based on minimum divergence estimators for analyzing ALT data of highly reliable devices under step-stress conditions and Gamma lifetime distributions. Robust test statistics generalizing the Rao test and divergence-based tests for testing linear null hypothesis are then developed. These hypotheses include in particular tests for the significance of the identified stress factors and for the validity of the assumption of exponential lifetimes.Article Fröbenius Expansions for Second-Order Random Differential Equations: Stochastic Analysis and Applications to Lindley-Type Damping Models(Elsevier, 2026) Zeghdoudi, Halim; Kerker, Mohamed Amine; Boduroglu, ElifThis paper develops a Frobenius series framework for the stochastic analysis of second-order random differential equations of the form Y(t) + A(t)Y(t) = 0, where the damping coefficient A(t) is a positive stochastic process and the initial conditions are square-integrable random variables. Assuming mean-square analyticity of A(t) in a neighborhood of the initial time, we establish existence and uniqueness of the solution in L2(Omega) and derive exponentially convergent truncation error bounds for the associated Frobenius expansion. The resulting series representation enables the numerical approximation of the probability density function of Y(t) via Monte Carlo simulation. To improve computational efficiency, a control variates strategy is incorporated for variance reduction. A comprehensive numerical study is conducted for a broad family of positive, right-skewed damping distributions, including the Lindley, XLindley, New XLindley (NXLD), Gamma-Lindley, Inverse-Lindley, Truncated-Lindley, Log-Lindley, and a newly proposed Mixed Lindley-Uniform model. The simulations illustrate how different tail behaviors and boundedness properties of the damping coefficient influence the stochastic dynamics and the accuracy of density estimation. Finally, stylized applications to option pricing and Value-at-Risk estimation are presented to illustrate how the Frobenius-based framework and control variates methodology can be embedded within standard uncertainty quantification workflows. Overall, the proposed approach provides a flexible and computationally efficient tool for the analysis of randomly damped dynamical systems.Article Regular AdS3 Black Holes From a Regularized Gauss-Bonnet Coupling(Elsevier, 2026) Alkac, Gokhan; Mesta, Murat; Unal, GonulWe obtain a three-dimensional bi-vector-tensor theory of the generalized Proca class by regularizing the Gauss-Bonnet invariant within the Weyl geometry. We show that the theory admits a regular AdS3 black hole solution with primary hairs. Introducing a deformation in the theory, a different regular AdS3 black hole solution is obtained. Charged generalizations of these solutions are given by coupling to Born-Infeld electrodynamics.Conference Object The Relationship Between Burnout, Caring Behaviors, and Emotional Intelligence in Oncology Nurses(Elsevier, 2025) Pars, H.; Sari, T.; Caliskan, B. B.; Guner, P.Article Citation - WoS: 1Citation - Scopus: 1Genomic Characterization of Five Novel Salmonella Phages and the Assessment of Their Biocontrol Potential for the Preservation of Chicken Meat(Elsevier, 2026) Cufaoglu, Gizem; Cengiz, Gorkem; Acar, Bahar Onaran; Kardogan, Ozlem; Onmaz, Nurhan Ertas; Unal, Gultekin; Ayaz, Naim Deniz; Onaran Acar, Bahar; Ertas Onmaz, NurhanThe rise of multidrug-resistant Salmonella poses a significant threat to food safety and public health, necessitating novel antimicrobial strategies. The primary objective of this study was to characterize novel bacteriophages and assess their biocontrol potential against predominant Salmonella serotypes. A total of 84 lytic bacteriophages specific to various Salmonella enterica serotypes were isolated from wastewater sources across T & uuml;rkiye. Five phages (S.Hadar 4-5-1, S.Inf 5-2, S.Typ Adana, S.Ent 1-35-3, and S.Kent 1-2-1) demonstrating broad lytic activity to tested major serotypes (S. Enteritidis, S. Typhimurium, S. Infantis, S. Kentucky, S. Newport, S. Hadar, S. Gallinarum and S. Pullorum) and genetic diversity were selected for detailed phenotypic and genomic analysis. These phages, four from Siphoviridae and one from Podoviridae, exhibited tolerance to thermal (up to 60 degrees C) and mildly acidic conditions (pH 4), as well as 12-month stability when stored in Tris-Buffered Saline (TBS) with 20 % (v/v) glycerol at -20 degrees C and - 80 degrees C. Whole-genome sequencing confirmed their novelty and the absence of antimicrobial resistance and virulence genes. A cocktail formulated from these phages was applied against Salmonella Enteritidis both in-vitro (at 37 degrees C) and on artificially contaminated chicken wings (at 4 degrees C). The phage cocktail effectively reduced Salmonella counts in both environments, keeping levels below the detection limit (< 1 log CFU/g) over 24 h. For chicken wings food model, bacterial reductions reached 3.30 log CFU/g and 4.86 log CFU/g. These results underscore the potential of the newly characterized Salmonella phages as effective tools for controlling bacterial contamination on chicken meat, supporting their use as a natural, and antibiotic-free strategy in modern food safety management.Article Citation - Scopus: 1Dynamic Market Efficiency Assessment in Sustainability Indices: Rolling Fractional Integration Analysis with Multiple Estimators(Elsevier, 2025) Gonul, Ibrahim Omer; Omay, TolgaThis study develops a comprehensive econometric framework for assessing market efficiency in sustainability indices through rolling fractional integration analysis. We employ four fractional integration estimators (Andrews-Guggenberger, Robinson GSE, GPH, and FELW) with formal statistical testing, addressing critical methodological gaps including single estimator dependency and static analysis approaches. Applied to 17 sustainability indices across 13 countries, our results reveal significant heterogeneity in market efficiency evolution. Developed markets exhibit timevarying efficiency patterns with periodic inefficiencies driven by institutional rebalancing dynamics, while emerging markets demonstrate superior efficiency characteristics. The BIST Sustainability Index exhibits exceptional efficiency, while the SP 500 ESG Screened Index shows the highest inefficiency levels among developed markets. The convergent validity between fractional integration and traditional unit root tests provides robust methodological validation. Our findings establish unprecedented robustness in sustainability market efficiency research while providing policy implications for financial regulators and investment managers.