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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Thermodynamic and Environmental Assessment of Integrating a Heat-Pump Tumble Dryer with a PEM Electrolyzer(Taylor & Francis Inc, 2026) Basdemir, Aziz; Tosun, Burcu; Erdogan, Anil; Nalbant Atak, YagmurHydrogen is increasingly regarded as an energy carrier for electrification and long-duration storage. This study presents a combined modeling and experimentally validated thermodynamic analysis of a household-scale hydrogen production concept integrating a heat-pump tumble dryer with a proton exchange membrane electrolyzer (PEME). The work combines steady-state thermodynamic and exergy modeling, experimental validation using air-side measurements, and a scenario-based life cycle assessment (LCA). A thermodynamic model of the integrated system was developed in engineering equation solver (EES), and a parametric analysis examined ambient temperature, relative humidity, tumble-air temperature, and alternative working fluids. Key metrics include coefficient of performance (COP), exergy destruction, condensate production, and hydrogen yield. Under baseline conditions, the system achieves COP = 4.90, produces 5.546 kg condensate/cycle, and yields 0.5453 kg H-2/cycle. Increasing ambient temperature (15-40 degrees C) raises COP by up to 14% and lowers exergy destruction (0.1999 -> 0.1775 kW). Raising tumble-air temperature (65-75 degrees C) increases COP (3.033 -> 5.406), reduces exergy destruction by 29%, and increases hydrogen output threefold. Exergy losses are dominated by the expansion valve (45%) and the condenser (39%). Among refrigerants, R600a and R1270 provide the highest gains in condensate and hydrogen production. A use-phase Life-cycle assessment (LCA) shows per-cycle Global Warming Potential (GWP) is reduced for condensate reuse (0.4087 -> 0.4070 kg CO2-eq/cycle). Overall, results suggest that dryer-condensate-fed electrolysis is technically feasible and offers thermodynamic and climate-impact benefits at the household scale.Article The Effect of Tax Justice on Income Redistribution: Empirical Evidence from OECD Countries(Akademiai Kiado Zrt, 2026) Ozkok Cubukcu, Dilek; Unalan, GokhanIncome taxation is theoretically considered one of the most effective and widely used tools of public finance for correcting income inequality. However, its actual redistributive capacity varies significantly across countries and depends on the design of tax instruments. This study isolates the effects of taxation from transfers to examine whether justice-based tax instruments-such as progressive tax rates, minimum living allowance (MLA), and tax credits-enhance redistribution. To empirically assess these relationships, a dynamic panel dataset covering 38 countries (37 OECD members and Bulgaria) between 2005 and 2020 is constructed. The System GMM method is applied to estimate the model. On average, taxation accounts for 26% of total redistribution, and its effect is significantly enhanced by equity-oriented tax policies. A one-point increase in tax progressivity leads to a 0.731-point rise in redistribution (P < 0.01), and tax credits have a similarly significant positive effect (+0.266). In contrast, personal allowances and zero-rate brackets show no statistically meaningful impact. A 10-point increase in the MLA index leads to a 0.4-point reduction in redistribution, suggesting that applying horizontal equity (equal treatment across household types) may undermine efforts to improve vertical equity (reducing income inequality). These findings highlight the importance of designing targeted and fairness-driven tax instruments to strengthen the redistributive role of taxation, beyond dependence on transfer mechanisms.Article The Association of Systemic Inflammation Index with Parathormone Levels in Hemodialysis Patients: A Cross-Sectional Study(Dustri-Verlag Dr Karl Feistle, 2026) Dheir, Hamad; Demir, Mehmet Emin; Çağlayan, Feyza Bayrakdar; Islam, Mahmud; Çankaya, EmreAim: Abnormal parathormone (PTH) levels are common in patients undergoing hemodialysis and have been linked to adverse outcomes. This study investigated the association between the systemic inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and parathyroid hormone (PTH) levels in patients undergoing maintenance hemodialysis (HD). Materials and methods: We performed a cross-sectional analysis of 225 patients undergoing HD at a single center. Demographic data, comorbidities, dialysis vintage, and laboratory values were obtained from medical records. Patients were stratified into three groups based on PTH level according to KDI-GO CKD-Mineral and Bone Disorder (CKD-MBD) guideline targets: PTH1 (< 150 pg/ mL), PTH2 (150-600 pg/mL), and PTH3 (> 600 pg/mL). The SII and NLR were calculated from complete blood counts. We compared the clinical characteristics across the PTH groups and used logistic regression to identify independent predictors of PTH levels outside the target range. Results: Of the 225 patients (mean age 61.3 +/- 17.5 years; 53.3% male), 17.3% were in the PTH1 group, 55.6% in PTH2, and 27.1% in PTH3. Patients in the PTH1 (low PTH) group were older and had a higher prevalence of diabetes mellitus than those in the target PTH group (p < 0.05). Serum calcium and phosphate levels were similar among the groups (p > 0.05). C-reactive protein (CRP) and ferritin levels were significantly higher in both the PTH1 and PTH3 groups compared to the PTH2 group (p < 0.05 for both). Accordingly, the novel inflammatory indices differed by PTH category: the median SII and NLR values were lowest in the PTH2 group and significantly elevated in both the low PTH and high PTH groups (PTH1 and PTH3, p < 0.05). In multivariate logistic regression, higher SII (p = 0.002) and NLR (p = 0.045) were independently associated with PTH levels outside the 150-600 pg/mL target range, even after adjusting for age, diabetes, CRP, ferritin, calcium, and phosphorus. HD duration showed a significant inverse correlation with PTH in the PTH1 group (r = -0.245, p = 0.022) but was not an independent predictor of PTH category overall. Conclusion: Hemodialysis patients with PTH levels below or above the recommended target range demonstrated elevated inflammatory markers (CRP and ferritin) and higher SII/NLR values, indicating a state of increased systemic inflammation. The SII and NLR were independent predictors of out-of-range PTH levels. These easily obtained indices may be useful for assessing inflammation in HD patients with altered mineral metabolism. Further research is warranted to determine whether addressing inflammation can modulate PTH levels or improve outcomes in this population.Article Robust Inference for an Interval-Monitored Step-Stress Experiment under Proportional Hazards(Taylor & Francis Ltd, 2026) 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 Robust Inference for Step-Stress Experiments under Interval-Censoring(Springer, 2026) Balakrishnan, Narayanaswamy; Jaenada, María; Pardo, LeandroMany moderns products have a long life before failure. Reliability analyses for such highly reliable devices therefore present a practical challenge as obtaining sufficient failure information to adequately assess lifetime behavior will require extended experimental duration. As an alternative, accelerated life testing (ALT) is commonly used to shorten the time to failure of units under test, with the results subsequently extrapolated to normal operating conditions. This paper provides a comprehensive review of robust inferential methods based on density power divergence for analyzing step-stress ALT data. Point estimates and approximate confidence intervals for model parameters, along with robust estimates of some important lifetime characteristics are developed for general lifetime distributions. Subsequently, explicit expressions are derived for four most prominent parametric lifetime distributions: exponential, Weibull, gamma, and lognormal. A semi-parametric approach based on the proportional hazards model and a competing risks scenario are also discussed as extensions of the proposed model. Throughout the manuscript, several open problems are highlighted, along with significant gaps in the literature, to motivate readers and also to promote further research in this important research area. Moreover, to illustrate the importance of step-stress ALTs and the practical utility of robust estimators, we also present some real data sets used in the literature and analyze one of them using robust methods. By analyzing real data, we demonstrate the stability of the Minimum Density Power Divergence Estimator (MDPDE) for different values of the tuning parameter in the presence of outliers. We also analyze the implications of distributional assumptions on parameter estimation. Confidence intervals, including transformed intervals, are examined, with transformed intervals resulting in confidence levels close to nominal level and also provide better interpretability. Our results highlight the importance of robust estimation techniques in the presence of data contamination and also in a careful selection of parametric models for modeling the lifetime data, as these choices significantly influence predictions of lifetime characteristics under normal operating conditions.Article Rational Torsion on Hyperelliptic Jacobian Varieties(Wiley-VCH Verlag GmbH, 2026) Suluyer, Hamide; Sadek, MohammadIt was conjectured by Flynn that there exists a constant such that, for any integer , any , there exists a hyperelliptic curve of genus over with a rational -torsion point on its Jacobian. Lepr & eacute;vost proved this conjecture with . In this work, we prove that given an integer in the interval , , satisfying certain partition conditions, there exist parametric families of hyperelliptic Jacobian varieties with a rational torsion point of order . In particular, we establish the existence of such varieties for when is odd and for when is even. A few explicit applications of this result produce the first known infinite examples of torsion 13 when , torsion 15 when , and torsion 17,18,21 when . In fact, we show that infinitely many of the latter abelian varieties are absolutely simple.Article Real-Time Experimental Investigation of Open- and Closed-Loop Speed Control for a Prototype EV Powertrain Incorporating a 2.2-kW BLDC Motor and Planetary Gearbox(IEEE-Inst Electrical Electronics Engineers Inc, 2026) Doruk, Resat; Hennache, Ali; Abouseda, Ayman Ibrahim; Amini, AliThis study presents an experimental investigation of open- and closed-loop speed control applied to a 2.2 kW brushless DC (BLDC) motor integrated with a planetary gearbox and evaluated under variable-speed and fixed-load conditions. The aim is to characterize the dynamic response, energy-conversion efficiency, and battery state-of-charge (SOC) behavior of the powertrain under real-time control strategies. A complete laboratory platform was developed using a commercial BLDC motor controller, a 60 V-17.4 Ah lithium-ion battery pack, an optical speed sensor, and an eddy-current dynamometer capable of applying load torques from 1.5 to 7.5 N & sdot;m. Open-loop operation regulated speed through direct voltage modulation, whereas closed-loop control was implemented using a proportional-integral-derivative (PID) algorithm executed in real time on a microcontroller. Real-time measurements of voltage, current, torque, and speed were used to compute electrical power, mechanical power, and system efficiency, while battery SOC variation was estimated using the Coulomb-counting method. The results indicate that open-loop control exhibits substantial speed-tracking errors, pronounced transient power surges during speed transitions, reduced efficiency, and an increased SOC depletion rate over the investigated speed range of 1000-2600 rpm. In contrast, the closed-loop PID controller maintains steady-state speed errors within approximately 1 % across all load levels, suppresses current fluctuations, mitigates transient losses, and enhances overall system efficiency by approximately 14-19 percentage points. Closed-loop operation further reduces SOC depletion by 0.49-0.75 percentage points, depending on the applied load torque. These findings demonstrate the effectiveness of feedback control in improving stability, energy utilization, and electric powertrain performance in BLDC-based propulsion systems, with direct relevance to electric-vehicle and hybrid powertrain systems.Article Robust Arrow-Hurwicz Method for High-Rayleigh Number Boussinesq Flow(Springer-Verlag Italia SRL, 2026) Takhirov, Aziz; Eroglu, Fatma G.; Aggul, Mustafa; Ergen, Sinan; Kaya, SongülWe develop and analyze a robust Arrow-Hurwicz (AH) iterative method for the numerical solution of steady Boussinesq flows with nonhomogeneous partitioned Dirichlet boundary conditions. Although a direct AH formulation may be applied to the momentum equation alone, we demonstrate that incorporating an AH-type update for the temperature equation is crucial for stability and convergence in buoyancy-driven systems, particularly at high Rayleigh numbers. The resulting Improved Arrow-Hurwicz (IAH) scheme avoids solving saddle-point systems at each iteration and yields a fully decoupled algorithm with low computational cost per step. We establish existence, uniqueness, uniform boundedness, and convergence under standard small-data assumptions, and provide corresponding error estimates for the finite element discretization. Extensive two- and three-dimensional numerical experiments verify the theoretical findings, demonstrate significant acceleration over the alternative AH scheme and the Penalty-Picard iteration, and confirm robust convergence in high-Rayleigh number regimes. The proposed method offers a scalable and efficient solver for steady natural convection and provides a promising alternative to continuation-based approaches traditionally used for high-Rayleigh flows.Article Rethinking the Second Life of Post-Disaster and Post-Conflict Temporary Housing(Ubiquity Press Ltd, 2026) Ay, Bekir Özer; Dino, İpek Gürsel; Akdede, NilProviding temporary housing (TH) units after natural hazards and social conflicts is often an urgent necessity. Beyond their initial configuration, the second life of these units is crucial, given their temporary nature. Despite growing interest in second-life strategies, many TH units and associated infrastructure remain unused or inefficiently managed after their initial deployment. Second-life strategies are presented for post-disaster and post-conflict (PDPC) TH units and settlements in Türkiye, using two case studies-the 2011 Van earthquakes and Syrians under temporary protection-and expert insights from the Disaster and Emergency Management Presidency of Türkiye (Afet ve Acil Durum Yönetimi Başkanlığı-AFAD). Athree-step methodology was employed, including a literature review, semi-structured expert interviews and hybrid deductive-inductive thematic analysis. Findings reveal that second-life outcomes are largely shaped by policy gaps, operational conditions, tenure constraints, institutional decisions and user practices rather than by design-based circular approaches. The proposed framework provides practical guidance for policymakers and practitioners in Türkiye and other crisis-prone contexts to improve resource efficiency and integrate second-life planning into preparedness and recovery processes.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.