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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Breaking the Cycle: A Systemic Analysis of Socio-Technical Barriers and Policy Priorities for Biomass Technology in an Emerging Economy(Elsevier Sci Ltd, 2026-07) Oztel, Ahmet; Erol, Ismail; Benli, Tolga; Ar, Ilker MuratThis study addresses the critical challenge of slow biomass technology adoption in emerging economies, using Türkiye-with a potential of 3.9 MToe annually-as a representative case. Despite its promise for clean energy and rural development, adoption is stifled by a complex web of socio-economic and cultural barriers. Moving beyond isolated analyses, this research employs a novel Interval-Valued Picture Fuzzy Interpretive Structural Modeling and Cross-Impact Matrix Multiplication Applied to Classification approach to model the interdependencies and uncertainties among 17 key barriers identified from literature and expert input. The findings of this study provide a strategic hierarchy for policymakers, revealing that weak regulatory frameworks, gender roles, health concerns, cultural taboos around waste use, and land-use conflicts are the fundamental driving barriers that perpetuate dependent challenges such as high costs and low awareness. To break this cycle, we propose a targeted policy framework prioritizing robust regulations with financial incentives, genderinclusive training programs, public health campaigns, and community-based ownership models. These interventions offer a systemic roadmap to accelerate sustainable biomass adoption, directly supporting progress towards UN Sustainable Development Goals 7 (Affordable and Clean Energy), 12 (Responsible Consumption), and 13 (Climate Action) in Türkiye and similar emerging economies where comparable socio-technical conditions prevail.Article Biocontrol of Listeria Monocytogenes in Milk: Isolation and Characterization of a Novel Bacteriophage Cocktail(Elsevier Sci Ltd, 2026-06) Unal, Gultekin; Cufaoglu, Gizem; Cengiz, Gorkem; Acar, Bahar Onaran; Ayaz, Naim Deniz; Erdinc, Ayse Nur; Vural, Ilgin Ata; Onaran Acar, Bahar; Ata Vural, Ilgın; Yıldız, TansuListeria monocytogenes is a significant foodborne pathogen known for its persistence in food processing environments and resistance to various stress conditions. This study aimed to isolate and characterize bacteriophages specific to L. monocytogenes and evaluate their potential as biocontrol agents in milk. A total of 43 phages were isolated from diverse wastewater sources across Türkiye. Based on their host range, lytic activity, and growth kinetics, two phages (LM1116TR and LM1418TR) were selected for further comprehensive phenotypic and genomic characterization. Host range assays revealed high specificity toward L. monocytogenes, with lytic activity observed against multiple serotypes (1/2a, 1/2b, 1/2c, and 4b). Transmission electron microscopy revealed that the phages exhibit a myovirus-like morphotype and belong to the class Caudoviricetes. Whole-genome sequencing confirmed that two phages had complete circular genomes lacking antimicrobial resistance genes. Thermal stability tests showed the phages remained detectable after 1 h at 40 degrees C, 50 degrees C, and 60 degrees C but were sensitive to acidic pH, especially to pH 3. Significant reductions in L. monocytogenes counts were observed following phage cocktail treatment, reaching up to 4.22 log CFU/mL in vitro (37 degrees C) and 1.66 log CFU/mL in UHT milk (4 degrees C) (p < 0.001). Additionally, one-year storage tests at +4 degrees C, -20 degrees C, and -80 degrees C in tryptic soy broth (TSB), SM buffer, physiological saline and Tris-Buffered Saline (TBS, 1 & times; ) identified TSB with 20% glycerol as the most suitable for preserving phage stability at subzero temperatures. These results show the potential of new phages as effective and stable biocontrol agents against L. monocytogenes in food safety applications, supporting their potential as biocontrol agents, particularly within the dairy industry.Article Acceptance Sampling Plan under Step Stress Accelerated Life Test for One-Shot Devices(Elsevier Sci Ltd, 2026-08) Lin, Chien-Tai; Balakrishnan, Narayanaswamy; Ling, Man-HoAcceptance sampling plans are essential in many manufacturing industries, serving as a statistical method to decide whether to accept or reject a batch of products based on the quality of a sample. The demand for reliable assessment methodologies has grown increasingly important as devices become more reliable under normal operating conditions. This trend poses challenges for reliability assessments, especially when there is limited failure data from tests. To address this, accelerated life testing (ALT) is widely employed to induce rapid failures for reliability analysis. This paper presents a comprehensive study of acceptance sampling plans under step-stress ALT (SSALT) for one-shot devices. We propose a tailored acceptance sampling plan that incorporates SSALT principles to enhance decision-making regarding product acceptance. Our methodology enables the determination of acceptable quality thresholds while evaluating the associated producer's and consumer's risks. Moreover, it can determine the minimum sample size required to ensure that both risks are adequately addressed, as well as to identify the optimal percentage of test items to examine at various testing stages. Two illustrative examples are provided to demonstrate the developed optimal acceptance sampling plans. This research highlights the significant impact of the choice of reliability index and stress pattern on inspection allocation.Article The Role of Emotional Intelligence in the Relationship between Burnout and Perceived Quality of Care Among Oncology Nurses(Elsevier Sci Ltd, 2026-02) Sari, Tugba; Calis, Behice Belkis; Pars, Hatice; Guner, Perihan; Çalışkan, Behice BelkısPurpose: This study aimed to examine the relationships between burnout, emotional intelligence, and perceived caring behaviours among oncology nurses and to assess the predictive and mediating roles of these variables in explaining caring behaviours. Methods: A descriptive, cross-sectional study was conducted with 202 oncology nurses in T & uuml;rkiye. Data were collected using validated instruments measuring burnout, emotional intelligence, and caring behaviors. Data analysis employed descriptive statistics, Pearson correlation analyses, multiple linear regression, and structural equation modeling. Results: Emotional intelligence was positively associated with caring behaviours (r = .359, p < .001) and negatively associated with burnout subdimensions. Caring behaviours were inversely related to emotional exhaustion (r = -.258, p < .001), depersonalisation (r = -.397, p < .001), and reduced personal accomplishment (r = -.214, p = .002). In the regression model (R2 = .214, p < .001), emotional intelligence significantly predicted caring behaviours positively ((3 = .218, p = .002), while depersonalisation was a significant negative predictor ((3 = -.288, p < .001). However, emotional intelligence did not mediate the relationship between burnout and caring behaviours (Sobel test p = .332). Conclusion: While emotional intelligence was positively associated with caring behaviours and buffered the impact of burnout-particularly depersonalisation-it did not mediate the relationship between burnout and caring. These findings support the value of enhancing emotional intelligence to improve care quality and nurse well-being, though contextual factors may influence its mediating role.Article Linear Two-Dimensional Consecutive K-Type Systems in Multi-State Case(Elsevier Sci Ltd, 2026-07) Yi, He; Balakrishnan, Narayanaswamy; Li, XiangIn the context of consecutive k-type systems, multi-state system models are only considered in the onedimensional case and not in the two-dimensional case due to the complexity involved. In this paper, we consider several linear two-dimensional consecutive k-type systems in the multi-state case for the first time, as generalization of consecutive k-out-of-n systems and l-consecutive-k-out-of-n systems without/with overlapping. These systems include multi-state linear connected-(k, r)-out-of-(m, n): G systems, multi-state linear connected-(k, r)-or-(r, k)-out-of-(m, n): G systems, multi-state linear 1-connected-(k, r)-out-of-(m, n): G systems without/with overlapping, and multi-state linear 1-connected-(k, r)-or-(r, k)-out-of-(m, n): G systems without/with overlapping. We then derive their reliability functions by using the finite Markov chain imbedding approach (FMCIA) in a new way. We also present several examples to illustrate all the results developed here.Article Policy Frameworks Without Practice? Exploring Marine Governance and Climate Integration Challenges in Türkiye(Elsevier Sci Ltd, 2026-04) Karli, AygunThe marine-climate nexus has emerged as a critical frontier in global environmental governance, yet its integration into national policy frameworks remains uneven. This article examines the case of T & uuml;rkiye, a middleincome country with extensive coastlines and increasing exposure to climate risks, to explore how marine and climate governance interact in practice. Drawing on 22 semi-structured interviews with experts from government, civil society, and academia, the study applies thematic analysis to identify six interrelated challenges: (1) the gap between legal frameworks and implementation, (2) crisis-based governance, (3) institutional fragmentation and coordination deficits, (4) dependence on European Union funding and external alignment, (5) societal indifference and limited marine literacy, and (6) the contested discourse of the blue economy. The findings demonstrate that although T & uuml;rkiye has adopted robust legal instruments and aligned with EU standards, enforcement and institutional integration remain weak. Governance is often reactive, fragmented, and externally driven, with limited societal demand for ambitious reforms. These dynamics reflect broader patterns in global marine-climate governance but are compounded by T & uuml;rkiye's context specific political and institutional constraints. The article argues that bridging the persistent policy-practice gap will require stronger institutional coordination, investments in capacity and literacy, and reframing the blue economy as a vehicle for climate adaptation and mitigation rather than narrow economic growth.Article Evaluation of Clinical Characteristics, Risk Factors and Prognosis of Herpes Zoster (Shingles) Infection in Turkiye: Varicomp-Adult Study(Elsevier Sci Ltd, 2025-12) Ozgen-Top, Ozge; Karacaer, Zehra; Ozkan, Ece Firuze; Ozger, Hasan Selcuk; Saltoglu, Nese; Oztoprak-Cuvalci, Nefise; Senol, EsinObjective: The study aimed to determine the estimated prevalence of herpes zoster (HZ) infection in the adult population in Turkiye and the rates of HZ-associated complications and risk factors. Methods: This retrospective, multicenter ( n = 11), cross-sectional study was conducted between January 2016 and January 2022 and included all patients aged >= 18 years diagnosed with shingles following screening based on ICD-10 codes. The prevalence of HZ infection was calculated; rates of HZ-related complications (recurrence, hospitalization, postherpetic neuralgia [PHN]) and associated risk factors were determined. Results: A total of 6114 HZ patients were included; the estimated 5-year HZ prevalence in Turkiye was 908.7 per 10 0,0 0 0 population. Of the patients, 851 (14.2%) were immunocompromised, 366 (6%) were hospitalized due to HZ, 284 (8.9%) experienced PHN, 97 (3.2%) experienced recurrence of the patients. Risk factors for PHN were older age ( >= 50 years [OR = 3.19; P < 0.001)], and trigeminal dermatome involvement (OR = 2.45; P = 0.006). Antiviral use was associated with reduced PHN risk (OR = 0.16; P < 0.001). Conclusions: Our multicenter cross-sectional study revealed the high burden of HZ in Turkiye and high-lighted the potential for increasing prevalence due to risk factors including aging and comorbidities. (c) 2025 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Article Investigations on the Effect of Secondary Treatments on Ti48Al2Cr2Nb Alloy Manufactured by Electron Beam Powder Bed Fusion Method(Elsevier Sci Ltd, 2025-12) Bilgin, Guney Mert; Ozer, Seren; Davut, Kemal; Esen, Ziya; Dericioglu, Arcan F.As-built Ti48Al2Cr2Nb alloy samples produced by electron beam powder bed fusion (PBF-EB) exhibited notable brittleness. The low ductility was attributed to coarse gamma bands aligned perpendicular to the building and tensile direction. Additionally, variations in aluminum content and hardness between the coarse colonies and fine gamma/alpha(2) lamellae contribute to this phenomenon. Electron backscattered diffraction (EBSD) studies revealed a higher amount of dislocation density and inherent strain after PBF-EB manufacturing. Hence, usage of Ti48Al2Cr2Nb alloy in the as-built condition in aviation applications with high loads and demanding environments is not found to be viable. To eliminate these negative aspects and make PBF-EB produced Ti48Al2Cr2Nb alloy available for demanding applications, two distinct post-processing heat treatments; namely, hot isostatic pressing (HIP) and annealing heat treatment (HT) were employed at 1200 degrees C. A comprehensive characterization covering microstructure analysis, EBSD, fracture surface examination, as well as room and high-temperature tensile tests allowed determination of the effect of post-processes. HIPing altered the banded structure observed in the as-built samples by increasing the amount of alpha(2) phase and grain size. On the other hand, HT made the banded structure more pronounced without significantly increasing the amount of alpha(2) phase. HT also strengthened the <001> texture, while HIPing introduced randomization of grains. On the other hand, complete recrystallization is achieved as a result of HT at 1200 degrees C for 2 h, whereas HIPing at the same temperature for 2 h induced only 80.5 % recrystallization. In both post-processes, dislocation density and inherent strain were reduced. Room temperature and high-temperature tensile tests demonstrated that both HIPing and HT eliminated the extreme brittleness of the as-built samples.Article Citation - WoS: 5Citation - Scopus: 5Protection or Redundancy: Which is Better and When in Terms of Mean Time to Failure and Cost(Elsevier Sci Ltd, 2026-01) Eryilmaz, SerkanThis article is about comparing the effectiveness of protection mechanism and redundancy methods in terms of mean time to failure and cost criteria. Under the protection mechanism, a component is assumed to have different failure rates when it is protected and nonprotected. The protection block is also subject to failure and has constant failure rate. Alternatively, a redundant component which has the same failure rate with the original component may be used to enhance the reliability. For single unit and series systems, necessary conditions on the failure rate of the component are obtained to have a relation between the mean time to failure values of the system under both protection and redundancy. The extension of the results to coherent systems is also discussed.Article Citation - WoS: 2Citation - Scopus: 7Precision Forecasting for Hybrid Energy Systems Using Five Deep Learning Algorithms for Meteorological Parameter Prediction(Elsevier Sci Ltd, 2025-09) Ceylan, Ceren; Yumurtaci, ZehraThe intermittent nature of renewable energy sources necessitates accurate power production forecasting to ensure system sustainability and balance between energy supply and demand. Although the deep learning-based meteorological forecasting is significantly studied in literature, most of the current literature applies single-algorithm based on each individual energy source and less multi-algorithm based on comparative studies on multiple architectures as applied to integrated hybrid systems. In addition, most of the research uses the same algorithmic solution to all the meteorological parameters without identifying parameter-specific optimization potential, and recent research is verified on actual future time steps instead of historical train-test split. This study presents a comprehensive comparative analysis of five deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and CNN-LSTM hybrid, for forecasting critical meteorological parameters (wind speed, ambient temperature, and solar radiation) that determine energy output in a wind and solar-based hybrid energy system (HES). Using five years of Istanbul meteorological data (2018-2022), optimal algorithms were systematically identified for each parameter through rigorous hyperparameter optimization and cross-validation. Key results demonstrate that GRU achieves superior performance in wind speed prediction (RMSE: 0.049 m/s, R2: 0.8634) and solar radiation forecasting (RMSE: 0.146 W/m2, R2: 0.6643), while CNN-LSTM excels in ambient temperature prediction (RMSE: 0.011 degrees C, R2: 0.9976). The integrated approach predicted annual hybrid system energy production with 89 % accuracy, demonstrating 0.48 % deviation from observed values. Most significantly, our framework successfully forecasted sixth year (2023) energy production with 1.55 % error, validating its real-world applicability. This research contributes to the methodological advancement of renewable energy forecasting by systematically identifying optimal algorithmic approaches for different meteorological parameters in hybrid systems, thereby supporting the integration of intermittent renewable sources into sustainable energy infrastructures.