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Prognostic value of histological subtypes and clinical factors in non-endemic nasopharyngeal carcinoma: A retrospective cohort study
No full textBackground and Objectives: Nasopharyngeal carcinoma (NPC) displays marked geographic and histopathological heterogeneity, and prognostic determinants in non-endemic regions remain incompletely defined. This study aimed to evaluate the impact of clinicopathological characteristics and treatment modalities on survival outcomes among patients with stage II-IVA NPC treated with curative intent at a single tertiary cancer center. Materials and Methods: A retrospective analysis was conducted on 81 consecutive patients with histologically confirmed NPC treated between 2000 and 2022. Demographic, clinical, and treatment parameters were extracted from institutional records. Survival outcomes-including disease-free survival (DFS), locoregional recurrence-free survival (LRFS), distant metastasis-free survival (DMFS), cancer-specific survival (CSS), and overall survival (OS)-were estimated using the Kaplan-Meier method and compared using the log-rank test. Prognostic variables identified in univariate analysis were further assessed by multivariable Cox proportional hazards regression (Cox's model). Results: The cohort included 59 men (72.8%) and 22 women (27.2%), with a median age of 50.8 years (range, 19-78). Most patients presented with locally advanced disease (T3-T4, 53.1%; N2, 60.5%; stage III-IVA, 87.7%). Non-keratinizing undifferentiated carcinoma (World Health Organization [WHO] type III) was the predominant histology (71.6%), followed by the non-keratinizing differentiated subtype (17.3%). Median DFS and OS were 94.6 and 139.4 months, respectively. According to the univariate analysis, histological subtypes and a family history of cancer were significantly associated with DFS, whereas comorbid systemic disease showed an unexpected association with longer DMFS. The multivariable Cox model identified the histological subtype as an independent predictor of disease recurrence (HR = 2.23, 95% CI: 1.00-4.94; p = 0.049). For OS, both histological subtype (HR = 2.40, 95% CI: 1.10-5.25; p = 0.029) and age at diagnosis (HR = 1.05, 95% CI: 1.02-1.09; p = 0.005) were independent adverse prognostic factors. Conclusions: In this long-term, single-center study from a non-endemic region, histological subtype emerged as the most powerful determinant of prognosis, significantly influencing both DFS and OS. Patients with non-keratinizing undifferentiated (WHO type III) carcinoma demonstrated superior outcomes compared with those with differentiated histology. Additionally, increasing age at diagnosis was independently associated with poorer OS. In contrast, inflammatory and nutritional biomarkers, the Pan-Immune-Inflammation Value (PIV) and the Prognostic Nutritional Index (PNI), showed no prognostic significance. These findings underscore the continued prognostic relevance of histopathologic classification and age and highlight the need for large-scale, standardized studies integrating Epstein-Barr virus (EBV) status and host-related factors in non-endemic NPC populations
Mechanical responses of recycled core sandwich structures with hybrid composite facings: A study of quasi-static and dynamic behavior
No full textIn this study, a sandwich composite structure was developed by combining a recycled, self-skinned corrugated polypropylene (PP) core with face sheets made from woven hybrid composites of glass, carbon, and aramid fibers. The face sheets were fabricated using the Vacuum-Assisted Resin Transfer Molding (VARTM) process following an optimized stacking sequence, and subsequently integrated with the core using an EVA-based thermoplastic adhesive. The performance of the produced structures was evaluated through quasi-static and dynamic three-point bending tests, as well as edge compression tests. The findings indicate that the interaction among the different fiber layers enhances interfacial integrity and improves structural stability. The obtained results reveal that integrating the hybrid face sheets with the core enhances the structural durability and positively influences the energy absorption and deformation behavior of the material. The structure developed in this context aims to be evaluated as a potential alternative for producing recyclable, environmentally sustainable, and functional components in the automotive industry, particularly in structures such as electric vehicle battery boxes. Additionally, the study presents a novel approach to the reuse of recycled thermoplastic cores in advanced engineering applications
Revisiting morbidities and predictors in transfusion-dependent thalassemia: A cohort study over 10 years from the national registry of hemoglobinopathies in Türkiye
No full textThe effect of emotional intelligence on the acceptance and use of technologies used i̇n occupational health and safety: A systematic literature review
No full textBackground While the complexity of today's business environments links the adoption of occupational health and safety (OHS) technologies with individual and institutional factors, emotional intelligence (EI) plays an important role in this process. It contributes to the development of a safety culture.Objective This study aims to analyze the effect of EI on the acceptance and use of OHS technologies using the systematic literature review (SLR) method.Methods This systematic literature review selected and evaluated 39 academic studies examining the relationship between OHS and EI in the context of technology acceptance and use between 2010 and 2025 using PRISMA and Mixed Methods Assessment Tool (MMAT) methods in Scopus, PubMed, Web of Science, and SpringerLink databases with the specified keywords.Results While the 39 studies evaluated according to the MMAT criteria generally offered high methodological quality and consistent analyses, it was observed that the themes of EI, occupational health and safety, and technology adaptation came to the fore, especially with the increasing number of publications after 2021.Conclusions This systematic review demonstrates that EI is a key determinant of accepting and using OHS technologies. Improvements are needed in methodological consistency and contextual diversity. Integrating EI as a mediating structure in technology acceptance models can enhance the effectiveness of OHS practices. Developing employee EI skills accelerates technology adoption within the Unified Technology Acceptance and Use Model 2 (UTAUT2) model, strengthening individual and organizational OHS performance
Sustainable design of broadband radar absorbers using metallurgical waste and multi-objective optimization
No full textThis study proposes a sustainable approach for converting metallurgical waste into value-added electromagnetic materials for broadband radar absorption applications. A total of 105 samples are fabricated from 14 industrial waste types using various shaping and additive techniques, and then electromagnetically characterized. A novel double-stage Artificial Bee Colony (DS-ABC) optimization algorithm is developed to design an effective five-layer absorber by independently optimizing layer sequence and thickness for transverse electric (TE) and transverse magnetic (TM) polarizations. The resulting multilayer structure achieves over 90 % absorption across the 2-18 GHz frequency range under multiple incidence angles. Beyond technical performance, this work demonstrates a scalable method for replacing hazardous waste with functional materials, thereby reducing environmental impact and aligning with the principles of a circular economy. The proposed approach offers practical relevance for sectors requiring electromagnetic interference (EMI) shielding and stealth technologies. It also contributes to sustainable production practices by repurposing industrial by-products
Combined effect of recycled tire steel fiber and blast furnace slag on the mechanical performance of 3d printable concrete
No full textThis study investigated the effects of waste steel fiber and high-volume blast furnace slag (BFS) substitution on the mechanical and physical properties of three-dimensional printable concrete (3DPC) to improve its environmental performance. BFS was substituted for cement at 0%, 25%, 50%, and 75% by volume. Waste steel fibers were added to the mixtures at three lengths (5, 10, and 15 mm) and two volumetric ratios (0.5% and 1.0%). Twenty-eight mixtures were optimized based on extrudability, buildability, and shape stability criteria. Parameters such as compressive and flexural strength, surface moisture content, and drying shrinkage were evaluated. The results showed that using up to 0.5% waste steel fibers increased compressive strength by up to 23%, but decreased it to a level of 1%. Fiber reinforcement improved the flexural strength of all blends by up to 53% at both ages, regardless of fiber ratio or length. Increasing the BFS substitution rate generally increased surface moisture however, this value decreased in mixtures containing 75% BFS and silica fume. Furthermore, using steel fibers and in-creasing fiber length significantly improved the drying shrinkage performance of the mixtures
Relationship between food insecurity and ultra-processed food consumption in adults with overweight and obesity
No full textAim: This study examined the relationship between food insecurity and ultra-processed food (UPF) consumption in adults with overweight and obesity. Methods: We conducted a cross-sectional analysis among outpatients seeking dietary counseling. Normality was assessed via skewness-kurtosis (-2 to +2). Daily UPF intake (g/day) was compared by sex using Student's t-test. Associations between food insecurity (food secure vs. mild/moderate/severe) and daily UPF intake were modeled using simple and multivariable linear regressions with progressive adjustment for sociodemographic and behavioral covariates. Results: Among 323 participants (mean age 46.9 +/- 13.1 years; 64.4 % women; mean BMI 33.8 +/- 11.0 kg/ m2), 14.9 % reported any food insecurity (9.6 % mild, 3.7 % moderate, 1.5 % severe). Total daily UPF intake was higher in individuals with any food insecurity than in food-secure individuals (286.3 +/- 370.6 vs. 143.8 +/- 205.0 g). Across fully adjusted models, food insecurity was associated with 124-143 g/day higher UPF consumption. Conclusion: Food insecurity is associated with higher daily UPF intake among adults with overweight or obesity. Policies should prioritize affordable, healthy substitutes and economic supports rather than assuming simple removal of UPFs. (c) 2025 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies
-Yazar Tespit Edilemedi- Neuropsychological test profile of compulsive buying behavior: A study on 50-year-old and over consumers
No full textThis study aims to contribute to the literature by identifying the neuropsychological test profile of compulsive buying behaviour among consumers aged 50 and above. Designed as a case-control study, the research was conducted at the Neurology Outpatient Clinic of Bursa Uludag University Faculty of Medicine and completed with 66 participants-33 in the case group and 33 in the control group. The Standardised Mini-Mental State Examination (SMMSE), the Minnesota Impulsive Disorders Interview (MIDI), the Wisconsin Card Sorting Test (WCST), and the Stroop Test-Capa Form (ST) were administered to assess executive functions. At the same time, the Iowa Gambling Task (IGT) was used to evaluate decision-making behaviour. Descriptive statistics were calculated, and chi-square, Shapiro-Wilk, independent samples t-test (for normally distributed data), and Mann-Whitney U test (for non-normally distributed data) were employed in the analyses. The WCST sub-scores-total number of errors, number of categories completed, total number of perseverative responses, total number of nonperseverative errors, percentage of perseverative errors, number of reactions to complete the first category, and number of conceptual level responses-differed significantly between groups. Similarly, significant differences were observed between groups in the completion times, number of errors, and spontaneous corrections in the first three sections of the ST, as well as in the net scores of the third, fourth, and fifth blocks of the IGT. The findings indicate that the compulsive buying group demonstrated lower executive function and decision-making performance compared to the control group. The results were discussed in the context of existing literature, and recommendations were proposed
A novel hybridization of birds of prey-based optimization with differential evolution mutation and crossover for chaotic dynamics identification
No full textParameter identification of chaotic systems such as Lorenz, Chen, and R & ouml;ssler has long been recognized as a challenging inverse problem, since even slight perturbations in system coefficients can yield qualitatively different trajectories. Conventional time-domain error formulations are often ill-conditioned under these conditions, which has motivated the design of more robust objective functions and the adoption of metaheuristic optimization strategies. In this study, a hybrid birds of prey-based optimization with differential evolution (h-BPBODE) is introduced to address these challenges. The method enriches the four canonical behavioral phases of BPBO (individual hunting, group hunting, attacking the weakest, and relocation) by embedding DE mutation and crossover operators after each candidate update. This design injects recombinative diversity while retaining BPBO's adaptive and collective search mechanisms, thereby improving the balance between exploration and exploitation. The algorithm is validated on Lorenz, Chen, and R & ouml;ssler systems, where the task is to recover unknown parameters by minimizing trajectory mismatches between true and simulated models. Comparative simulations against standard BPBO, starfish optimization, hippopotamus optimization, particle swarm optimization (PSO), and DE confirm that h-BPBODE consistently achieves exact parameter recovery with negligible residuals, faster convergence, and markedly lower run-to-run variance. Statistical analyses, convergence traces, and parameter evolution curves further demonstrate its robustness and precision. These findings establish h-BPBODE as a reliable and efficient framework for chaotic system identification and suggest its potential for broader nonlinear estimation tasks
Demand and lead time prediction with machine learning methods in maritime shipping
Get PDFDeğişken küresel ticaret dinamiklerinin yaşandığı bir çağda, deniz taşımacılığı uluslararası lojistiğin temel bir bileşenidir. Ancak deniz taşımacılığı, dalgalanan talep, operasyonel kısıtlar ve çevresel belirsizliklerden kaynaklanan kesintilere maruz kalmaktadır. Tez çalışmasının temel amacı, Türk denizcilik sektöründe operasyonel karar alma süreçlerini iyileştirmek üzere, konteyner iş hacmi talebi ve teslim süresi tahmininde yüksek doğruluk sağlayan, veri odaklı ve pratik uygulanabilir makine öğrenmesi (ML) modelleri geliştirmektir. Gerçek dünya verilerine dayalı olarak, çalışma, konteyner iş hacmi talebini ve teslim süresini etkileyen karmaşık, doğrusal olmayan etkileşimleri yakalamak için hibrit mimariler dahil olmak üzere bir dizi tahmin modeli geliştirmekte, eğitmekte ve değerlendirmektedir. Tez çalışmasında, denetimli öğrenme metodolojileri benimsenmiş ve çeşitli ML algoritmaları karşılaştırılmıştır. Temel etkileyici faktörleri belirlemek için gri ilişkisel analiz yöntemi kullanılmıştır. Önceki çalışmalardan farklı olarak, bu çalışmada, konteyner iş hacmi çıktısı ve sevkiyat teslim sürelerini eş zamanlı olarak tahmin etmek için entegre bir yaklaşım sunulmuştur. Bu iki odaklı yaklaşım, mevcut literatürde nadiren birlikte ele alınmıştır. Önerilen sistem, geleneksel istatistiksel yöntemlere kıyasla tahmin doğruluğunda önemli iyileştirmeler göstererek, nakliye operatörleri, liman otoriteleri ve tedarik zinciri paydaşları için eyleme dönüştürülebilir içgörüler sağlamaktadır. Sonuçlar, önerilen modellerin literatürdeki yaklaşımlara kıyasla daha yüksek tahmin doğruluğu sunduğunu ortaya koymuş, ayrıca, geliştirilen kullanıcı dostu arayüz sayesinde modellerin saha uygulamalarında etkin biçimde kullanılabileceği anlaşılmıştır. Bu tez, yalnızca denizcilik lojistiği tahminlemesinin akademik anlayışını ilerletmekle kalmayıp, aynı zamanda Türk ticaret altyapısının bölgesel karmaşıklıklarına uyarlanmış ölçeklenebilir araçlar da sunmaktadır.In an era of volatile global trade dynamics, maritime transport is a fundamental component of international logistics. However, maritime transport is subject to disruptions caused by fluctuating demand, operational constraints, and environmental uncertainties. The primary objective of this thesis is to develop data-driven and practically applicable machine learning (ML) models that provide high accuracy in predicting container volume demand and delivery times, with the aim of improving operational decision-making processes in the Turkish maritime sector. Based on real-world data, the study develops, trains, and evaluates a series of prediction models, including hybrid architectures, to capture the complex, non-linear interactions that influence container cargo volume demand and delivery times. The thesis adopts supervised learning methodologies and compares various ML algorithms. The grey relational analysis method has been used to identify the key influencing factors. Unlike previous studies, this study presents an integrated approach to simultaneously predict container cargo volume output and shipment delivery times. This dual-focused approach is rarely addressed together in the existing literature. The proposed system provides actionable insights for shipping operators, port authorities, and supply chain stakeholders, demonstrating significant improvements in prediction accuracy compared to traditional statistical methods. The results demonstrate that the proposed models offer higher prediction accuracy compared to approaches in the literature, and the developed user-friendly interface makes them usable for field applications. This thesis not only advances the academic understanding of maritime logistics forecasting but also provides scalable tools adapted to the regional complexities of Turkey's trade infrastructure