3D Bioprinting Scaffold of Gelatine Reinforced-Zinc Nanoparticles Synthesized by Green Synthesis: Comparative Evaluation of Mechanical and Thermal Properties

The development of sustainable, biocompatible, and mechanically robust biomaterials is essential for nextgeneration biomedical applications. In this study, zinc oxide nanoparticles (ZnONPs) were synthesized using a green, gelatin-mediated approach and incorporated into gelatin-based bioinks to fabricate 3D-bioprinted composite scaffolds. Structural analyses confirmed the successful formation of crystalline ZnONPs and their uniform dispersion within the gelatin matrix. Mechanical testing demonstrated a clear concentration-dependent enhancement, with Young’s modulus, tensile strength, and toughness increasing up to 67%, 67%, and 110%, respectively, in Gel–ZnONPs(5) compared to pristine gelatin. Antibacterial assays revealed strong inhibition against S. aureus and Escherichia coli, with zones reaching 23.1 mm and 20.2 mm, approaching the efficacy of Gentamicin. Cytocompatibility remained high across all tested concentrations, with cell viability consistently exceeding 85%, fulfilling ISO 10,993–5 non-cytotoxicity criteria. The 3D bioprinting process yielded structurally stable scaffolds with precise geometry, demonstrating the synergistic advantages of combining green nanoparticle synthesis with additive manufacturing. Overall, the results highlight Gel–ZnONPs composites as promising candidates for tissue engineering, wound management, and antimicrobial biomedical devices, offering a sustainable strategy to enhance functionality, mechanical integrity, and biological performance in biofabricated materials

The Mediating Role of Narcissistic and Borderline Personality Disorder Tendencies in the Relationship Between Core Beliefs of Worthlessness and Self-Critical Rumination

Yeni bir kavram olan öz eleştirel ruminasyon, zihinde tekrarlayan olumsuz öz eleştirel süreçleri içermektedir ve sınırlı sayıda çalışmaya konu olmuştur. Çalışmanın amacı, değersizlik negatif temel inancı ile öz eleştirel ruminasyon arasındaki ilişkide narsisistik ve borderline kişilik bozukluğu eğilimlerinin aracı rolünü incelemektir. Çalışma 18 yaş ve üstü, 498 kadın (%83,4), 97 erkek (%16,2) ve diğer seçeneğini işaretleyen 2 katılımcıdan (%0,03) oluşan 597 kişilik bir katılımcı grubu ile gerçekleştirilmiştir. Çalışmada demografik bilgi formu, Öz eleştirel Ruminasyon Ölçeği, Olumsuz Çekirdek İnanışlar Ölçeği ve Coolidge Eksen II Plus Envanteri kullanılmıştır. Narsisistik ve bor-derline kişilik bozukluğu eğilimlerinin öz eleştirel ruminasyon ve değersizlik negatif temel inancı arasındaki ilişkide aracılık rollerini ince-lemek için SPSS Process makrosu kullanılmıştır. Analizler sonucunda, değersizlik negatif temel inancı, narsisistik ve borderline kişilik bozukluğu eğilimlerinin öz eleştirel ruminasyonu pozitif yönde yordadığı; değersizlik negatif temel inancı ile öz eleştirel ruminasyon arasındaki ilişkide hem narsisistik hem de borderline kişilik bozukluğu eğilimlerinin aracılık rolü olduğu belirlenmiştir. Bu araştırmanın sonuçlarına göre, psikoterapi sürecini ve sonuçlarını son derece olumsuz etkileyen öz eleştirel ruminasyon ile çalışırken değersizlik negatif temel inancı, narsisistik ve borderline kişilik bozukluğu eğilimleri ile de çalışmanın gerekliliği ortaya çıkmaktadır.As a new concept, self-critical rumination involves repetitive negative self-critical mind processes and has been explored by a limited number of studies. The present study aimed to examine the mediating role of narcissistic and borderline personality disorder tendencies in the relationship between negative core belief of worthlessness and self-critical rumination. The study was conducted with 597 partici-pants aged 18 years and over, consisting of 498 females (83.4%), 97 males (16.2%), and 2 participants (0.03%) who chose the other option. Demographic Information Form, Self-Critical Rumination Scale, Negative Core Beliefs Scale, and Coolidge Axis II Plus Inven-tory were used in the study. SPSS Process Macro was used to examine the mediating roles of personality disorder tendencies in the relationship between core belief of worthlessness and self-critical rumination. The results yielded core belief of worthlessness, narcissistic, and borderline personality disorder tendencies were all positive predictors of self-critical rumination. Furthermore, the results revealed that both narcissistic and borderline personality tendencies significantly mediated the relationship between core belief of worthlessness and self-critical rumination. Regarding the results of the present study, it seemed necessary to work with the core belief of worthlessness and narcissistic and borderline personality disorder tendencies as well while working through self-critical rumination in psychotherapies as it is a critical burden for both the psychotherapeutic process and the outcomes

A Microstrip Monopole Antenna Design for 5G Sub-6 GHz Applications Using Deep Learning

This study presents the design and optimization of a microstrip monopole antenna for 5G sub-6 GHz applications, employing a deep learning-based surrogate model combined with honeybee mating optimization (HBMO). The studied antenna structure employs air via arrays, intended to enhance antenna performance, including improved impedance matching and increased bandwidth. It is important to note that, unlike conventional antennas, the proposed design does not include a fully enclosed metallic cavity similar to a substrate integrated waveguide (SIW) antenna designs. A sensitivity analysis was conducted to assess the impact of these parameters, emphasizing the need for optimal tuning. To generate training and test datasets efficiently, Latin hypercube sampling (LHS) was used. A convolutional neural network (CNN) surrogate model was trained, outperforming other machine learning (ML) algorithms in predictive accuracy and generalization. The proposed CNN-HBMO framework reduced computational costs by minimizing the need for expensive electromagnetic (EM) simulations, enabling rapid design space exploration. The optimized antenna was fabricated and validated through experimental measurements, achieving 2–3 dBi gain and 11 < − 10 dB across the 2.7–5.2 GHz band. Compared to existing designs, the proposed antenna offers a compact size (34 ×34 mm) with competitive performance, making it suitable for multi-band 5G applications

A Dual-Model AI Framework for Alzheimer’s Disease Diagnosis Using Clinical and MRI Data

Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that requires advanced diagnostic strategies for early and accurate detection. Methods: This study introduces a hybrid AI-driven diagnostic framework that integrates an Artificial Neural Network (ANN) trained on clinical data from 1,200 patients using 31 demographic, symptomatic, and behavioral features with a Convolutional Neural Network (CNN) trained on 4,876 MRI images to classify AD into four stages. Results and Discussion: The ANN achieved an accuracy of 87.08% in earlystage risk prediction, while the CNN demonstrated a superior 97% accuracy in disease staging, supported by Grad-CAM visualizations that improved model interpretability. This dual-model approach effectively combines structured clinical data with imaging-based analysis, addressing the sensitivity and scalability limitations of traditional diagnostic methods and providing a more comprehensive assessment of AD. Conclusion: The integration of ANN and CNN enhances diagnostic precision and supports AI-assisted clinical decision-making, with future work focusing on lightweight CNN architectures and wearable technologies to enable broader accessibility and earlier intervention

Depth Defect Analysis of BaO Thin Films Doped with Cd Via Positron Annihilation Techniques

Thin films of pure and cadmium-doped barium oxide (BaO) with 2, 4, and 6 wt% Cd were made using the spin-coating method and placed on glass at 450°C. Atomic force microscopy (AFM) revealed coarse, textured surfaces with BaO crystallites ranging from 1.4 to 150 nm in size, depending on the Cd concentration. Optical properties were investigated using UV–visible spectroscopy, revealing high transparency and direct bandgap energies between 3.467 and 3.728 eV. Defects were studied using Doppler broadening spectroscopy (DBS), which showed that there were different types of defects linked to oxygen and barium. A correlation was observed between the S parameter of DBS, crystallite size, and optical bandgap. Additionally, positron annihilation lifetime spectroscopy (PALS) was used to study vacancy-type defects and verify the positron lifetimes connected to the S parameter. The results demonstrate that Cd doping significantly influences the microstructure, defect landscape, and optoelectronic properties of BaO thin films

Mapping Design and Creative Thinking in Architecture and Design: A SciMAT-Based Conceptual and Thematic Analysis

The aim of this research is to examine the conceptual and theoretical foundation of creative thinking and design thinking. In this study, a systematic literature review was conducted on the concepts of "design," "design thinking," "design-oriented thinking," creativity," and "creative thinking." The steps followed in the research were in the first stage the publications within the scope of the architecture and design disciplines that were examined; in the second stage the articles were critically reviewed, and the articles that were not relevant were excluded; and finally, bibliometric and content analysis of the selected articles were carried out. In addition, the current publication trends, sub-themes, and conceptual variations were visualized using specialized software. The analyses of the research were performed using the SciMAT (Science Mapping Analysis Software Tool) software through strategic diagrams, network maps, and thematic maps. It is possible to develop various clustering methods and conduct analyses using different bibliometric networks with the SciMAT program. The study's conclusions provide recommendations that emphasize current trends in design education and design studio softwarebased, as well as suggestions for future research

An Adaptive Hybrid Metaheuristic Algorithm for Lung Cancer in Pathological Image Segmentation

Background/Objectives: Histopathological images are fundamental for the morphological diagnosis and subtyping of lung cancer. However, their high resolution, color diversity, and structural complexity make automated segmentation highly challenging. This study aims to address these challenges by developing a novel hybrid metaheuristic approach for multilevel image thresholding to enhance segmentation accuracy and computational efficiency. Methods: An adaptive hybrid metaheuristic algorithm, termed SCSOWOA, is proposed by integrating the Sand Cat Swarm Optimization (SCSO) algorithm with the Whale Optimization Algorithm (WOA). The algorithm combines the exploration capacity of SCSO with the exploitation strength of WOA in a sequential and adaptive manner. The model was evaluated on histopathological images of lung cancer from the LC25000 dataset with threshold levels ranging from 2 to 12, using PSNR, SSIM, and FSIM as performance metrics. Results: The proposed algorithm achieved stable and high-quality segmentation results, with average values of 27.9453 dB in PSNR, 0.8048 in SSIM, and 0.8361 in FSIM. At the threshold level of T = 12, SCSOWOA obtained the highest performance, with SSIM and FSIM scores of 0.9340 and 0.9542, respectively. Furthermore, it demonstrated the lowest average execution time of 1.3221 s, offering up to a 40% improvement in computational efficiency compared with other metaheuristic methods. Conclusions: The SCSOWOA algorithm effectively balances exploration and exploitation processes, providing high-accuracy, low-variance, and computationally efficient segmentation. These findings highlight its potential as a robust and practical solution for AI-assisted histopathological image analysis and lung cancer diagnosis systems

Revisiting Workplace Mobbing: Tweets and Qualitative Analysis in Türkiye Case

The globality of mobbing points to huge influence of economic issues over social and societal aspects in the life dynamics of work. COVID-19 presents a new kind of crisis that transforms these factors and establishes new norms in working life simultaneously. Mobbing is to be defined, in this perspective, as the modifications of situation of work and expectations of workers retraining the boundaries and manifestation of mobbing. This study examines the impact of dislocating mobbing, which is a kind of violence that deteriorates the quality of life for employees as well as workplace productivity, in terms of the new dynamics of mobbing and existing dimensions of mobbing-the COVID-19 perspective. Mixed methods research was carried out through macrolevel collection and analysis of tweet data alongside micro-level focus group interviews. While macro findings identified general mobbing dimensions, micro findings revealed more indirect, implicit and specific means of power imbalance. The findings of the research identify emerging gaps in organisational practice regarding diversity and inclusion via the lens of increasing and latent specific power imbalances. In both data analyses, a new dimension of mobbing was identified: the perception of injustice. The emergence of injustice as a new dimension provides a more comprehensive perspective on current practices. The findings of this research are expected to provide valid approaches towards reiteration of existing organisational practices and human resources training

Wearable Technology for 2D MXene Based Supercapacitors

The growing demand for wearable electronics has intensified the need for lightweight, flexible, and highperformance energy storage systems. MXene-based supercapacitors have emerged as a promising solution due to their high electrical conductivity, large surface area, mechanical flexibility, and excellent electrochemical performance. These features enable rapid charge–discharge capability, long cycling stability, and seamless integration with flexible and stretchable substrates. This study reviews the application potential of MXene-based supercapacitors in wearable technologies such as health monitoring systems, fitness trackers, smart textiles, and AR/VR devices. In addition, key challenges, including large-scale production, oxidation stability, electrolyte compatibility, and mechanical durability, are discussed. Recent strategies to enhance material stability and device performance through surface modification and hybrid configurations are highlighted. MXene-based supercapacitors are expected to play a crucial role in the development of next-generation self-powered and smart wearable systems

Time-Varying Inflation Co-Movement: Dynamic Factor Model with Global, Group, and Country-Specific Factors

This study examines global inflation co-movement by employing a dynamic factor model with time-varying parameters and stochastic volatility to extract global, group, and country-specific factors across 86 developed and developing economies from 1971 to 2023. The results reveal that (i) the global factor has gradually receded as the primary source of inflation variation, giving way to more group- or country-specific dynamics—though brief episodes of global synchronization reemerge during major crises; (ii) the group factor dominates inflation variation in developed countries; and (iii) the country-specific factor remains the main driver of inflation in developing countries