Analysis of the impact of the viscoelastic foundation on bending and vibration of fg porous nanoplates within integral higher-order shear deformation theory

Abstract: This work examines the bending and vibration responses of a functionally graded (FG) 2D nanostructure resting on the viscoelastic foundation. The FG structure properties vary gradually in the thickness direction. In this investigation, three porosity patterns are examined. The nonlocal equilibrium equations are derived by Hamilton’s principle using Eringen’s nonlocal elasticity theory, which incorporates the integral plate theory with a reduced number of unknowns. The results computed for the studied simply supported FG nanoplates are compared with those published in the open literature. Several parametric studies are performed to illustrate various influences of the plate geometry, material inhomogeneity, elastic damping coefficient, and nonlocal effect on the stresses, frequency, and central deflection of FG nanoplates

Cardiometabolic risk in non-diabetic metabolic dysfunction-associated steatotic liver disease (MAFLD) patients: insights from the triglyceride-glucose, plasma atherogenic, and cardiometabolic index

Introduction: The objective of our study was to examine the correlation between hepatosteatosis and the triglyceride-glucose index (TyG), plasma atherogenic index (PAI), and cardiometabolic index (CMI) in nondiabetic patients. We also aimed to assess the usefulness of these indices in evaluating cardiometabolic risk in metabolic dysfunction-associated steatotic liver disease (MAFLD). Material and methods: This retrospective cross-sectional study included 695 individuals who did not have diabetes, with an average age of 39.8 ±11.3 years. A total of 595 individuals, comprising 359 women and 236 men, were diagnosed with MAFLD. The control group consisted of 100 individuals who did not have MAFLD. All the subjects underwent transabdominal ultrasonography, anthropometric measurements, and blood analyses. The groups were assessed based on the TyG index, PAI, and CMI. Results: TyG, PAI, and CMI were greater in patients with MAFLD than those without MAFLD. The TyG index, with a cutoff point of 8.47, excluded significant simple steatosis with a sensitivity of 65.3% and a specificity of 66.0%. The PAI and CMI cutoff values were 0.39 and 1.40, with sensitivities of 66.6% and 70.1% and specificities of 67.0% and 70.1%, respectively. The TyG index was independently associated with MAFLD (OR = 2.21, 95% CI: 1.339–3.665). Conclusions: The presence of MAFLD patients with a normal BMI and waist circumference indicates that these variables alone do not provide enough evidence for the diagnosis of MAFLD. Hence, it is advisable to incorporate the TyG index, the PAI, and the CMI into regular clinical practice to obtain a more precise and thorough evaluation of MAFLD and cardiometabolic risk

Can a large language model judge a child’s statement?: a comparative analysis of ChatGPT and human experts in credibility assessment

Purpose: This study investigates the inter-rater reliability between human experts (a forensic psychologist and a social worker) and a large language model (LLM) in the assessment of child sexual abuse statements. The research aims to explore the potential, limitations, and consistency of this class of AI as an evaluation tool within the framework of Criteria-Based Content Analysis (CBCA), a widely used method for assessing statement credibility. Materials and methods: Sixty-five anonymized transcripts of forensic interviews with child sexual abuse victims (N = 65) were independently evaluated by three raters: a forensic psychologist, a social worker, and a large language model (ChatGPT, GPT-4o Plus). Each statement was coded using the 19-item CBCA framework. Inter-rater reliability was analyzed using Intraclass Correlation Coefficient (ICC), Cohen’s Kappa (κ), and other agreement statistics to compare the judgments between the human-human pairing and the human-AI pairings. Results: A high degree of inter-rater reliability was found between the two human experts, with the majority of criteria showing “good” to “excellent” agreement (15 of 19 criteria with ICC >.75). In stark contrast, a dramatic and significant decrease in reliability was observed when the AI model’s evaluations were compared with those of the human experts. The AI demonstrated systematic disagreement on criteria requiring nuanced, contextual judgment, with reliability coefficients frequently falling into “poor” or negative ranges (e.g. ICC = -.106 for “Logical structure”), indicating its evaluation logic fundamentally differs from expert reasoning. Discussion: The findings reveal a profound gap between the nuanced, contextual reasoning of human experts and the pattern-recognition capabilities of the LLM tested. The study concludes that this type of AI, in its current, prompt-engineered form, cannot reliably replicate expert judgment in the complex task of credibility assessment. While not a viable autonomous evaluator, it may hold potential as a “cognitive assistant” to support expert workflows. The assessment of child testimony credibility remains a task that deeply requires professional judgment and appears far beyond the current capabilities of such generative AI models

The relationship between bacterial changes and dietary intervention in non-alcoholic fatty liver disease

Background and aim: This study aimed to investigate the levels of Faecalibacterium prausnitzii (F. prausnitzii) and Eubacterium rectale (E. rectale) in patients with non-alcoholic fatty liver disease (NAFLD) and evaluate the impact of dietary intervention on these bacterial populations. Materials: An interventional study was conducted with 38 NAFLD patients recruited from the Marmara University Gastroenterology Institute. Participants were divided into two groups: a diet intervention group (n = 21) and a control group (n = 17). The dietary intervention consisted of a balanced diet containing 50–55 % carbohydrates, 30–35 % fats, and 15–20 % protein. Fecal samples were collected at baseline and after six weeks for both groups, and bacterial quantification was performed via deoxyribonucleic acid (DNA) analysis of the fecal samples. Results: In the diet intervention group, a significant increase in E. rectale abundance was observed after six weeks (p = 0.008). Additionally, intakes of dietary fiber, vitamin E, vitamin C, and thiamine were significantly higher in the intervention group compared to the control group by the end of the study (p < 0.05). However, no significant changes were detected in F. prausnitzii levels in either group. Conclusion: The findings demonstrate that dietary intervention can significantly increase E. rectale abundance in NAFLD patients, while F. prausnitzii levels remain unaffected. These results highlight the selective influence of dietary modifications on gut bacterial populations, offering potential implications for the management of NAFLD.Marmara University SAG-C-YLP-110618-030

Gendered dynamics of rural livelihood diversification: Tea farmers in the Black Sea Region of Turkey

This study examines the gendered dynamics of rural livelihood diversification in tea farming communities in Rize, Turkey, with the onset of neo-liberal policies. Drawing on extensive fieldwork, the research explores how migration, access to education, and land ownership intersect with the unique characteristics of tea farming, such as its seasonal harvest cycle and labour-intensity, to shape gendered labour division. It highlights how migration intensifies the feminisation of agriculture by increasing women's agricultural and domestic responsibilities. Additionally, education, while a potential pathway for mobility, often reinforces traditional gender roles for female students balancing household duties, agricultural work, and studies. Finally, the study underscores how patriarchal norms in land ownership, marginalise women and consolidate male control over land, perpetuating structural inequalities. By situating these findings within the specific socio-economic and ecological context of tea farming, this study contributes to broader debates on rural livelihood diversification, gender inequalities, and the intersection of agricultural practices with neo-liberal economic policies

Sketchup Commands

12. Hafta Ders Notu Konusu : Sketchup Command

Piperonal-derived Schiff base molecules as potential multi-target therapeutic agents against Alzheimer’s and diabetes

Background: The dual burden of diabetes and Alzheimer’s highlights the urgent need for multifunctional therapeutic agents. This study explores piperonal-derived Schiff base derivatives as potential dual-action enzyme inhibitors against α-amylase (AA), α-glucosidase (AG), acetylcholinesterase (AChE), and butyrylcholinesterase (BChE), offers a promising strategy for managing both conditions. Methods: Schiff base derivatives of piperonal (heliotropin) were synthesized, structurally characterized, and explored against established drug targets of diabetes mellitus (DM) and Alzheimer’s disease (AD). Results: Compounds 7 (IC50 = 5.73 ± 0.01; 3.52 ± 0.02 µM) and 17 (IC50 = 10.91 ± 0.02; 7.38 ± 0.02 µM) showed potent inhibitory effects against AG and AA enzymes, in comparison to acarbose (IC50 = 14.98 ± 0.02 µM; 14.64 ± 0.02 µM). However, analogs 7, 9, 10, 14, and 15, compounds 7 (IC50 = 2.92 ± 0.02; 3.34 ± 0.02 µM) and 9 (IC50 = 8.16 ± 0.03; 7.19 ± 0.03 µM) showed remarkable inhibitory results against AChE and BChE, respectively, compared to standard donepezil chloride (IC50 = 37.89 ± 0.02 µM; 41.56 ± 0.03 µM). Comprehensive kinetic analyses and molecular docking supported findings by invitro studies. Synthesized derivatives were also checked for their antioxidant potential and demonstrated significant activity. Conclusion: These complementary studies highlight several hit candidates for further development as therapeutic agents against DM and AD

Urban energy efficiency in China: Examining the role of renewable energy, smart Grids, and sustainable design through spatial and policy perspectives (1990–2022)

The study investigates urban energy efficiency in China from 1990 to 2022 via the perspectives of renewable energy, smart grids, sustainable architecture, and regulatory assistance using Sustainable Development Goals 7 (Affordable and Clean Energy) and 13 (Climate Action). Switching to renewable energy reduces carbon emissions (SDG-13) and boosts clean, inexpensive power (SDG-7). Smart grids (SDG-7) improve energy supply efficiency and reliability by integrating renewables and reducing energy waste. Making cities and infrastructure more energy efficient is Goal 7 of sustainable development to decrease emissions. Regulating these technologies and behaviors promotes widespread application and climate resilience (SDG-13) via policies and incentives. The study uncovers compelling insights by utilizing a robust methodology, specifically the Generalized Method of Moments. Renewable energy penetration (β = -1.479, p < 0.000), energy-efficient urban design (β = -1.816, p < 0.000), and public transportation adoption (β = -0.631, p < 0.028) exhibit negative correlations with urban energy efficiency. Conversely, implementing innovative grid technology (β = 2.386, p < 0.000) and utilizing building energy management systems (β = 0.337, p < 0.000) demonstrate positive impacts on urban energy efficiency. Exploration uses the impulse response function to predict future dynamics. Advanced grid integration is likely to reduce urban energy efficiency, while sustainable urban design is expected to improve it during the next decade. Variance decomposition study shows that renewable energy sources influence urban energy efficiency changes the greatest. After that, smart grid adoption, building energy efficiency, policy and regulatory assistance, and sustainable public transport decreased in importance. The results provide insights into greener city design, smarter grids, and increased use of renewable power sources in urban energy policy and practice. Energy-efficient and emission-reducing regulations may also improve sustainable urban development and climate resilience

Accuracy of electronic apex locators during retreatment with organic gutta-percha solvents

Background: This study aimed to compare the accuracy of electronic apex locators (EALs) during the retreatment procedure using organic gutta-percha solvents. Methods: The actual working length (AWL) was determined with a stereomicroscope on 72 single-rooted teeth selected for the study. After the obturation, the teeth were embedded in an alginate mold and divided into 3 groups (n = 24) based on the gutta-percha solvent used: eucalyptol, turpentine, and orange oil. Once the solvents were applied, the WL was measured using the Root ZX Mini and Woodpex III. Two-way ANOVA and Fisher’s exact test were performed using SPSS with a 5% significance threshold. Results: There was no significant difference in the accuracy of the EALs among the solvent groups (p > 0.05). Root ZX Mini showed accuracies of 40%, 41.7%, and 80% within ±0.5 mm for eucalyptol, turpentine, and orange oil, respectively, while the corresponding values for Woodpex III were 30%, 41.7%, and 70%. No overestimation (deviation from AWL > 0.5 mm) was observed with either device when orange oil was used. Conclusion: Different types of EALs demonstrated acceptable determination of WL when using different gutta-percha solvents. The absence of overestimation in the orange oil group may affect clinical preferences

An investigation of nile tilapia (oreochromis niloticus) movement trajectories under ammonia stress using image processing techniques

This study examined the behavioral responses of Nile Tilapia (Oreochromis niloticus), a key aquaculture species, to ammonia stress using non-invasive image processing techniques. The experiment was conducted under controlled laboratory conditions and involved four groups exposed to ammonium chloride concentrations (0, 100, 200, and 400 mg·lt−1). Movement trajectories of individual fish were recorded over 10 h using high-resolution cameras positioned above and beside glass tanks. Images were processed with the Optical Flow Farneback algorithm in Python, implemented in Visual Studio Code with OpenCV and NumPy libraries, achieving a 91.40% accuracy rate in tracking fish positions. The results revealed that increasing ammonia levels restricted movement areas while elevating movement irregularity and activity. The 0 mg·lt−1 group utilized the glass tank homogeneously, covering 477 m. In contrast, the 100 mg·lt−1 group showed clustering in specific areas (796 m). At 200 mg·lt−1, clustering intensified, particularly along the glass tank’s left edge (744 m), and at 400 mg·lt−1, fish exhibited severe restriction near the water surface with markedly increased activity (928 m). Statistical analyses using Kruskal–Wallis and Dunn tests confirmed significant differences between the 400 mg·lt−1 group and others. No difference was observed between the 0 mg·lt−1 and 100 mg·lt−1 group, indicating tolerance to lower concentrations. The study highlights the importance of ammonia levels in water quality management and reveals the potential of image processing techniques for automation and stress monitoring in aquaculture