Gazi University

This paper deals with improving the combustion performance of NH3 by mixing it with hydrogen-rich coal gases (HRCG). To this aim, temperature and NO emission profiles of NH3/Coke Oven Gas (COG) and NH3/Water Gas (WG) fuel mixtures were investigated. In addition, adiabatic flame temperature and laminar burning velocity (LBV) characteristics of the mixtures were also predicted, and all results obtained were compared with the predictions of the NH3/air blend. Adding COG or WG increased LBV and adiabatic flame temperature values consistent with the increasing amounts of HRCG in the fuel mixtures. For 45% mixing ratios of HRCG, the maximum LBV value of NH3/air increased by 216% and 149% whereas its’ maximum adiabatic flame temperature value increased by 5% and 4% when mixed with COG or WG, respectively. In addition, blending the NH3/air mixture with HRCG increased temperature distributions within the combustor. However, this promoted the NO formation of NH3/air flame. The main reason for the increase in NO emissions is that adding HRCG into the NH3/air mixture triggered the decomposition of NH3 in the fuels and caused higher flame temperatures. This finding was confirmed by estimating the concentrations of O, OH, and HNO radicals in the flame zone.

Objective Before commonly used targets such as the Retrogasserian Zone (RGZ) and the Root Entry Zone (REZ) were adopted for the radiosurgical treatment of trigeminal neuralgia (TN), a more anterior target involving the Gasserian ganglion was used. Thanks to advancements in imaging technology, it is now possible to identify and target separate nerve divisions in Meckel’s Cave as desired. Although this approach has been mentioned previously, no clinical study has investigated it until now. This study aims to fill this gap in the literature. Methods Trigeminal neuralgia patients who received radiosurgical treatment between February 2019 and June 2022 in a single centre were included in the study. Pain relief, medication dependency and side effect profiles of the investigated anterior selective target (AST) were compared to those of the classical targets at 1 week, 1–3-6 months, and 1 year. Results A total of 66 patients were included in the study. Effectiveness, safety and application convenience parameters were compared between; the REZ (n = 21), RGZ (n = 20) and AST (n = 25) groups. All groups showed significant improvement in pain with similar results to each other. AST treatments were performed in significantly shorter beam-on-times and with significantly lower brainstem doses. Conclusions The investigated AST showed comparable results to the classical targets without any indication of superiority or inferiority in terms of efficacy and safety in this preliminary investigation. As no blocks were needed to protect the brainstem with this method, it can be used for select patients as needed and could even be investigated in larger studies as an alternative approach.

Background Exacerbation is an independent risk factor for chronic obstructive pulmonary disease (COPD)-related morbidity and mortality. Despite optimal care, there may be risk factors that lead to difficulties in managing exacerbations that may be associated with prolongation of length of hospital stay (LOS). Methods This is a multicenter prospective observational study of COPD patients hospitalized with exacerbations. Prolonged LOS was calculated according to the 50th percentile and defined as ≥ 9 days. Potentially predicting factors of LOS were stratified into 4 pillars as patient-related, disease and exacerbation-related, treatment-related and, hospital utility-related. These categories were systematically documented throughout the duration of the hospitalization. Results A total of 434 patients, 361 males and 73 females, with a mean age of 69.2 ± 9.3 years, were included in the study. Variables of each pillar were tested with univariate analysis to identify potential risk factors for prolonged LOS. Subsequently significant factors excluding factors associated with hospital utility were tested with multivariate logistic regression analysis for detecting potential associated factors for difficult-to-manage COPD exacerbation. Biomass exposure, past history of non-invasive mechanical ventilation (NIMV), low bicarbonate levels at admission, antibiotic switching, need for theophylline, increasing oxygen requirement, need for in-hospital non-invasive mechanical ventilation, nutritional support and physiotherapy were found as defining factors. Conclusions The DiMECO study can help to identify COPD exacerbators who are at risk for prolonged hospitalizations that may associate with difficult-to-manage COPD exacerbations. Difficult to manage COPD exacerbation may serve as a provocative framework, underscoring the necessity for a better understanding of the multifaceted approaches to the management of COPD exacerbations. This conceptualization warrants further investigation across diverse clinical settings to validate its applicability and efficacy.

In this study, the far‐field characteristics of a plasma dielectric resonator antenna are investigated. The internal structure of the antenna is filled with a plasma material. Surface currents are obtained in an imaginary closed area formed at a certain point outside the plasma antenna. Then, the near field‐far field transformation is performed with the FFT method using the surface currents. The field distributions in the far field of the plasma antenna have been evaluated using three‐dimensional FDTD. The system has shown to work in multiband with wider bandwidths.

Observational skills, including radiologic perceptual abilities, are critical for medical professionals. Numerous studies have shown the positive impact of various visual art courses on observational skills. Some institutions have even incorporated art courses into their curriculum for this purpose. However, the underlying reason for this improvement remains unclear. This prospective, controlled study aims to determine the positive impact of a virtual art evaluation course on medical students’ radiologic labeling skills and to uncover the underlying reason. This study examines whether a 12-week art evaluation course with monitored attendance enhances medical students’ ability to detect brain abnormalities in MRI scans. Medical students participated in pre- and post-tests identifying abnormalities, while a control group received no intervention. The art course focused on elements such as composition and balance. MRI characteristics, such as the contrast-to-noise ratio (CNR), were measured to assess image quality. To evaluate test difficulty and student performance, the Discrimination Index (DI) was calculated. No significant difference was found in pre-test scores between the study and control groups (p = 0.35). A significant increase in post-test scores was observed in the study group (9.52 ± 3.11 vs. 10.69 ± 2.72, p = 0.04), compared to controls (8.69 ± 3.03 vs. 9.30 ± 2.88, p = 0.19). A moderate positive correlation was found between score improvement and course attendance in the art group (r = 0.42, p = 0.0407). Strong positive correlations were calculated between the DI and CNR in the art group (r = 0.511, p = 0.0205; r = 0.513, p = 0.0212). Virtual art courses, which are easy to organize and enjoyable educational activities, improve medical students’ radiologic labeling skills and are associated with an increase in their contrast sensitivity.

Background: Manually creating multiple-choice questions (MCQ) is inefficient. Automatic item generation (AIG) offers a scalable solution, with two main approaches: template-based and non-template- based (AI-driven). Template-based AIG ensures accuracy but requires significant expert input to develop templates. In contrast, AI-driven AIG can generate questions quickly but with inaccuracies. The Hybrid AIG combines the strengths of both methods. However, neither have MCQs been generated using the Hybrid AIG approach nor has any validity evidence been provided. Methods: We generated MCQs using the Hybrid AIG approach and investigated the validity evidence of these questions by determining whether experts could identify the correct answers. We used a custom ChatGPT to develop an item template, which were then fed into Gazitor, a template- based AIG (non-AI) software. A panel of medical doctors identified the answers. Results: Of 105 decisions, 101 (96.2%) matched the software’s correct answer. In all MCQs (100%), the experts reached a consensus on the correct answer. The evidence corresponds to the ‘Relations to Other Variables’ in Messick’s validity framework. Conclusions: The Hybrid AIG approach can enhance the efficiency of MCQ generation while maintaining accuracy. It mitigates concerns about hallucinations while benefiting from AI.

In this work, flexible transparent conductive silver nanowire (AgNW) electrodes were fabricated on polyethylene naphthalate (PEN) substrates using the aerosol jet printing (AJP) technique, providing a versatile and cost-effective alternative to conventional transparent conductive oxide (TCO) material production. Additionally, the impact of printing cycles on the transparency and surface resistivity of the electrodes was investigated. Ultraviolet–visible (UV–Vis) spectrometry, optical microscopy, and four-point probe techniques were used to characterize the obtained AgNW electrodes. When the three-cycle printing process was applied, AgNW electrodes with sheet resistance of 30.96 Ω/sq and average transparency of 78% in the visible region were obtained. This means that the electrodes produced with both good properties and flexibility can be used in several optoelectronic and electrochemical applications.

Tinkering learning is a pedagogical strategy that emphasizes hands-on exploration, experimentation, and learning from mistakes in STEM education. It involves using personal fabrication tools, such as a 3D printer, to develop and improve ideas through interactive play. Design-based making activities have gained popularity in K-12 classrooms as they provide students with this authentic learning experience. This descriptive case study aims to understand the impact of students' interactions with a 3D printer on their tinkering learning during a formal design-based making activity. Specifically, the study explores what types of learning paths students follow when developing and improving their ideas through tinkering and what factors negatively affect this iterative design experience. In this design-based making activity, students tinker both in the digital world with Tinkercad and in the physical world with a 3D printer. Approaching real-world problems through iterative design can change their production-oriented actions. To understand the impact of this change on their tinkering learning, the study observes students’ actions and collects their reflections on their tinkering through multiple surveys. The analysis revealed that students followed one of three different paths that led to varying levels of tinkering learning and that their tinkering experiences were negatively impacted by five major factors.

The aim of this study is to investigate the activity of KIT‐6 supported nickel (Ni) and cobalt (Co) catalysts, and the effect of Co incorporation to the Ni@KIT‐6 catalyst in the formic acid (FA) dehydrogenation. Ni and Co are inexpensive and readily available non‐noble transition metals that are considered ideal for dehydrogenation reactions due to their high activity against C‐C and C‐H bond breaking. In this study, KIT‐6 supported catalysts were tested for hydrogen production from FA in a conventionally heated packed‐bed continuous‐flow system. N2 adsorption‐desorption isotherms of the samples were found to be consistent with Type‐IV according to the International Union of Pure and Applied Chemistry (IUPAC) classification. The introduction of metal loading resulted in the preservation of the mesoporous structure of the support material. X‐ray diffraction (XRD) patterns of the catalysts exhibited the characteristic amorphous silica structure. Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFT) analysis, Lewis acidity of Co‐based catalysts was found to be higher than the Ni‐based catalysts. The complete formic acid conversion was observed at 200‐350 °C. The highest H2 selectivity was obtained with the 3Ni@KIT‐6 catalyst. The Co‐based catalysts exhibited relatively lower catalytic activity, which was linked to increased coke formation within these catalysts.

In this article, we examine two problems: a fractional Sturm-Liouville boundary value problem on a compact star graph and a fractional Sturm-Liouville transmission problem on a compact metric graph, where the orders {\alpha }_{i} of the fractional derivatives on the ith edge lie in (0,1) . Our main objective is to introduce quantum graph Hamiltonians incorporating fractional-order derivatives. To this end, we construct a fractional Sturm-Liouville operator on a compact star graph. We impose boundary conditions that reduce to well-known Neumann-Kirchhoff conditions and separated conditions at the central vertex and pendant vertices, respectively, when {\alpha }_{i}\to 1 . We show that the corresponding operator is self-adjoint. Moreover, we investigate a discontinuous boundary value problem involving a fractional Sturm-Liouville operator on a compact metric graph containing a common edge between the central vertices of two star graphs. We construct a new Hilbert space to show that the operator corresponding to this fractional-order transmission problem is self-adjoint. Furthermore, we explain the relations between the self-adjointness of the corresponding operator in the new Hilbert space and in the classical {L}^{2} space.

The HCCI combustion mode has the critical advantages of avoiding locally rich mixtures, reducing gas temperatures, and minimizing NOx and PM emissions. However, these advantages come with problems, such as knock risk, difficulty starting combustion, control of the combustion phase, and limited operating range. In order to eliminate these problems, engine operating conditions, and fuel properties must be controlled simultaneously. For this purpose, a numerical model created using Converge CFD software has been validated with experiments. In the combustion analysis, oxygen-containing alcohol derivatives (methanol, ethanol, and butanol) were used as low-reactivity fuels, and n-heptane was used as a high-reactivity fuel. According to the results, fuels containing 10% alcohol caused knocking at high loads, while optimum operating conditions were obtained with increasing alcohol content. When B10, E10, and M10 fuels were analyzed, the highest pressure was recorded as 4.04 MPa for E10 fuel under common operating conditions with an equivalence ratio of 0.45. With increasing alcohol content, CA50 shifted to after TDC, and ITE increased. The highest ITE of 40.22% was obtained at an equivalence ratio of 0.35 using E20 fuel. Under similar operating conditions, the ITE values for B20 and M20 fuels were found to be 37.26 and 34.08%, respectively. It was observed that the MPRR decreased with increasing alcohol content and leaner mixture. The lowest average MPRR was obtained with M20 fuel. It was found that using alcohol-derived mixture fuels in HCCI combustion mode in low compression ratio engines positively affects engine performance.

Objectives Acute central nervous system (CNS) infections in children can lead to neurological complications and mortality. This study aimed to identify the clinical manifestations, laboratory parameters, and cerebrospinal fluid characteristics indicative of CNS infections and define the risk factors that lead to pediatric intensive care unit (PICU) admission in the pediatric population of Şanlıurfa, a city in southeastern Turkey. Methods This retrospective analysis included patients aged 1 month to 18 years who were treated for acute CNS infections in the Şanlıurfa Training and Research Hospital between January 2020 and May 2023. Clinical data were obtained from the hospital electronic medical records. Results A total of 68 patients with acute CNS infections were included in this study. The median patient age was 3 (0.94–8.75) years. Fever was the most prevalent symptom in 92.6% of the patients. Of the total, 25% (n = 17) of the patients had an identified causative agent and 35.3% (n = 24) were admitted to the PICU. Serum C-reactive protein (CRP) levels were significantly higher in patients with bacterial meningitis than in those with viral meningitis (p = 0.007). Patients with impaired consciousness and seizure were significantly more likely to require admission to the PICU than patients without these conditions (both p < 0.001). Patients requiring PICU admission had significantly higher platelet counts (p = 0.01). Conclusions Impaired consciousness, seizure, and thrombocytosis on admission were important risk factors for PICU admission. Serum CRP levels can serve as an indicator of bacterial meningitis. A combination of physical findings from clinical evaluations and laboratory data is necessary to accurately diagnose bacterial CNS infections.

This study examines the diffusion bonding of 316 L stainless steel and H13 hot work tool steel, aiming to optimize process parameters and assess the resulting microstructural and mechanical properties. Both materials were bonded at varying temperatures (700, 750, and 850 °C) and times (15, 30, and 60 min). The joints are analyzed using scanning electron microscopy (SEM), energy‐dispersive spectroscopy, and X‐ray diffraction (XRD) to evaluate interfacial morphology, chemical composition, and phase formation. Microhardness measurements indicate an increase in hardness from the 316 L side to the H13 side, suggesting intermetallic phase formation. Shear strength tests show the highest strength at 850 °C for 30 min, with longer times leading to strength reduction due to brittle intermetallic compounds. SEM analysis reveals improved bonding interfaces with fewer voids at higher temperatures and longer times, but the Kirkendall effect causes void formation, negatively impacting mechanical properties. XRD confirms α‐Fe and γ‐Ni phases, with Fe 3 C forming at 850 °C for 60 min. This study underscores the importance of process parameters in optimizing joint properties and minimizing brittle phase formation, providing insights for industrial applications requiring robust and corrosion‐resistant joints.