Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/1364
  Deep learning-based detection of bowel sound events in continuous recordings

  Çelik, Yusuf

  Accurate identification of bowel sound events is essential for the long-term and non-invasive monitoring of gastrointestinal activity. In this study, we present a band-aware multi-band deep learning approach that explicitly accounts for the distinct acoustic characteristics of bowel sounds across different frequency ranges by jointly analyzing low- and high-frequency components. The proposed method operates on time–frequency representations extracted from continuous recordings to produce frame-level bowel sound probabilities, which are subsequently integrated into recording-level decisions through a unified decision-making strategy. Despite the pronounced class imbalance in the dataset, the proposed system achieved accuracy levels exceeding 98% at the frame level and 99% at the recording level, yielding stable and consistent outcomes through probability aggregation and temporal smoothing steps. These results indicate that the proposed approach provides a reliable and well-structured framework for bowel sound event detection and establishes a solid methodological basis for the analysis of long-duration recordings.

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  AtıfScopus2·WoS2·OpenAlex2

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/1335
  The effect of hydrostatic water level on the local scour downstream of plunging aerated jets

  Tunc, Mustafa; Aytac, Ayca; Tuna, M. Cihat; Acar, Ramazan

  This paper reports an experimental study on the effect of hydrostatic water level on local scour downstream of plunge aerated jets. To examine the shape of the scour for non-cohesive bed material, different flow and air rates, and different aeration capabilities, hydrostatic water level circumstances were tested. The water jets were aerated using conduit systems with varying cover opening ratios. Measurements were made to determine the length of the scour hole, the value of the maximum scour depth, the location of the maximum scour depth, and the scour hole profile in equilibrium. The current findings show that downstream hydrostatic water levels have a significant impact on the maximum depth and area of scour. Additionally, it was discovered that the conduit gate opening ratio and aeration performance (Qa/Qw) are crucial factors that affect the geometry and diameters of scour holes. The properties of scour caused by various hydrostatic levels were systematically compared to develop empirical correlations for predicting the maximum scour depth. Consequently, predictive emprical formulas incorporating these hydrostatic variations and aeration parameters are presented to improve engineering design accuracy.

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  İncele
• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/1289
  The relationship between empathy levels of obstetrics and gynecology specialists and their attitudes toward posthumous organ donation

  ÖZBEY, Gürkan; YEŞİLTEPE, Akgün; Dokuzcan, Deniz Aslı

  Empathy is recognized as a critical factor in shaping attitudes toward organ donation among healthcare professionals. Given the continuous patient interaction and decision-making roles of obstetrics and gynecology specialists, the limited number of studies examining the link between empathy levels and attitudes toward postmortem organ donation represents a significant gap in literature. This study aims to investigate the relationship between empathy levels and attitudes toward postmortem organ donation among obstetrics and gynecology specialists. This correlational cross-sectional study included 142 obstetrics and gynecology specialists. Data were collected via Google Forms using a personal information form, the Toronto Empathy Questionnaire, and the Attitude toward Posthumous Organ Donation for Transplantation Scale. Analyses were conducted using SPSS 26 and JASP 0.19, including the Spearman’s correlation, Mann-Whitney U, Kruskal-Wallis, and Machine Learning-Random Forest regression analysis methods. 93% of the participants stated that their empathy levels influenced organ donation decisions, and 74.6% reported considering organ donation. Their mean TEQ score was 56.25 ± 7.51, while their mean APODS score was 4.37 ± 0.57. A statistically significant moderate positive correlation was found between empathy and general attitudes toward postmortem organ donation (r = 0.428, p < 0.05). Statistically significant, weak-to-moderate positive correlations were also found between empathy levels and the APODS Positive Attitudes dimension (r = 0.373 p < 0.01), Religion dimension (r = 0.266, p < 0.01), and Family Approval dimension (r = 0.352, p < 0.01) scores of the participants. Significant differences were observed in empathy scores based on gender, empathy levels, and organ donation consideration status (p < 0.05). Attitudes toward posthumous organ donation also varied significantly by empathy levels, donation consideration status, ethical/humanitarian perception of donation, and religious influence (p < 0.05). In the exploratory Random Forest model, attitudes toward organ donation had the highest relative contribution to model performance. Obstetrics and gynecology specialists exhibit moderate empathy levels and highly positive attitudes toward posthumous organ donation. Higher empathy scores were associated with more favorable attitudes toward organ donation among obstetrics and gynecology physicians. Interventions addressing empathy and donation awareness may be valuable, but their effects on attitudes and donation-related behavior should be tested in longitudinal and interventional studies.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/1136
  Quantifying agricultural resilience under climate variability: a data-driven climate resilience index for European cereal systems

  Utku, Anil; Radulescu, Magdalena; Barut, Abdulkadir; Alofaysan, Hind

  Climate variability and extreme weather events pose an increasingly serious threat to agricultural productivity in Europe. Although many studies have focused on the mean yield response to climate change, relatively few have attempted to offer a comprehensive, multi-dimensional view of agricultural resilience, separating long-term productivity trends from short-term climate-induced fluctuations. In this paper, a data-driven Climate Resilience Index is proposed to assess the resilience of European cereal systems under climate stress. Annual yield time series are decomposed into trend and anomaly components to identify interannual deviations driven by climate variability. Machine learning and deep learning algorithms, including RF, CatBoost, CNN, LSTM, TCN, and a TCN-LSTM hybrid model, are used to assess the predictive validity of climate extreme indices and persistence patterns. Among the evaluated models, the TCN-LSTM architecture achieved the highest predictive performance with 0.8347 R2, outperforming standalone temporal and ensemble-based models. The PCA-based exposure framework explained 68.4% of the total climate variability within the first principal component, indicating a highly concentrated climate-stress structure. Feature importance analyses further revealed that lagged yield anomalies and rolling volatility indicators were the dominant predictors of resilience dynamics. The findings show that temporal models perform better than traditional ensemble methods, emphasizing the significance of multi-year recovery mechanisms in anomaly evolution. To provide a consistent measure of exposure, principal component analysis is used to reduce correlated climate indicators into a multi-dimensional climate stress index. The CRI captures these three essential elements: climate exposure, yield variability, and recovery. The results at the country level show substantial variability across Europe, indicating that while exposure intensity is important, recovery dynamics are also critical to understanding resilience. The results also show that there are structurally distinct resilience profiles, and robustness tests indicate that country rankings are not sensitive to different weights and recovery functions. The results clearly show that recovery and adaptive capacity are critical to agricultural sustainability amid growing climate uncertainty. The CRI developed in this paper provides a clear, empirically valid framework for comparing resilience in agricultural systems.

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  AtıfScopus1·OpenAlex2

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/908
  A two-stage volunteer assignment model for post-disaster search and rescue operations

  Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet

  Effective volunteer management requires ensuring operational continuity and maximizing benefits from all team members. Prioritizing volunteers with adequate knowledge and experience in task assignments is crucial for maintaining workflow continuity. This study employs a two-stage model for allocating areas and tasks to volunteers in search and rescue operations. The first stage identifies the optimal number of volunteer response centers using the P-median problem. Considering population density as demand, 7 out of 14 accessible and protected disaster collection areas meeting basic needs are selected as optimal response centers based on distance. In the second stage, a mixed-integer programming model is proposed for volunteer assignment, which prioritizes assigning the most knowledgeable and experienced volunteers to critical positions. The model’s flexibility and applicability are demonstrated by incorporating voluntary rest periods, which are allocated based on the urgent needs of response centers in various post-disaster scenarios. Solved using GAMS/CPLEX, the model’s results show that expert volunteers in low-demand scenarios are prioritized, working 5 out of 9 shifts, while other volunteers receive insufficient assignments. In high-demand scenarios, some response centers face volunteer shortages, with a deficit of 62 volunteers across 9 shifts in non-emergency areas. The study evaluates the benefits and drawbacks of the volunteer assignment model and offers recommendations for future research.

  AtıfScopus2·WoS2·OpenAlex3

  İncele
• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/725
  Optimization of scours downstream of conduit aerators

  Arici, Erdinc; Tuna, M. Cihat; Aytac, Ayca; Acar, Ramazan; Tunc, Mustafa

  Dams, wastewater treatment plants, and aquaculture areas often require aeration, making it crucial for hydraulic engineers to predict the physical properties of scour holes occurring on the downstream side of conduits. Conduit systems that provide high aeration performance necessitate multiple optimization studies to simultaneously maximize the scour parameters and the system’s physical properties. In this study, the physical parameters of conduit systems and downstream scour parameters were optimized using Artificial Neural Networks (ANN). The optimum system parameters were identified based on the experimental results through ANN-based optimization. Additionally, the real and optimal effects of the parameters on aeration performance and scour were determined. The results of the study demonstrated that ANN can be effectively used in studies aimed at optimizing the aeration performance and scour values of conduits. This study is the first to apply ANN for the simultaneous optimization of both aeration efficiency (Qa/Qw) and scour characteristics (dmax and δ) in a conduit-based hydraulic system. Previous studies have typically focused on either scour or aeration individually; this study integrates both through a multi-objective ANN model. The findings provide novel insights for the design and retrofitting of energy-dissipating conduit structures in high-head dam applications. Unlike traditional empirical or regression-based approaches, the ANN model captures complex, nonlinear relationships among multiple interacting hydraulic variables. It identified optimal parameter combinations — such as 70% gate opening, 1.30–1.50 m conduit length, and 9 mm air hole diameter — that improve both aeration and scour behavior. These outcomes offer direct applicability for real-world hydraulic system optimization.

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  AtıfOpenAlex1

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• MakaleAçık Erişim2025Scopus SJRQ1/r/munzur/1363
  One-pot synthesis of quercetin-functionalized silver and copper nanoparticles for enhanced optical, antimicrobial, and computational properties

  Aziz, Dara Muhammed; Amin, Alla Ahmed Muhammed; Hassan, Sangar Ali; Özmen, Habibe; INCILI, Gökhan Kursad; Say, Yakup

  The emergence of multidrug-resistant bacterial strains has intensified the need for novel antimicrobial agents. Herein, we report a facile one-pot green synthesis of quercetin-stabilized silver (Qn@AgNPs) and copper (Qn@CuNPs) nanoparticles using quercetin as both reductant and capping ligand. The resulting nanocomposites were fully characterized by UV–Vis spectroscopy (surface plasmon resonance peaks at 420 nm for Ag and 580 nm for Cu), FTIR (confirming quercetin–metal coordination), SEM/EDX (spherical particles, and XRD (face-centered cubic Ag and Cu phases). Density functional theory (B3LYP/3-21G) calculations yielded frontier molecular orbital gaps of 0.164 eV for Qn@AgNPs and 0.245 eV for Qn@CuNPs, with corresponding high softness values (12.20 and 8.16 eV⁻¹), indicating enhanced electron-transfer propensity. Molecular electrostatic potential maps revealed increased charge polarization around the metal centers. Antibacterial assays against Escherichia coli and Staphylococcus aureus demonstrated minimum inhibitory concentrations of 2.11 ± 1.22 µg/mL and 4.69 ± 2.68 µg/mL for Qn@AgNPs, and 7.50 ± 0.00 µg/mL and 6.25 ± 0.17 µg/mL for Qn@CuNPs, significantly outperforming free quercetin (188 and 375 µg/mL). In silico docking against the S. epidermidis TcaR regulator (PDB: 1KZN) and E. coli DNA gyrase B (PDB: 1HSK) revealed strong binding affinities (–7.54 to − 10.15 kcal·mol⁻¹), consistent with the observed antimicrobial potency. This integrated experimental–computational study elucidates the mechanistic underpinnings of quercetin-mediated nanoparticle bioactivity and provides a rational framework for designing next-generation flavonoid-functionalized metal nanotherapeutics.

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  AtıfScopus12·WoS11·OpenAlex14

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• MakaleAçık Erişim2023Scopus SJRQ1/r/munzur/2188
  The effect of oral administration of undenatured type II collagen on monosodium iodoacetate-induced osteoarthritis in young and old rats

  Sahin, Emre; Orhan, Cemal; Erten, Fusun; Saiyed, Zainulabedin; Azari, Elnaz Karimian; Durkee, Shane; Sahin, Kazim

  We investigated whether different doses of undenatured type II collagen (undenatured collagen, UC-II) help improve monosodium iodoacetate (MIA)-induced (osteoarthritis) OA in young and old rats. A total of 70 rats were divided into five groups: (1) control; (2) MIA (a single intra-articular injection of MIA); (3)–(5) MIA+ Undenatured Collagen with various oral doses (0.66, 1.33, and 2 mg/kg). The results showed that all doses of undenatured collagen in both age groups reduced knee diameter, while the two higher doses (1.33 mg/kg and 2 mg/kg) reduced the Mankin score and increased most gait measurements as early as day 14 compared to the MIA rats. However, the 2 mg/kg dose showed the best efficacy in improving Mankin score and gait measurements by 28 days post-OA induction. In young but not old rats, all doses of undenatured collagen reduced the Kellgren-Lawrence score compared to the MIA group. Undenatured collagen reduced the levels of most inflammatory and cartilage breakdown markers in serum and knee joint cartilage in both age groups. In conclusion, this data suggests that while all doses of undenatured collagen supplementation may ameliorate MIA-induced OA symptoms, the higher doses showed faster improvement in gait measurements and were more efficacious for overall joint health in rats.

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  AtıfScopus17·WoS17·OpenAlex15

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• MakaleAçık Erişim2022Scopus SJRQ1/r/munzur/2846
  Free convective trickling over a porous medium of fractional nanofluid with MHD and heat source/sink

  Lin, Yuanjian; Rehman, Sadique; Akkurt, Nevzat; Shedd, Tim; Kamran, Muhammad; Qureshi, Muhammad Imran; Botmart, Thongchai; Alharbi, Abdulaziz N.; Farooq, Aamir; Khan, Ilyas

  Nanofluids are considered as smart fluids that can improve heat and mass transfer and have numerous applications in industry and engineering fields such as electronics, manufacturing, and biomedicine. For this reason, blood-based nanofluids with carbon nanotubes (CNTs) as nanoparticles in the presence of a magnetic field are discussed. The nanofluid traverses the porous medium. The nanofluids move on a vertical plate that can be moved. The free convection heat transfer mode is considered when the heat source and heat fluxes are constant. Convective flows are often used in engineering processes, especially in heat removal, such as geothermal and petroleum extraction, building construction, and so on. Heat transfer is used in chemical processing, power generation, automobile manufacturing, air conditioning, refrigeration, and computer technology, among others. Heat transfer fluids such as water, methanol, air and glycerine are used as heat exchange media because these fluids have low thermal conductivity compared to other metals. We have studied the effects of MHD on the heat and velocity of nanofluids keeping efficiency in mind. Laplace transform is used to solve the mathematical model. The velocity and temperature profiles of MHD flow with free convection of nanofluids were described using Nusselt number and skin friction coefficient. An accurate solution is obtained for both the velocity and temperature profiles. The graph shows the effects of the different parameters on the velocity and temperature profiles. The temperature profile improved with increasing estimates of the fraction parameter and the volume friction parameter. The velocity of the nanofluid is also a de-escalating function with the increasing values of the magnetic parameter and the porosity parameter. The thickness of the thermal boundary layer decreases with increasing values of the fractional parameter.

  AtıfScopus13·OpenAlex12

  İncele
• MakaleYayıncıda açık erişim2022Scopus SJRQ1/r/munzur/2824
  Compressible unsteady steam flow and heat transport analysis: a numerical investigation

  Hussain, Azad; Arsaln, Muhammad; Rehman, Aysha; Alharbi, Fahad M.; Akkurt, Nevzat; Eldin, Sayed M.; Althobaiti, Saad

  The unsteady compressible steam laminar flow associated with heat transfer in fluids in a squared cylinder is examined in this work. The current challenge was created utilizing the CFD approach. The laminar flow is chosen with a low Mach number. With the geometric wall, the flow has a no-slip condition. The pressure on the flow is kept at 0 pas, and the temperature in the flow regime is 305.13. A 0.5 m/s velocity is used to start the flow. With the use of graphics, the effects of time on velocity and pressure distributions are discussed. Different outcomes are also mentioned, such as drag coefficients, lift coefficients, and heat distributions. The velocity drops from 2.5 to 1.6 m/s at t = 7 s in the absence of anybody's force and temperature 305.13 K. Pressure increases from 0.00098 to 0.001 Pas in the flow interval of 10 s. Surface temperature increases from 360 to 375 K in time intervals of 10 s keeping pressure constant. And contour temperature increases from 371.56 to 374.2 K in time intervals of 10 s keeping the pressure constant. This information provides us with caution about the emission of steam from the chimneys of furnaces. It implies that when steam flows from a cylindrical geometry like chimneys of furnaces it heats the upper inner and outer parts which may destroy the material. So for safety, that emission should be taken for a short interval of time otherwise it will result in a havoc process. The lift coefficient remains constant and the drag coefficient increases from 0.0005 to 0.065. Under that condition, fluid has to face more resistance. To overcome that difficulty fluid should be provided with high velocity to continue it for a long time. The technique used to solve modeled problems is the Backward Difference Formula.

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