Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Uzun, Sevda(77)
- Merdan, Mehmet(73)
- Duran, Celal(54)
- Ozdes, Duygu(50)
- Baltaci, Cemalettin(45)
- Kaygusuz, Abdullah(45)
- Kulakaç, Nurşen(39)
- Ashyralyyev, Charyyar(38)
- Karsli, Orhan(37)
- Demir, Selim(36)
- Öztürk, Serkan(36)
- Dokuz, Abdurrahman(35)
- Turan, Ibrahim(35)
- Araz, Onur(33)
- Kandemir, Raif(31)
- Sipahi, Ferkan(30)
- Topal, Fevzi(30)
- Kurt, Kemal(28)
- Peker, Iskender(28)
- Arslan, Mehmet(27)
- Baltacı, Cemalettin(27)
- Maden, Nafiz(27)
- Ozturk, Samet(27)
- Aydin, Aydanur(26)
- Vural, Alaaddin(26)
- Bayrakdaroglu, Serdar(25)
- Kurnaz, Muammer(25)
- Reis, Hatice Catal(25)
- Akar, Zeynep(24)
- Aydin, Faruk(24)
- Gücer, Mehmet Ali(24)
- Topal, Meryem(24)
- Yolcu, Halil(24)
- Yücel, Cem(24)
- Anaç, Halil(23)
- Kankal, Murat(23)
- Ürkek, Bayram(23)
- Aliyazicioglu, Yuksel(22)
- Günen, Mehmet Akif(22)
- Tuncer, Metin(22)
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ1The mediating effect of self-compassion and cognitive emotion regulation on the relationship between tolerance and social appearance anxiety in adolescents
Bingöl, Orhan; Çelebi, Gülin Yazıcı; Kaya, Feridun
The aim of this study is to examine the effect of tolerance on social appearance anxiety and to test the roles of emotion regulation and self-compassion as mediating psychological mechanisms in this relationship. The sample of the study consists of 647 adolescent individuals living in Turkey. The Personal Information Form, Cognitive Emotion Regulation Questionnaire, Tolerance Scale, Self-Compassion Scale – Short Form, and Social Appearance Anxiety Scale were used in the study. Data were collected online using convenience sampling methods. Pearson correlation analysis was used to determine the relationships between the variables in the study, while regression-based mediation analysis (Process macro model 81) was used to test the mediation model examined in the study. Upon examining the findings, tolerance was positively correlated with self-compassion (r =.323, p <.001) and adaptive cognitive emotion regulation (r =.200, p <.001); while tolerance was negatively and statistically significantly related to maladaptive cognitive emotion regulation (r = -.250, p <.001) and social appearance anxiety (r = -.229, p <.001). Additionally, a positive correlation was found between self-compassion and adaptive cognitive emotion regulation (r =.358, p <.001); and negative and statistically significant relationships between self-compassion and maladaptive cognitive emotion regulation (r = -.576, p <.001) and social appearance anxiety (r = -.530, p <.001). Finally, a statistically significant negative relationship was found between social appearance anxiety and adaptive cognitive emotion regulation (r = -.219, p <.001); and a statistically significant positive relationship was found between social appearance anxiety and maladaptive cognitive emotion regulation (r =.484, p <.001). The mediation analysis, tested with 10,000 bootstrap samples at a 95% confidence interval, revealed that emotion regulation dimensions and self-compassion have a full mediating effect. The findings indicate that the tolerance factor reduces social appearance anxiety not only directly but also indirectly through emotion regulation and self-compassion. In line with these findings, it was concluded that individuals with high tolerance levels need to be supported not only through mindfulness programs but also through emotion regulation and self-compassion levels.
- MakaleYalnız künye2026Scopus SJRQ2Organic Geochemical Properties of the Miocene Coal Seam in the Ömerler Field, Tunçbilek Basin, Western Türkiye: Implications for Depositional Environment
Saydam Eker, Çiğdem; Köse, Yeliz
In this comprehensive study, which was conducted based on data obtained from the Ömerler Field İğdekuzu underground mine located in the Tunçbilek Basin (Kütahya/W. Turkey), the aim was to reveal the organic matter content, origin, thermal maturation level, depositional environment, and conditions of Miocene-aged coals. Coal samples collected from the underground coal mine were subjected to proximate analysis, Rock-Eval pyrolysis/Total organic carbon (TOC), gas chromatography (GC), gas chromatography–mass spectrometry analysis (GC–MS) of aromatic and saturated biomarkers and extraction analysis. On an air-dry basis, the average moisture (Mad), volatile matter (Vad), ash (Aad), fixed carbon (FCad) and total sulphur contents of coals are 2.79%, 33.93%, 18.71%, 44.31% and 1.40%, respectively. TOC content is so high; the highest mean TOC content is 86.75% calculated in the upper coal seam, followed by the middle seam with 85.14% and the lower seam with 79.01%. In the GC–MS of the coal samples, the n-alkane distribution varies between C12 and C36. The lowest homohopane index (HHI) value was calculated as 0.02 for OR-5, and the highest HHI value was 0.05 for TB-8. The upper coal seam sample exhibits the order of C29>C28>C27 sterane (%), and the lower and middle coal seam samples exhibit the order of C29>C27>C28 sterane (%). The coal samples under study exhibit early mature oil window behaviour according to all geochemical maturity parameters. These coals indicate a mixed organic matter of Type II/III and III kerogens, as demonstrated by medium and long-chain n-alkanes, terrestrial/aquatic organic matter ratios (TAR), aquatic plants to terrestrial plants ratios (Paq), C24 Tet/C26 Tri and C19/C23 Tri ratios, and distributions of C27–29 ααα20R, likely deposited in a paralic, oxic-dyoxic transitional environment. Although the TOC value of the Miocene-aged coal samples is so high, they have not yet reached the level of producing hydrocarbons due to low and medium hydrogen index (HI), low quality index (QI), production index (PI), and bitumen index (BI) values, but it has been evaluated that they have the potential to produce gas.
- MakaleAçık Erişim2026Scopus SJRQ2Land Subsidence Susceptibility Mapping in Semi-Arid Regions Using PS-InSAR and Tree-Based Ensemble Machine Learning: A Case Study From Çumra, Türkiye
Bilgilioğlu, Burhan Baha
Land subsidence is an increasing environmental hazard in semi-arid agricultural basins where intensive groundwater abstraction, compressible geological units, and expanding land-use pressures interact. This study presents a PS-InSAR and machine-learning-based framework for land subsidence susceptibility mapping in the Çumra District of the Konya Closed Basin, Türkiye. A time-series PS-InSAR analysis was conducted using 172 Sentinel-1A ascending images acquired between 2018 and 2023, and 11,718 high-confidence subsidence points were extracted as the inventory dataset. Fourteen conditioning factors representing topographic, hydrogeological, lithological, environmental, and anthropogenic controls were integrated with eight tree-based ensemble models optimized using Optuna. Random Forest achieved the highest overall performance, with an accuracy of 0.9745, precision of 0.9562, recall of 0.9945, F1 score of 0.9750, and Cohen's Kappa of 0.9490, followed by Extremely Randomized Trees and XGBoost. Class-specific validation also confirmed the reliability of Random Forest in delineating the Very High Susceptibility class. Variable importance analysis identified land use, proximity to settlements, well density, and groundwater level change as the dominant predictors, emphasizing the role of groundwater-related anthropogenic pressure in subsidence development. The resulting susceptibility maps provide a spatial decision-support basis for groundwater management, land use planning, and subsidence risk mitigation.
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İncele - MakaleYalnız künye2026Scopus SJRQ1Nurses' artificial intelligence anxiety levels, their attitudes towards artificial intelligence, and their skills in acting humanistically in nursing practices
Cin, Aynur; Coşar, Dilan Aktepe; Demirağ, Hatice
Aim This study aims to investigate the levels of artificial intelligence-related anxiety among nurses, their attitudes towards the use of AI in clinical settings, their ability to maintain humanistic approaches in nursing care, and the interrelationships among these variables. Design This study was designed as a descriptive and cross-sectional pilot study. Method The sample of the descriptive study consisted of 267 nurses working in X and Y hospitals in Gümüşhane province. The data of the research was collected between December 2023 and May 2024 using the “Nurse Introduction Form”, “Artificial Intelligence Anxiety Scale”, “General Attitude Scale towards Artificial Intelligence” and “Humanistic Practice Ability of Nursing”. Results Total “Artificial Intelligence Anxiety Scale” mean scores were found to be higher in nurses who were women, and had more than five years of working experience ( p < 0.05). It was determined that the total “General Attitude Scale Towards Artificial Intelligence” score averages of nurses working in surgical clinics were higher than those working in pediatric clinics ( p < 0.05). Positive “General Attitude Scale Towards Artificial Intelligence” mean scores were higher in nurses who had a postgraduate degree, worked in a surgical clinic, and had five years or less experience ( p < 0.05). Again, the total mean of the “ Humanistic Practice Ability of Nursing “ was higher in nurses who had a bachelor's degree or less, and worked in management and surgery clinics ( p < 0.05). Conclusion It was found that nurses' artificial intelligence anxiety, general attitudes towards artificial intelligence, and ability to act humanistally varied according to some sociodemographic characteristics.
AtıfScopus1WoS1OpenAlex1
İncele - MakaleAçık Erişim2026Scopus SJRQ2Critical Success Factors for Building Resilience in Circular Supply Chains of Electric Vehicle Batteries: Evidence from an Emerging Country
Erol, Ismail; Oztel, Ahmet; Peker, Iskender; Ar, Ilker Murat; Searcy, Cory
Given the global expansion of electric vehicles (EVs), decision makers in developing and emerging countries must address important challenges across EV battery supply chains (EVBSCs) toward circularity. For example, batteries usually make up about 40% of an EVs’ value, and the race to achieve net zero emissions will further underscore the critical need for vital minerals and metals, such as lithium, cobalt, and graphite, necessary to make batteries. Stakeholders routinely question the resilience of circular (C) EVBSCs worldwide, from mining valuable materials to manufacturing the batteries necessary to support the widespread deployment of EVs. Identifying and investigating critical success factors (CSFs) of any system is a necessary step in achieving its targets. Little research, however, has been performed to investigate the CSFs for building resilience in EVBSCs, particularly those focused on building a circular supply chain. The goal of this research is, therefore, to systematically scrutinize the CSFs of resilient C-EVBSCs in Türkiye. To this end, a decision framework applying inter-valued neutrosophic ISM-MICMAC is proposed. Based on expert opinions, an application of the decision framework finds that effective government policies, directives, and incentives and well-established dynamic capabilities, are key driving CSFs to building resilience in a C-EVBSC.
AtıfScopus3WoS3OpenAlex3İncele - MakaleAçık Erişim2026Scopus SJRQ3Influence of Container Type and Growing Media on Seedling Growth of Pinus sylvestris in the Nursery
Tilki, Fahrettin; Er, Omer
Type of container and growing media are two important factors that affect seedling quality. The present study aimed to evaluate the effects of the growing media (local peat sources and Finnish peat) and Enso tube containers (type with vertical slits and rocket type) on the morphological attributes of two-year-old container-grown Pinus sylvestris L. seedlings using a completely randomised block experimental design in the nursery. Both container types and growing media significantly affected some seedling morphological attributes such as seedling height (SH), root collar diameter (RCD), the Dickson quality index (DQI), shoot and root dry weights (SDW and RDW, respectively), and sturdiness quotient (SQ) of P. sylvestris seedlings. When the containers were evaluated, the fixed Enso container type with greater volumes, which has vertical slits on the sidewalls, gave better results in terms of most measured seedling morphological characteristics than the Enso-rocket container type with smooth walls. It was also determined that the growing media significantly affected P. sylvestris seedlings’ morphological indices, and low growing media acidity because high local peat pH decreased some morphological quality attributes of P. sylvestris seedlings. The results suggest that lowering local peat pH can increase the potential of local peat as a Finnish peat substitute in container growing media for P. sylvestris seedling production.
- MakaleYayıncıda açık erişim2026Scopus SJRQ2Measurement-aware zero-phase iterative learning control for robust regulation of nonideal boost converters in electric vehicle fast charging
Altan, Aytaç; Alzaidi, Mohammed S.; Yanarateş, Cağfer
Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise and quantization across successive trials without introducing phase lag. The averaged small-signal model is validated against a 960 kHz switched simulation, with agreement within 0.2% at the operating point and a transient-waveform correlation of 0.91, while the bandwidth limitations imposed by the lightly damped resonance and the nonminimum-phase dynamics on feedback are quantified from the loop frequency response. Because feedback alone is bandwidth-limited, the learning feedforward recovers the intrinsic converter speed for the repetitive task and reduces the periodic tracking error by more than an order of magnitude relative to a fairly tuned baseline. A bounded-error convergence theorem shows that, under real sensing, the tracking error converges to a neighbourhood whose size is proportional to the measurement-disturbance level; this is confirmed numerically, with the asymptotic error scaling approximately linearly with the noise standard deviation once the noise dominates the filter bias. Systematic sweeps of converter resolution, noise, and sensor delay show that the zero-phase measurement-aware law remains bounded where a naive learning law diverges, and a 500-sample Monte Carlo study confirms robustness to component tolerances, load variation, and parasitic aging. The primary physical task is the rejection of a repeating high-current charging pulse: over successive charging cycles the scheme reduces the periodic output-voltage sag from 35% to below 0.01%, whereas the best feedback comparator leaves a 17% residual, and the sinusoidal reference used elsewhere serves as a spectral diagnostic that isolates the feedback-bandwidth ceiling at a single known frequency. The learning law is further verified in closed loop on the cycle-by-cycle switched large-signal converter, where it converges and stays bounded. A per-unit scale-invariance analysis then establishes the conditions under which the design obtained on the low-power benchmark transfers to fast-charging power levels, as confirmed on a 400 V, 6.1 kW stage that reproduces the benchmark convergence exactly.
- MakaleAçık Erişim2026Scopus SJRQ2Immediate effects of cervical spine and sacroiliac joint manipulations on the autonomic nervous system and pedobarographic analysis: Randomized controlled trial
Turgut, Hayriye; Büyükkırlı, İlker Can; Hatık, Sefa Haktan; Aydın, Emine Büşra
Background: This study aimed to investigate the immediate effects of cervical and sacroiliac joint manipulations on autonomic nervous system activity and baropodometric parameters. Methods: Participants were randomly assigned to three groups with equal gender distribution. The cervical manipulation group received chiropractic manipulation at the C3–C5 level, while the sacroiliac group received manipulation at the sacroiliac joint. The control group received no intervention. Pre- and post-treatment evaluations were conducted after a 30-minute interval. Plantar pressure was measured via a pedobarographic device. Autonomic nervous system activity was assessed using the Polar H10. Blood pressure and heart rate were manually recorded using a sphygmomanometer and pulse oximeter. Statistical significance was set at p < 0.05. Results: No significant differences were found among groups in terms of age, gender, height, or BMI (Kruskal-Wallis, p > 0.05). The cervical manipulation group showed significant decreases in systolic and diastolic blood pressure and heart rate post-intervention (Wilcoxon, p < 0.05). The sacroiliac group showed a significant increase in heart rate only (Wilcoxon, p < 0.05). No significant changes were observed in baropodometric parameters or autonomic activity within or between groups (Wilcoxon and Kruskal-Wallis, p > 0.05). However, post-intervention comparisons showed cervical manipulation led to a greater reduction in systolic blood pressure, while sacroiliac manipulation led to a greater increase in heart rate compared to controls (Mann-Whitney U with Bonferroni correction, p < 0.05). Conclusion: While no significant changes were observed in baropodometric or autonomic parameters, chiropractic manipulation demonstrated short-term effects on blood pressure and heart rate. The accuracy of heart rate variability assessments should be reviewed, and further studies are needed to evaluate long-term cardiovascular and autonomic outcomes.
- MakaleAçık Erişim2026Scopus SJRQ1Microwave-assisted natural deep eutectic solvent-based system for sustainable eritadenine extraction from shiitake mushroom (Lentinula edodes)
Kaya, Murat; Berktas, Serap; Alasalvar, Hamza; Cam, Mustafa
Shiitake (Lentinula edodes) mushrooms contain a significant level of eritadenine, a cholesterol-lowering compound. However, volatile organic solvents such as methanol are commonly used in the extraction of eritadenine. To overcome this disadvantage, in the present study, microwave-assisted natural deep eutectic solvents (NADESs) extraction was tested for the extraction of eritadenine. The efficiency of NADESs was compared with benchmark solvents (water, aqueous ethanol, aqueous methanol). NADES, composed of betaine and sorbitol, demonstrated superior efficiency in the extraction of eritadenine. Based on the results obtained from preliminary experiments, microwave-assisted extraction was optimized using a statistical optimization method. A microwave power of 300 W and an extraction time of 15 s were established as optimal conditions with an eritadenine content of 10.63 mg/g dry weight (DW). Further comparisons using NADES revealed the superiority of microwaves over homogenization and stirring methods. The highest level of eritadenine was measured with the microwave-assisted method (10.56 mg/g DW), followed by homogenization (7.22 mg/g DW) and stirring (1.03 mg/g DW). A similar trend was detected in the total phenolic content of the extracts (microwave: 8.27 mg GAE/g DW, homogenization: 2.32 mg GAE/g DW, and stirring: 0.46 mg GAE/g DW). The DPPH and ABTS antioxidant capacities of the extracts ranged from 1.18 to 29.40 mg TE/g DW and 2.42-34.69 mg TE/g DW, respectively. According to the sample preparation metric of sustainability tool, the microwave-assisted approach for the extraction of eritadenine was more sustainable due to the short extraction time. Overall, NADES combined with microwave technology represents an efficient approach for recovering eritadenine, enhancing extraction efficiency and sustainability from shiitake mushrooms.
- MakaleAçık Erişim2026Scopus SJRQ1Social Gender in a Language Without Grammatical Gender: Relational and Status Encoding in Kazakh Female Nominations
Gulzhan, Shokym; Bagila, Muratbek; Kürüm, Mesut; Zhanna, Tektigul; Nurbol, Saduakas; Nurdaulet, Aldashev; Zhanar, Amirgali
This article examines how Social Gender is organized in Kazakh in the absence of grammatical gender. The study is based on a lexicographically verified corpus of Kazakh female nominations, supplemented by a limited contrastive set of gender-neutral and male-linked kinship terms. The material includes basic female reference terms, kinship and affinal nominations, status-hierarchical designations, evaluative and address forms, socially conferred female roles, widowhood and step-relation terms, as well as analytic constructions marking age and social personhood. Methodologically, the analysis combines lexical-semantic, linguistic-anthropological, sociolinguistic, and pragmatic approaches within a framework that distinguishes Linguistic Gender, Natural Gender, and Social Gender. The results show that Kazakh female nominations form a structured lexico-pragmatic subsystem in which female reference intersects with relationality, hierarchy, evaluation, politeness, speaker dependence, and personhood-related distinctions. The analysis further demonstrates that this subsystem is not uniformly gender-differentiated: alongside female-specific nominations, Kazakh also employs selectively gender-neutral kinship terms and classificatory extensions, revealing where gender salience is strengthened, backgrounded, or redistributed. Social Gender in Kazakh is thus encoded not through grammatical agreement, but through a distributed system of relational, status-based, evaluative, politeness-based, speaker-dependent, and age/personhood-related nominations.
- MakaleYalnız künye2026Scopus SJRQ1Freeze–ohmic thawing: A novel pretreatment strategy for cold-pressed black cumin oil production
Tunç, Merve Tuğçe
Cold pressing is one of the most preferred techniques for producing high-quality vegetable oils; however, its relatively low extraction efficiency remains a major limitation. Although ohmic thawing has been investigated as a rapid thawing technique for frozen foods, its application as a pretreatment prior to cold-press oil extraction has not yet been reported. Therefore, this study investigated, for the first time, the potential of freeze–thawing (FT) and freeze-ohmic thawing (FOT) as pretreatment strategies to enhance the recovery and preserve the quality of cold-pressed black cumin oil. FT and FOT pretreatments were applied for one, two, and three cycles before cold pressing, and the extracted oils were comparatively evaluated in terms of oil recovery, physicochemical properties, antioxidant characteristics, FTIR, aroma profile, and fatty acid composition. Both FT and FOT significantly improved oil recovery compared with the untreated control. While FT2 increased the extraction yield to 51.68 ± 2.21%, FOT2 achieved the highest extraction yield (63.11 ± 1.50%), corresponding to a 41% increase over the control. FTIR analysis confirmed the preservation of the characteristic functional groups of black cumin oil following both pretreatments. Thymoquinone was largely preserved, with only a slight reduction in FT2. Likewise, the fatty acid profile remained stable, with no significant differences (p > 0.05) among treatments. These findings demonstrate, for the first time, that freeze-ohmic thawing can be successfully employed as a pretreatment prior to cold pressing, substantially improving black cumin oil recovery while preserving its physicochemical, structural, and compositional quality.
- Derleme MakaleYalnız künye2026Scopus SJRQ2Sustainable Mining: Environmental Challenges, Mine Tailings Management and Technological Innovations
Orak, Mürsel
Mining provides essential raw materials for global economic development; however, it is also associated with significant environmental impacts including land degradation, water contamination, and the generation of large volumes of mine tailings. Sustainable mining has emerged as a strategic framework aimed at balancing economic benefits with environmental protection and social responsibility. This study presents a comprehensive review of sustainable mining practices with particular emphasis on environmental impacts, mine tailings management strategies, acid mine drainage mitigation, and innovative technologies such as cemented paste backfill (CPB). In addition, the role of circular economy approaches, digital mining technologies, and mine closure strategies in improving sustainability performance is discussed. The findings indicate that integrating advanced tailings management strategies and technological innovations can significantly reduce environmental risks and enhance the long-term sustainability of mining operations.
- MakaleYalnız künye2026Scopus SJRQ2Some are more equal than others: workplace favoritism and hospital employees’ intent to quit
Özbek, Mehmet Ferhat; Banai, Moshe; Stefanidis, Abraham; Bekar, Fevziye; Roberts, Sara J.
Purpose – This study refines equity theory by explaining the mediating roles of job frustration and job dissatisfaction, as well as the moderating role of personal income in the relationship between discriminatory workplace favoritism and hospital employees’ intent to quit. Design/methodology/approach – The study consists of two samples. In the first sample, survey questionnaires were administered to 267 public hospital employees in Turkey. In the second sample, 1, 426 university healthcare students in Turkey answered four different scenarios that narrated school favoritism as well as students’ frustration, dissatisfaction and intent to quit. Structural equation modeling and ANOVA statistical analyses were conducted. Findings – Workplace favoritism positively affected employees’ intent to quit through the mediation of job frustration and job dissatisfaction. The mediating role of job frustration between workplace favoritism and intent to quit was stronger for high-income than for low-income employees and students. Practical implications – Favoring one employee may result in voluntary organizational exit by other employees, which is costly for the organization. Favoritism may encourage employees who were not previously prone to favoritism to seek favoritism. This may create a cycle that spreads favoritism further within the organization. Originality/value – This is the first study to investigate the role of income in the relationship between workplace favoritism and employees' intent to quit.
AtıfScopus1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ3Approximate Analytical Solutions of the Time-Fractional Swift–Hohenberg Equation via Yang Transform Adomian Decomposition Method
Ali, Mustafa Ahmed; Merdan, Mehmet
This study examines approximate analytical solutions of the time-fractional Swift–Hohenberg equation involving the Caputo–Fabrizio fractional derivative. The main objective of this study is to investigate efficient analytical approximation techniques using the Yang transform Adomian decomposition method (YTADM). The proposed approach combines the Yang transform with the Adomian decomposition technique to construct a rapidly convergent series solution for the fractional partial differential equation. The effects of the fractional order and system parameters on the behavior of the solution have been examined via tables and are graphically represented. The results confirm that the proposed method provides accurate and computationally efficient approximate solutions to the fractional Swift–Hohenberg equation. These results show that YTADM is an appropriate and useful analytical tool to solve nonlinear fractional partial differential equations arising in mathematical physics, especially those equations involving nonsingular fractional operators. The principal contribution of this work effort is the development and application of the YTADM framework for solving the fractional Swift–Hohenberg equation; therefore, it serves as a reliable analytic tool for nonlinear fractional partial differential equations arising in mathematical physics.
AtıfScopus1WoS1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ1Prioritization of Internal and External Corporate Sustainability Dimensions: Evidence from Sustainability Auditors Using AHP
Wang, Yufu; Yeşilçelebi, Gül; Tosunoğlu Kusan, Büşra; Çam, Alper Veli; Dumitru, Mihaela
Corporate sustainability has traditionally been evaluated through environmental, social, and economic dimensions. However, increasing sustainability challenges, stakeholder expectations, and regulatory requirements indicate that sustainability extends beyond conventional performance measures and requires an integrated perspective that considers both internal organizational capabilities and external institutional conditions. This study develops an integrated internal–external sustainability framework and prioritizes sustainability dimensions from the perspective of licensed sustainability auditors in Türkiye. The proposed framework comprises governance, ethical, behavioral, cultural, environmental, social, economic, legal, and technological dimensions. The Analytic Hierarchy Process (AHP) was applied to pairwise comparison data collected from 15 licensed sustainability auditors to determine the relative importance of these dimensions. The results indicate that external sustainability dimensions received substantially higher priority (70.97%) than internal dimensions (29.03%), demonstrating that sustainability assessments are primarily shaped by environmental challenges, regulatory requirements, stakeholder expectations, technological developments, and market conditions. Among the nine corporate sustainability dimensions, environmental sustainability received the highest overall priority, followed by technological, ethical, social, economic, legal, governance, cultural, and behavioral dimensions. These findings suggest that although internal organizational capabilities remain important, corporate sustainability is predominantly influenced by external institutional and environmental factors. By proposing an integrated internal–external sustainability framework, this study extends conventional sustainability assessment approaches and contributes to the sustainability governance and assurance literature. The findings also provide practical implications for sustainability reporting, assurance, governance, and strategic decision-making by identifying the sustainability dimensions that deserve the greatest managerial and regulatory attention.
- MakaleYalnız künye2026Scopus SJRQ1Thermal inactivation kinetics of Listeria monocytogenes in fat/water emulsions and fat tissue – effect of fat content
Ozturk, Samet; Huang, Lihan; Hwang, Cheng-An; Sheen, Shiowshuh
Significantly increased thermal resistance was found in Listeria monocytogenes inoculated to beef tallow. However, how the relative compositions of fat and water in emulsions affect bacterial survival during heating has not been evaluated. This study aimed to evaluate the effect of fat levels in solid fat/water (SF/W) emulsions on thermal resistance of L. monocytogenes. SF/W emulsions, containing 0, 25, 50, 60, and 75 % of tallow by weight, were prepared by mixing tallow with soybean lecithin and Tween 80 in 0.1 % peptone water using an ultrasonic processor. A 4-strain cocktail of L. monocytogenes was inoculated to the emulsions and subjected to isothermal heating between 55 and 65 °C. The survival curves were analyzed to estimate the kinetic parameters and evaluate thermal resistance. Linear survival was observed in emulsions with fat below 50 %. However, increased thermal resistance, evidenced by the increasing D and z values with the fat content, was observed. For example, the average D values in SF/W emulsions at 60 °C are 0.54, 1.04, and 2.53 min, respectively, with 0, 25, and 50 % fat. For SF/W emulsions with 60 and 75 % fat and in beef trim fat (BTF, 86.9 % fat), the survival curves became convexly nonlinear and could be described with the Weibull model. The exponents of the Weibull model range between 0.45 and 0.456, suggesting almost identical convexity of the survival curves. The convex survival curves indicate initial sensitivity to heat but the resistance increases with time at each temperature. The estimated time to a 5-log reduction becomes 11.9 and 26.4 min in 60 and 75 % SF/W emulsions, respectively, and 36.5 min in BTF at 60 °C. The study demonstrates the effect of fat levels on thermal resistance of L. monocytogenes in SF/W emulsions and BTF. The results of this study may help the food industry to properly kill L. monocytogenes in fat-containing meat products during thermal processing.
AtıfScopus2WoS2OpenAlex2İncele - MakaleYalnız künye2026Scopus SJRQ2A Comprehensive Deep-Learning Framework Integrating Lesion Segmentation and Stage Classification for Enhanced Diabetic Retinopathy Diagnosis
İncir, Ramazan; Bozkurt, Ferhat
Diabetic retinopathy (DR), one of the most prevalent microvascular complications of diabetes, stands as a leading cause of vision loss globally. Due to its asymptomatic nature in early stages, delayed diagnosis and staging may result in irreversible visual impairment. Therefore, accurate and simultaneous lesion segmentation and stage classification of DR are of critical clinical importance. In this study, a two-stage, end-to-end, holistic framework is proposed for automated DR diagnosis. In the first stage, an Improved U-Net architecture enhanced with residual blocks and additional convolutional layers is employed to segment small and low-contrast lesions such as microaneurysms, hemorrhages, and hard/soft exudates with high precision. Model hyperparameters are optimized using the harmony search algorithm to enhance training efficiency. In the second stage, lesion-based weight maps obtained from the segmentation step are applied to fundus images from the APTOS dataset, generating enriched inputs for classification. A vision transformer (ViT)-based model, augmented with a Convolutional Block Attention Module (CBAM), is utilized to improve feature extraction. In addition, features derived from ViT are further refined using a graph convolutional network (GCN) and traditional machine-learning classifiers. The proposed approach achieves high performance in multi-class DR stage classification. Compared to existing studies, the framework demonstrates notable improvements in both segmentation and classification accuracy, offering a robust and generalizable solution for DR diagnosis.
AtıfScopus2WoS1OpenAlex3İncele - Derleme MakaleYalnız künye2026Scopus SJRQ1A review study of recent advancements in polymer heat exchanger technology in the aspect of heat transfer
Celen, Ali; Budak, Selahattin; Celen, Pınar; Dalkılıç, Ahmet Selim
Many applications use metallic heat exchangers, but some operating conditions, such as desalination, exhibit wear and corrosion problems. Thus, it is important to develop and use alternative materials to metals for such conditions. Although polymers have low thermal conductivity, corrosion resistance, cost-effectiveness, and lightweight, polymer heat exchangers can be constructed to overcome this problem. They were introduced in the last decades; advancements in 3D printing technology help manufacture complex, novel, and thin heat transfer surfaces. Although review studies are limited, recent research has not explored heat transfer-based reviews of heat exchangers produced by additive manufacturing and polymer hollow fibre methods. In this study, polymer heat exchanger works were reviewed and classified according to tube diameter as polymer and polymeric hollow fibre heat exchangers as the most updated ones. Generally, the studies focused on the thermal performance of heat exchangers constructed with metal and polymer materials, and the results were compared to determine the usability of polymer-based ones. As a result, polymeric hollow fibre heat exchangers may compete with metallic ones due to low wall resistance and enhanced heat transfer surface area because of the development of manufacturing technology. Also, the cost and weight of polymeric hollow fibre exchangers are lower, and they can be operated under corrosive conditions. Finally, it is obvious that increased research is needed to enhance the properties of polymer materials to increase the performance of this type of heat exchanger.
AtıfScopus3WoS4OpenAlex2İncele - MakaleAçık Erişim2026Scopus SJRQ1Predicting suicide probability in young adults: contributions of vulnerable narcissism, grudge, and demographic variables
Çelebi, Gülin Yazıcı
Suicide is a significant public health problem worldwide. The aim of this study is to examine the potential effects of levels of vulnerable narcissism and grudge on the likelihood of suicide. In addition to these variables, the potential effects of some demographic variables (gender, marital status, age, socioeconomic status, education level, perceived religiosity, number of siblings) were also investigated. A convenience sampling method was used to determine the study group. The study group consisted of a total of 500 individuals; 368 (73.6%) were women and 132 (26.4%) were men. The mean age of women was 26.31 (SD = 9.60, min-max = 18–64), the mean age of men was 29.01 (SD = 10.76, min-max = 18–55), and the mean age of the entire sample was 26.84 (SD = 9.88, min-max = 18–64). The Suicide Probability Scale, Vulnerable Narcissism Scale, Grudge Scale, and Personal Information Form were used as data collection tools in the study. Pearson correlation coefficient was used to examine the relationships between variables in the analysis of the data. Multiple linear regression analysis was conducted to examine the extent to which vulnerable narcissism, grudge, and sociodemographic characteristics are associated with suicide probability. The regression model showed that the independent variables significantly predicted the probability of suicide. According to the results obtained, the independent variables explained 38% of the variation in the probability of suicide {[R = 0.619, R2 = 0.383, F(8, 499)= 38.12, p < 0.0001]}, and vulnerable narcissism and grudge are positive predictors of the probability of suicide. Vulnerable narcissism (β = 0.34, p < 0.001) and grudge (β = 0.22, p < 0.001) are positive predictors of the probability of suicide. Age (β = −0.23, p < 0.001), education level (β = −0.08, p = 0.003), and SEL (β = −0.19, p < 0.001) are significant variables that negatively predict the probability of suicide. Based on the results, it can be said individuals with high levels of narcissism and grudge have a higher probability of suicide, and that some socio-demographic characteristics may influence these relationships. The findings are discussed in light of the literature.
- MakaleAçık Erişim2026Scopus SJRQ1Machine learning–enabled ECG arrhythmia classification: a systematic and educational study from signal processing to decision support
Melek, Negin
Electrocardiogram (ECG) signals play a critical role in the early detection of cardiac arrhythmias, which remain a major cause of morbidity and mortality worldwide. While deep learning approaches have achieved high classification accuracy, their increasing complexity often limits interpretability and practical applicability. This study presents a systematic and interpretable framework for multi-class ECG arrhythmia classification, examining the effects of signal processing, feature extraction, feature selection, and evaluation strategies on classification performance. Experiments were conducted on the MIT-BIH Arrhythmia Database using two feature representations: (i) morphological and temporal features, and (ii) a compact wavelet-based representation. Sequential Forward Feature Selection (SFFS) revealed that classification performance saturates at approximately 15 features, indicating that most discriminative information is captured within a compact subset. Using this feature space, the support vector machine (SVM) achieved the best overall performance, reaching 98.54% accuracy with stable results across different configurations. The wavelet-based representation further improved performance balance, yielding lower Golden Distance (GD) values (as low as 0.0249), indicating more consistent behavior across evaluation metrics. Overall, the results demonstrate that carefully designed feature extraction and selection enable classical machine learning methods, particularly SVM, to achieve high and reliable performance, providing an interpretable alternative to more complex black-box models in ECG arrhythmia classification.
AtıfScopus1İncele