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[Gebelerin İnternet Yoluyla Karar Alma Düzeyi Üzerine Risk Algısının, Sosyo-demografik ve Obstetrik Faktörlerin Etkisinin İncelenmesi: Çoklu Doğrusal Regresyon Analiz Modeli]
No full textObjective: This study examines the effect of risk perception and socio-demographic and obstetric factors on the level of decision-making of pregnant women via the internet. Method: This study employed a cross-sectional and analytical design and was conducted online with 384 pregnant women living in Turkey. Data were collected using descriptive information forms, such as the decision-making scale via the internet on pregnancy and the perception of pregnancy risk scale. Descriptive statistics, including percentages and means, as well as multiple linear regression analysis, were utilized to analyze the data. Results: As the risk perception in pregnancy increased, the level of decision-making via the internet increased (β=0.118, p=0.000). Among pregnant women experiencing pregnancy-related health issues, a significant increase in decision-making via the internet was observed (β=0.092, p=0.046). As the age of women increased (β=-2.623, p=0.013) and income was perceived to be equal to expenses (β=-1.499, p=0.011) or more than expenses (β=-1.953, p=0.023), decision-making via the internet during pregnancy decreased. Unwanted pregnancy has a “reducing” effect of approximately two times on online decision-making (β=-1.919, p=0.026). The number of pregnancies, education and family type were found to have no statistical effect on decision-making (p>0.05). Conclusion: As the risk perception increases in pregnant women, online decision-making also increases. Factors such as some socio-demographic and obstetric factors affect online decision-making of pregnant women. © 2025 The Author.2-s2.0-10501499260
Mathematical analysis of fractional order Covid 19 epidemic model
No full textThis article aims to examine the dynamics of the fractional epidemic model of covid 19. The model in question incorporates the notion of a compatible derivative. Given their consistent and worldwide characteristics, fractional derivatives are presently employed to address nu-merous practical issues. In addition, we employ two numerical techniques, namely the con-formal differential transform and the variational iteration approach, to provide an approxi-mate solution for the given model. The research closes by providing an in-depth analysis and visually representing the numerical findings. Furthermore, it has been demonstrated that the solution obtained is convergent. © Author.2-s2.0-10502071870
Flexural Behavior and Sustainability of Dual-Waste Fiber-Reinforced Concrete Designed for Pavement Applications
No full textThis study evaluates the mechanical performance and sustainability potential of fiber-reinforced concrete incorporating mine tailings as the fine aggregate and waste tire wire as the reinforcing fiber. The concrete mixtures contained 0.2%, 0.4%, and 0.6% waste tire wire with the natural fine aggregate replaced entirely with Pb-Zn-Cu tailings. The mixtures were tested for porosity, water absorption, compressive strength, splitting tensile strength, flexural strength, toughness, fracture energy, and ductility to assess their mechanical performance and durability. The mine tailings improved the microstructure and reduced water absorption, particularly with tire wire. Using waste tire wire improved the compressive, tensile, and flexural performance; in particular, W-6 showed a 18.2% rise in compressive strength and a more than twofold increase in flexural strength relative to the control mix. The flexural toughness and fracture energy rose by up to 161%, while the ductility peaked at a fiber content of 0.2%. These gains were attributed to fiber crack-bridging and post-cracking energy absorption. The dual-waste system also reduced porosity, improved durability, and demonstrated strong potential for rigid pavement applications such as highways, industrial yards, and airport runways that require high fatigue resistance and a long service life. Beyond technical performance, this approach offers a sustainable solution that lowers maintenance, reduces life-cycle costs, and aligns with circular economy principles. © 2025 by the authors.2-s2.0-10501922334
DSCIMABNet: A novel multi-head attention depthwise separable CNN model for skin cancer detection
No full textSkin cancer is a common type of cancer worldwide. Early diagnosis of skin cancer can reduce the risk of death by increasing treatment success. However, it is challenging for dermatologists or specialists because the symptoms are vague in the early stages and cannot be noticed by the naked eye. This study examines digital diagnostic techniques supported by artificial intelligence, focusing on early skin cancer detection and two methods have been proposed. In the first method, DSCIMABNet deep learning architecture was developed by combining multi-head attention and depthwise separable convolution techniques. This model provides flexibility in learning the dataset's local features, abstract concepts, and long-term relationships. The DSCIMABNet model and modern deep learning models trained on ImageNet are proposed to be combined with the ensemble learning method in the second method. This approach provides a comprehensive feature extraction process that will increase the performance of the classification process with ensemble learning. The proposed approaches are trained and evaluated on the ISIC 2018 dataset with image enhancement applied in preprocessing. In the experimental results, DSCIMABNet achieved 84.28% accuracy, while the proposed hybrid method achieved 99.40% accuracy. Moreover, on the Mendeley dataset (CNN for Melanoma Detection Data), DSCIMABNet achieved 92.58% accuracy, while the hybrid method achieved 99.37% accuracy. This study may significantly contribute to developing new and effective methods for the early diagnosis and treatment of skin cancer. © 2024 Elsevier Lt
Efficiency analysis using the machine learning algorithms: model development and verification
No full textRecently, machine learning (ML) algorithms have been employed intensively in the field of finance as in all sectors. The issues such as financial distress prediction, bank credit risk calculation, etc., have been analyzed using ML algorithms. This study aimed to determine firm performance with the data envelopment analysis (DEA) method, sensitivity analysis, and ML algorithms and analyze the efficiency of companies via artificial neural networks (ANNs), support vector machines (SVMs), and logistic regression (LR) classification algorithms. In the study, first, 10 financial ratios were categorized into two parts, such as output and input, and efficiency scores were determined in MS Excel software. The obtained scores were included in the ML algorithm as a categorical dependent variable. Secondly, the data were extracted and included in the analysis software as 80% training and 20% test data, and the accuracy of ML algorithms was tested. Lastly, a comparative analysis of the estimation and classification algorithms of active and inactive companies was conducted. As a result of the analysis, the best classification prediction was seen as the ANN algorithm. SVM and LR algorithms also made an acceptable level of classification prediction. It was expected that the study would have contributed to the literature in terms of testing the companies whose efficiency scores were determined by the DEA method with ML techniques and determining which technique was more successful. © The Author(s), under exclusive licence to Springer Nature B.V. 2025
Psychosocial problems experienced by intensive care nurses regarding sleep pattern within the scope of working conditions: A phenomenological study
No full textBackground: Nurses working in intensive care units experience insomnia and accompanying psychosocial problems due to working conditions.
Aim: This study explores with a phenomenological approach the psychosocial problems experienced by intensive care nurses regarding sleep patterns within the scope of working conditions.
Study design: In this phenomenological study, semi-structured in-depth interviews were conducted with 16 nurses working in the surgical intensive care unit of a state hospital in Türkiye. Criterion sampling method, one of the purposive sampling methods, was used to reach the sample group. Researchers' interviews continued until they reached data saturation. All interviews were recorded on a voice recorder after obtaining the necessary permissions from the nurses and then transcribed. The study data were evaluated using thematic analysis. The current manuscript was reported following the COREQ checklist.
Results: Data analysis revealed three main themes (how working as an intensive care nurse changes sleep patterns, the relationship between shift work, work performance, patient care and how working as an intensive care nurse changes individual life and coping strategies) and nine subthemes (mental, physical, social, work performance, patient care, nutrition, family life, social life and coping).
Conclusion: The study's findings revealed that nurses working in intensive care experienced psychosocial difficulties related to sleep patterns and had trouble coping. In particular, it was determined that sleep problems of intensive care nurses cause difficulties in family life, nutrition and social life. It is recommended that the number of personnel in workplaces be increased, overtime hours should be limited, and professional development and training on the importance of sleep for all nurses should be provided.
Relevance to clinical practice: Nurses working in intensive care units may experience psychosocial problems due to working conditions, which may negatively change their coping skills. Therefore, organizing the working conditions of nurses positively changes their coping skills.3974676
Effects of Web-Based Psychotherapeutic Interventions on Depression in Mood Disorders: A Meta-Analysis Study
No full textPURPOSE: To investigate the effects of web-based psychotherapeutic interventions on depression among individuals with mood disorders. METHOD: For this meta-analysis study, data were obtained from October to December 2023 by searching PubMed, Web of Science, EBSCOhost, Google Scholar, and YÖK Thesis Center for articles published in the past 5 years. In the first stage of the search, 12,056 records were obtained. After removing duplicate studies, 4,910 records were considered for title and abstract review. After this evaluation, 139 studies were identified for full-text review. After the review, six studies reporting results on the effectiveness of web-based psychotherapeutic interventions on depression among individuals with mood disorders were ultimately included. RESULTS: Web-based interventions had significant positive effects and provided decreases in depression levels (standardized mean difference = –0.168, 95% confidence interval [–0.315, –0.021]; Z = –2.243; p < 0.05). CONCLUSION: Web-based interventions for mood disorders may play an effective role in reducing the burden of chronic mental illness and improving patient outcomes. © SLACK INCORPORATED.3950866
Future of Clean Cooking Energy Access in Emerging Economies by 2030
No full textThis study assesses the future of clean energy and technology access for cooking in emerging economic blocs—BRICS, MINT, ASEAN, and MENA—through 2030. Cooking contributes 3% of global greenhouse gas emissions, with over half of household emissions coming from cooking. Therefore, clean cooking energy is critical for sustainability and human health. The study aims to evaluate the likelihood of achieving the UN Sustainable Development Goal of universal clean cooking energy access by 2030 and the 2050 net-zero emissions target. Machine learning techniques, such as support vector regression, gradient boosting, and linear regression, alongside an ensemble approach, provide forecasts for these regions. The findings show a varied outlook. Within ASEAN, two countries are expected to reach 100% clean energy access for cooking by 2030, while two are likely to experience a decline. The MENA region shows stronger progress, with eight countries expected to meet the 2030 target. Among BRICS countries, only India is projected to reach full accessibility, while Russia faces a decline. The MINT countries face challenges, with none expected to meet the target, and Nigeria is projected to experience a decrease in clean energy access. The study concludes that the current trajectory makes achieving the 2030 Sustainable Development Goals and the 2050 net-zero emissions target unlikely for these regions. Policymakers must reassess their strategies and learn from successful countries to improve outcomes. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025
Paleolatitudinal movements of the eastern Sakarya Zone from Jurassic to Eocene
No full textThe study area covers a region oriented north-south from the Black Sea coastline in the north to the Kelkit Basin in the south within the eastern Sakarya Zone in northern Türkiye. The objective of this study is to investigate the paleolatitudinal movements of the eastern Sakarya Zone during the Jurassic-Eocene time interval through paleomagnetism. Various volcanic and sedimentary units (e.g., the Şenköy, Berdiga, Mescitli, Çatak, Kızılkaya, and Çağlayan Formations) spanning the time interval from the Early Jurassic to Middle Eocene were identified. A total of 98 locations belonging to Early/Middle Jurassic to Eocene volcanic and sedimentary units were selected for paleomagnetic core sample collection. The samples were subjected to demagnetization through thermal and alternating field methods. Characteristic remanent magnetization directions (ChRM) were obtained. Isothermal remanent magnetization (IRM) and high temperature susceptibility (HTS) measurements were made to identify the minerals responsible for magnetization. To ascertain whether magnetization was acquired through rock formation or as a consequence of subsequent tectonic processes, conglomerate and fold tests were performed. The results showed that magnetization was acquired before folding, i.e., the rocks have primary magnetization. Polarity tests were also conducted using coeval normal and reverse polarity sites. The results indicate that the mean magnetization direction for the Early-Middle Jurassic is 18.1°/55.2° (D/I) and 3.3°/51.5° (D/I) for sedimentary and volcanic rocks, respectively, and 348.7°/46.7° (D/I) for Late Jurassic/Early Cretaceous sedimentary rocks. In the Late Cretaceous period, the mean magnetization direction is 8.0°/49.3° (D/I) and 9.1°/47.0° (D/I) for sedimentary and volcanic rocks, respectively. In the case of the Early/Middle Eocene, the mean magnetization direction is 348.6°/52.7° (D/I) and 5.9°/48.8° (D/I) for sedimentary and volcanic rocks, respectively. In this study, the E/I correction was applied to the Late Jurassic/Early Cretaceous sedimentary rocks, and paleolatitude data obtained from sedimentary rocks were also utilized. Our paleomagnetic results indicate that the eastern Sakarya Zone was situated at latitudes spanning from 27.9° to 35.7° during the Early Jurassic - Middle Eocene time interval. In consequence, the eastern Sakarya Zone constituted a portion of the southern margin of the Eurasian continent during the Late Jurassic and Middle Eocene periods. © 2024 Elsevier B.V
Parents' experiences on the management of the process after sexual abuse of their children in northern region of Turkey: Qualitative study
No full textBackground: Child abuse is a universal problem with medical, legal, and psychosocial dimensions that every child is at risk of encountering all over the world.
Aim: The aim of this study was to evaluate the experiences of parents regarding the management of the process after sexual abuse of their children using a qualitative approach.
Methods: In this qualitative study, semi-structured in-depth interviews were conducted with the parents of 15 children who were exposed to qualified sexual abuse living in a city in Northern Turkey. Criterion sampling method, one of the purposive sampling methods, was used to reach the sample group. Interviews continued until data saturation was achieved. All interviews were audio recorded and then transcribed. The data of the study were evaluated using thematic analysis. The study was conducted and reported according to the consolidated criteria for reporting qualitative research (COREQ) checklist.
Results: In the analysis of the data, three themes (effects of child sexual abuse on the family, sexual abuse and process management, and attitudes and approaches to the child after sexual abuse), and nine sub-themes (mental, physical, social, reactions, difficulties experienced, coping, cognitive dimension, emotional dimension, behavioral dimension) were identified.
Conclusion: As a result of the study, it was determined that parents were negatively affected psychologically by the sexual abuse of their children. This study reveals that the concept of family is very important in all aspects of the sexual abuse of children. As a result of the study, it was determined that families were not very effective in process management and some parents blamed themselves for the incident they experienced.4044382