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Abstract Background This study aimed to investigate the relationship between exercise-induced leg pain, fear of pain, kinesiophobia and injury anxiety in amateur and professional athletes. Secondarily, the present study also aimed to investigate the relationship between women or men athletes and individual or team sports. Methods A cross-sectional study was conducted with a total of 304 athletes. Participants were categorized as amateur and professional athletes, male and female athletes, individual and team athletes. Participants were evaluated with Exercise Induced Leg Pain Questionnaire (EILP), Fear of Pain Questionnaire (FOPQ), Sports Injury Anxiety Scale (SIAS), and Tampa Scale of Kinesiophobia (TSK). Parametric tests were used for statistical analysis. A statistical significance level of 0.05 was chosen. Results Fear of pain and anxiety about sports injury were significantly less in men (p

Objective: This study aimed to analyze the clinical causes, resuscitation interventions, and outcomes of pediatric cardiopulmonary arrest to identify key predictors of survival and neurological prognosis. Design: A retrospective observational cohort study was conducted to evaluate pediatric cardiopulmonary arrest cases and their clinical outcomes. Subjects/Patients: A total of 150 pediatric patients aged 0 to 18 years who experienced cardiopulmonary arrest at a tertiary hospital were included in the study. Patients were categorized based on whether the arrest occurred in-hospital or out-of-hospital. Methods: Patient data, including demographics, causes of cardiopulmonary arrest, resuscitation interventions, and clinical outcomes, were collected from hospital records between September 1, 2019, and August 31, 2024. Statistical analyses were performed to assess the association between key variables and survival outcomes. Results: The return of spontaneous circulation was significantly higher in in-hospital cases compared to out-of-hospital cases. Early resuscitation was strongly associated with improved survival outcomes. Mortality rates were highest during early morning hours. The most common causes of cardiopulmonary arrest were cardiac, respiratory, and systemic diseases. Conclusion: Timely resuscitation and the location of cardiopulmonary arrest significantly impact survival and neurological outcomes in pediatric patients. The findings emphasize the importance of rapid intervention and structured emergency protocols to improve clinical outcomes in pediatric resuscitation.

Abstract Management of melanoma has changed significantly with the discovery of targeted therapies and immune checkpoint inhibitors (ICI). Our aim in the study is to determine which treatment alternatives, specifically dabrafenib plus trametinib and ICIs, are effective in adjuvant therapy and which treatment is effective as first-line metastatic therapy. This retrospective, multicenter study included 120 patients diagnosed with stage IIIB-IIID melanoma receiving both adjuvant and first-line metastatic treatment between 2007 and 2023. Data on clinicopathologic characteristics, treatment regimens and outcomes were collected. Objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS) and overall survival (OS) were analyzed. Patients treated with dabrafenib plus trametinib as adjuvant therapy had the longest relapse-free survival (RFS) (median: 8.3 months), followed by those treated with interferon (4.1 months) and nivolumab (1.9 months) (p = 0.002). Metastatically, the highest ORR was observed in patients treated with dabrafenib plus trametinib (54.5%), followed by ICI (52.0%) and chemotherapy (33.3%). Similarly, DCR was superior for dabrafenib plus trametinib (86.3%) compared to ICI (70.8%) and chemotherapy (66.6%). Median PFS was 9.7 months (95% CI 7.2–12.2 months) in the whole group. This was 14.3 months (95% CI 9.6–19.0 months) with ICI, 10.3 months (95% CI 4.2–16.4 months) with BRAF/MEK inhibitors and 6.3 months (95% CI 4.7–7.9 months) with chemotherapy, which was statistically significant (p 6 months, ORR are all independent factors for OS prognosis. In our study, dabrafenib plus trametinib combination was more effective in adjuvant treatment of melanoma, while immunotherapy was more effective in metastatic first-line treatment.

Abstract Purpose The aim of this study was to compare the wear and fracture resistance of single crowns produced from newly developed 3D printer resins used to produce permanent crowns and currently used composite CAD/CAM discs, after being thermomechanically aged in a chewing simulator. Materials and methods A total of 112 stainless steel die models simulating mandibular left first molars were produced, 8 for each group. Single crowns were produced from 3 different discs (Grandio Voco [GR], breCAM HIPC [HC], and Shofu HC [SF]) by CAD/CAM milling method and manufactured from from 4 different permanent composite resins (Nexdent C&B MFH [ND], Permanent Bridge Saremco [PB], VarseoSmile Crownplus [VSC], and Şenertek P-Crown [PC]) using the 3D printing method. Stereomicroscopy, scanning electron microscope (SEM) and Finite Element Method (FEM) analysis was performed. Data were analyzed using ANOVA, paired-t tests and Tukey’s HSD test (alpha = 0.05). Results As a result of thermomechanical aging, significant difference was found between the groups in wear and fracture resistance (P

Earth observation satellites capture panchromatic images at high spatial resolution and multispectral images at lower resolution to optimize the use of their onboard energy sources. This results in a technical necessity to synthesize high-resolution multispectral images from these data. Pansharpening techniques aim to combine the spatial detail of panchromatic images with the spectral information of multispectral images. However, due to the discrete nature of these images and their varying local statistical properties, many pansharpening methods suffer from numerical artifacts such as chromatic and spatial distortions. This paper introduces the L0-Norm-based pansharpening method (L0pan), which addressed these challenges by maximizing the number of similar pixels between the synthesized pansharpened image and the original panchromatic and multispectral images. L0pan was optimized using a population-based colony search algorithm, enabling it to effectively balance both chromatic fidelity and spatial resolution. Extensive experiments across nine different datasets and comparison with nine other pansharpening methods using ten quality metrics demonstrated that L0pan significantly outperformed its counterparts. Notably, the colony search algorithm yielded the best overall results, highlighting the algorithm's strength in refining pansharpening accuracy. This study contributed to the advancement of pansharpening techniques, offering a method that preserved both chromatic and spatial details more effectively than existing approaches.

This study aims to exhibit a bibliometric analysis of history education research in Türkiye. A total of 127 documents from 70 sources indexed in the Web of Science and Scopus databases in the years 2000-2023 were used in the analysis. The analysis provides a review of history education research in Türkiye by identifying the dynamics of research by presenting a wide in-depth knowledge concerning the periodical process, current situation, and future directions. Since 2006, history education studies in Türkiye have become more visible in the relevant databases. The annual increase rate of the studies was determined as 8.49 percent. Among the 127 documents accessed, research articles are the most common with a total of 104 articles. From the analysis, it could be said that history education research in Türkiye is mostly conducted in Turkish journals and by Turkish authors. Compared to international literature in history education, studies on ‘historical consciousness’ in Türkiye that were indexed in WOS and Scopus databases were found to be rare in the analysis. Despite this, it is observed that new approaches have started to be studied within the framework of concepts such as 'oral history', 'postmodernism', and 'museum education' in history education studies originating from Türkiye that were indexed in WOS and Scopus databases. In the analysis, it has been observed that although academic studies in qualified databases originating from Türkiye in the field of history education are not sufficient, they have been on an increasing trend in recent years.

Background: Cigarette smoking poses a major public health risk, requiring scalable and accessible interventions. Chatbots offer a promising solution, given their potential in providing personalized, long-term interactions. Despite their promise, limited research has examined their efficacy and the intertwined relationship between user experience and effectiveness over an extended period of time. Methods: In this prospective, single-arm study, we developed and evaluated Roby, a 5-session chatbot intervention incorporating motivational interviewing and cognitive behavioral therapy to help smokers quit. Roby engaged Dutch adult smokers (N = 102) in conversations covering topics such as setting a quit date, managing withdrawal and cravings, and relapse prevention. The primary outcome was the continuous abstinence rate at the end of the intervention, and secondary outcomes included 7-day point prevalence abstinence, self-efficacy, and cravings. User engagement, therapeutic alliance, and interaction satisfaction were measured weekly, and the trajectory was analyzed using Linear Mixed Models. Results: Following an intention-to-treat principle, 18.6 % of participants achieved continuous abstinence, and 37.3 % achieved 7-day point prevalence abstinence. Self-efficacy significantly improved over the intervention, and cravings decreased over time. A slight decreasing trend was observed in engagement and satisfaction, likely due to a novelty effect. However, the decrease did not affect the intervention's outcomes. Conclusion: This study demonstrates the feasibility and initial usefulness of Roby, highlighting the potential for chatbots in long-term cessation support. Future research should further validate these findings with randomized controlled trials. Additional efforts should focus on monitoring and maintaining user experience in the long term to enhance effectiveness.

Electroanatomic mapping guides complex atrial tachycardia ablations; however, challenges may emerge after pulmonary vein isolation. 3D mapping systems can reveal the mechanism of tachycardia and critical areas that need to be ablated. Sometimes, however, these areas may be located deep inside, to the extent that they cannot be successfully reached by endocardial ablation. In this study, we present a unique case of a patient in whom vein of Marshall (VOM) ethanol ablation, a conventional secondary intervention, promptly terminated a Marshall bundle–related atrial tachycardia without further endocardial radiofrequency application, suggesting VOM ethanol ablation as a potential primary strategy.

BackgroundCigarette smoking poses a major public health risk. Chatbots may serve as an accessible and useful tool to promote cessation due to their high accessibility and potential in facilitating long-term personalized interactions. To increase effectiveness and acceptability, there remains a need to identify and evaluate counseling strategies for these chatbots, an aspect that has not been comprehensively addressed in previous research. ObjectiveThis study aims to identify effective counseling strategies for such chatbots to support smoking cessation. In addition, we sought to gain insights into smokers’ expectations of and experiences with the chatbot. MethodsThis mixed methods study incorporated a web-based experiment and semistructured interviews. Smokers (N=229) interacted with either a motivational interviewing (MI)–style (n=112, 48.9%) or a confrontational counseling–style (n=117, 51.1%) chatbot. Both cessation-related (ie, intention to quit and self-efficacy) and user experience–related outcomes (ie, engagement, therapeutic alliance, perceived empathy, and interaction satisfaction) were assessed. Semistructured interviews were conducted with 16 participants, 8 (50%) from each condition, and data were analyzed using thematic analysis. ResultsResults from a multivariate ANOVA showed that participants had a significantly higher overall rating for the MI (vs confrontational counseling) chatbot. Follow-up discriminant analysis revealed that the better perception of the MI chatbot was mostly explained by the user experience–related outcomes, with cessation-related outcomes playing a lesser role. Exploratory analyses indicated that smokers in both conditions reported increased intention to quit and self-efficacy after the chatbot interaction. Interview findings illustrated several constructs (eg, affective attitude and engagement) explaining people’s previous expectations and timely and retrospective experience with the chatbot. ConclusionsThe results confirmed that chatbots are a promising tool in motivating smoking cessation and the use of MI can improve user experience. We did not find extra support for MI to motivate cessation and have discussed possible reasons. Smokers expressed both relational and instrumental needs in the quitting process. Implications for future research and practice are discussed.

Alignment of each optical element at a synchrotron beamline takes days, even weeks, for each experiment costing valuable beam time. Evolutionary algorithms (EAs), efficient heuristic search methods based on Darwinian evolution, can be utilized for multi-objective optimization problems in different application areas. In this study, the flux and spot size of a synchrotron beam are optimized for two different experimental setups including optical elements such as lenses and mirrors. Calculations were carried out with the X-ray Tracer beamline simulator using swarm intelligence (SI) algorithms and for comparison the same setups were optimized with EAs. The EAs and SI algorithms used in this study for two different experimental setups are the Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). While one of the algorithms optimizes the lens position, the other focuses on optimizing the focal distances of Kirkpatrick–Baez mirrors. First, mono-objective evolutionary algorithms were used and the spot size or flux values checked separately. After comparison of mono-objective algorithms, the multi-objective evolutionary algorithm NSGA-II was run for both objectives – minimum spot size and maximum flux. Every algorithm configuration was run several times for Monte Carlo simulations since these processes generate random solutions and the simulator also produces solutions that are stochastic. The results show that the PSO algorithm gives the best values over all setups.

OBJECTIVE: Tobacco use is an important risk factor for more than 20 types of cancer, especially cardiovascular and respiratory diseases, and many other health problems. Cigarettes are one of the most commonly used tobacco products in the world, and they can cause both physical and mental addiction. Adolescence is known to be the highest-risk period in terms of addiction among all age groups. As a result, smoke-free campus practices have become even more important in universities. This study investigates the prevalence of smoking among Pamukkale Medical School students and their views and behaviors regarding smoke-free campus practices. MATERIAL AND METHODS: This cross-sectional study was conducted with 548 medical students at Pamukkale Universıty Faculty of Medicine during the academic year 2021-2022, between April 1-29, 2022. A face-to-face interview was conducted. Students’ smoking status and their views about a smoke-free campus were assessed. In the questionnaire, the independent variables were socio-demographic characteristics, duration of staying in a smoke-free environment, smoking status in the place of residence, areas where smoking is most common, Fagerström nicotine dependence level, knowledge about smoke-free campus applications and campuses with the smokefree application. The Statistical Package for the Social Sciences version 21.0 package program was used to analyze the data. Descriptive statistics are presented with numbers and percentages for categorical variables, while the arithmetic mean and standard deviation are used for continuous variables. The chi-square test was used to compare categorical variables,and the Kolmogorov-Smirnov analysis was used to test the compatibility of data to normal distribution. RESULTS: The student smoking rate increased significantly as the number of semesters increased (P = .021). The smoking rate of male students was higher than that of female students (P = .001). The smoking rate of students living with their family or relatives was lower (P = .020). Smokers (14.7%) were more likely to have heard about the introduction of smoke-free zones on campus than nonsmokers (11%) (P = .280). 81.4% of students affirmed the statement, “The number of smoke-free rooms should be increased,” and 84.3% responded, “I support the existence of smoke-free spaces.” Nonsmoking students (90.8%) are more likely to agree that smoke-free spaces should be increased than those who smoke (57.7%) (P < .001). Among the students, 17.6% of nonsmokers and 37.8% of smokers find the information about smoke-free spaces sufficient (P < .001). The rate of those who consider smoke-free space inspections to be sufficient is lower for nonsmoking students than for nonsmokers (P = .017). Nonsmokers (89.5%) support the existence of smoke-free spaces to a higher degree than smokers (71.2%) (P < .001). CONCLUSION: One-third of Pamukkale University Faculty of Medicine students smoke, and smoking rates are higher among men and those who do not live with family or relatives. All participants strongly support the existence of smoke-free zones (84.3%), while a proportion of tobacco users (31.4%) support the implementation of a smoke-free campus. Student opinions of the smoke-free zones and the smoke-free campus application are more positive among nonsmokers than smokers.

Antik dönemde İç Karia Bölgesi’nin önemli kentlerinden biri olan Stratonikeia, günümüzde Muğla İli, Yatağan İlçesi, Eskihisar Mahallesi sınırları içinde bulunmaktadır. MÖ 5. yy’ın başlarında bölgenin isminin Idrias olarak geçtiği anlaşılmaktadır. Stratonikeia territoriumu MÖ 268 yılından sonra I. Antiokhos’un son dönemlerinde Seleukosların kontrolüne girmiş ve bölge MÖ 260’lı yıllarda Stratonikeia ismini almıştır. Çalışmamız Hellenistik kentin en önemli yapılarından birisi olan tiyatroda gerçekleştirilmiştir. Tiyatronun cavea kısmı kuzeye bakar şekilde Yunan tiyatrolarında olduğu gibi tamamen doğal yamaca yerleştirilmiştir. Hellenistik Dönemde (MÖ 2. yüzyıl) tek katlı inşa edilmiş olan tiyatronun sahne binası Augustus Döneminde iki kat eklenerek üç katlı yapılmıştır. Stratonikeia Antik Kenti’nde Tiyatro yapısının üç ayrı bölümünden alınan özgün harç numunelerinin spot testler ve iletkenlik ölçümleri, kalsinasyon (kızdırma kaybı), asit kaybı ve elek analizi yapılmış, nokta yükleme dayanımları belirlenmiştir. Yapılan analiz sonuçlarının değerlendirilmesinde, Stratonikeia Tiyatrosu’na ait harçların bağlayıcı/agrega karışım oranları kabaca 1/3 olarak hesaplanmıştır. Mevcut analiz sonuçları doğrultusunda buradaki harç karışım oranlarının Vitruvius’un tavsiye ettiği antik dönem harç ölçüleri ile uyumlu olduğu görülmüştür. Ayrıca suda çözünebilen tuzların varlığı ile iletkenlik ölçümleri ve kızdırma kaybı sonuçlarına bağlı olarak puzolanik harç durumları araştırılmış, nokta yükleme testi sonucu tek eksenli basınç dayanımları belirlenmiştir.

This study aimed to exhibit a bibliometric analysis of systems thinking (ST) research in the field of science education. A total of 340 articles from 201 sources indexed in the Web of Science database in the years 1991–2022 were used in the analysis. The analysis aimed to provide a review of systems thinking research in science education by identifying the dynamics of research by presenting the periodical process, current situation, and future directions. Research on systems thinking has been acknowledged to demonstrate a significant increase in recent years. Bibliometric data prove that systems thinking research concerning studies in science education exhibits a parallel increase too. This is mainly due to UNESCO’s (2015) declaration of The Education for 2030 Framework for Action. There systems thinking was defined as a key competency among eight competencies for education for sustainable development. Correspondingly, the analysis in this study suggests that systems thinking research in science education is a lively and developing subject in the past decade.

Abstract Thorough evaluation of suburban rail route alternatives is essential for determining the appropriate route. Suburban lines provide transportation services to suburban areas; that is, they provide transportation services to distant points of the city where demand is high. In this study, five alternative suburban rail routes in the commuter rail standard, starting from the Fatih Sultan Mehmet Bridge’s European exit and ending at Istanbul Airport, were determined as a sample corridor in the province of Istanbul. High-standard suburban rail routes and their infrastructure construction costs were determined, and route options were delineated according to their construction costs. Multi-criteria decision-making (MCDM) methods were examined, including the application of the decision matrix method (DMM) and analytical hierarchy process (AHP) to rank the routes in terms of the factors examined in the study. These routes were ranked according to the construction costs and according to the DMM and AHP methods, and the results were compared. In the decision matrix application, geomorphological-geological, geotechnical, infrastructural, and environmental factors were considered in the evaluation and determination process. A solution was developed in which all aspects were weighted to indicate their relevance, and these factors contributed to the determination of the results. The AHP method was also applied, in which five criteria were included in the evaluation: geology (including geomorphology and soil properties), engineering structures, construction costs, population values addressed by the routes, and railroad length. In addition, the distances to the active faults were examined according to the Turkey Earthquake Hazard Map specified in the Turkish Building Earthquake Code (TBDY) 2018. Depending on the factors studied, the ordering of the routes was the same for all three methods.

Clouds play a pivotal role in determining the weather, impacting the daily lives of everyone. The cloud type can offer insights into whether the weather will be sunny or rainy and even serve as a warning for severe and stormy conditions. Classified into ten distinct classes, clouds provide valuable information about both typical and exceptional weather patterns, whether they are short or long-term in nature. This study aims to anticipate cloud formations and classify them based on their shapes and colors, allowing for preemptive measures against potentially hazardous situations. To address this challenge, a solution is proposed using image processing and deep learning technologies to classify cloud images. Several models, including MobileNet V2, Inception V3, EfficientNetV2L, VGG-16, Xception, ConvNeXtSmall, and ResNet-152 V2, were employed for the classification computations. Among them, Xception yielded the best outcome with an impressive accuracy of 97.66%. By integrating artificial intelligence technologies that can accurately detect and classify cloud types into weather forecasting systems, significant improvements in forecast accuracy can be achieved. This research presents an innovative approach to studying clouds, harnessing the power of image processing and deep learning. The ability to classify clouds based on their visual characteristics opens new avenues for enhanced weather prediction and preparedness, ultimately contributing to the overall accuracy and reliability of weather forecasts.

International food and raw material security issues has gained much more importance than ever. This study examines that the following questions ‘Who depends on whom?’ and ‘What is the level of dependency?’ considering relationships between “fisheries context” (catch and aquaculture production, total fisheries export and import, fisheries export and import value, fish consumption per capita, and processed fisheries product) and human development of countries (as Human Development Index-HDI). The overall result of the study pointed that the countries located in the highest categories in terms of HDI were both export and import-dependent. The most importance levels of dependency for the Low Developed Countries (HDI < 0.550) were fish consumption, and total imports; for Medium Developed Countries (0.550 ≤ HDI < 0.699) were export value, exports, and catch production; for High Developed Countries (0.699 ≤ HDI

Objectives:To analyze the effect of macular choroidal thickness (MCT) and peripapillary choroidal thickness (PPCT) on the classification of obese and healthy children by comparing the performance of the random forest (RF), support vector machine (SVM), and multilayer perceptrons (MLP) algorithms.Materials and Methods:Fifty-nine obese children and 35 healthy children aged 6 to 15 years were studied in this prospective comparative study using optical coherence tomography. MCT and PPCT were measured at distances of 500 μm, 1,000 μm, and 1,500 μm from the fovea and optic disc. Three different feature selection algorithms were used to determine the most prominent features of all extracted features. The classification efficiency of the extracted features was analyzed using the RF, SVM, and MLP algorithms, demonstrating their efficacy for distinguishing obese from healthy children. The precision and reliability of measurements were assessed using kappa analysis.Results:The correlation feature selection algorithm produced the most successful classification results among the different feature selection methods. The most prominent features for distinguishing the obese and healthy groups from each other were PPCT temporal 500 μm, PPCT temporal 1,500 μm, PPCT nasal 1,500 μm, PPCT inferior 1,500 μm, and subfoveal MCT. The classification rates for the RF, SVM, and MLP algorithms were 98.6%, 96.8%, and 89%, respectively.Conclusion:Obesity has an effect on the choroidal thicknesses of children, particularly in the subfoveal region and the outer semi-circle at 1,500 μm from the optic disc head. Both the RF and SVM algorithms are effective and accurate at classifying obese and healthy children.

İslam düşünce tarihinin en etkili şahsiyetlerinden biri Fahreddin Râzî’dir (ö. 606/1210). Başta metafizik ve teolojik bahisler olmak üzere birçok konu ile ilgili problem oluşturan müşekkik, sorunları mezhepler üstü çözmeye çalışan muhakkik ve birçok farklı görüşü en üst kavramlarda buluşturan câmi kimlikleri, kendinden sonraki bütün düşünürleri ciddi anlamda etkilemiştir. Bu yüzden gelenekte bütün ekoller onun geride bıraktığı felsefî ve ilmî dinamizmi tevarüs etmek zorunda kalarak oluşturduğu problemler ve sunduğu çözümlerle ilgili bir tutum sergilemiştir. Onu bu denli vazgeçilemez ve etkili kılan asıl önemli saik ise onun problem oluşturan, kelamı felsefeye, felsefeyi de kelama taşıyan, kelamı esas alarak felsefeyi, felsefeyi de esas alarak kelamı eleştiren müşekkik kimliğidir. Bu nedenle hayatı boyunca siyasi ve toplumsal olarak Eş‘arîlik içinde değerlendirilen Râzî’nin eserlerine bakıldığında onun farklı ekoller tarafından sahiplenilmeye ve farklı şekillerde yorumlanmaya uygun bir düşünür olduğu açıkça görülmektedir. Birçok Ehl-i sünnet kelamcısının, Râzî’nin kelâmî-Eş‘arî bir tema ile yazdığı eserleri ön plana çıkarması, onun mezhepler üstü muhakkik kimliğinin gölgelenmesine neden olmuştur. Buna karşılık bazı düşünürlerin Râzî’yi filozof-kelamcı ve muhakkik kimliği ile bilinmesi ve tanınması noktasında bir gayret içinde oldukları görülmektedir. Özellikle Kemâleddin İbn Yunus’tan (ö. 639/1242) bir şekilde istifade eden ilmî şahsiyetlerde bu gayret açık bir şekilde ortaya çıkmaktadır. Buna örnek olarak Efdâlüddin el-Hûnecî (ö. 646/1248), Esîrüddin el-Ebherî (ö. 663/1265 ), Necmüddin el-Kâtibî (ö. 675/1277) verilebilir. Bu şahsiyetler bir taraftan Râzî’nin ilmî mirasının yaygınlaşması noktasında etkin bir rol oynarken, diğer taraftan ise Râzî’nin mezhepler üstü muhakkik kimliği ile ön plana çıkarılmasında etkili olmuşlardır. Onun söz konusu ilmî mirasını tevarüs eden Sirâceddin el-Urmevî (ö. 682/1283) de, onun daha çok mezhep üstü sorunları çözen muhakkik kimliğini tesis eden önemli isimler arasında yer almaktadır. Bu tesisin bariz bir şekilde ortaya çıktığı konuların başında ise insan fiilleri gelmektedir. Urmevî, insan fiilleri konusunda başta el-Erba‘în olmak üzere Râzî’nin insanın kudret ve tesirini yok sayacak düzeyde cebrîliği andıran ifadelerini revize etmeye çalışmaktadır. O, Lübâb isimli eserinde bir taraftan Râzî’nin el-Erba‘în isimli eserini ihtisar ederken, diğer taraftan ise Râzî’nin insan fiilleri konusundaki Eş‘arî tutumunu ciddi şekilde eleştirmektedir. Bunu da büyük ölçüde bizzat Râzî’nin el-Metâlibü’l-‘âliye mine’l-‘ilmi’l-ilâhi gibi ansiklopedik eserlerinde dile getirdiği argümanlar ekseninde yapmaktadır. Kuşkusuz bunun da sıradan bir durum olmadığı açıktır. Çünkü insan fiilleri, düşünürlerin ulûhiyyet tasavvurunu ve Allah-insan ilişkisini belirleyen konuların başında gelmektedir. Bu çalışmada Râzî’nin bu konudaki tutumu, Urmevî’nin felsefî ve kelâmî eleştirileri tespit edilmeye çalışılacaktır. Böylece insan fiilleri ekseninde onun Râzî’yi muhakkik olarak tesis etmeye çalıştığı açıkça görülmektedir.

Obstructive sleep apnea is common in adults with cardiovascular disease. Accumulating evidence suggests an association between obstructive sleep apnea and cardiovascular disease independent of the traditionally recognized cardiovascular disease risk factors. Observational studies indicate that obstructive sleep apnea is a risk factor for development of cardiovascular disease and that alleviation of obstructive events with positive airway pressure may improve cardiovascular disease outcomes. However, recent randomized controlled trials have not supported the beneficial effect of positive airway pressure in cardiac populations with concomitant obstructive sleep apnea. Some evidence suggests that the relationship between obstructive sleep apnea and traditionally recognized cardiovascular disease risk factors is bidirectional, suggesting that patients with cardiovascular disease may also develop obstructive sleep apnea and that efficient treatment of cardiovascular disease may improve obstructive sleep apnea. Recent data also indicate that the apnea–hypopnea index, which is commonly used as a diagnostic measure of obstructive sleep apnea severity, has limited value as a prognostic measure for cardiovascular disease outcomes. Novel markers of obstructive sleep apnea-associated hypoxic burden and cardiac autonomic response seem to be strong predictors of adverse cardiovascular disease outcomes and response to treatment of obstructive sleep apnea. This narrative review and position paper from the Turkish Collaboration of Sleep Apnea Cardiovascular Trialists aims to update the current evidence about the relationship between obstructive sleep apnea and cardiovascular disease and, consequently, raise awareness for health professionals who deal with cardiovascular and respiratory diseases to improve the ability to direct resources at patients most likely to benefit from treatment of obstructive sleep apnea and optimize treatment of the coexisting cardiovascular diseases. Moreover, the Turkish Collaboration of Sleep Apnea Cardiovascular Trialists aims to contribute to strengthening the efforts of the International Collaboration of Sleep Apnea Cardiovascular Trialists in this context.

Soccer is a sport branch in which a wide range of movements of different intensities are applied, which includes long-term, rapidly changing runs as a game structure, and physical parameters such as strength, agility and endurance are kept in the foreground in addition to tactical and technical skills. At this point, it is aimed to examine the relationship between different performance tests applied in young soccer players in this study. 21 male soccer players (16,33± 0,66 years, height; 172,4± 6,05 cm, body weight: 57,00± 8,81 kg) from an amateur soccer team in Konya voluntarily participated in the study. In the study, anthropometric measurements, two legged vertical jump test, yo-yo intermittent recovery 1 and 2 test, 30m sprint test and agility t test parameters were measured. The data were analyzed using the SPSS 24 package program, and the Pearson Correlation method was used in the analysis of the obtained data. As a result of the analysis of the data; A negative correlation was found between two legged vertical jump data and 30m speed and agility t test. A positive and significant correlation was found with the 30m sprint test and the agility t test. And also, a significant negative correlation was found between agility t test and yo-yo intermittent recovery 1 and yo-yo intermittent recovery 2 tests. In addition, a significant positive correlation was observed between the yo-yo intermittent recovery 2 test and the yo-yo intermittent recovery 1 test. As a result, it has been observed that different performance tests applied in young soccer players in determining the basic motoric characteristics are both negatively and positively correlated with each other.

Purpose: The aim of this research is to analyze the bibliometric and altmetric scores of highly cited articles in the area of age related macular degeneration (AMD) research and to assess the correlations between them. Material and methods: The data of publications in last decade were retrieved from the Web of Science Core Collection database using "age related macular degeneration" as a search term. The top 100 cited articles (T100) list was analyzed by author name, publication year, main topic, study type, journal name, journal impact factor (IF), H-index, total citation number (TCN), average citation per year (ACpY), Altmetric attention score (AAS), and number of tweets (NTs). VOSviewer software was utilized for visualization of bibliometric data. Results: We discovered 16.984 articles in the last decade. The median values for TCN and AAS were 221 (IQR 178–380.75) and 13 (IQR 4-37.75), respectively in T100 list. The majority of the highly cited articles in AMD research have mainly focused on AMD treatment (n=34), especially anti-vascular endothelial growth factor therapy. However, social attention was primarily on the stem cell therapy. While AAS and NTs did not have significant correlation with TCN, they did show a significant positive correlation with ACpY. AAS and NTs showed significant positive correlation with journal IF and H-index. Conclusion: Treatment for AMD is the most interested issue in the area. Stem cell therapies are popular on social media. The interest of social media is on articles that continue to be cited over the years rather than articles with high total citations.

Recently, radiation therapy with protons has received much attention. In 2020, nearly 250,000 patients in 110 centers around the world preferred radiation therapy with protons for treatment. One of them, proton-based stereotactic radiosurgery, is a treatment option after surgical interventions in Arteriovenous Malformation (AVM). The main goal of this research is to compute the amount of linear energy transfer (LET) delivered to the target because the highly preferred liquid embolic agents weaken the proton beam. LET, recoils, lateral straggle and crystalline vanacies accumulated by three different embolization materials: Ethylene vinyl alcohol (On), Cyanoacrylate (Ca) and polyvinyl alcohol (Pa) were analysed with an aim to calculate the ionization, rebound, phonon and lateral straggle of the brain at different depths for a 2 cm diameter AVM using Monte Carlo-based simulation. The obtained data were evaluated and the results compared against water. The closest Bragg peak value to water was found in Ca with a 4.1% difference. The closest to water in beam range was On with 0.9% difference. The highest recoils value was observed in PVA embolization material. The lowest lateral straggle value at all beam energy levels was in PVA embolization material.

Abstract Patients with higher-risk myelodysplastic syndromes (MDS) refractory to hypomethylating agents (HMAs) have limited therapeutic options and an expected overall survival (OS) of 3–5 months. Eltanexor is an investigational oral selective inhibitor of nuclear export with low central nervous system penetrance and an acceptable tolerability profile. Preclinical studies suggest that myeloid malignancies are sensitive to nuclear export inhibition. Eltanexor exhibited efficacy in hematologic models, supporting exploration in a clinical trial. This phase 1/2 study (NCT02649790) assessed single-agent activity of eltanexor in patients with higher-risk MDS and 5–19% myeloblasts. Two starting doses of eltanexor were evaluated: 20 mg (n = 15), 10 mg (n = 5), both administered on days 1–5 each week of a 28-day cycle. Twenty patients with primary HMA-refractory MDS, with a median age of 77 years (range 62–89), and a median of two prior treatment regimens (range 1–4) were enrolled. Of these, 15 were evaluated for efficacy and 20 for safety. The overall response rate (ORR) was 53.3%, with seven patients (46.7%) achieving marrow complete remission (mCR) and one additional patient achieving hematologic improvement (HI). In the 10 mg group, three patients (60%) reached mCR and two (40%) stable disease (SD), while for 20 mg, four patients (40%) had mCR and two (20%) SD. A total of three patients (20%) had HI and became transfusion independent ≥ 8 weeks. Median OS for the efficacy-evaluable patients (n = 15) was 9.86 months (7.98, NE). Overall, the most frequently reported treatment-related adverse events were nausea (45%), diarrhea (35%), decreased appetite (35%), fatigue and neutropenia (both 30%). Single-agent oral eltanexor was active, safe, and well tolerated in patients with higher-risk, primary HMA-refractory MDS.

INTRODUCTION: Breast cancer is the most common cancer and major cause of cancer death in women worldwide. The importance of usage positron emission tomography (PET)/computed tomography (CT) in oncology is increasing. In our study, we planned to investigate the relationship between 18 F-fluoro-2-deoxy-D-glucose (18 F-FDG) uptake and characteristics of the tumor. METHODS: The medical records of 414 patients who applied to our oncology clinic with the diagnosis of breast cancer and underwent PET/CT were analyzed retrospectively. Patients with breast cancer aged between 18-90 years were included in the study. Patients with secondary malignancy, mentally unstable, younger than 18 years of age and older than 90 years of age were excluded from the study. FDG uptake was investigated according to molecular subtypes, tumor sizes, body mass index and proliferation indices. RESULTS: The mean age of 414 patients included in the study was 48.8 years. The vast majority of patients had invasive ductal carcinoma. While 86 patients were in the metastatic stage at the time of diagnosis, 327 patients had local or locally advanced disease. In the study, there was a correlation between the increase in Ki-67 and the increase in FDG uptake and it was statistically significant (p

Abstract Background Cigarette smoking poses a major threat to public health. While cessation support provided by healthcare professionals is effective, its use remains low. Chatbots have the potential to serve as a useful addition. The objective of this study is to explore the possibility of using a motivational interviewing style chatbot to enhance engagement, therapeutic alliance, and perceived empathy in the context of smoking cessation. Methods A preregistered web-based experiment was conducted in which smokers (n = 153) were randomly assigned to either the motivational interviewing (MI)-style chatbot condition (n = 78) or the neutral chatbot condition (n = 75) and interacted with the chatbot in two sessions. In the assessment session, typical intake questions in smoking cessation interventions were administered by the chatbot, such as smoking history, nicotine dependence level, and intention to quit. In the feedback session, the chatbot provided personalized normative feedback and discussed with participants potential reasons to quit. Engagement with the chatbot, therapeutic alliance, and perceived empathy were the primary outcomes and were assessed after both sessions. Secondary outcomes were motivation to quit and perceived communication competence and were assessed after the two sessions. Results No significant effects of the experimental manipulation (MI-style or neutral chatbot) were found on engagement, therapeutic alliance, or perceived empathy. A significant increase in therapeutic alliance over two sessions emerged in both conditions, with participants reporting significantly increased motivation to quit. The chatbot was perceived as highly competent, and communication competence was positively associated with engagement, therapeutic alliance, and perceived empathy. Conclusion The results of this preregistered study suggest that talking with a chatbot about smoking cessation can help to motivate smokers to quit and that the effect of conversation has the potential to build up over time. We did not find support for an extra motivating effect of the MI-style chatbot, for which we discuss possible reasons. These findings highlight the promise of using chatbots to motivate smoking cessation. Implications for future research are discussed.

In the study, Natural jute composite materials, which have environmental advantages due to their easily degradable nature were drilled with different processing parameters and the effects of thrust force, vibration and temperature changes on hole quality were investigated. The effect of feed and spindle speed was statistically analyzed using ANOVA method. The thrust force, vibration and temperature factors that occur depending on the drilling parameters vary and affect the roughness and delamination values. The effect of feed and speed on thrust force was calculated as 97.87% and the feed effect (90.85%) is far greater than the speed (9.15%). The effect of drilling parameters on vibration is statistically insignificant due to the different spread behavior in the layers of the composite material (R2 = 0.2329). However, feed effect on vibration (94.6%) is greater than the speed effect (6.06%). The temperature is affected by 96.93% of the drilling parameters and the speed is 84.16% and the feed is 15.83%. The roughness effect depending on the drilling parameters is measured as 84.91%. The effect of speed on roughness (90.26%) is greater than the feed (9.73%). It has been determined that this situation is mostly related to vibration and temperature.

This paper addresses the problem of navigating decentralized multi-agent systems in partially cluttered environments and proposes a new machine-learning-based approach to solve it. On the basis of this approach, a new robust and flexible Q-learning-based model is proposed to handle a continuous space problem. As in reinforcement learning (RL) algorithms, Q-learning does not require a model of the environment. Additionally, Q-Learning (QL) has the advantages of being fast and easy to design. However, one disadvantage of QL is that it needs a massive amount of memory, and it grows exponentially with each extra feature introduced to the state space. In this research, we introduce an agent-level decentralized collision avoidance low-cost model for solving a continuous space problem in partially cluttered environments, followed by introducing a method to merge non-overlapping QL features in order to reduce its size significantly by about 70% and make it possible to solve more complicated scenarios with the same memory size. Additionally, another method is proposed for minimizing the sensory data that is used by the controller. A combination of these methods is able to handle swarm navigation low memory cost with at least18 number of robots. These methods can also be adapted for deep q-learning architectures so as to increase their approximation performance and also decrease their learning time process. Experiments reveal that the proposed method also achieves a high degree of accuracy for multi-agent systems in complex scenarios.

This study discusses Caryl Churchill's play Owners in terms of confusion of gender roles and capitalistic concerns through a socialist feminist criticism. The play is based on motherhood, social control, possession and material concerns. Marion's wish for an excessive possession and power brings greed and violence through subverting her feminine identity to quest gender roles. Male characters are submissive in contrast to Marion. Buddhist and Taoist philosophy in contrast to Western culture is expressed through the character Alec's passivity by exceeding his masculine roles. The depiction of the character Marion subverts the conventional patriarchal norms, still bringing no improvement for women in collectives. Marion achieves an individualistic material success when she exceeds her boundaries as a female and represses another woman. At this point analysing the play through the socialist feminist lens becomes meaningful in Churchill's depicting the egoistical figures like Marion that brings no improvement in women's social position. [ABSTRACT FROM AUTHOR]

CoCrMo alloy is widely used in artificial orthopedic joint applications due to its high mechanical properties. But, high levels of the metal ion release from alloy surfaces cause variable toxic and allergic effects on the patient in vivo use. This case restricts the lifetime of the implant and results in the failure of the artificial joint. In order to enhance the corrosion resistance and to decrease the metal ion release, alloy surface was multilayer-coated by closed field unbalanced magnetron system. The protective efficiency of the coatings was determined by potentiodynamic polarization tests and static immersion tests were performed for 45, 60 and 90 days in the simulated body fluid in order to understand the effect of the coatings on the metal ion release. The metal ion concentrations in the simulated body fluids were determined by using inductively coupled plasma mass spectrometry device. The electrochemical corrosion results showed that the multilayer coatings provided 93 % protective efficiency in terms of corrosion resistance. Multilayer coatings decreased the metal ions release levels significantly, especially Co leaking was decreased approximately 52 times compared to uncoated samples.

Previous studies have suggested favorable outcomes of hydrocortisone, ascorbic acid (vitamin C), and thiamine (HAT) therapy in patients with sepsis. However, similar results have not been duplicated in sequential studies. This meta-analysis aimed to reevaluate the value of HAT treatment in patients with sepsis. Electronic databases were searched up until October 2020 for any studies that compared the effect of HAT versus non-HAT use in patients with sepsis. Data from 15 studies (eight randomized controlled trials [RCTs] and seven cohort studies) involving 67,349 patients were included. The results from the RCTs show no significant benefit of triple therapy on hospital mortality (risk ratio [RR], 0.99; P=0.92; I2=0%); intensive care unit (ICU) mortality (RR, 0.77; P=0.20; I2=58%); ICU length of stay (weighted mean difference [WMD], 0.11; P=0.86; I2 =37%) or hospital length of stay (WMD: 0.57; P=0.49; I2=17%), and renal replacement therapy (RR, 0.64; P=0.44; I2=39%). The delta Sequential Organ Failure Assessment (SOFA) score favored treatment after a sensitivity analysis (WMD, –0.72; P=0.01; I2=32%). However, a significant effect was noted for the duration of vasopressor use (WMD, –25.49; P

Human microbiota refers to the trillions of microorganisms that inhabit our bodies and have been discovered to have a substantial impact on human health and disease. By sampling the microbiota, it is possible to generate massive quantities of data for analysis using Machine Learning algorithms. In this study, we employed several modern Machine Learning techniques to predict Inflammatory Bowel Disease using raw sequence data. The dataset was obtained from NCBI preprocessed graph representations and converted into a structured form. Seven well-known Machine Learning frameworks, including Random Forest, Support Vector Machines, Extreme Gradient Boosting, Light Gradient Boosting Machine, Gaussian Naïve Bayes, Logistic Regression, and k-Nearest Neighbor, were used. Grid Search was employed for hyperparameter optimization. The performance of the Machine Learning models was evaluated using various metrics such as accuracy, precision, fscore, kappa, and area under the receiver operating characteristic curve. Additionally, Mc Nemar’s test was conducted to assess the statistical significance of the experiment. The data was constructed using k-mer lengths of 3, 4 and 5. The Light Gradient Boosting Machine model overperformed over other models with 67.24%, 74.63% and 76.47% accuracy for k-mer lengths of 3, 4 and 5, respectively. The LightGBM model also demonstrated the best performance in each metric. The study showed promising results predicting disease from raw sequence data. Finally, Mc Nemar’s test results found statistically significant differences between different Machine Learning approaches.

In this study, transfer learning has been used to overcome multilabel classification tasks. As a case study, movie genre classification by using posters has been chosen. Six state-of-the-art pretrained models, VGG16, ResNet, DenseNet, Inception, MobileNet, and ConvNeXt, have been employed for this experiment. The movie posters have been obtained from Internet Movie Database (IMDB). The dataset has been divided using an iterative stratification technique. A sequence of dense layers has been added on top of each model and these models have been trained and fine-tuned. All the results of the models compared considered accuracy, loss, Hamming loss, F1-score, precision, and AUC metrics. When the metrics used were evaluated, the most successful result regarding accuracy has been obtained from the modified DenseNet architecture at 90%. Also, the ConvNeXt, which is the newest model among all, performed quite satisfactorily, reaching over 90% accuracy. This study uses an iterative stratification method to split an unbalanced dataset which provides more reliable results than the classical splitting method which is the common method in the literature. Also, the feature extraction capabilities of the six pretrained models have been compared. The outcome of this study shows promising results regarding multilabel classification. As for future work, it is planned to enhance this study by using natural language processing and ensemble methods.

Deep learning and diagnostic applications in oral and dental health have received significant attention recently. In this review, studies applying deep learning to diagnose anomalies and diseases in dental image material were systematically compiled, and their datasets, methodologies, test processes, explainable artificial intelligence methods, and findings were analyzed. Tests and results in studies involving human-artificial intelligence comparisons are discussed in detail to draw attention to the clinical importance of deep learning. In addition, the review critically evaluates the literature to guide and further develop future studies in this field. An extensive literature search was conducted for the 2019–May 2023 range using the Medline (PubMed) and Google Scholar databases to identify eligible articles, and 101 studies were shortlisted, including applications for diagnosing dental anomalies (n = 22) and diseases (n = 79) using deep learning for classification, object detection, and segmentation tasks. According to the results, the most commonly used task type was classification (n = 51), the most commonly used dental image material was panoramic radiographs (n = 55), and the most frequently used performance metric was sensitivity/recall/true positive rate (n = 87) and accuracy (n = 69). Dataset sizes ranged from 60 to 12,179 images. Although deep learning algorithms are used as individual or at least individualized architectures, standardized architectures such as pre-trained CNNs, Faster R-CNN, YOLO, and U-Net have been used in most studies. Few studies have used the explainable AI method (n = 22) and applied tests comparing human and artificial intelligence (n = 21). Deep learning is promising for better diagnosis and treatment planning in dentistry based on the high-performance results reported by the studies. For all that, their safety should be demonstrated using a more reproducible and comparable methodology, including tests with information about their clinical applicability, by defining a standard set of tests and performance metrics.

The purpose of this study is to examine Pam Gems' Play Dusa, Fish, Stas and Vi (1977), which portrays the inner lives of four women, through a blend of three major feminist perspectives; namely liberal feminism, radical feminism, and socialist feminism. The play supports the "the personal is political" feminism as well, since the reason of the oppression of women is the political decisions of men that have great impact on the lives of each individual woman. The four title characters represent a spectrum of female experience and women narratives in a style of biographical theatre. The common foreground for them is their struggle to survive in a male-dominated society. The play depicts friendship as a bond intended for solving individual problems with men rather than collectives fight against patriarchal power. The unbalanced gap between the political and the personal life causes Fish's downfall when she realizes women have no complete liberation in the private life. [ABSTRACT FROM AUTHOR]

A 39-year-old man presented with recurrent syncope. A 12-lead electrocardiogram and a 24-h Holter recording demonstrated atypical persistent Mobitz type I and high-degree atrioventricular block, respectively. The functional nature of the atrioventricular block was confirmed by atropine challenge, exercise testing, and electrophysiological study. The patient was successfully treated with a cardioneuroablation procedure. (Level of Difficulty: Intermediate.)

Introduction:This study aimed to evaluate patients who presented with eyelid tumour and to evaluate the masses pathologically.Methods:Between March 1, 2016- April 1, 2019, 2019, age, gender, eyelid side, pathological evaluation results and surgical margin status of the patients who presented to our clinic with eyelid mass were evaluated.Results:During the study period, 212 patients with a mean age of 55±16 years (range, 15-85 years) who underwent surgery because of an eyelid mass were included in the study. Among these patients, 78 (37.8%), 74 (35.9%) and 54 (26.2%) underwent surgery of the right, left and both eyelids, respectively, whereas 55 (26.9%), 128 (62.7%) and 21 (10.2%) underwent surgery of the lower, upper and both lower and upper eyelids, respectively. A total of 376 eyelid mass surgeries were performed. Among these masses, 371 (98.6%) were benign and 5 (1.3%) were malignant. Regarding pathological types of benign masses, 71 (19.1%) were seborrheic keratosis, 70 (18.8%) were squamous papilloma, 53 (14.21%) were fibroepithelial polyps, 52 (14.2%) were xanthelasma, 35 (9%) were intradermal nevus, 22 (5.9%) were epidermoid cyst, 14 (3.8%) were verruca vulgaris and 51 (13.7%) were different types of tumours. Five patients were diagnosed with malignant eyelid tumours; three of them had basal cell carcinoma, one had squamous cell carcinoma and one had malignant melanoma.Conclusion:Although eyelid tumours are mostly benign tumours, malignant tumours may be present in some cases. Pathological evaluation of valve masses obtained surgically is important to determine the prognosis of patients.

The world’s high-resolution images are supplied by a radar system named Synthetic Aperture Radar (SAR). Semantic SAR image segmentation proposes a computer-based solution to make segmentation tasks easier. When conducting scientific research, accessing freely available datasets and images with low noise levels is rare. However, SAR images can be accessed for free. We propose a novel process for labeling Sentinel-1 SAR radar images, which the European Space Agency (ESA) provides free of charge. This process involves denoising the images and using an automatically created dataset with pioneering deep neural networks to augment the results of the semantic segmentation task. In order to exhibit the power of our denoising process, we match the results of our newly created dataset with speckled noise and noise-free versions. Thus, we attained a mean intersection over union (mIoU) of 70.60% and overall pixel accuracy (PA) of 92.23 with the HRNet model. These deep learning segmentation methods were also assessed with the McNemar test. Our experiments on the newly created Sentinel-1 dataset establish that combining our pipeline with deep neural networks results in recognizable improvements in challenging semantic segmentation accuracy and mIoU values.