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A detailed study of the combustion-fuel behavior of nanofuels containing boron/catalyst nanohybrid particles
No full textBoron, with its high theoretical calorific value, is a promising alternative fuel, but its problematic oxidation behavior prevents complete combustion and limits its potential. This study focuses on the production of amorphous boron (AB) particles with reduced B2O3 layers using ball milling and their decorating with perovskite-type nano catalysts (La0.7 Nd0.3MnO3, Nd0. 7Ba0.3MnO3, La0.5 Nd0.3Ba0.2MnO3) by a cost-effective ultrasonication methods. The structural characterizations of all particles were characterized by SEM and XRD techniques. To evaluate the catalytic activity of the nanocatalysts, elemental analysis and surface area measurements were carried out by XPS and BET analysis, respectively. Combustion tests on gasoline-based nanofuels (2.5 and 7.5 wt%) in a controlled droplet-scale chamber showed that higher particle concentrations reduced ignition delay. However, boron hybrid particles had ignition delays similar to pure boron particles. Residual aggregate temperatures of 7.5 wt% AB-LNM1, AB-NBM, and AB-LNBM1 droplets were 111.5 %, 100 %, and 110.4 % higher than those with AB-BM. SEM-EDX analyses of residues revealed that AB-LNBM1 hybrids had the highest catalytic efficiency, with 5.47 % carbon and 17.53 % oxygen, significantly improving boron and soot oxidation. Engine tests using 250 ppm diesel blends highlighted NBM nanoparticles as having the lowest BSFC, while AB-LNBM1 achieved the highest HRR increase (12.69 %) and CO2 emissions (9.53 %) at 60 Nm. AB-LNBM1 also reduced HC emissions by 53.33 % at 15 Nm, and NBM provided the largest NOx reduction (9.70 %) at 30 Nm. Overall, boron/catalyst nanohybrids enhanced combustion behavior, improved fuel efficiency, and reduced pollutant emissions. These findings suggest that such hybrids have significant potential for advancing alternative fuel applications and reducing the environmental impact of hydrocarbon fuels
Liposomal propolis loaded xanthan gum-salep hydrogels: Preparation, characterization, and in vitro bioaccessibility of phenolics
No full textLiposomes are gaining interest in food and pharmaceutical applications due to their biocompatibility and non-toxicity. However, they suffer from low colloidal stability, leakage of encapsulated substances, and poor resistance to intestinal digestive conditions. To address these issues, propolis extract (PE) was encapsulated within a hybrid system combining liposomes and hydrogels. PE encapsulated in phosphatidylcholine liposome formulations incorporated with two different food additives: polyethylene sorbitan monooleate (T80) and ammonium phosphatide (AMP) was embedded in xanthan gum-salep hydrogels. The embedded liposomes protected their structure and did not change the flow behaviour of the hydrogels. AMP-liposomal gels exhibited a stronger solid character. The mucoadhesiveness of liposomal gels was mostly governed by the higher xanthan gum ratio, while PE loading also yielded higher mucoadhesiveness. The bioaccessibility (BI%) of the phenolic compounds ranged from 10.13 to 582.75 % in the liposomal gel. The proposed hybrid encapsulation method not only provided enhanced solubility to hydrophobic PE but also protected its phenolic compounds against simulated digestion conditions. Moreover, converting aqueous liposomes into gel structures would also expand their application range in various functional food formulations
THE EFFECT OF GAMIFIED ELEMENTS ON ACADEMIC WRITING ACHIEVEMENT AND MOTIVATION OF ENGLISH PREPARATORY STUDENTS
No full textPRENATAL TANIDA TRİZOMİ RİSK TAHMİNİ İÇİN QF-PCR SONUÇLARI, DEMOGRAFİK, KLİNİK VE GENETİK VERİLERİN ENTEGRASYONUNUN MAKİNE ÖĞRENMESİ TABANLI ANALİZİ
No full textPrenatal tanı süreci, fetüste olası genetik ve kromozomal anomalileri gebelik sırasında tespit etmeyi hedefleyen kritik bir süreçtir. Özellikle Trizomi 21 (Down sendromu), Trizomi 18 (Edwards sendromu) ve Trizomi 13 (Patau sendromu) gibi yaygın kromozomal bozuklukların erken teşhisi, gebelik yönetimi ve fetal sağlık açısından büyük önem taşır. Bu çalışmada, QF-PCR (Kantitatif Floresan Polimeraz Zincir Reaksiyonu) yöntemi ile elde edilen sonuçlar, hastaların demografik (yaş, sigara kullanımı, hamilelik geçmişi), klinik (ultrasonografi bulguları, tarama test sonuçları) ve genetik verileriyle birlikte değerlendirildi. Bu veriler makine öğrenmesi yöntemleri ile entegre edilerek trizomi riskinin erken ve doğru tahmin edilmesi amaçlandı. Toplanan veriler, Lojistik Regresyon, Random Forest, Karar Ağacı ve K-Nearest Neighbors (KNN) gibi makine öğrenmesi algoritmaları kullanılarak analiz edildi. Ve modellerin performansları AUC, F1 skoru ve doğruluk gibi metriklerle ölçüldü.Random Forest algoritması, AUC değeri 0.99 ve F1 skoru 0.87 ile en yüksek doğruluk oranına ulaşarak trizomi riskini tahmin etmede diğer algoritmalar arasında en iyi performansı gösterdi. Lojistik Regresyon algoritması güçlü bir doğruluk oranı (AUC: 0.86) sunarken, KNN algoritması beklenenin altında bir performans gösterdi (AUC: 0.52). Bu sonuçlar, yapay zeka ve makine öğrenmesi tabanlı yaklaşımların, prenatal dönemde yüksek doğruluk oranıyla trizomi riskini tahmin etmekte ve gereksiz invaziv testlerin önüne geçmede etkin bir araç olabileceğini göstermektedir.Çalışmanın bulguları, prenatal tanıda trizomi risk tahminlerinin doğruluğunu artırmanın yanı sıra, bu tahminlerin klinik uygulamalara entegrasyonu için değerli içgörüler sunmaktadır. Bu modelleme, özellikle yüksek riskli gebeliklerde hızlı ve bilinçli kararlar alınmasını destekleyerek hasta yönetim sürecini optimize etmektedir. Makine öğrenmesi algoritmalarının prenatal tanı süreçlerine entegrasyonu, hem maddi hem de manevi açıdan sağlık sistemine katkı sağlamakta; genetik danışmanlık süreçleri, hasta yönetimi ve gelecekteki prenatal tanı yöntemlerine dair önemli ilerlemeler sunmaktadır.Prenatal diagnosis is a critical process aimed at detecting potential genetic and chromosomal anomalies in the fetus during pregnancy. Early detection of common chromosomal disorders, particularly Trisomy 21 (Down syndrome), Trisomy 18 (Edwards syndrome) and Trisomy 13 (Patau syndrome) is crucial for pregnancy management and fetal health. In this study, results obtained through QF-PCR (Quantitative Fluorescent Polymerase Chain Reaction) were evaluated in conjunction with patients' demographic (age, smoking status and pregnancy history), clinical (ultrasonography findings and screening test results) and genetic data. These data were integrated with machine learning methods to achieve early and accurate prediction of trisomy risk. The collected data were analyzed using machine learning algorithms such as Logistic Regression, Random Forest, Decision Tree and K-Nearest Neighbors (KNN) and the models' performances were measured using metrics such as AUC, F1 score and accuracy.The Random Forest algorithm demonstrated superior performance among other algorithms in predicting trisomy risk, achieving the highest accuracy rate with an AUC value of 0.99 and F1 score of 0.87. While the Logistic Regression algorithm provided a robust accuracy rate (AUC: 0.86), the KNN algorithm showed lower than expected performance (AUC: 0.52). These results indicate that artificial intelligence and machine learning-based approaches can serve as effective tools in predicting trisomy risk with high accuracy during the prenatal period and preventing unnecessary invasive tests.The study's findings not only enhance the accuracy of trisomy risk predictions in prenatal diagnosis but also provide valuable insights into the integration of these predictions into clinical practice. This modeling optimizes patient management processes by supporting rapid and informed decision-making, particularly in high-risk pregnancies. The integration of machine learning algorithms into prenatal diagnostic processes contributes both financially and ethically to the healthcare system, offering significant advancements in genetic counseling processes, patient management and future prenatal diagnostic methods.</p
Atıl Turizm Tesislerinin Rasyonel Kullanımına Yönelik Bir Öneri : Yaşlılar İçin Yaşam Turizmine Dönüştürülmesi
No full textÖzet: Türkiye’nin ekonomik kalkınmasında inşaat ve turizm sektörü çok önemli bir role sahiptir. Ancak, turizm sektörünün sağlıklı bir şekilde sürekliliğinin sağlanması, ülkenin sosyo-ekonomik, sosyopolitik ve istikrarlı bir demokrasinin sağlanmasını gerektirir. Diğer riskler ise küresel boyuttadır. Yaşanan pandemi ve Rusya-Ukrayna Savaşı gibi riskler turizmi derinden etkilemiş, bir kısım tesis kapanmış ya da sezonluk hizmet ile ayakta duramayan tesislerin sayısı artmıştır. Bu bildiri turizm sektörünün ekonomik anlamda darboğaza düşme riskine karşı sürdürülebilir bir kullanım önermektedir. Mevcutta atıl kalmış, ekonomik anlamda sıkıntı yaşayan tesislerinin mevsimlik kullanıma bağlı kalmaması ve sezonluk değil sürekli doluluk yaratan yabancı yaşlılara yaşam turizmine yönelik bir model önermektedir. Özellikle ülkemize gelmek isteyen ama bir nedenle güvenlik, sağlık vb. gerekçelerle ev alıp ya da kiralayarak evde yaşamak istemeyen yaşlılar için, süre kısıtı olmayan alternatif bir yaşam turizmi sunulabilir. Yaşlı yaşam turizmine dönüştürülecek tesislerin turizmde mevsimlik dalgalanmalardan etkilenmemesi hedeflenmektedir. Turizmde on iki ayı verimli hale getirmek için yaşlı turizmine yönelik kullanım seçenekleri geliştirilmelidir. Anahtar Kelimeler: Yaşlı Turizmi, Turizm, Mimari Tasarım</p
Investigation of the Effects of Ammonium Hydroxide Addition on Morphological, Crystal Structure and Porosity in Boron Nitride Nanosheets
No full textIn this study the addition of ammonium hydroxide on themorphology, crystal structure and porosity of boron nitride nanostructures wereexamined. The results of study indicatethat the augmentation of ammonium hydroxide in the starting chemicals of boricacid and urea led to an elevation in crystallinity and a reduction in poreformation. The use of ammonium hydroxide changed the boron nitride structurefrom its original bulk form containing open pores to initially to nanosheetform and then to a prismatic rod structure. The formation of clustered boronnitride nanosheets are observed when 1 mol/L ammonium hydroxide is used.Although it is understood that boron nitride rods form at the 2 mol/L ofammonium hydroxide addition, the surfaces of nanorods are still decorated withnanosheets with similar size and morpholoy. The nanosheets on the rods werepositioned in a regular and ordered spacings. When the ammonium hydroxide addition isincreased further to 4 mol/L, the nanosheets are still visible on the boronnitride rods but their sizes were increased and their regular spacings aredisrupted. Finally, when the ammonium hydroxide addition is increased tomaximum of 8 mol/L the boron nitride nanosheet formation ceases to exist andthe surfaces of boron nitride rods appear totally smooth. For the boron nitridenanostructures, there is a clear correlation between the total surface area,pore diameters, and the amount of ammonium hydroxide addition. While the poresize decreases with increasing ammonium hydroxide, the surface area decreasesaccordingly. The results indicate that the ammonium hydroxide addition could beutilized to tailor the surface quality of boron nitride nanostructures thatcould affect the storage capability. Keywords: Boron nitride nanosheets, sol-gel,ammonia hydroxide, crystallinity, porosity</p
A Two-Stage Analysis of Interaction Between Stock and Exchange Rate Markets: Evidence from Turkey
No full textIn this study, we use a novel approach to explore possible connections between foreign exchange and stock returns using Turkish financial data from 2005 to 2022. Our method involves a two-stage technique. The first stage begins by decomposing individual time series signals into separate intrinsic mode functions (IMFs) with a complete ensemble empirical mode decomposition with added noise algorithm. Extracted IMFs are then used to construct high and low-frequency components through a fine-to-coarse algorithm. In the second phase, we utilized a cross-quantilogram technique to analyze the dependence in quantiles of the original return series along with frequency components obtained in the previous stage. Results revealed several important insights. Firstly, a relatively higher effect ran from stock returns to exchange rate returns for the pertinent period. Secondly, tail dependence is apparent, as returns are discernibly linked. Thirdly, the tail dependence in the returns is more profound in the high-frequency composition than in the low-frequency component. Lastly, the structure of dependence has stayed mostly constant throughout the sample period analyzed