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Impact of carbon quantum dot nanoparticles on combustion, performance and emissions in diesel/microwave-assisted canola oil biodiesel blend
No full textUsage of biodiesel produced with conventional transesterification methods decreases the conversion of biodiesel from vegetable oil. Microwave-assisted production enables higher reaction efficiency, providing better conversion of vegetable oils. It also causes to obtain poorer characteristics of biodiesel, such as higher viscosity and density. It was aimed to improving the properties of biodiesel with microwave-assisted production and mixing it with nanoparticles to investigate the performance, combustion and emission characteristics. The influences of nanoparticle addition (carbon quantum dot) on engine performance, combustion and emissions have been analyzed in a direct injection CI engine. A single cylinder water cooled CI engine was used in the experiments. Experiments were performed at 4.12, 9.61, 15.10, 20.60 Nm and 2200 rpm. Canola biodiesel was obtained via the microwave-assisted transesterification method and mixed with diesel at the ratio of 20% (B20). 50, 100 and 150 ppm nanoparticle were added to the obtained B20 and tested in a CI engine. Specific Fuel Consumption (SFC) raised by 2.03%, 4.83%, 4.40% and 1.69% with B20, B20CQD 50 ppm, B20CQD 100 ppm and B20CQD 150 ppm respectively compared that diesel at 15.10 Nm. Remarkable reduction was found on CO, HC with B20CQD 50 ppm, B20CQD 100 ppm and B20CQD 150 ppm according to B20. In addition, an impressive reduction was realized on soot emissions with the usage of nanoprticle addition. But, NOx increased using fuel blends. As a result, the usage of quantum dot nanoparticle improved the poor properties of canola oil biodiesel and test fuels were used easily without modification in a diesel engine.Afyon Kocatepe University Scientific Research Projects Coordination Unit [21.TEKNOLOJ_I.02]This study was supported by Afyon Kocatepe University Scientific Research Projects Coordination Unit with the project number 21.TEKNOLOJ_I.02. The authors thank Afyon Kocatepe University Scientific Research Projects Coordination Unit
Fragments of open- and closed-canopy habitat host significant fruit-feeding butterfly diversity in a large city in Southern India
No full textUrban environments can host a wide variety of wild animals and plants, potentially contributing to conservation and facilitating city-dwellers' contact with nature. However, we have limited knowledge about biodiversity in tropical cities, including butterfly diversity. To gauge the diversity, community composition, and temporal variation of butterflies in urban habitats, we sampled fruit-feeding butterflies (species that feed on fruit rather than flower nectar) in a large city in southern India. We performed longer-term sampling in two sites with mainly open habitats (fragments of rural landscape), and more modest sampling in two closed-canopy urban sites (semi-natural and agroforestry) and a nearby natural forest. We caught 3625 butterflies belonging to 29 species, of which seventeen species were recorded in the open habitats, and a further five species in the closed-canopy sites in the city. The natural site had the highest number of species. Also taking into account published data on another natural site in the wider region, about half of the region's fruit-feeding butterfly fauna was recorded from the urban sites. The community composition differed significantly between the open- and closed-canopy sites. Notably, the open habitats in the city featured a protected species, and closed-canopy sites harboured charismatic forest species. There was extensive temporal variation in butterfly community composition that was partly seasonal. Overall, our results show that habitats within the city harbour a rich and valuable fruit-feeding butterfly diversity, and are thus worth conserving for nature education.Naradowe Centrum Nauki [2021/43/B/NZ8/00966]; INSPIRE Faculty Award [DST/INSPIRE/04/2013/000476]We thank Ullasa Kodandaramaiah for supporting the fieldwork, and Kalesh Sadasivan for advice on sampling sites, identifications, and corrections on the manuscript. For help with the fieldwork, we are grateful to Sridhar Halali, Dheeraj Halali, Jisha Vijaykumar, O. Vignesh, Bharat Parthasarathy, and Soumen Mallick. The fieldwork of FM was funded through an INSPIRE Faculty Award to Ullasa Kodandaramaiah (DST/INSPIRE/04/2013/000476), and data curation to manuscript preparation was made possible by grant 2021/43/B/NZ8/00966 from the Naradowe Centrum Nauki (National Science Centre, Poland). We thank anonymous reviewers for insightful and numerous comments on a previous version of the manuscript
Topluluk öğrenmesi kullanılarak arıza tahmini: sentetik ve gerçek dünya veri setleriyle karşılaştırmalı bir çalışma
No full textThe ability to predict and prevent machine failures is a crucial
task for businesses on a global scale at a time of increasing
dependence on automation and technology. This paper
primarily addressed a novel failure prediction model approach
based on ensemble learning. Commonly used machine learning
models including Decision Trees, K-Nearest Neighborhood,
Support Vector Machines, and Logistic Regression and two
different ensemble learning strategies were used: bagging and
majority voting. The SZVAV real-life failure dataset provided by
Lawrence Berkeley National Laboratory and the AI4I2020
Predictive Maintenance synthetic dataset were utilized to
evaluate the performance of the proposed ensemble models.
The preprocessing stage included the application of
oversampling since there is an imbalance problem in both
datasets. In this context, a comparison of three oversampling
techniques was also presented for the datasets considered in
the study. As a result of the tests, it was seen that the proposed
models are superior to individual machine learning methods and
Random Forest, which is an ensemble model itself, for the
considered datasets. In addition, the proposed ensemble
models were compared with the original failure prediction
models previously presented in the literature on the AI4I2020
dataset, and it was reported that more successful results are
obtained with the proposed approach.Makine arızalarını tahmin etme ve önleme yeteneği, otomasyon
ve teknolojiye olan bağımlılığın arttığı bir zamanda küresel
ölçekte işletmeler için kritik bir görevdir. Bu çalışma öncelikle
topluluk öğrenmeye dayalı özgün bir arıza tahmin modeli
yaklaşımını ele almaktadır. Karar Ağaçları, K-En Yakın Komşuluk,
Destek Vektör Makineleri ve Lojistik Regresyon dahil olmak
üzere yaygın olarak kullanılan makine öğrenmesi modelleri ve iki
farklı topluluk öğrenme stratejisi kullanılmıştır: torbalama ve
çoğunluk oylaması. Lawrence Berkeley Ulusal Laboratuvarı
tarafından sağlanan SZVAV gerçek yaşam arıza veri seti ve
AI4I2020 Tahmini Bakım sentetik veri seti, önerilen topluluk
modellerinin performansını değerlendirmek için kullanılmıştır.
Her iki veri setinde de bir dengesizlik sorunu olduğu için ön
işleme aşaması aşırı örnekleme uygulamasını içermektedir. Bu
bağlamda, çalışmada ele alınan veri setleri için üç aşırı
örnekleme tekniğinin bir karşılaştırması da sunulmuştur. Testler
sonucunda, ele alınan veri setleri için önerilen modellerin
bireysel makine öğrenmesi yöntemlerinden ve kendisi bir
topluluk modeli olan Rastgele Orman'dan üstün olduğu
görülmüştür. Ayrıca önerilen topluluk modelleri, AI4I2020 veri
seti üzerinden literatürde daha önce sunulan orijinal hasar
tahmin modelleri ile karşılaştırılmış ve önerilen yaklaşımla daha
başarılı sonuçlar elde edildiği raporlanmıştır
Photodiagnosis with deep learning: A GAN and autoencoder-based approach for diabetic retinopathy detection
No full textBackground: Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide, necessitating early detection and accurate diagnosis. This study proposes a novel framework integrating Generative Adversarial Networks (GANs) for data augmentation, denoising autoencoders for noise reduction, and transfer learning with EfficientNetB0 to enhance the performance of DR classification models. Methods: GANs were employed to generate high-quality synthetic retinal images, effectively addressing class imbalance and enriching the training dataset. Denoising autoencoders further improved image quality by reducing noise and eliminating common artifacts such as speckle noise, motion blur, and illumination inconsistencies, providing clean and consistent inputs for the classification model. EfficientNetB0 was fine-tuned on the augmented and denoised dataset. Results: The framework achieved exceptional classification metrics, including 99.00 % accuracy, recall, and specificity, surpassing state-of-the-art methods. The study employed a custom-curated OCT dataset featuring high-resolution and clinically relevant images, addressing challenges such as limited annotated data and noisy inputs. Conclusions: Unlike existing studies, our work uniquely integrates GANs, autoencoders, and EfficientNetB0, demonstrating the robustness, scalability, and clinical potential of the proposed framework. Future directions include integrating interpretability tools to enhance clinical adoption and exploring additional imaging modalities to further improve generalizability. This study highlights the transformative potential of deep learning in addressing critical challenges in diabetic retinopathy diagnosis
Investigation of bituminous binder properties modified with plastic bags and glass wastes
Get PDFDünyada hızla artan insan nüfusu, tüketime bağlı atık miktarının artışını doğrudan etkilemektedir. Mevcut hammadde kaynaklarının orantısız tüketimi, toprak, su ve hava kirliliği, zamanla yetersiz atık depolama alanları gibi öncelikle insan ve çevre sağlığını etkileyen sorunları ortadan kaldırmanın en temel yolu, etkili atık yönetiminden geçmektedir. Bu bağlamda, günümüzde hızla artan atık malzemelerin, geri dönüşüm için bile enerji tüketmeden tekrar kullanılması, atık bertarafı için önemli bir çözümdür. Bu çalışmada,atık cam şişeler ve plastik poşetler bitüm modifikasyonunda kullanılmıştır. 15 adet modifiye bitüm ve 1 adet saf bitüm (kontrol), her ikisini de farklı oranlarda bitüm içeren cam atığı (%0, 0,5, 1,0, 1,5, 3,0, 5,0%), plastik torba atığı (%0, 0,5, 1,0, 1,5, 3,0, 5,0%) ve hibrit atık (%0,5 CA + 0,5 PPA; 0,5 CA + 1,0 PPA; 0,5 CA + 1,5 PPA; 0,5 CA + 2,0 PPA; 1,0 CA + 2,0 PPA) malzemelerinin farklı oranlarda karıştırılmasıyla hazırlanmış ve numuneler üzerinde fiziksel ve reolojik testler yapılmıştır. Test sonuçlarına göre %1 serisi cam atığı, %3 serisi plastik poşet atığı ve 0,5 CA + 1,5 PPA serisi hibrit atık numuneleri daha iyi davranış göstermiştir.The rapidly increasing human population in the world directly affects the increase in the amount of waste. The most basic way to eliminate problems that primarily affect human and environmental health, such as disproportionate consumption of existing raw material resources, soil, water and air pollution, and insufficient waste storage areas over time, is through effective waste management. In this context, reusing waste materials, which are rapidly increasing today, without consuming energy even for recycling, is an important solution for waste disposal. In this study, waste glass bottles and plastic bags were used in bitumen modification. 15 modified bitumen and 1 pure bitumen, glass waste (0, 0.5, 1.0, 1.5, 3.0, 5.0%), plastic bag waste (0, 0.5, 1.0, 1.5, 3.0, 5.0%) and hybrid waste (0.5 WGP + 0.5 NBW; 0.5 WGP + It was prepared by mixing the materials (1.0 NBW; 0.5 WGP + 1.5 NBW; 0.5 WGP + 2.0 NBW; 1.0 WGP + 2.0 NBW) in different proportions and physical and rheological tests were performed on the samples. According to the test results, 1% series glass waste, 3% series plastic bag waste and 0.5 WGP + 1.5 NBW series hybrid waste samples showed better behavior
Barriers to school principals' effective instructional supervision practices: evidence from a centralised educational context
Get PDFAlthough improving instructional supervision has already been featured in theoretical debates and even advocated for in the policy frameworks of many nations - including the USA, UK, and countries across Europe - little is known beyond the Western world about the potential difficulties faced by school principals seeking to implement instructional supervision practices to promote teaching and learning in their schools. This study investigated barriers to school principals' effective instructional supervision practices. The participants of this qualitative study included a total of 57 principals and teachers working in secondary schools. Data were collected through interviews and analysed through qualitative content analysis. Bringing evidence from a centralised educational context, we identified four major barriers to the effective instructional supervision process: (i) lack of supervisory skills and content knowledge, (ii) negative attitudes to supervision, (iii) maintaining a family-like school atmosphere, and (iv) lack of time and heavy workload. Based on the findings, we provide several implications for policy and practice
Fabrication and characterization of alkali-activated Fe-rich fayalitic slag as a sustainable radiation shielding material
Get PDFThe development of innovative materials for radiation shielding is gaining attention due to the increasing need for sustainable alternatives. This study investigates alkali-activated Fe-rich fayalite slag (FS) as a potential radiation shielding material. Five different mixtures such as cement paste (CP), cement mortar (CM), fayalite slag cement mortar (FSCM), fayalite slag paste (FSP), and fayalite slag mortar (FSM) were prepared and analysed for physical, mineralogical, mechanical, and gamma-ray attenuation properties. Density measurements revealed that FS-based materials, particularly FSP and FSM, exhibited higher densities (3000 +/- 1.5 kg/m(3) and 2800 +/- 1.2 kg/ m(3), respectively) compared to cement-based samples. FTIR and XRD analyses confirmed the presence of different structural units, distinguishing FS-based materials from traditional concretes. Compressive strength tests showed that, except for FSM, all samples were suitable for structural applications. Gamma-ray shielding properties were assessed through experimental, Monte Carlo simulation, and theoretical (EpiXS) methods. FS-based materials demonstrated superior linear attenuation coefficients (>0.17 cm(-1) at 0.662 MeV) compared to cement-based counterparts (<0.13 cm(-1)), attributed to the high iron content in FS. It can be concluded that alkali-activated fayalite slag offers a promising, eco-friendly alternative for radiation shielding applications, combining high attenuation performance with sustainable material utilization.Research Council of Finland [354263, 355001]; Jane ja Aatos Erkko Foundation; Tiina ja Antti Herlin Foundation; Scientific and Technological Research Council of Turkiye; Centre for Material Analysis, University of Oulu, FinlandThis work was supported by the Research Council of Finland (#354263) and Advanced Steels for Green Planet project funded by Jane ja Aatos Erkko Foundation and Tiina ja Antti Herlin Foundation. The participation of R. Kurtulus and C. Kurtulus were funded by The Scientific and Technological Research Council of Turkiye, Science Fellowships and Grant Programme Directorate, within the scope of 2219-International Postdoctoral Research Fellowship Program for Turkish Citizens. O. Mankinen participation was funded by Research Council of Finland (#355001) . Part of the work was carried out with the support of the Centre for Material Analysis, University of Oulu, Finland. Mr. Jani Osterlund, Mr. Jarno Karvonen, and Mrs. Elisa Wirkkala are acknowledged for their help in the laboratory work
Vaka raporu: bir kedide zambak (lilium orientalis) zehirlenmesi
No full textSome lily species are toxic to cats. The main harmful effect is on the kidneys and leads to acute renal damage. Ingestion of any part of the plant can cause poisoning. Even the ingestion of small amounts of plant parts can have serious consequences. The mechanism of toxicity is not known exactly. Symptoms develop rapidly. In the progress of the disease, the gastrointestinal system is primarily affected. Afterward, polyuria, dehydration, and renal failure accompany the symptoms. Seizures may occur in severe cases. In acute cases, the animal may be tried to induce vomiting, and/or applications to reduce toxin absorption may be made. Renal perfusion is attempted to be provided with intravenous fluid applications. Treatment options are more limited in the cases of lily intoxication if renal failure develops. Taking precautions against the plant is more effective than treatment. Therefore, it is important to raise awareness of cat owners. In the present case, stargazer poisoning in an elderly female British Shorthair cat brought to a private veterinary clinic for examination and treatment was discussed. Toxication was diagnosed based on clinical, hematological, and biochemical findings. The cat presented with symptoms such as vomiting, anorexia, lethargy, and urinary obstruction, all indicative of lily toxicosis. This case report aims to emphasize the toxicity that may be caused by lily plants in cats living at home. Also, it provides information about diagnostic and therapeutic procedures.Bazı zambak türleri kediler için toksiktir. Başlıca toksik etkisi böbrekler üzerinde görülür ve akut renal hasara yol açar. Bitkinin herhangi bir kısmının alınması zehirlenmeye neden olabilir. Az miktarda bitki parçası yutulduğunda dahi ciddi sonuçlarla karşılaşılabilir. Toksisitenin mekanizması tam olarak bilinmemektedir. Belirtiler hızla gelişir. Hastalık seyrinde öncelikle gastrointestinal sistem etkilenir, sonrasında tabloya poliüri, dehidrasyon ve böbrek yetmezliği eşlik eder. Şiddetli vakalarda nöbet görülebilir. Akut olgularda hayvan kusturulmaya çalışılabilir ve/veya toksin emilimini azaltıcı uygulamalar yapılabilir. İntravenöz sıvı uygulamaları ile renal perfüzyon sağlanmaya çalışılır. Böbrek yetmezliği gelişmiş toksikasyon vakalarında tedavi seçenekleri daha sınırlıdır. Bitkiye karşı önlem almak tedaviden daha etkilidir. Bu nedenle kedi sahiplerinin bilinçlendirilmesi önemlidir. Sunulan raporda özel bir veteriner kliniğe muayene ve tedavi amaçlı getirilen bir yaşlı dişi british shorthair ırkı kedide stargazer zehirlenmesi konu edildi. Anamnezde kusma, iştahsızlık, durgunluk ve idrar yapamama şikayeti bulunan kediye klinik, hematolojik ve biyokimyasal bulgular ve anamnez bilgi dahilinde zambak toksikasyonu tanısı kondu. Bu olgu sunumu; evde yaşayan kedilerde zambak bitkisinin neden olabileceği toksikasyona dikkat çekmeyi ve yanı sıra tanı ve tedavi prosedürü hakkında bilgi vermeyi hedeflemektedir
Study of Impact Behavior of Glass-Fiber-Reinforced Aluminum Composite Sandwich Panels at Constant Energy Levels
No full textIn this investigation, we assessed the potential of aluminum composite panels (ACPs) in sustainable engineering applications, focusing on the effects of different glass fiber weights on impact resistance and energy absorption capacity. Aluminum composite panels are an attractive option for sustainable applications due to their lightweight and high-strength properties. In this study, low-velocity impact tests were conducted on panels with glass fiber weights of 200 g/m2 and 400 g/m2 and equal numbers of fiber layers. The tests were performed using a constant impact energy of 55 joules, and the force-time, force-displacement, energy-time, and energy-displacement behaviors of ACP, 200 ACP, and 400 ACP samples were analyzed. The results showed that the 400 ACP samples exhibited the highest impact strength, the highest energy absorption capacity, and the least damage. In contrast, the other two samples showed lower impact resistance and exhibited fiber breaks, delaminations, and core material damage on their surfaces. The different glass fiber weights used in this study contributed to increases in the impact resistance and energy absorption capacity. Positive correlations were found between the glass fiber weight, layer thickness, and impact strength. These findings provide new insights into how composite materials can be designed to optimize mechanical properties by adjusting the fiber weights in coatings. These results also offer valuable information for the development of next-generation materials used in various sustainable engineering fields, such as automotive engineering and vehicle technology
Effect of Glass Fiber Reinforcement on Mechanical Properties of Wood Material
No full textIncreasing the mechanical strength of wooden materials with glass fiber fabric reinforcement and composite elements can be a very suitable method for restoration and strengthening techniques in historical wooden structures. In this study, the effects of fiber-reinforced laminated wood composites were examined with respect to bending strength and modulus of elasticity in bending. Experimentally, 0 degrees/90 degrees woven glass fiber fabrics with areal weights of 200, 300, and 400 g/m2 were bonded using epoxy resin to the longitudinal surfaces of two different wood species (Scots pine and Turkish beech). An evaluation of the bending properties of these wooden sandwich structures revealed that the incorporation of glass fiber fabric reinforcement led to a significant enhancement in their bending strength. In addition, a significant improvement was achieved in the modulus of elasticity. It was observed that glass fiber fabric, especially the 400 g/m2 weight options, increased the durability of wood materials more. As a result, the bending strength of wood materials can be significantly increased with glass fiber fabric reinforcement. This method can be considered a promising reinforcement technique, particularly in the fields of engineering and construction. However, in the context of historical restoration, the use of external reinforcement must be approached with caution due to conservation principles such as material authenticity, reversibility, and minimal intervention