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Brood Rearing and Dose Optimisation for Induced Breeding of Raikor, Cirrhinus reba (Hamilton, 1822)
No full textAn experiment on brood rearing and induced breeding of the near threatened fish species Raikor, Cirrhinus reba using the pituitary gland (PG), was conducted from March to August 2020 at the Floodplain Sub-station of Bangladesh Fisheries Research Institute, Santahar, Bogura. Broods were collected and reared in the ponds of the hatchery complex. The total length (cm), body weight (g), gonad weight (g), and gonado-somatic index (%) of this species were measured during the rearing period. To standardize the breeding technique, a total of 90 brood fish of C. reba were treated with different doses of PG, specifically, 2.0, 4.0, 6.0 mg/kg body weight for females and 1.0, 2.0, 3.0 mg/ kg body weight for males in different treatments, namely T1, T2, and T3 respectively. A significant difference (p<0.05) was observed in fecundity, ovulation (%), and the fertilization rate (%) among the treatments. Based on the results, T2 (4.0 mg/kg body weight for females, 2.0 mg/kg body weight for males) produced the most favorable results. The current observations could be applied to C. reba stimulated breeding for the advancement of hatchery formation. More research on the nursing, nurturing, and culture of the near- threatened C. reba at varied densities and feedings is necessary for their conservation and restoration
Modelling and performance-based PD controller of the electric autonomous vehicles with the environmental uncertainties
No full textThe popularity of Electric Autonomous Vehicles (EAVs) is rising continuously because they offer lower emissions, less energy consumption, safer, and more comfortable driving technologies. In this paper, a dynamic model of the EAV is derived, and analysed extensively in terms of the corresponding stability region for the linear and nonlinear EAV with a DC motor. Considering the dynamic environment, there are various uncertainties such as the puddles, bumps, and roundabout turnings that the vehicles must interact in real life applications. In order to model such uncertainties, the motions of the EAV have been analysed through observing the responses of the vehicles in the dynamic environments and then physical laws are utilized to accurately model them. Finally, a performance-based Proportional Derivative (PD) controller, specified with the desired maximum overshoot, settling time, rising time is constructed to handle such environmental uncertainties. To justify the developed model and controller, the corresponding motion, stability region and control of the EAV results obtained in the simulation environment are analysed comprehensively.Adana Alparslan Turkes Science and Technology University Scientific Research Projects [21303004]This work was supported by Adana Alparslan Turkes Science and Technology University Scientific Research Projects [grant number 21303004]
Development of Boron-Containing PVA-Based Cryogels with Controllable Boron Releasing Rate and Altered Influence on Osteoblasts
No full textCryogel formation is an effective approach to produce porous scaffolds for tissue engineering. In this study, cryogelation was performed to produce boron-containing scaffolds for bone tissue engineering. A combination of the synthetic polymer, poly(vinyl alcohol) (PVA), and the natural polymers, chitosan and starch, was used to formulate the cryogels. Boron was used with a dual purpose: as an additive to alter gelation properties, and to exploit its bioactive effect since boron has been found to be involved in several metabolic pathways, including the promotion of bone growth. This project designs a fabrication protocol enabling the competition of both physical and chemical cross-linking reactions in the cryogels using different molecular weight PVA and borax content (boron source). Using a high ratio of high-molecular-weight PVA resulted in the cryogels exhibiting greater mechanical properties, a lower degradation rate (0.6-1.7% vs. 18-20%) and a higher borax content release (4.98 vs. 1.85, 1.08 nanomole) in contrast to their counterparts with low-molecular-weight PVA. The bioactive impacts of the released borax on cellular behaviour were investigated using MG63 cells seeded into the cryogel scaffolds. It was revealed that the borax-containing scaffolds and their extracts induced MG63 cell migration and the formation of nodule-like aggregates, whilst cryogel scaffolds without borax did not. Moreover, the degradation products of the scaffolds were analysed through the quantification of boron release by the curcumin assay. The impact on cellular response in a scratch assay confirmed that borax released by the scaffold into media (similar to 0.4 mg/mL) induced bone cell migration, proliferation and aggregation. This study demonstrated that boron-containing three-dimensional PVA/starch-chitosan scaffolds can potentially be used within bone tissue engineering applications.Scientific and Technological Research Council of Turkey [TUBITAK/2219-1059B191900823]; EPSRC, UK of Centre for Doctoral Training in Regenerative Medicine [EP/F500491/1]This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK/2219-1059B191900823) for SC; and partially by EPSRC, UK of Centre for Doctoral Training in Regenerative Medicine (EP/F500491/1) for RD
A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds
No full textHigh precision demands in a large number of emerging robotic applications strengthened the role of the modern control laws in the position control of the Permanent Magnet Synchronous Motor (PMSM) servo system. This paper proposes a learning-based adaptive control approach to improve the PMSM position tracking in the presence of the friction uncertainty. In contrast to most of the reported works considering the servos operating at high speeds, this paper focuses on low speeds in which the friction stemmed deteriorations become more obvious. In this paper firstly, a servo model involving the Stribeck friction dynamics is formulated, and the unknown friction parameters are identified by a genetic algorithm from the offline data. Then, a feedforward controller is designed to inject the friction information into the loop and eliminate it before causing performance degradations. Since the friction is a kind of disturbance and leads to uncertainties having time-varying characters, an Adaptive Proportional Derivative (APD) type Iterative Learning Controller (ILC) named as the APD-ILC is designed to mitigate the friction effects. Finally, the proposed control approach is simulated in MATLAB/Simulink environment and it is compared with the conventional Proportional Integral Derivative (PID) controller, Proportional ILC (P-ILC), and Proportional Derivative ILC (PD-ILC) algorithms. The results confirm that the proposed APD-ILC significantly lessens the effects of the friction and thus noticeably improves the control performance in the low speeds of the PMSM
Microwave drying of quince coated with seed gum and pectin: A Taguchi optimization, techno-functional properties, and aromatic compounds
No full textIn this study, the effects of coating quince slices with CaCl2 and pectin (C + P) followed by drying with microwave (MWD-C + P) or with hot air (HAD-C + P) were investigated to determine the physicochemical, techno-functional, textural, and volatile components of dried quince slices. A Taguchi orthogonal experimental design was set up with 18 points (L-18), and the best conditions for drying were obtained using signal/noise ratio method. Coating quince slices with C + P and then drying with microwave at 450 W displayed the higher results compared to other points in terms of color, total phenolic, antioxidant activity, antimicrobial activity, and water holding capacity. MWD-C + P application dramatically changed the textural properties of dried quince slices in terms of hardness, gumminess, and chewiness. Moreover, MWD, lasted 12-15 min, was superior to HAD in the context of drying time. Ultrasonication as a pretreatment had no positive impact on dried products. GC-MS analyses revealed that MWD-C + P had positive effects on dried quince slices in terms of ethyl hexanoate and octanoic acid. However, MWD-C + P application triggered the formation of furfural in dried products.Erciyes University Scientific Research Projects Unit [FDK-2021-10938]ACKNOWLEDGMENTS This work was supported by the Erciyes University Scientific Research Projects Unit (Project Number: FDK-2021-10938)
Fatty acids, triglycerides, tocol, and sterol contents of oils of some Moringa seed varieties
No full textThree moringa oliefera varieties (MOMAX 3, ODC and PKM-1) seeds were used in this study. The oil was extracted from the seeds of ODC, PKM1 and MOMAX 3 moringa varieties by cold press (CP) and the solvent extraction (SE) method. Fatty acids, triglycerides, tocols (tocopherols and tocotrienols) and sterol contents of moringa seed oils obtained by two different methods were determined and compared with one another. The crude oil yield was between 26.46 - 28.19% in solvent extraction and 24.20 - 26.30% in the cold press method. It was determined that the main fatty acid in moringa seed oils (ODC, PKM1 and MOMAX 3) was Oleic acid (63.31 - 70.04%). Other dominant fatty acids were determined to be palmitic acid (16:0) (5.59-7.26%), stearic acid (18:0) (5.37-5.89%), oleic acid (18:1 n9) (%63.31-70.04), arachidic acid (20:0) (2.67 - 3.71 %) and behenic acid (22:0) (3.82 5.73%). It was determined that the main triglyceride in moringa seed oils was triolein (000; 35.63 - 36.50%), the main sterol was [3-Sitosterol (39.04 - 42.11 %) and the main tocopherol was a-tocopherol (15.88 -18.91 pg/g).Adana Al- parslan T0rke Science and Technology University Scientific Research Projects Unit [20332002]Acknowledgment This study was financially supported by Adana Al- parslan T0rke Science and Technology University Scientific Research Projects Unit (Project number: 20332002)
Harmonizing Heritage and Artificial Neural Networks: The Role of Sustainable Tourism in UNESCO World Heritage Sites
No full textThe classification of the United Nations Educational, Scientific, and Cultural Organization (UNESCO) World Heritage Sites (WHS) is essential for promoting sustainable tourism and ensuring the long-term conservation of cultural and natural heritage sites. Therefore, two commonly used techniques for classification problems, multilayer perceptron (MLP) and radial basis function (RBF) neural networks, were utilized to define the pros and cons of their applications. Then, according to the findings, both correlation attribute evaluator (CAE) and relief attribute evaluator (RAE) identified the region and date of inscription as the most prominent features in the classification of UNESCO WHS. As a result, a trade-off condition arises when classifying a large dataset for sustainable tourism between MLP and RBF regarding evaluation time and accuracy. MLP achieves a slightly higher accuracy rate with higher processing time, while RBF achieves a slightly lower accuracy rate but with much faster evaluation time
Mapping The Nexus of Corruption and Business Ethics: A Bibliometric Study
No full textBusiness ethics and corruption are closely related aspects of the social and corporate environment that are regularly monitored by the international community. Corruption has several harmful repercussions for individuals, organizations, and societies. Even while organizations are fighting corruption with increasing intensity, it cannot be eliminated. This scenario has drawn scholars from numerous disciplines to this subject. In accordance with the significance of the field, there are numerous established research projects and reviews in the field, but no bibliometric study has yet been conducted at the intersection of corruption and business ethics. Our study fills this gap and makes a direct contribution to the field by examining 990 articles from the Web of Science core collection published between 1980 and 2022. Using citation, co-words, and co-citation analyses, we aim to illustrate the conceptual, intellectual, and social structure of the field. The findings of the study may be helpful to scholars since this show both the current performance of authors, documents, and journals, as well as the progression of themes
A study on the effects of web design projects on the basic coding education of children
No full textLisansüstü Eğitim Enstitüsü, Ekonomik ve Sosyal Etki Değerlendirme Çalışmaları Ana Bilim Dalı, Proje Yönetimi Bilim DalıAraştırmada web tasarım projelerinin çocukların temel kodlama eğitimine etkileri üzerine bir çalışma incelenmiştir. 2021 – 2022 eğitim öğretim yılında Adana ili Çukurova ilçesinde bir devlet okulunda ilkokul 5.sınıfta öğrenim görmekte olan 30 öğrenciye rastgele seçilen 15'i deney gurubu diğer 15'i ise kontrol gurubu olarak 3 hafta süren bir eğitim uygulanmıştır. Eğitim sürecinde kontrol gurubuna temel kodlama eğitimi ders içeriği anlatılırken deney gurubuna temel kodlama eğitimi ders içeriğinin yanında örnek web sitesi uygulanmıştır. Çalışmada 3 haftalık eğitim öncesinde her iki guruba beceri testi ön test uygulanmış olup, eğitim sonunda ise her iki guruba beceri testi son test uygulanmıştır. Ayrıca eğitim sonunda öğrencilere Kodlama Eğitimine Yönelik Tutum Ölçeği uygulanmıştır. Ön test sonuçları analiz edildiğinde deney grubu öğrencilerinin ortalaması ?X = 4,33 kontrol grubu öğrencilerinin ortalaması ise ?X = 4,47 olarak bulunmuştur. Bağımsız örneklem t – Testinde p=0,723 olup, bulunan bu p değeri 0,05 değerinden büyük olduğundan her iki gurup arasında anlamlı bir farklılığın olmadığı görülmüştür. Son test sonuçları analiz edildiğinde ise deney grubu öğrencilerinin ortalaması ?X = 4,13 kontrol grubu öğrencilerinin ortalaması ise ?X = 0,13 olarak bulunmuştur. Bağımsız örneklem t-Testi sonucunda p=0,000 olup, bulunan bu p değeri 0,05 değerinden küçük olduğundan iki grup arasında istatiksel olarak anlamlı bir farklılık olduğu ve bu farkın deney gurubu öğrencileri lehine olduğu gözlemlenmiştir.In the research, a study on the effects of web design projects on children's basic coding education was examined. In the 2021-2022 academic year, a 3-week education was applied to 30 students who were studying in the 5th grade of primary school in a public school in Çukurova district of Adana province, 15 of which were randomly selected as the experimental group and the other 15 as the control group. While the basic coding training course content was explained to the control group during the training process, a sample website was applied to the experimental group besides the basic coding training course content. In the study, a pre-test was applied to both groups before the 3-week training, and a post-test was applied to both groups at the end of the training. In addition, the Attitude Scale towards Coding Education was applied to the students at the end of the training. When the pre-test results were analyzed, the mean of the experimental group students was ?X = 4.33, and the mean of the control group students was ?X = 4.47. In the independent sample t-Test, p=0.723, and since this p value was greater than 0.05, it was seen that there was no significant difference between the two groups. When the post-test results were analyzed, it was found that the average of the experimental group students was ?X = 4.13, and the average of the control group students was ?X = 0.13. As a result of the independent sample t-Test, p=0.000 and since this p value is less than 0.05, it was observed that there was a statistically significant difference between the two groups and this difference was in favor of the experimental group students
Dijital ikiz ile güneş paneli çiftliklerinde elektrik üretiminin dijitalleştirilmesi ve yüksek verimlilikle çalıştırılması
No full textLisansüstü Eğitim Enstitüsü, Elektrik ve Elektronik Mühendisliği Ana Bilim DalıYenilenebilir enerji kaynakları, özellikle güneş enerjisi, popülaritesinde ve üretim kapasitesinde önemli bir artışa tanık oldu. 2022'nin sonuna kadar dünya çapında 1000 GW'ın üzerinde fotovoltaik panel kuruldu ve faaliyete geçti. Ancak, yüksek enerji üretim verimliliği sağlamak, sistemdeki hataları önlemek ve tespit etmek giderek daha acil hale geldi. Güneş enerjisi üretiminin doğrusal olmayan doğası ve öngörülemezliği, üretimde öngörülebilirliği ve anlık değişimi zorlaştırır. Bu nedenle, bu tez, dijital bir ikiz geliştirerek ve sistemin performansını optimize etmek için gerekli araçları kullanan bir platform oluşturarak güneş enerjisi santrallerinin izlenebilirliğini artırmayı amaçlamaktadır. Başlangıçta Matlab'da tasarlanan güneş enerjisi santrali, çalışma karakteristiklerini değerlendirmek ve tasarımını iyileştirmek için bir simülasyon ortamına taşınmıştır. Toplanan veriler, sistemi izlemek, gelecekteki senaryoları tahmin etmek ve olağandışı bir olay veya güç kaybı meydana geldiğinde kullanıcıları bilgilendirmek için kullanılan makine öğrenimi algoritmalarını eğitmek için kullanıldı. Ek olarak, kirlenme sorunlarını gidermek ve panel temizliğini optimize etmek için bir algoritma oluşturuldu. Esnek ara bağlantı ile birlikte bu yöntemlerin ve programların entegrasyonu, izlenebilirliği iyileştirerek gelişmiş veri görselleştirme sağlar. Bu tezin, güneş enerjisi santrali davranışını incelemek ve güneş enerjisi santrallerinin etkinliğini ve izlenebilirliğini artırmak isteyen araştırmacılara ve tesis sahiplerine katkı sağlayacağı umulmaktadır.Renewable energy sources, particularly solar energy, have witnessed significant growth in popularity and production capacity. Over 1000 GW of photovoltaic panels have been installed and operational worldwide by the end of 2022. However, ensuring high-energy production efficiency, preventing, and detecting errors in the system have become increasingly urgent. The non-linear nature and unpredictability of solar power production make predictability and instantaneous change in production challenging. Therefore, this thesis aims to enhance the traceability of solar power plants by developing a digital twin and creating a platform utilizing the necessary tools to optimize the system's performance. Initially designed in Matlab, the solar power plant was moved to a simulation environment to evaluate its operating characteristics and refine its design. The data collected were used to train machine learning algorithms, which are employed to monitor the system, predict future scenarios, and notify users when an unusual event or power loss occurs. Additionally, an algorithm was created to address contamination issues and optimize panel cleaning. The integration of these methods and programs, along with flexible interconnection, provides enhanced data visualization, improving traceability. It is hoped that this thesis will contribute to researchers and plant owners who want to examine solar power plant behavior and increase the efficiency and traceability of solar power plants