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Determining the effect of tung biodiesel on thermodynamic, thermoeconomic, and exergoeconomic analyses at high engine speeds
No full textTung biodiesel is a promising alternative fuel type produced from the tung tree. In the current study, the effect of the addition of 20%, by volume, of tung biodiesel to diesel fuel was evaluated in terms of energetic-exergetic analyses based on the first and second laws of thermodynamic at various high engine speeds (2,400, 2,600, and 2,800 rpm). Additionally, this study aimed to assess the thermoeconomic and exergoeconomic aspects of a diesel engine. The findings revealed that the amount of energy converted to useful work for the diesel fuel was higher than that of the DTB20 fuel, even though the fuel energy obtained from DTB20 fuel was higher than that of diesel fuel at all engine speeds. The highest energy and exergy efficiencies for the engine fueled with diesel fuel were obtained as 31.07% and 29.15% respectively, while the corresponding values for the engine fueled with DTB20 fuel were determined as 27.15% and 25.19% at the engine speed of 2,400 rpm, respectively. However, at 2,800 rpm, a significant decrease in both the energy and exergy efficiencies was observed for both diesel and tung biodiesel blended fuels due to the increased mechanical friction of the engine components. Furthermore, at the highest engine speed, entropy generation increased, owing to a higher exergy destruction rate. The entropy generation rate increased to 0.38 kW/K for diesel fuel and 0.46 kW/K for DTB20 fuel since the enhancement of the engine speed caused the ascent of the fuel consumption rate. Regarding thermoeconomic-exergoeconomic analyses, for both diesel and tung biodiesel blended fuels, there is no distinct difference in the thermoeconomic-exergoeconomic parameters at 2,400 and 2,600 rpm as the values of these parameters at the engine speed of 2,800 rpm increased significantly. In light of all the findings, it can be concluded that the engine speed of 2,800 rpm is not applicable to run the engine due to higher friction and corresponding energy destruction in the engine system
Efficacy of Magnesium Sulfate and Labetalol in the Treatment of Pregnancy-Induced Hypertension and Its Effect on Anxiety and Depression: A Retrospective Cohort Study
No full textBackground: In this study, the effect of magnesium sulfate and labetalol in treating pregnancy- induced hypertension (PIH) and its influence on anxiety and depression in patients are observed, and new ideas for treating anxiety and depression in PIH are introduced. Methods: A retrospective cohort study was conducted to select patients with PlH diagnosed from July 2020 to July 2023 from Affiliated Hospital of Electronic Science and Technology University and Chengdu Women’ s and Children’s Central Hospital in Chengdu of Sichuan Province. The changes in blood pressure, Edinburgh Postnatal Depression Scale (EPDS), and generalized anxiety disorder 7 (GAD-7) in patients with hypertensive pregnancy were collected and analyzed. Results: In our investigation, 219 patients completed the study, and 36.1% (79/219) of them developed anxiety and depression. According to whether the patients were treated with magnesium sulfate and labetalol, 49 cases were assigned to the magnesium sulfate and labetalol treatment (MSLT) group, and 30 cases were assigned to the conventional treatment (CT) group. Edinburgh Postnatal Depression Scale scores and GAD-7 scores in the MSLT group were significantly lower than those in the CT group, indicating that magnesium sulfate and labetalol can improve anxiety and depression in hypertensive patients during pregnancy. The difference was statistically significant (P < .05). According to the changes in systolic blood pressure, the clinical efficacy of patients was evaluated, and no significant difference in efficacy existed between the MSLT and CT groups. Conclusion: Magnesium sulfate and labetalol can control the blood pressure of patients with PIH and indirectly improve anxiety and depression in patients with PIH, thereby introducing new ideas for the treatment of PIH accompanied by anxiety and depression
Multi-Classification of Depression Levels Based on Blood Biomarkers
No full text8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 -- 21 September 2024 through 22 September 2024 -- Malatya -- 203423Depression is a psychiatric condition characterized by a persistent feeling of sadness and diminished interest in significant activities. Diagnosing this health problem is challenging because it relies on several social and physiological factors. The timely identification of depression aids in the prevention of severe outcomes, such as suicide. Early detection of depression levels is crucial to prevent adverse effects and enhance the quality of everyday life. The purpose of this work is to use data preprocessing techniques to create a clean dataset from noisy and incomplete medical data that includes blood biomarker values of patients and then apply data mining techniques to this dataset to predict the degree of depression. Adana Dr. Ekrem Tok Mental Health Hospital supplied the raw data for the study, with consent from the ethics committee. Missing data are completed by filling with the constant value and the most frequent value methods (i.e., 0 and mode values) in the relevant column. The classification of the dataset is performed using AdaBoost, Decision Tree (DT), and Logistic Regression (LR) classifiers, which have been previously used in medical datasets and demonstrated to be effective. The Logistic Regression classifier achieved the highest success rate (Accuracy: 0.541 and weighted F-score: 0.481). © 2024 IEEE
Decision-making under stress: Executive functions, analytical intelligence, somatic markers, and personality traits in young adults
No full textThe main goal of the study was to scrutinize mediating and moderating mechanisms identified in line with the predictions of Somatic Marker Hypothesis (SMH) and Dual Process Theory of the effect of acute stress on decision making. The sample group of the research comprised of 61 (31 females, 30 males) healthy university students aged between 18 and 23 (x = 21, SD = 1.28). Data measurement tools were Skin Conductance Response Measurement, Iowa Gambling Test, Wisconsin Card Sorting Test, Wechsler Memory Scale-III Spatial Span Subtest, Stroop Test TBAG Form, Wechsler Adult Intelligence Matrix Reasoning Subtest, Stress Rating Scale, The State-Trait Anxiety Inventory, Big Five Personality Traits Scale, Ways of Coping Inventory, Beck Depression Inventory. The findings indicated that acute stress gives rise to decision-making failures by suppressing the SCR emphasized in SMH and mental processes defined in System 2. Furthermore, neuroticism had a moderating role in the relationship between stress and decision-making. Accordingly, the abovementioned theories cannot separately be sufficient to explain decision-making under stress; but, the predictions of these theories can complement each other to thoroughly make out the physiological and cognitive mechanisms of decision-making
A room temperature chemical process for homogeneous mixing of precursor phases for low temperature tetracalcium phoshate preparation
No full textThe aim of this study was to prepare phase pure tetracalcium phosphate (TTCP) from the precursor phase mixtures homogeneous at the nano/microscale level at lower heat treatment temperatures in much shorter dwell times. Two different precursor powder mixtures were prepared by reacting CaCO3 with H3PO4 in ethanol or water. The resultant precursor powder mixtures were heat treated at temperatures in the 1200–1350 °C range for 2 and 5 h. Phase structures of the powders were characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR) and Raman spectroscopy analysis. Scanning electron microscopy (SEM) was used for the investigation of powder particle sizes and morphology. Powders synthesized by the heat treatment of both of the starting powder mixtures prepared in ethanol or water with 2 and 5 h of dwell times at 1350 °C were determined to be phase pure TTCP. SEM analysis along with the phase identification showed that the precursor powder prepared in ethanol had micron sized plates formed by aggregation of sub-micron sized thin CaHPO4 plates covering CaCO3 particles. The precursor powder prepared in water contained large aggregates of sub-micron sized CaCO3 particles whose surface was covered by precipitated nano-sized hydroxyapatite. TTCP powders were composed of large irregularly shaped particles formed by sintering of smaller equiaxed grains. Average grain and particles sizes of the TTCP powders synthesized from the precursor powder prepared in ethanol were 3.2–3.9 and 8.1–8.4 ?m, respectively. Average grain and particle sizes of the TTCP powders synthesized from the precursor powder prepared in water however were measured to be 3.3–5.1 and 11.2–11.6 ?m, respectively. The TTCP preparation method presented in this study provides homogeneous and well-mixed precursor powders prepared from cheap and commonly available precursors without milling and decreases the heat treatment time to 2 h at 1350 °C. © 2024 Elsevier Ltd and Techna Group S.r.l.Department of Materials Science and Engineering; Department of Mining Engineering in Adana Alparslan Türkeş Science and Technology University; Çukurova Universit
Current Status of Occupational Health and Safety Education in Engineering Departments of Earth Sciences at Universities
No full textIn this study, Occupational Health and Safety (OHS) education in Geological Engineering, Geophysical Engineering, Mineral Processing Engineering and Mining Engineering departments, which are categorised as “earth sciences” departments, is examined. Earth sciences, which is one of the significant industries of our country, is one of the leading business lines that require expertise, experience, knowledge and constant surveillance due to the risks it contains by its nature. The reason why occupational diseases and work accidents are encountered more frequently than in other sectors is that it is a labour-intensive line of work. In adjunct to this, the truth that there is still not sufficient and necessary realisation on OHS and that the significance is not at the level it should be is is also of fundamental relevance in occurence of occupational diseases and accidents. OHS, which is a methodical and scientifically orientated set of studies carried out to protect workers and third parties from conditions that may be harmful to safety and health such as physical, chemical and psychosocial reasons during work in workplaces, has been improving since the beginning of the programme. Although OHS has increasingly become more important in our country in the last few years, there are still deficiencies in OHS education. The demand for qualified human resources in the field of OHS has a tendency to rise further with the entry into force of Law No. 6331. In Earth Sciences Engineering departments, which are in the category of high-risk occupations, a good education is required in order to shape OHS awareness in students in the right way. In this work, the present situation of OHS courses was investigated by analysing the curricula of Mining Engineering in 23 universities, Mineral Processing Engineering in 1 university, Geological Engineering in 33 universities and Geophysical Engineering in 12 universities in Turkey. On the basis of the data acquired, solution suggestions for the improvement of OHS education are presented
Changes in bioactive compounds and antioxidant activity of Gaziantep and Kastamonu garlic during black garlic production
No full textGarlic (Allium sativum L.), a member of the Alliaceae family, has been widely used in cuisine and traditional medicine since ancient times. Black garlic is produced by fermentation of fresh garlic under controlled conditions for a certain period at high temperature (60-90°C) and high humidity (70-90%). According to the Turkish Statistical Institute (TURKSTAT) data, Kastamonu and Gaziantep garlic varieties are the most cultivated garlic varieties in our country. Changes in protein, sugar content, antioxidant capacity (DPPH and ABTS methods), total phenolic content, 5-hydroxymethylfurfural (HMF) content, and organosulfur compound profiles were investigated in samples taken from Kastamonu and Gaziantep fresh garlic at 7, 14, 21, and 28 days of black garlic production under 65°C temperature and 70% humidity conditions. With these analyses, the differences between black garlic and fresh garlic and the changes in black garlic during the production process were revealed in detail. It was determined that the amount of total phenolic content and antioxidant capacities increased in the black garlic production processes of both regions compared to fresh garlic. While sucrose was fresh garlic’s dominant sugar, fructose was black garlic’s dominant sugar. Among the organosulfur compounds, allicin was dominant in fresh garlic and SAC in black garlic. It was determined that SAC was formed after the enzymatic conversion of ?-glutamyl-S-alk(en)yl-L-cysteine and ?-glutamyl and the temperature and fermentation time used in black garlic production increased the formation of SAC. The protein content ranging between 5.8%-7.3% in fresh garlic was 13.1-14.2% in black garlic. Fresh and black garlic from the Gaziantep region was determined to have higher total phenolic content, antioxidant capacity, and organosulfur compound contents
Biyoinformatik ve metin madenciliği analizine dayalı nörodejeneratif hastalıklar için ilaç yeniden konumlandırma
No full textLisansüstü Eğitim Enstitüsü, Biyomühendislik Ana Bilim Dalı, Biyomühendislik Bilim DalıNörodejeneratif hastalıklar (NDH), nörodejenerasyonun olduğu, ilerleyici ve tedavi seçeneği kısıtlı olan hastalıklardır. Bu tezde, makine öğrenmesi ile entegre kapsamlı bir biyoinformatik yaklaşımı kullanarak seçtiğimiz NDH olan Alzheimer Hastalığı (AD), Parkinson Hastalığı (PD), Huntington Hastalığı (HD) ve Amyotrofik Lateral Skleroz (ALS) için ilaç repozisyon çalışmalarına odaklandık. Hastalık ve sağlıklı örnekleri içeren transkriptomik veriler seçildi ve gruplandırıldı. Farklı şekilde ifade edilen genler (DEG'ler) belirlendi ve ortak DEG'lere yönelik ko-ekspresyon ağı analizi yapıldı. Önemli gen kümelerini belirlemek için Rastgele Orman, Destek Vektör Makinesi (SVM) ve K-En Yakın Komşu (KNN) algoritmaları kullanıldı. Bu gen kümeleri, ilaç yeniden konumlandırma analizi için kullanıldı. Potansiyel ilaç adaylarını belirlemek amacıyla beş makine öğrenimi algoritması (Doğrusal Regresyon, SVR, Rastgele Orman, Gradient Boosting ve Sinir Ağı) uygulandı ve en yüksek öngörülen kat değişimine sahip ilaçlar belirlendi. Bu ilaçların yeniliği, metin madenciliği ile doğrulandı. AD için 5 aday ilaç: Dmnq, İnterferon beta-1b, Siflutrin, Torcetrapib ve Vx. PD için 9 aday ilaç: İnterferon beta-1b, Aplidin, Androstanolon, Ribavirin, Dmnq, Doğal alfa interferon, İnterferon beta-1a, Klinafloksasin ve Bikalutamid. ALS için 5 aday ilaç: Nilotinib, Trovafloksasin, Apratoxin A, Karboplatin ve Klinafloksasin. Dmnq ve İnterferon beta-1b AD ve PD, Klinafloksasin ise ALS ve PD için ortak olarak belirlendi. Bulgularımızın wet lab çalışmalarıyla doğrulanması, NDH için yeni tedavi seçenekleri sunabilir. Anahtar Kelimeler: ilaç yeniden konumlandırma, makine öğrenmesi, nörodejeneratif hastalıklarNeurodegenerative diseases (NDDs) are a group of complex diseases with limited treatment options. This thesis presents a comprehensive bioinformatics approach to identify repurposed drug candidates for NDDs, focusing on Alzheimer's Disease (AD), Parkinson's Disease (PD), Huntington's Disease (HD), and Amyotrophic Lateral Sclerosis (ALS). Transcriptomic data including disease and healthy samples were selected and grouped. Differentially expressed genes were identified and co-expression network analysis was performed. Machine learning (ML) algorithms were applied to identify prominent gene clusters. These significant gene clusters were used for drug repositioning analysis. Five ML algorithms (Linear Regression, SVR, Random Forest, Gradient Boosting and Neural Network) were performed to predict the fold change of potential drug candidates. The novelty of these drugs was verified by text mining analysis. For AD, we identified 5 candidate drugs: Dmnq (2,3-dimethoxy-1,4-naphthoquinone), Interferon beta-1b, Cyfluthrin, Torcetrapib, and Vx. For PD, 9 candidate drugs: Interferon beta-1b, Aplidin, Androstanolone, Ribavirin, Dmnq, Natural alpha interferon, Interferon beta-1a, Clinafloxacin, and Bicalutamide. Lastly, for ALS, 5 candidate drugs: Nilotinib, Trovafloxacin, Apratoxin A, Carboplatin, and Clinafloxacin. Among these novel drugs, Dmnq and Interferon beta-1b drugs were common for AD and PD, while Clinafloxacin is common for ALS and PD. Validation of these findings with wet lab studies may provide new treatment options for NDDs. Keywords: drug repurposing, machine learning, neurodegenerative disease
Grafen doplu yakıt karışımlarının sera gazı emisyonları üzerindeki etkilerinin araştırılması
No full textLisansüstü Eğitim Enstitüsü, Makine Mühendisliği Ana Bilim Dalı, Matematik Mühendisliği Bilim DalıSürdürülebilir enerji kaynakları arayışı, iklim değişikliğini hafifletme ve çevresel bozulmayı azaltma ihtiyacı nedeniyle onlarca yıldır küresel bir endişe kaynağı olmuştur. Sanayi devriminden bu yana, kömür, petrol ve doğal gaz gibi fosil yakıtlara olan bağımlılık, modern medeniyetin enerji tüketiminin temel taşı olmuştur. Ancak, bu fosil yakıtların yanması, atmosfere önemli miktarda sera gazı (GHG), öncelikle karbondioksit (CO2), metan (CH4) ve azot oksit (N2O) salmaktadır ve bu da küresel ısınma ve iklim değişikliğine katkıda bulunmaktadır. Enerji, günümüzde insanlar için en önemli ihtiyaçlardan biridir. Günümüzde fosil yakıtların piyasaya girmesi ve zararlarının ortaya çıkması nedeniyle, inşaat yeni ve daha çevre dostu bir yakıt kaynağına yönlendirilmiştir. Bunlardan biri, nano partiküllerden oluşan grafen ve grafen oksittir. Bu ışıldayan grafen ve grafen oksit ilaveli yakıtlar üzerinde çalışmalar yapılmaktadır. Bu çalışmada, çeşitli grafen oranları ile karıştırılmış optimum yakıt karışımına karar vermek için yedi farklı MCDM yöntemi kullanılmıştır.The quest for sustainable energy sources has been a pressing global concern for decades, driven by the need to mitigate climate change and reduce environmental degradation. Since the industrial revolution, reliance on fossil fuels such as coal, oil, and natural gas has been the cornerstone of modern civilization's energy consumption. However, the combustion of these fossil fuels releases significant quantities of greenhouse gases (GHGs), primarily carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), into the atmosphere, contributing to global warming and climate change.Energy is one of the most important needs for people today. Nowadays, due to the introduction of fossil fuels into the market and their damages, construction has been directed to a new and more environmentally friendly fuel source. One of these is graphene and graphene oxide consisting of nano particles. Studies on these glowing graphene and graphene oxide added fuels are taken. In this study, seven different MCDM method was used in order to decide the optimum fuel blend mixed with various graphene ratios