Zonguldak Bülent Ecevit University Institutional Repository
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Doğal Gaz Fiyatının Elman Sinir Ağları ve Yusufçuk Optimizasyon Algoritmasına Dayalı Hibrit Model ile Tahmini
No full textDünya nüfusunun artışı ile çeşitli fosil ve yenilenebilir enerji kaynaklarının kullanımı giderek artmaktadır. Doğal gaz, fosil enerji kaynakları arasında yer alan kömür ve petrolle karşılaştırıldığında, daha düşük karbondioksit emisyonu, yüksek verimlilik, kolay erişim ve düşük depolama maliyeti gibi özellikleri nedeniyle bireysel ve kurumsal düzeyde kullanım alanı bulmuştur. Doğal gaz fiyatı ekonomik açıdan önemli olduğu kadar stratejik öneme de sahiptir. Özellikle doğal gaz fiyatının gelecekte alacağı değerin tahmini, enerji üreticilerine ve tüketicilerine, yatırımcılara ve hükümetlere stratejik kararlar alırken yol gösterici olmaktadır. Bu çalışmada, Elman Sinir Ağları (ENN) ve Yusufçuk Optimizasyon Algoritması (DOA) yaklaşımları kullanılarak bir adım sonraki doğal gaz kapanış fiyatının tahmini yapılmıştır. Çalışma 01,06,2009-31,05,2024 tarihleri arasında 3986 adet kapanış fiyatı içeren veri seti kullanılarak yapılmıştır. Bir adım sonraki kapanış fiyatının tahmini için yapay zekâ yaklaşımlarından ENN yöntemi kullanılmıştır. Geri beslemeli sinir ağları arasında yer alan ENN, geçmiş verileri dikkate alarak gelecekteki değerleri tahmin etme yeteneğine sahiptir ve özellikle zaman serisi tahmininde kullanılmaktadır. Model eğitim aşamasında yusufçukların avlanma ve göç etme davranışlarından ilham alınarak geliştirilmiş bir sezgisel optimizasyon algoritması olan DOA yöntemiyle ENN’nin ağırlık ve bias değerleri bulunmuştur. Modelin değerlendirilme aşamasında veri setinin eğitim, doğrulama ve test setlerine bölünmesiyle modelin genelleme kapasitesi daha güvenilir bir şekilde ölçülmektedir. Model başarımı, çeşitli istatistiksel hata kriterleri kullanılarak değerlendirilmiş ve elde edilen sonuçlar tatminkâr bulunmuştur. Yapay zekâ yaklaşımlarının kullanımı, enerji piyasaları gibi dinamik ve karmaşık sistemlerde tahmin doğruluğunu artırmak için kritik önem taşımaktadır. ENN ve DOA’nın birleşimi, bu tür problemler için güçlü ve esnek bir çözüm sunmaktadır. Bu çalışma, doğal gaz fiyatlarının tahmininde yapay zekâ yöntemlerinin etkinliğini göstermekte ve bu yaklaşımların pratik uygulamalarda kullanılabilirliğini ortaya koymaktadır.</jats:p
Global analysis of a monkeypox virus model considering government interventions
No full textAbstract Monkeypox is an infectious disease that threatens human life. The recent spread of the virus has increased global health concerns and risks. In this paper, an innovative mathematical modeling approach is presented to investigate the transmission dynamics of the monkeypox virus. The mathematical model is constructed considering the spread of the virus in both human and rodent populations. It also provides a more realistic approach by including a saturated incidence rate. The model is usable by including potential interventions that governments can adopt. The local and global asymptotic stability of the equilibrium points with the basic reproduction number R 0 is examined. In addition, a bifurcation analysis is conducted to reveal significant changes in the dynamics of the model. Sensitivity analysis is given to evaluate the effects of potential measures that can be taken to eliminate the disease. Finally, the obtained theoretical results are supported by numerical simulations.</jats:p
Numerical investigation of the flow induced by a transcatheter intra-aortic entrainment pump
No full textThis study evaluates the fluid dynamics inside and outside transcatheter blood pump positioned in the aorta. We focus on the pump's impact on blood component damage and arterial wall stress. CFD simulations were performed for rotational speeds ranging from 6000 to 15000 rpm, with a blood flow rate of 1.6 L/min. Results show that significant blood damage may occur at speeds as low as 12000 rpm, and the pump's outflow jet induces elevated wall shear stress, potentially leading to arterial aneurysms. These findings suggest the need for further design improvements to reduce risks when used in prolonged or transplant-related applications.Research Pape
Leveraging Artificial Intelligence and Machine Learning for Characterizing Protein Corona, Nanobiological Interactions, and Advancing Drug Discovery
No full textProteins are essential for all living organisms, playing key roles in biochemical reactions, structural support, signal transduction, and gene regulation. Their importance in biomedical research is highlighted by their role as drug targets in various diseases. The interactions between proteins and nanoparticles (NPs), including the protein corona’s formation, significantly affect NP behavior, biodistribution, cellular uptake, and toxicity. Comprehending these interactions is pivotal for advancing the design of NPs to augment their efficacy and safety in biomedical applications. While traditional nanomedicine design relies heavily on experimental work, the use of data science and machine learning (ML) is on the rise to predict the synthesis and behavior of nanomaterials (NMs). Nanoinformatics combines computational simulations with laboratory studies, assessing risks and revealing complex nanobio interactions. Recent advancements in artificial intelligence (AI) and ML are enhancing the characterization of the protein corona and improving drug discovery. This review discusses the advantages and limitations of these approaches and stresses the importance of comprehensive datasets for better model accuracy. Future developments may include advanced deep-learning models and multimodal data integration to enhance protein function prediction. Overall, systematic research and advanced computational tools are vital for improving therapeutic outcomes and ensuring the safe use of NMs in medicine.</jats:p
On Higher-Order Generalized Fibonacci Hybrid Numbers with q-Integer Components: New Properties, Recurrence Relations, and Matrix Representations
No full textMany properties of special numbers, such as sum formulas, symmetric properties, and their relationships with each other, have been studied in the literature with the help of the Binet formula and generating function. In this paper, higher-order generalized Fibonacci hybrid numbers with q-integer components are defined through the utilization of q-integers and higher-order generalized Fibonacci numbers. Several special cases of these newly established hybrid numbers are presented. The article explores the integration of q-calculus and hybrid numbers, resulting in the derivation of a Binet-like formula, novel identities, a generating function, a recurrence relation, an exponential generating function, and sum properties of hybrid numbers with quantum integer coefficients. Furthermore, new identities for these types of hybrids are obtained using two novel special matrices. To substantiate the findings, numerical examples are provided, generated with the assistance of Maple.</jats:p
Could serum Raftlin and GPER-1levels be new biomarkers for early detection of non-small cell lung cancer?
No full textLung cancer is the leading cause of cancer-related deaths worldwide. Therefore, the search for new biomarkers continues in order to diagnose lung cancer at an early stage. In this study, we investigated blood levels of G-protein associated membrane estrogen receptor (GPER)-1 and Raftlin as markers of early-stage in lung cancer.Lung cancer cases admitted to our hospital between 2016 and 2018 were included in our study. GPER-1 and Raftlin levels were measured by Enzyme-Linked Immunosorbent Assay (ELISA) in blood samples taken from patients diagnosed with lung cancer and healthy volunteers.There were 64 cases in total, 32 cases in lung cancer group and 32 cases in control group. We evluated GPER-1 levels for each group. GPER-1 level was 2.54 (IQR: 1.08-5.78) ng/mL in the lung cancer group and 5 (IQR: 2.69-7.99) ng/mL in the control group. ROC analysis value for GPER-1, (AUC) was 0.66 (p < 0.01). Raftlin levels were 4.5 (IQR: 3.3-11.52) ng/mL in control group and 7.77 (IQR: 6.24-9.85) ng/mL in lung cancer group. ROC analysis value for Raftlin, (AUC) was 0.629(P = 0.09).In our study, there was no statistically significant difference between our groups in terms of Raftlin values. Therefore, it was thought that Raftlin could not be a specific marker in the diagnosis of lung cancer. GPER-1 was found to be lower in the lung cancer group than in healthy individuals. Therefore, it was thought that GPER-1 could be evaluated as a diagnostic marker in lung cancer. However, we think that more definitive results can be obtained by determining the tissue and expression level of GPER in lung cancer with further studies
Prussian‐Blue Catalysis and NFC Synergy: a Battery‐Free Laser‐Induced Graphene‐Based Platform for Urine Glucose Monitoring at Point‐of‐Care
No full textAbstractPrussian‐blue nanoparticles (PBNPs) show promise in electrochemical hydrogen peroxide (H2O2) sensing but face operational stability challenges without complex strategies. This study introduces a simplified, polymer‐based synthesis method, enhancing their stability in a single step. Chemical polymerization of Prussian‐blue (PB) and poly(3,4‐ethylenedioxythiophene) (PEDOT) with gelatin as a polycationic soft template yields a self‐assembled PB‐infused Catalytic Hetero‐interface Architecture (PB‐CHIA) that remarkably improves the stability of PBNPs and offers functional groups for enzyme immobilization, supporting robust biosensing applications. The softened PEDOT rigidity extends PB‐CHIA's applicability to various carbonaceous electrode substrates, including glassy carbon and laser‐induced graphene (LIG) via simple drop‐casting. A fluidic cell module designed with the optimized LIG morphology (nano‐fibrous fringes, LIG‐F, diameter: 72.87 ± 12.24 nm) modified with PB‐CHIA and glucose oxidase enables non‐invasive urine glucose monitoring. The configuration accurately quantifies glucose within a linear range of 10–400 µM [R2: 0.991, Sensitivity: 29.88 ± 4.98 µA mM⁻¹ cm⁻2, Detection Limit: 4.52 ± 2.24 µM], covering medical needs. A near‐field communication potentiostat is devised for a fully integrated, batteryless, wireless point‐of‐care (POC) prototype, enabling rapid smartphone readouts in 15 s for daily home‐based use. The stable operation of PB‐CHIA allows working electrodes’ scalable production, highlighting its potential for diverse POC devices in urinary analysis reliant on H2O2 assays.</jats:p
Adapting Responsibility to Protect (r2p) for a Multipolar World: Sovereignty, Intervention, and Veto Power
No full textAbstract This article discusses how the Responsibility to Protect (r2p) doctrine can evolve within a shifting global order, marked by multipolarity and declining liberal norms. It identifies three main challenges: sovereignty, selective implementation, and the use of veto power. Although r2p frames sovereignty as a responsibility, resistance from non-Western powers like China and Russia underscores the need to integrate diverse perspectives on state sovereignty, reflecting these countries’ growing influence in international norms. This resistance has exposed the fragile consensus around r2p within the United Nations, as inconsistent application has led to scepticism and diminished credibility. To sustain r2p’s relevance, the article proposes adapting the doctrine to align with geopolitical realities, advocating a nuanced approach that respects varied views on intervention while encouraging accountability in veto use for atrocity prevention. In doing so, it offers pathways for r2p to retain its humanitarian goals amid the complexities of a multipolar world.</jats:p
Türk Vergi Sistemi Neden ve Ne Kadar Karmaşık Algılanıyor?: Bir Karma Yöntem Araştırması
No full textVergi karmaşıklığı, mükelleflerin vergiye uyum davranışlarını olumsuz etkilemekte ve gerek mükellefler için uyum maliyetlerini gerekse vergi idareleri için operasyonel maliyetleri artırarak devleti vergi geliri kaybına uğratabilmektedir. Bu nedenle, vergi sisteminin basitleştirilmesi yönündeki çabalar önem kazanmaktadır. Ancak, vergi karmaşıklığının azaltılması veya ortadan kaldırılması için öncelikle mevcut vergi karmaşıklığı düzeyinin belirlenmesi gerekmektedir. Bu araştırma; vergi karmaşıklığı algısını belirleyen faktörlerin saptanmasını, vergi karmaşıklığı algısını ölçmek üzere endeks geliştirilmesini ve bu endeks aracılığıyla Türk Vergi Sistemi’nin algılanan karmaşıklık düzeyinin ölçülmesini amaçlamaktadır. Araştırmada muhasebe meslek mensupları, vergi dairesi personeli, maliye alanında araştırma yapan akademisyenler ve vergi hukukunu ilgilendiren konularda hizmet veren avukatlardan oluşan 26 katılımcıyla yarı-yapılandırılmış görüşmeler gerçekleştirilmiş ve ulaşılan bulgulara dayalı olarak bir endeks geliştirilmiştir. Aynı meslek gruplarından belirlenen 507 katılımcıya ait anket verisiyle bu endeks kullanarak yapılan hesaplama sonucunda tüm katılımcıların “genel vergi karmaşıklığı algısı” skorlarının ortalaması 1 üzerinden 0,69 olarak bulunmuş ve Türk Vergi Sistemi’nin yüksek düzeyde karmaşık olarak algılandığı tespit edilmiştir. Araştırma, vergi karmaşıklığı konusunda literatüre ve politika yapıcılara özgün ve önemli katkılar sağlamaktadır. Anahtar Kelimeler: Vergi Karmaşıklığı, Vergi Karmaşıklığı Algısı, Vergi Karmaşıklığı Endeksi, Vergi Sisteminin Basitleştirilmesi, Vergi Uyumu JEL Sınıflandırması: H2, K30</jats:p