WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Tuning Properties of Amorphous Boron Via Hydrogenation: An Ab Initio Study
(Elsevier, 2026) Durandurdu, Murat
Ab initio simulations are employed to investigate the structural, mechanical, and electronic properties of hydrogenated amorphous boron (a-B:H) across a range of hydrogen concentrations (approximate to 6-21 at.%). The results indicate that pentagonal-like boron clusters constitute the primary structural motifs. The bonding environment consists of both B-H terminal bonds and B-H-B bridging bonds, with the fraction of bridging bonds ranging from 10 % to 16 %. Increasing the hydrogen content leads to a reduction in density and bulk modulus, accompanied by a systematic widening of the electronic band gap. These results demonstrate that hydrogen incorporation profoundly modifies the atomic structure, softens the network, and enhances the semiconducting character of a-B:H, highlighting the tunability of properties in boron-based amorphous materials.
A Potential Hemostatic Chitosan/Gelatin Cryogel Impregnated with Verbascum Thapsus Leaf Extract for Noncompressible Hemorrhage Management
(IOP Publishing Ltd, 2025) Uzuner, Hacernur; Yuruk, Adile; Isoglu, Ismail Alper
In this study, we prepared a series of chitosan/gelatin (CS/GEL) cryogels containing Verbascum thapsus (V. thapsus) leaf extract and identified a lead formulation for noncompressible hemorrhage (NCH). Cryogels with average pore diameters ranging from 225 to 478 mu m were fabricated through cryogelation at various CS/GEL ratios. C15 was chosen as the base scaffold due to its homogeneous pore distribution, with a pore size coefficient of variation (CV) of approximately 0.22. Extract loading was 1%, 5%, 10%, and 20% w/v. Functional porosity was reported by the relative accessible void index (RAVI). In PBS, the values relative to neat C15 were 1.00, 0.27, 0.20, 0.13, and 0.09 for concentrations of 0%, 1%, 5%, 10%, and 20% w/v, respectively. In citrated blood, the series was 1.00, 0.29, 0.12, 0.14, and 0.09. After loading, equilibrium swelling decreased and the compressive modulus increased, consistent with partial pore filling in a fixed network. The cryogels maintained an interconnected macroporous network and showed swelling from 300% to 3600% in blood and PBS. Antibacterial activity reached 89% inhibition, and cell viability remained above 80%. Hemolysis was low and within acceptance limits. Clotting improved in whole blood as the blood clotting index decreased from 11.9 to 6.5, and the clotting time was approximately 6 min. The 5% w/v group provided the optimal balance of clotting, antibacterial effects, and biocompatibility. This study presents a novel hemostatic CS/GEL cryogel containing V. thapsus leaf extract that holds strong potential for future applications in NCH management.
Neuroinflammatory Human Brain Organoids Enable Comprehensive Drug Screening Studies: Fingolimod and Its Analogues in Focus
(Bentham Science Publishing Ltd, 2026) Acar, Busra; Pepe, Nihan Aktas; Zivkovic, Aleksandra; Stark, Holger; Sen, Alaattin
Introduction The absence of physiologically relevant models for neuroinflammatory brain disorders, such as multiple sclerosis (MS), highlights the need for improved drug screening platforms. To bridge this gap, this study aimed to develop a human brain organoid (hBO) model incorporating essential neural cell types, including astrocytes, microglia, and oligodendrocytes.Methods hBOs were generated from H9 stem cells, and neuroinflammatory characteristics were elicited by lipopolysaccharide (LPS). The expression of specific neuronal and inflammatory markers was assessed through qRT-PCR, immunofluorescence staining (IFS), and ELISA.Results IFS of mature hBOs with anti-SOX2, anti-SATB2, anti-MAPT, anti-GFAP, anti-MBP, and anti-IBA1 antibodies and images collected with the confocal microscope confirmed the differentiation of H9 cells into cortical neurons, astrocytes, microglia, and oligodendrocyte cell types. Elevated GFAP, IBA1, NF-kappa B, and IL-6 levels, along with reduced CNPase expression with LPS treatment, were considered reflective of MS-like pathology and were used to test fingolimod and its derivatives. Fingolimod and all its derivatives, specifically ST-1505, decreased MAPT (2.1-fold in ELISA, 1.7-fold in IFS), GFAP (1.8-fold in IFS), TNF alpha (5.4-fold in qRT-PCR), and FABP (1.5-fold in ELISA) levels, and increased IL-10 (11-fold in qRT-PCR) and MBP (2.9-fold in IFS) levels.Discussion The present data collectively showed LPS to evoke neuroinflammation in the hBO model, while fingolimod and its derivatives, particularly ST-1505, exhibited significant anti-inflammatory and neuroprotective properties by counteracting these evoked changes in the hBO model.Conclusion The findings supported the applicability of brain organoids as a model system for drug screening studies for neuroinflammatory brain diseases.
Security Through Digital Twin-Based Intrusion Detection: A Swat Dataset Analysis
(IEEE, 2023) Bozdal, Mehmet
Digital twin, as a virtual replica of physical entity, offer valuable insights into Industrial Control System (ICS) behavior and characteristics. Leveraging the convergence of digital twins and cybersecurity, this research explores its role in securing critical infrastructure, using the Secure Water Treatment (SWaT) system as a case study. Existing intrusion detection systems (IDS) for SWaT encounter challenges related to requiring huge amounts of a dataset for training, being unable to adopt high data dimensionality, and adaptability to emerging threats. To address these issues, a hybrid digital twin model is proposed, combining physics-based models and data-driven approaches. This model facilitates precise attack localization and explainable IDS outcomes. The method exhibits promising capabilities for enhancing critical infrastructure security and adapting to evolving cyber threats. Experimental results demonstrate the ability to detect eight out of nine attack types.
Fully Inorganic Colloidal CsPbBr3 Perovskite Nanocrystals with Zn-Doping and Metal Oxide Encapsulation for Luminescent Display Panels
(Amer Chemical Soc, 2025) Khorasani, Azam; Soheyli, Ehsan; Mutlugun, Evren
Perovskite nanocrystals (PeNCs) are emerging as exceptional materials due to their high photoluminescence quantum yield, tunable bandgap, and excellent charge carrier mobility, enabling a wide range of colors and promising applications in optoelectronics and photovoltaics. Despite their advantages, PeNCs face stability challenges caused by environmental factors. In the presented study, a facile and versatile colloidal hot-injection method was used to apply the beneficial aspects of Zn-doping in cesium lead bromide (CsPbBr3) PeNCs. The uniform platelet-shaped Zn-doped CsPbBr3 PeNCs were prepared by doping with a 0.1 molar ratio of zinc-oleate solution in the perovskite precursors during synthesis. Then, zinc-oxide (ZnO) and nickel-oxide (NiO) coating layers were utilized separately to effectively reduce surface defects, encapsulate PeNCs, and improve their stability issues. To fabricate the coated PeNCs with metal oxides, zinc acetate and nickel(II) acetate tetrahydrate solutions were prepared individually and added to the crude perovskite solutions. The quantum yield of Zn-doped CsPbBr3 (CsPb1-xZnxBr3) PeNCs coated with ZnO increased from 50% for bare CsPbBr3 to over 84%, while NiO-coated PeNCs exhibited a higher yield of 90% both of which remarkably enhanced the emission stability. Moreover, NiO coatings represented a proper protection against surface imperfections and improved resistance to external stimuli. The combination of facile/effective preparation method, excellent emission efficiency, and reliable emission stability nominates the prepared colloidal composite for display pixels, detectors, and lasers.
A Novel Signaling Pathway That Governs Tumor Metastasis: Ceramide Regulates Direct Crosstalk Between TGF-Β and Sonic Hedgehog Signaling
(Wiley-Blackwell, 2016) Gencer, S.; Ogretmen, B.
Toward the Design of New Α-Carboline Derivatives Against Anaplastic Lymphoma Kinase (Alk): A Comprehensive in Silico Approach
(Wiley-VCH Verlag GmbH, 2025) Sari, Ceyhun; Akcok, Ismail
After the first description of anaplastic lymphoma kinase (ALK) in an anaplastic large cell lymphoma cell line as a nucleophosmin (NPM) fusion partner, ALK and its various fusion partners have been implicated in numerous cancers such as non-small cell lung cancer (NSCLC), anaplastic large cell lymphoma (ALCL), neuroblastoma, and rhabdomyosarcoma. In the last decade, several compounds targeting ALK have been developed and approved by the Food and Drug Administration (FDA). Despite the advances of generations of ALK inhibitors, a recent study highlighted that around half of the ALK-positive NSCLC patients will go through disease progression in response to first-line alectinib, which is a second-generation ALK inhibitor. In this study, we aimed to propose a novel alpha-carboline compound targeting the ALK tyrosine kinase domain to be used against various types of cancer in which ALK fusion proteins may be involved. In this regard, we designed more than 200 alpha-carboline derivatives and investigated their binding properties against ALK tyrosine kinase by using in silico protocols consisting of molecular docking studies, molecular dynamics simulations, MM/PBSA binding free energy calculation, and essential dynamics analysis. Considering the obtained results, we developed two promising candidates, compounds 208 & 209 with -9.05 and -9.80 binding energies, respectively, which demonstrated improved binding profiles over the course of a 300 ns simulation.
Boundaries of Belonging: the Spatial and Social Logic of Being Yilli People in Kayseri
(Sage Publications Inc, 2025) Mus Ozmen, Nihan; Asiliskender, Burak; Ozmen, Zehni
This study explores the spatial, social, and cultural dynamics of being yilli, a deeply rooted local identity in Kayseri, Turkey. Drawing on ethnographic fieldwork, oral histories, and spatial analysis, it examines how the yilli people negotiate urban transformation through selective adaptations to modernization while maintaining traditional social boundaries. The research shows that the yilli do not passively resist change but actively reinterpret modernization to reinforce status, kinship, and symbolic belonging. Spatial relocation and investment patterns reflect economic strategies and efforts to preserve cultural distinction amid urban expansion. The findings demonstrate that urban transformation in Kayseri is both a material and cultural process, shaped by layered histories of memory, hierarchy, and social imagination. Through the case of the yilli, the study contributes to broader debates in urban sociology and cultural geography, offering insights into how culture-centered societies adapt to and reshape modernization processes.
Citation - WoS: 1
Citation - Scopus: 1
Measuring Eudaimonic and Hedonic Wellbeing: Development and Validation of the Holistic Wellbeing Measure
(Routledge, 2025) Arslan, G.; Coşkun, M.
The primary goal of this study was to develop a concise, theoretically grounded tool –the Holistic Wellbeing Measure (HWM)– that captures both hedonic and eudaimonic facets of wellbeing. Items for the HWM were generated through a careful review of existing wellbeing scales and literature, followed by expert consultation, pilot testing, and iterative refinement to ensure conceptual coverage, clarity, and face validity. Data were collected from three distinct samples: adolescents (n = 453), young adults (n = 361), and adults (n = 358). Exploratory and confirmatory factor analyses supported a two-factor structure, with 12 items reflecting independent but related hedonic and eudaimonic wellbeing dimensions. The measure demonstrated strong internal reliability and evidence of convergent, discriminant, and concurrent validity across all age groups. Regression analyses further indicated that the HWM contributed unique variance to the prediction of general health indicators (physical, social, and mental health) and psychological problems (depression, anxiety, and somatization), above the effects of gender, age, and psychological wellbeing. These results suggest that the HWM is a valid and reliable measure for assessing both aspects of wellbeing across age groups and can support strategies aimed at promoting overall mental health. © 2025 Taylor & Francis Group, LLC.
Development and Characterization of Starch-Fatty Acid Complexes Produced with Buckwheat Starch and Capric/Stearic Acid Using Different Reaction Conditions
(Elsevier, 2025) Oskaybas-Emlek, Betul; Ozbey, Ayse; Aydemir, Levent Yurdaer; Kahraman, Kevser
The aim of present study was to investigate the impact of reaction parameters on the complex formation between buckwheat starch and capric acid (B-Capric) or stearic acid (B-Stearic). The most effective parameters on complex formation indicator (Complex index (CI) value) were found as reaction temperature (60-90 degrees C) and pH (5-8). Additionally, the effect of these parameters on physicochemical, pasting, and in-vitro digestibility properties of complex samples were evaluated. XRD and FTIR was also used in characterize the complex samples. In general, increasing pH increased the CI values of B-Stearic samples while decreasing those of B-Capric samples. Syneresis of buckwheat starch increased after complexation while paste clarity and swelling power diminished. The pasting properties of native starch significantly changed after complex formation. The FTIR results showed that starch structure changed with complex formation. XRD revealed that buckwheat starch, having an A-type pattern, converted to V-type pattern after complexation. Complex formation of buckwheat starch with capric and stearic acid significantly increased the RS content of buckwheat starch (19.01 %) by up to 36.25 % and 30.60 %, respectively. These results highlight the possibility of using buckwheat starch-capric acid/stearic acid complexes in food formulation to enhance the RS content.
Stagnant Wages in the Ottoman State Textile Factories in the Nineteenth Century: Comparison With European Wages
(Oxford University Press, 2025) Güven, T.
This study presents a new wage series for the textile factories established by the Ottoman state between 1848 and 1900. The data reveal that the real wages of Ottoman textile workers remained stagnant over this period compared to workers in other sectors within the Empire and in textile factories in Belgium and England. As the Corden-Neary model predicts, after 1820, the increase in international trade led to deindustrialization, resulting in a negative divergence in textile wages. Additionally, the state's implementation of wage setting as a cost-reducing measure further contributed to the stagnation of wages in the state textile factories. © 2025 The Author(s). Published by Oxford University Press on behalf of the European Historical Economics Society. All rights reserved.
An Ultra-Low Fabric Capacitive Glove for Real-Time Motion Tracking and Human–computer Interaction
(Institute of Physics, 2025) Başıbüyük, Y.; Mutluç, M.N.; Şavur, Ö.; İçöz, K.
This study presents the development of a wearable glove system that integrates ultra-low-cost, fabric-based capacitive sensors for motion detection and human–computer interaction. The system combines touch and bend sensors fabricated from commercially available silver-coated fabric and silicone acrylic tape, enabling real-time tracking of finger movements via measurable capacitance changes. The glove translates physical gestures into digital commands, facilitating intuitive control in virtual environments. Experimental evaluation demonstrated stable operation across a wide pressure range (10–200 g, equivalent to 1.25–25 kPa), with an unnormalized sensitivity of ∼0.00504 pF g−1 (∼0.0040 pF kPa−1), corresponding to a normalized sensitivity of ∼0.0067 kPa−1 when referenced to the baseline capacitance (C0 ≈ 6 pF). The device exhibited high repeatability over 4000 loading cycles, and minimal signal variation (coefficient of variation, CV < 0.005). Integration with a Unity-based interface enabled low-latency gesture tracking in real time. Each sensor was fabricated for less than $0.05 using simple, scalable methods, without nanomaterials or cleanroom processing. Owing to its affordability, fabrication simplicity, and mechanical robustness, the proposed glove system provides a practical and scalable platform for wearable motion tracking, with strong potential in rehabilitation, assistive technologies, and interactive systems. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Citation - WoS: 6
Citation - Scopus: 3
Separation of Fe and Mn From Manganiferous Iron Ores via Reductive Acid Leaching Followed by Magnetic Separation
(Society for Mining, Metallurgy and Exploration theng@smenet.org 12999 E Adam Aircraft Circle Englewood,Colorado 80112 Colorado, 2019) Top, S.
In this study, a process to separate manganese and iron from manganiferous iron ores by reductive acid leaching followed by magnetic separation was conceived and experimentally tested. In the leaching process, sulfuric acid was used as lixiviant and oxalic acid was used as reductant. The experimental results showed that the manganese and iron separation was optimal when the concentrations of the sulfuric acid and oxalic acid were 0.75 M and 30 g/L, respectively, at a temperature of 80 °C, a solid/liquid ratio of 67 g/L, stirring speed of 400 rpm and leaching duration of 60 min. Under these conditions, 90.49 percent and 6.78 percent of Mn and Fe were dissolved, respectively, from the ore sample in a size fraction of smaller than 106 μm. It was determined that the leaching of manganese from the ores was a second-order reaction with activation energy, Ea, of 53.38 kJ/mol. The leaching residues obtained under the optimal conditions were subjected to wet high-intensity magnetic separation tests to recover the remaining iron content. This separation process produced a concentrate containing 56.20 percent Fe and 1.79 percent Mn with iron and manganese recoveries of 56.83 and 66.73 percent, respectively. To the best of our knowledge, this is the first time that a magnetic separation process was used on a residue obtained from the reductive acid leaching of manganiferous iron ores to recover iron. © 2019 Society for Mining, Metallurgy and Exploration. All rights reserved.
Leveraging MicroRNA-Gene Associations With Mirgedinet: An Intelligent Approach for Enhanced Classification of Breast Cancer Molecular Subtypes
(Springer International Publishing AG, 2025) Qumsiyeh, Emma; Bakir-Gungor, Burcu; Yousef, Malik
Understanding the molecular subtypes of breast cancer is crucial for advancing targeted therapies and precision medicine. For the BRCA molecular subtype prediction problem, this study employs miRGediNET, a machinelearning approach that integrates data from miRTarBase, DisGeNET, and HMDD databases to investigate shared gene associations between microRNA (miRNA) activity and disease mechanisms. Using the BRCA LumAB_Her2Basal dataset, we evaluate miRGediNET's performance against traditional feature selection methods, including CMIM, mRmR, Information Gain (IG), SelectKBest (SKB), Fast Correlation-Based Filter (FCBF), and XGBoost (XGB). These feature selection techniques were assessed using various classification algorithms including Random Forest (RF), Support Vector Machine (SVM), LogitBoost, Decision Tree, and AdaBoost, all executed with default parameters. The feature selection methods were tested using Monte Carlo Cross-Validation, where performance metrics obtained for each iteration were averaged to ensure robustness. Our findings reveal that miRGediNET outperforms traditional methods in accuracy and Area Under the Curve (AUC), emphasizing its superior capability to identify key genes that bridge miRNA interactions and breast cancer mechanisms. Notably, both miRGediNET and Information Gain (IG) feature selection consistently identified ESR1, a critical biomarker frequently reported in recent research associated with breast cancer prognosis and resistance to endocrine therapies. This integrative approach provides deeper biological insights into miRNA-disease interactions, paving the way for enhanced patient stratification, biomarker discovery, and personalized medicine strategies. The miRGediNET tool, developed on the KNIME platform, offers a practical resource for further exploration in the field of bioinformatics and oncology.
Forecasting the Consumer Price Index in Türkiye Using Machine Learning Models: A Comparative Analysis
(Gazi Univ, 2025) Söylemez, İsmet; Ünlü, Ramazan; Nalici, Mehmet Eren
This study utilizes machine learning models to forecast Türkiye's Consumer Price Index (CPI), thereby addressing a critical gap in inflation prediction methodologies. The central research problem involves the forecasting of CPI in a volatile economic environment, which is essential for informed policymaking. The primary objective of this study is to evaluate the performance of three machine learning models, such as Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM), in forecasting CPI over periods ranging from one to six months, utilizing data from 2012 to 2024. The study's unique contribution lies in the application of the \"SelectKBest\" method, which identifies the most relevant indices, thereby enhancing the efficiency of the models. An ensemble method, Averaging Voting, is also employed to combine the strengths of these models, producing more accurate and robust predictions. The findings indicate that while the RF model consistently generates the most accurate forecasts across all shifts, the SVM model demonstrates a particular strength in the domain of short-term predictions. The ensemble model demonstrates a substantial performance improvement, with a R2 value of 0.962 for one-month ahead of estimates and 0.956 for five-month forecasts. This combined approach has been shown to outperform individual models, offering a more reliable framework for CPI forecasting. The findings offer valuable insights for economic policymakers, enabling more precise and stable inflation predictions in Türkiye.
The Trajectory of ‘tanpınar Studies’ From Post-Kemalism To Global Tanpınar
(Routledge, 2025) Çelebi, M.C.
Tanpınar holds a pivotal place in Turkish literature, shaping debates on Turkey's history. This article traces his critical reception from post-Kemalist readings to global interpretations. In the 1980s, he was central to post-Kemalist critiques of modernization; later, his works were reinterpreted through global modernity. Global Tanpınar teaches us two lessons: intellectually, it calls for a post-post-Kemalist perspective that situates Turkey's historical experience within the context of global crises. Culturally, it advocates a policy that goes beyond the traditional East-West synthesis and ‘standard’ multiculturalism by transcending the essentialist dichotomies that underpin global inequalities. © 2025 Informa UK Limited, trading as Taylor & Francis Group.
Vim-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein Expression
(Nature Portfolio, 2025) Dogan, Refika Sultan; Akay, Ebru; Dogan, Serkan; Yilmaz, Bulent
The dataset in this study includes 202 videos with a total of 422 minutes, reaching Kayseri City Hospital's gastroenterology department as colonoscopy videos and 1903 microscopy images between 2019 and 2021. It includes 399 colonoscopy, microscopy images, and pathological diagnoses of polyps, as well as immunohistochemical staining results for proteins that play an important role in the assessment of cancerous cells, such as staining results for p53 (clone: bp53-11), Ki-67 (clone: 30-9), CD34 (clone: QBend/10), PD-L1 (clone: SP142), BRAF (clone: V600E) and VEGF (clone: SP125). By sharing the data openly, we aim to facilitate benchmarking, exploratory analysis and transfer-learning studies on colorectal polyps and cancer. In combination with external datasets or pretrained models, the resource can help advance data-driven detection and characterisation work. The diverse range of polyps assigned to cancer stages from 201 patients makes this tool valuable for researchers and clinicians in furthering diagnosis and treatment.
TextNetTopics+: Enhancing Text Classification Through Classifier Diversity and Model Ensembling
(Springer International Publishing AG, 2025) Voskergian, Daniel; Bakir-Gungor, Burcu; Yousef, Malik
TextNetTopics is an innovative text classification framework that integrates topic modeling with feature selection to improve model accuracy and interpretability. Unlike traditional methods that rely on individual words, TextNetTopics selects cohesive topics extracted via Latent Dirichlet Allocation as features for document representation, effectively reducing dimensionality while preserving the semantic structure of the text. This study evaluates the performance of TextNetTopics utilizing multiple machine learning algorithms in the M (Modeling) component, including Random Forest, Support Vector Machine, Gradient Boosting, eXtreme Gradient Boosting, and Logistic Regression. To further enhance classification performance, we introduce TextNetTopics+, an ensemblebased extension that leverages both hard voting and soft voting mechanisms to combine the strengths of multiple classifiers. Comprehensive experiments on the LitCovid and WOS datasets demonstrate that ensemble learning in TextNetTopics + significantly outperforms individual classifiers in TextNetTopics, confirming its effectiveness in improving model robustness and generalization.
Engineering a Bilayered Scaffold as a Potential Cardiac Patch: From Scaffold Design to in Vitro Assessment
(Springer Singapore Pte Ltd, 2025) Yuruk, Adile; Duzler, Ayhan; Isoglu, Sevil Dincer; Isoglu, Ismail Alper
In this study, we developed a novel bilayered scaffold consisting of a bottom layer composed of the Decellularized Bovine Pericardium (DP) coated with Polyaniline Nanoparticles (PANINPs) and a top layer made of an electrospun Poly(lactic-co-glycolic acid)/Gelatin (PLGA/Gel) membrane incorporated with Vascular Endothelial Growth Factor (VEGF) and hawthorn extract. Functionally, the DP supplies native Extracellular Matrix (ECM) components and mechanical support, while PANINPs provide conductivity. The electrospun PLGA/Gel layer mimics fibrous ECM. It incorporates bioactives, with VEGF promoting pro-angiogenic stimulation and hawthorn extract enhancing anticoagulant activity, as well as increasing surface hydrophilicity. The tissue adhesive ensures the interfacial integrity between the two layers. Decellularization efficiency was confirmed histologically using 4 ',6-diamidino-2-phenylindole (DAPI) and Hematoxylin-Eosin (H&E) staining. The DP exhibited a DNA content of 115.9 +/- 47.8 ng/mg DNA, compared to 982.88 +/- 395.42 ng/mg in Native Pericardium (NP). The PANINPs had an average particle size of 104.94 +/- 13.7 nm. The conductivity of PANINPs-coated decellularized pericardium was measured to be 9.093 +/- 8.6 x 10- 4 S/cm using the four-point probe method. PLGA/Gel membranes containing hawthorn extract (1%, 5%, 10%, and 15% w/v) and VEGF (0.1 mu g/mL, 0.5 mu g/mL, and 1 mu g/mL) were fabricated by electrospinning, resulting in fiber diameters between 850 and 1200 nm and pore sizes between 14 and 20 mu m. The anticoagulant efficiency of the membranes containing hawthorn extract reached 430 s in the Activated Partial Thromboplastin Time Assay (aPTT). Mechanical testing revealed a tensile strength of 22.70 +/- 6.33 MPa, an elongation of 53.58 +/- 10.63%, and Young's modulus of 0.67 +/- 0.10 MPa. The scaffold also exhibited over 91% cell viability and excellent cardiomyocyte adhesion. The hemolysis ratio was determined to be 0.421 +/- 0.191%, which confirms its blood compatibility. Our results indicate that the proposed bilayered scaffold can be a promising candidate for cardiac patch applications.
Cyber Threats to Green Hydrogen Production Within a Solar Microgrid
(Springer International Publishing AG, 2025) Bozdal, Mehmet; Pourmirza, Zoya
The transition towards sustainable energy systems depends heavily on the reliable operation of renewable energy infrastructure, which is increasingly interconnected and digitized. Therefore, ensuring cybersecurity resilience is essential for maintaining the reliability and safety of renewable energy systems in a rapidly evolving digital landscape. This paper investigates the economic implications of data integrity and system configuration attacks on a green hydrogen production system within a solar microgrid. Through a comprehensive analysis, the vulnerability of the system to cyber intrusions that manipulate relay settings, electricity prices, and hydrogen level, is examined. Drawing on a multidisciplinary framework encompassing energy economics, cybersecurity, and renewable energy technologies, a methodological approach is developed to quantify the direct economic impacts of attacks. Simulation results indicate that such attacks can decrease profits by up to 14%.

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