155199 research outputs found
Sort by
A data-driven approach to arsenic classification in groundwater in geothermal Systems: Meta-Analysis and machine learning applications in Western Anatolia, Turkiye
No full textWestern Anatolia, Türkiye, is renowned for its diverse geothermal resources, encompassing high, medium, and low enthalpy systems. While these systems are valuable for energy production and economic development, they are also associated with significant environmental challenges, particularly high concentration arsenic and boron contamination. This study highlights critical hotspots, including Sandıklı (27 mg/L) and Banaz-Hamamboğazı (95.64 mg/L), with arsenic levels far exceeding the World Health Organization's (WHO) maximum permissible limit of 10 ppb. Such contamination poses significant risks to water quality, agriculture, and public health, especially in major agricultural provinces like Aydın and Manisa. To address these challenges, machine learning models were applied to classify arsenic concentrations. Ensemble methods, including AdaBoost (ABC) and Extra Trees (ETC) classifiers, consistently outperformed others, showing high accuracy of about 97 % in distinguishing geochemical signatures and predicting arsenic levels. In contrast, the k-Nearest Neighbors Classifier (KNNC) proved less effective, with frequent misclassifications. The combination of machine learning and meta-analysis provided a robust framework for identifying spatial and temporal patterns of contamination, offering valuable insights for environmental monitoring. This approach not only enhanced the understanding of arsenic distribution in geothermal systems but also provided actionable insights for mitigating contamination risks. The findings underscore the importance of combining computational techniques with environmental geochemistry to improve the management of geothermal wastewater. Future research should expand these methodologies to other regions and contaminants, leveraging machine learning to develop more effective environmental protection strategies. This study demonstrates the potential of data-driven approaches to address critical environmental issues and supports sustainable development in geothermal-rich areas
ADÖLESAN İDİOPATİK SKOLYOZLU ÇOCUKLARDA BEDEN ALGISI İLE İLİŞKİLİ FAKTÖRLERİN BELİRLENMESİ – ÖN ÇALIŞMA
No full text
Techno-economic assessment of green hydrogen production in Izmir: Evaluating electrolyzer technologies, modularization strategies, and renewable energy integration
No full textThe transition to low-carbon energy has accelerated with the expansion of renewable power capacity and the adoption of hydrogen as a clean energy carrier. Green hydrogen production via renewable-powered electrolysis offers a sustainable alternative but faces cost challenges compared to fossil-based methods. This study conducts a techno-economic analysis of wind-powered green hydrogen production in Izmir, Türkiye. First, two power allocation strategies (Daisy Chain and Average Allocation) are evaluated in a 10 MW wind-integrated PEMWE system to determine the most effective approach. Then, using the selected strategy, three electrolyzer technologies (Alkaline, Proton Exchange Membrane, and Anion Exchange Membrane) are compared based on their impact on the LCOH. The key novelty of this study is the separate consideration of SEC values for the stack and BoP in a modular electrolyzer system operated with different power allocation strategies. A case study across four locations in Izmir identifies Çeşme as the most viable site, where a 10 MW wind farm with a 7.5 MW PEMWE system achieves a net profit of 133.4 million US. Reducing electrolyzer capacity from 10 MW to 7.5 MW also lowers LCOH from 7.52 US/kg. The study also highlights that direct investment in wind power is more cost-effective than a PPA scenario for a price of 54 US$/MWh. These findings provide key insights for designing modular electrolyzer systems and improving the economic feasibility of green hydrogen production
The G protein-coupled receptor GPR89A is a novel potential therapeutic target to overcome cisplatin resistance in NSCLC Calu1 cells
No full textLung cancer is the most frequently diagnosed cancer type worldwide and is characterised by its high metastatic potential. Standard therapy for nonsmall cell lung cancer (NSCLC) cases includes chemotherapy with the platinum-based chemotherapeutic agent cisplatin. Although lung cancer cases respond well to cisplatin at the beginning of treatment, similar to 60% develop chemotherapy resistance during this process. In this study, a genome-wide CRISPR-Cas9-based genetic screening approach was employed to identify genes that cisplatin-resistant NSCLC Calu1 cells are more addicted to than sensitive cells. Cisplatin-resistant Calu1 cells were generated by the dose escalation method, and genome-wide CRISPR-Cas9-based genetic screening was performed with the Brunello CRISPR knockout library. Bioinformatics analyses of the obtained next-generation sequencing data revealed 63 potential candidate genes responsible for cisplatin resistance, including G protein-coupled receptor 89A (GPR89A), Poly(U) binding splicing factor 60 (PUF60), NBAS subunit of NRZ tethering complex (NBAS) and GrpE like 1, mitochondrial (GRPEL1). The GPR89A protein is located in the Golgi cisterna and Golgi-associated vesicle membrane, enables voltage-gated anion channel activity, and is involved in intracellular pH reduction. Functional studies carried out with GPR89A-knockout cisplatin-resistant Calu1 cells resulted in cell cycle arrest in the G2/M phase and increased polyploidy, and also prevented colony formation and cell migration. Cisplatin treatment, on the other hand, resulted in increased cell death by apoptosis upon cell cycle arrest in the S phase. In conclusion, this is the first study that identified GPR89A as a potential therapeutic target to overcome cisplatin resistance in NSCLC Calu1 cells
Investigation of Diffusion Induced Fiber–Matrix Interface Damages in Adhesively Bonded Polymer Composites
No full textComposite materials have the advantages of high strength and low weight, andare therefore used in many areas. However, in humid and marine environments, mechanicalproperties may deteriorate due to moisture diffusion, especially in glass fiber reinforcedpolymers (GFRP) and carbon fiber reinforced polymers (CFRP). This study investigatedthe damage formation and changes in mechanical properties of single-layer adhesivebonded GFRP and CFRP connections under the effect of sea water. In the experiment,0/90 orientation, twill-woven GFRP (7 ply) and CFRP (8 ply) plates were produced asprepreg using the hand lay-up method in accordance with ASTM D5868-01 standard. CNCRouter was used to cut 36 samples were cut from the plates produced for the experiments.The samples were kept in sea water taken from the Aegean Sea, at 3.3–3.7% salinity and23.5 ◦C temperature, for 1, 2, 3, 6, and 15 months. Moisture absorption was monitoredby periodic weighings; then, the connections were subjected to three-point bending testsaccording to the ASTM D790 standard. The damages were analyzed microscopically withSEM (ZEISS GEMINI SEM 560). As a result of 15 months of seawater storage, moistureabsorption reached 4.83% in GFRP and 0.96% in CFRP. According to the three-point bendingtests, the Young modulus of GFRP connections decreased by 25.23% compared to drysamples; this decrease was 11.13% in CFRP. Moisture diffusion and retention behaviorwere analyzed according to Fick’s laws, and the moisture transfer mechanism of single-lapadhesively bonded composites under the effect of seawater was evaluated.</p
Emission based sensing of phosphate ions and ATP via a newly synthesized Cu(II) chelated tetra N-phenyl carbazole porphyrin derivative
No full textIn this work spectral properties and sensor characteristics of a newly synthesized porphyrin derivative were investigated by absorption, excitation and emission spectroscopy. We also treated this molecule as a metal-ion chelation based fluorescent probe and investigated its response for PO43- and hydrolyzed adenosine triphosphate. Tetra-N-phenyl-carbazole-porphyrin derivative (TN-PCP) equipped with four symmetrical carbazole units via phenyl linkages exhibited high quantum yield in DMSO (& Fcy;=0.55.1). We reported effect of the Cu (II) and Ag (I) ions on the fluorescence of the TN-PCP considering general sensor parameters including calibration studies, selectivity and LOD values. Metal chelation by Cu (II) and Ag (I) quenched the fluorescence of the probe with I-0/I-100 ratios of 20.1 and 2.5, respectively. Considering the higher magnitude and effectiveness of the Cu(II)-induced quenching, we tested some analytes that could restore the emission of Cu[TN-PCP], thereby signaling the analytes including chelating anions. Among them, phosphate ion exhibited an exceptional and selective response towards the Cu[ TN-PCP] complex at pH 12.0 in a buffered solution. We measured 14.0 and 2.0-fold increase in emission intensity of the dye at 360 and 687 nm, upon phosphate binding, respectively. Additionally, we reported a very promising and selective response for the ATP molecule (I-0/I-100 = 50.0) for a concentration range; 1.8*10(-4) M -1.7*10(-2) M, at 420 nm, which can easily determine the ATP levels in bacteria, yeast, mammalian cells, muscle cells and even in intercellular spaces. The LOD value of the probe was found to be 2.1*10(-5) M for the ATP molecule. We have also demonstrated that the proposed probe can be used as an emission-based sensor capable of exhibiting good detection limits for these two metal cations