PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collections

Permanent URI for this collectionhttps://hdl.handle.net/20.500.13091/5

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Now showing 1 - 20 of 125

Citation - WoS: 9
Citation - Scopus: 11
Adrenal Tumor Segmentation Method for Mr Images
(ELSEVIER IRELAND LTD, 2018) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Background and objective: Adrenal tumors, which occur on adrenal glands, are incidentally determined. The liver, spleen, spinal cord, and kidney surround the adrenal glands. Therefore, tumors on the adrenal glands can be adherent to other organs. This is a problem in adrenal tumor segmentation. In addition, low contrast, non-standardized shape and size, homogeneity, and heterogeneity of the tumors are considered as problems in segmentation. Methods: This study proposes a computer-aided diagnosis (CAD) system to segment adrenal tumors by eliminating the above problems. The proposed hybrid method incorporates many image processing methods, which include active contour, adaptive thresholding, contrast limited adaptive histogram equalization (CLAHE), image erosion, and region growing. Results: The performance of the proposed method was assessed on 113 Magnetic Resonance (MR) images using seven metrics: sensitivity, specificity, accuracy, precision, Dice Coefficient, Jaccard Rate, and structural similarity index (SSIM). The proposed method eliminates some of the discussed problems with success rates of 74.84%, 99.99%, 99.84%, 93.49%, 82.09%, 71.24%, 99.48% for the metrics, respectively. Conclusions: This study presents a new method for adrenal tumor segmentation, and avoids some of the problems preventing accurate segmentation, especially for cyst-based tumors. (C) 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 50
Citation - Scopus: 55
Advanced Oxidation of Landfill Leachate: Removal of Micropollutants and Identification of By-Products
(ELSEVIER, 2021) Ateş, Havva; Argun, Mehmet Emin
Landfill leachate contains several macropollutants and micropollutants that cannot be removed efficiently by conventional treatment processes. Therefore, an advanced oxidation process is a promising step in post or pre-treatment of leachate. In this study, the effects of Fenton and ozone oxidation on the removal of 16 emerging micropollutants including polycyclic aromatic hydrocarbons (PAHs), phthalates, alkylphenols and pesticides were investigated. The Fenton and ozone oxidation of the leachate were performed with four (reaction time: 20-90 min, Fe(II) dose: 0.51-2.55 g/L, H2O2 dose: 5.1-25.5 g/L and pH: 3-5) and two (ozonation time: 10-130 min and pH: 4-10) independent variables, respectively. Among these operating conditions, reaction time played more significant role (p-value < 0.05) in eliminating di-(2-Ethylhexyl) phthalate, 4-nonylphenol and 4-tert-octylphenol for both processes. The results showed that Fenton and ozone oxidation processes had a high degradation potential for micropollutants except for the PAHs including four and more rings. Removal efficiencies of micropollutants by ozone and Fenton oxidation were determined in the range of 5-100%. Although the removal efficiencies of chemical oxygen demand (COD) and some micropollutants such as phthalates were found much higher in the Fenton process than ozonation, the degradation products occurred during the Fenton oxidation were a higher molecular weight. Moreover, the oxidation intermediates for the both processes were found as mainly benzaldehyde, pentanoic acid and hydro cinnamic acid as well as derivatives of naphthalenone and naphthalenediol. Also, acid ester with higher molecular weight, naphthalene-based and phenolic compounds were detected in the Fenton oxidation.
Citation - WoS: 18
Citation - Scopus: 19
Antibacterial Activity of Linezolid Against Gram-Negative Bacteria: Utilization of Epsilon-Poly Capped Silica Xerogel as an Activating Carrier
(MDPI, 2020) Kaya Güzel, Gülcihan; Medaglia, Serena; Candela-Noguera, Vicente; Tormo-Mas, Maria Angeles; Marcos, Maria Dolores; Aznar, Elena; Martinez-Manez, Ramon
In recent times, many approaches have been developed against drug resistant Gram-negative bacteria. However, low-cost high effective materials which could broaden the spectrum of antibiotics are still needed. In this study, enhancement of linezolid spectrum, normally active against Gram-positive bacteria, was aimed for Gram-negative bacteria growth inhibition. For this purpose, a silica xerogel prepared from a low-cost precursor is used as a drug carrier owing to the advantages of its mesoporous structure, suitable pore and particle size and ultralow density. The silica xerogel is loaded with linezolid and capped with epsilon-poly-l-lysine. The developed nano-formulation shows a marked antibacterial activity against to Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. In comparison to free linezolid and epsilon-poly-l-lysine, the material demonstrates a synergistic effect on killing for the three tested bacteria. The results show that silica xerogels can be used as a potential drug carrier and activity enhancer. This strategy could provide the improvement of antibacterial activity spectrum of antibacterial agents like linezolid and could represent a powerful alternative to overcome antibiotic resistance in a near future.
Citation - WoS: 5
Citation - Scopus: 6
Appraisal of Inorganic and Lignocellulosic Organic Shell Wastes as a Green Filler in Epoxy-Based Hybrid Composites
(Elsevier, 2025) Ahmetli, Gulnare; Kocaman, Suheyla; Soydal, Ulku; Kocak, Beril; Ozmeral, Nimet; Musayev, Nijat
Hybrid composites are now becoming increasingly important regarding economic and ecological compatibility. This study presented the research results that evaluate the feasibility of using cherry pit shell (CPSh) and chicken eggshell (ChESh) natural wastes as a new hybrid filler mixture for the first time. CPSh and ChESh can reduce the composite material cost and increase the biobased content. CPSh was treated with a 5 % NaOH alkali solution to enhance the lignocellulosic filler-matrix interfacial interaction. Hybrid green organic and inorganic fillers were used in the epoxy matrix (ER). Morphological, water absorption, thermal, and mechanical performance of hybrid composites were investigated. The tensile strength of ER increased max. by 5.73, 7.3, 17.98, and 14.27 % in the case of raw CPSh, ChESh, and hybrid filler mixtures at 1:1 and 1:3 wt mixing ratios of alkali-treated CPSh (NaOHCPSh) and ChESh, respectively. The composites' thermal stability and dynamic-mechanical properties in different aging environments (seawater and hydrothermal) were examined by thermogravimetric analysis (TGA) and dynamic-mechanical analysis (DMA). Hydrothermal was the most affected aging condition on the composite properties. In addition, ANOVA is applied to find the significant effect of different weight percentages of hybrid fillers on the mechanical properties of composites.
Citation - WoS: 2
Citation - Scopus: 3
Assessment of University Students' Earthquake Coping Strategies Using Artificial Intelligence Methods
(Nature Portfolio, 2025) Sulak, Suleyman Alpaslan; Koklu, Nigmet
Earthquakes are one of the most destructive natural disasters that pose a serious threat to human life and infrastructure worldwide. The aim of this study is to evaluate the coping strategies of adult individuals in Turkey regarding earthquake stress using artificial intelligence-based methods. The data was collected from 858 university students living in Turkey during January, February, and March 2024. A dataset was created using the 'Coping Scale for Earthquake Stress.' Prediction models were established using artificial intelligence algorithms such as Logistic Regression (LR), Bagging, and Random Forest (RF) based on information from 24 variables. The cross-validation method was applied during model training. The Logistic Regression algorithm achieved the highest accuracy rate of 98.60%, while the Bagging algorithm demonstrated the lowest performance with an accuracy rate of 79.95%. The Random Forest algorithm showed moderate performance with an accuracy rate of 85.89%. The findings provide important insights into the coping strategies of the community regarding earthquake stress. This study is expected to contribute significantly to areas such as disaster management, psychology, public health, and community resilience.
Citation - WoS: 3
Citation - Scopus: 14
Author Correction: a Portrait of the Higgs Boson by the Cms Experiment Ten Years After the Discovery (nature, (2022), 607, 7917, (60-68), 10.1038/S41586-022-04892-x)
(Nature Research, 2023) Tumasyan A.; Adam W.; Andrejkovic J.W.; Bergauer T.; Chatterjee S.; Damanakis K.; Dragicevic M.; Gürpınar Güler, Emine; Güler, Yalçın
Correction to: Nature Published online 4 July 2022 In the version of this article initially published, CMS Collaboration author names, affiliations and acknowledgements were omitted and have now been included in the HTML and PDF versions of the article. © 2023, The Author(s).
Citation - WoS: 37
Citation - Scopus: 47
Behaviour of Waste Polypropylene Pyrolysis Char-Based Epoxy Composite Materials
(SPRINGER HEIDELBERG, 2020) Soğancıoğlu, Merve; Yel, Esra; Ahmetli, Gülnare
In this study, polypropylene (PP) plastic wastes were pyrolysed. Solid pyrolysis product (char) was used as filler material for the preparation of epoxy composite. 300, 400, 500, 600 and 700 degrees C were selected as final pyrolysis temperatures. Solid pyrolysis product (char) was analysed by elemental, FTIR, SEM, BET and TGA analysis. The epoxy composite samples were prepared with char obtained from pyrolysis. Mechanical properties of composites were analysed by hardness, tensile strength, elongation at break, electrical conductivity tests to explain the effects of pyrolysis temperature and char doses over composite properties. Thermogravimetric properties of composites were determined by TGA analyses. The water absorption behaviour of composite samples was determined by water adsorption test. Epoxy composite produced from PP char obtained under 300 degrees C showed the most ideal behaviour.
Citation - WoS: 1
Citation - Scopus: 1
Bending Performance of Reinforced Concrete Beams With Partial Waste Glass Aggregate Replacement Assessed by Experimental, Theoretical and Digital Image Correlation Analyses
(Nature Portfolio, 2025) Ozkilic, Yasin Onuralp; Basaran, Bogachan; Aksoylu, Ceyhun; Karalar, Memduh; Zeybek, Ozer; Althaqafi, Essam; Umiye, Osman Ahmed
This study examines the usage of waste glass aggregate (WGA) for the consumption of sustainable reinforced concrete regarding the replacement of fine aggregate (FA) and coarse aggregate (CA). For this purpose, a series of tests consisting of a total of 12 beams were carried out to explore the bending performance. The quantity of the longitudinal reinforcement section area and WGA percentage were selected as the prime variables. For this purpose, the aggregate was swapped with WGA with weight percentages of 10% and 20% for the FA and 10% and 20% for coarse aggregate. The test outcomes revealed that the crack and bending properties of the reinforced concrete beams (RCBs) were greatly affected by the section area of tension reinforcement and the percentage of the WGA. The WGA percentage might be effectively used as 20% of the partial replacement of FA. With the addition of FA to the mixture, the load-bearing capacity of RCB increases. The increase in the WGA percentage by more than 10% might cause a considerable reduction in the capacity of the RCBs, especially when the longitudinal reinforcement ratio is high. Furthermore, the digital image correlation method was used to show the cracks/micro-cracks and to define displacement in RCBs.
Citation - WoS: 12
Citation - Scopus: 15
Biopolymeric Nanofibrous Scaffolds of Poly(3-hydroxybuthyrate)/Chitosan Loaded With Biogenic Silver Nanoparticle Synthesized Using Curcumin and Their Antibacterial Activities
(Elsevier B.V., 2024) Bayram, Sarıipek, F.
The increasing prevalence of multi-drug resistant bacteria poses a significant threat to public health, especially in wound infections. Developing new bactericidal agents and treatment strategies is crucial to address this issue. In this study, biopolymeric nanofibrous scaffolds containing green-synthesized silver nanoparticles (AgNPs) with curcumin (CUR) were evaluated as antimicrobial materials for wound healing therapy. Firstly, CUR was utilized to synthesize AgNPs, which were then analyzed using various analytical methods. The microstructural analysis revealed that the biogenic AgNPs, which had a spherical shape and an average size of 19.83 nm, were uniformly anchored on PHB/CTS nanofibers. Then, the AgNPs with various content (0.25–1%wt) were incorporated into PHB/CTS matrix to enhance its wettability, thermal and bactericidal behaviors. The nanofibrous scaffolds were characterized by FT-IR, FE-SEM, TGA analysis and water contact angle measurement. Overall, the addition of CUR-AgNPs to the PHB/CTS matrix led to a reduction in fiber diameter, enhanced hydrophilicity and improved thermal properties. Additionally, antibacterial activity against Staphylococcus aureus and Escherichia coli was performed on samples of AgNPS and PHB/CTS/CUR-Ag. The synthesized AgNPs showed antibacterial activity against both microorganisms, especially against S. aureus. Higher concentrations of AgNPs in nanofibers led to a significant reduction in bacterial colony formation. The results displayed that PHB/CTS/CUR-AgNPs nanofibrous scaffolds could be a promising material for the biomedical applications such as wound healing. © 2023 Elsevier B.V.
Citation - WoS: 11
Citation - Scopus: 9
Capture and Release Recyclable Dimethylaminomethyl-Calixarene Functional Cloths for Point-Of Removal of Highly Toxic Chromium Water Pollutants
(AMER CHEMICAL SOC, 2020) Bieber, Vera S.; Özçelik, Egemen; Cox, Harrison J.; Ottley, Christopher J.; Ratan, Jatinder K.; Karaman, Mustafa; Badyal, Jas Pal S.
Chromium(VI) contamination of drinking water arises from industrial activity wherever there is a lack of environmental legislation enforcement regarding the removal of such pollutants. Although it is possible to remove such harmful metal ions from drinking water through large-scale facilities, there currently exists no safe and simple way to filter chromium(VI) oxoanions at the point of use (which is potentially safer and necessary in remote locations or humanitarian scenarios). High-surface-area cloth substrates have been functionalized with calixarene molecules for the selective capture of aqueous chromium(VI) oxoanions in the presence of structurally similar anions. This is accomplished by pulsed plasmachemical deposition of a linker layer and subsequent functionalization with dimethylaminomethyl-calixarene (5,11,17,23-tetrakis [(dimethylamino)methyl]-25,26,27,28-tetrahydroxycalix[4]arene. Chromium(VI) oxoanions are captured by simply passing polluted water through the functionalized cloth, while other ions not harmful/beneficial to human health remain in the water. These cloth filters are simple to use, highly selective, and easily recyclable-thus making them attractive for point-of-use application in geographic regions lacking appropriate wastewater treatment plants or flawed environmental monitoring systems. Chromium(VI) pollutants have been successfully removed from real-world contaminated industrial wastewater streams using the dimethylaminomethyl-calixarene functionalized cloths.
Citation - WoS: 16
Citation - Scopus: 21
Carcinogenic-Potential Ecological Risk Assessment of Soils and Wheat in the Eastern Region of Konya (turkey)
(SPRINGER HEIDELBERG, 2021) Öztürk, Alican; Arıcı, Ömer Kağan
The drainage channel where the wastewater of Konya city center is discharged, the solid waste storage center, the soils surrounding the industrial area, the potential accumulation of toxic elements (PTE) accumulated in the wheat grown in these soils, and their effects on human health were examined. Between 1977 and 2010, the water in the drainage channel was used for a variety of crops, mainly wheat grown in the nearby agricultural areas until the commissioning of the wastewater treatment plant. Industrial facilities, solid waste landfills, and military firing areas are actively used and are thought to be important factors in heavy metal accumulation in soils. In addition, the investigation area is on the sediments of the deposits stored in the large Konya Lake depending on the geological structure around Konya and caused geogenic heavy metal accumulation as a result of the separation and transportation of ophiolitic, magmatic, metamorphic, and sedimentary rocks in the region. In the research, PTE accumulation was determined in the samples of N1 (Pb, As, and Hg), N9 (Cd, As), and N10 (Cd and As) and N8 (Pb) in wheat. The carcinogenic risk factor of Ni, Al, Mn, and Cr elements in the territory of the region has been found as medium for children and adults. It has been determined that the potential source of toxic elements does not only depend on anthropogenic events but also occurs as a result of geological events.
Citation - WoS: 237
Citation - Scopus: 311
Cnn-Based Transfer Learning-Bilstm Network: a Novel Approach for Covid-19 Infection Detection
(ELSEVIER, 2021) Aslan, Muhammet Fatih; Ünlerşen, Muhammed Fahri; Sabancı, Kadir; Durdu, Akif
Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019 and has spread rapidly all over the world since the beginning of 2020, has infected millions of people and caused many deaths. For this pandemic, which is still in effect, mobilization has started all over the world, and various restrictions and precautions have been taken to prevent the spread of this disease. In addition, infected people must be identified in order to control the infection. However, due to the inadequate number of Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests, Chest computed tomography (CT) becomes a popular tool to assist the diagnosis of COVID-19. In this study, two deep learning architectures have been proposed that automatically detect positive COVID-19 cases using Chest CT X-ray images. Lung segmentation (preprocessing) in CT images, which are given as input to these proposed architectures, is performed automatically with Artificial Neural Networks (ANN). Since both architectures contain AlexNet architecture, the recommended method is a transfer learning application. However, the second proposed architecture is a hybrid structure as it contains a Bidirectional Long Short-Term Memories (BiLSTM) layer, which also takes into account the temporal properties. While the COVID-19 classification accuracy of the first architecture is 98.14%, this value is 98.70% in the second hybrid architecture. The results prove that the proposed architecture shows outstanding success in infection detection and, therefore this study contributes to previous studies in terms of both deep architectural design and high classification success. (C) 2020 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Co-Flotation of Effluents From Detergent and Marble Processing Industries in Denver and Dispersed Air Flotation Systems
(Elsevier Ltd, 2024) Yel, E.; Onen, V.; Kalem, M.
Suspended solids in the marble processing wastewater (MPWW) have the potential to pollute receiving media. Likewise, detergent production wastewater (DPWW) needs treatment prior to discharge as they include surfactants and others. Flotation and its modifications are common for separation purposes in various engineering solutions. To increase flotation performance by changing the surface tension some collector and frother chemicals, surfactants are utilized. Detergents are among important surfactants and they may act as both frother and collector in flotation. Therefore, the purpose of this study was to determine the effectiveness of DPWW in co-flotation with MPWW. Two effluents were mixed at varying ratios and dispersed air (DISP) and Denver (DEN) flotation co-treatment were applied to the mixtures. Volume ratio, time and air flow rate on treatment performance were investigated. Turbidity, solids, COD, phosphate removals were achieved at varying levels when the flotation was applied to the mixture. The highest treatment performance was achieved at 90%MPWW-10%DPWW mixture. 10 min flotation time and 2 L min−1 air flow rate for the DEN system, and 20 min and 6 L min−1 for the DISP system were recommended. Under these conditions turbidity, SS, COD, phosphate and alkalinity residuals (and removal efficiencies) were 2400 NTU(82%), 1720 mg.L−1(89%), 313.6 mg.L−1(10%), 20 mg.L−1(20%) and 600 mg.L−1CaCO3(92%) in the DEN system, respectively. Whereas, in the DISP system, under the same conditions, final values of 1880 NTU(86%), 1540 mg.L−1(91%), 262 mg.L−1(17%), 21 mg.L−1(20%) and 470 mg.L−1(94%) were obtained, respectively. The highest SludgeSS concentration increased up to 19300 mg.L−1 in the 90%–10% mixture. In all samples, dewaterable sludge was obtained. By this study, co-flotation of these two effluents was recommended. Within SDGs, this approach will replace frother chemical usage. The process performance can further be enhanced via flotation modifications and technology can be developed as further study. © 2024 Elsevier Ltd
Co-Occurrence and Molecular Characterization of ESBL-Producing and Colistin-Resistant Escherichia Coli Isolates From Retail Raw Meat
(MDPI, 2025) Telli, Arife Ezgi; Telli, Nihat; Bicer, Yusuf; Turkal, Gamze; Yilmaz, Tahir; Ucar, Gurkan
Background: The emergence of extended-spectrum beta-lactamase (ESBL) producing and colistin-resistant Escherichia coli in retail meat poses a significant public health risk. Method: A total of 180 retail meat samples (chicken parts, internals, processed products; lamb; beef; fish) were purchased from markets and butcher shops across Turkiye. Presumptive ESBL-producing isolates were screened on chromogenic agar and phenotypically confirmed. Species identity was verified by uspA PCR, and resistance genes (blaCTX-M, blaTEM, blaOXA, blaSHV, mcr-1, mcr-2, mcr-3) were analyzed. Colistin MICs were determined by broth microdilution, while antimicrobial susceptibility of ESBL-positive isolates was assessed by disk diffusion. Results: Overall, ESBL-producing E. coli were detected in 21.7% (n = 39) of the 180 meat samples analyzed, with the highest prevalence observed in chicken parts (26/40, 65.0%) and giblets (6/10, 60%). All ESBL-E. coli isolates harbored blaCTX-M, with blaCTX-M-1 identified as the sole variant. The blaTEM gene was detected in 61.5% (24/39) of ESBL-positive E. coli isolates. Colistin resistance was identified in six isolates (15.4%), all of which carried the mcr-1 gene. Additionally, one lamb minced meat isolate harbored the mcr-2 gene. Co-occurrence analysis revealed that the most frequent resistance gene combination among ESBL-producing isolates was blaCTX-M1 + blaTEM, detected predominantly in chicken meat samples, while mcr-1 was observed only in isolates harboring single or limited resistance genes, suggesting a distinct acquisition pattern. Conclusions: A high prevalence of blaCTX-M-1 and the co-occurrence of mcr genes were detected in E. coli isolates from retail meat, particularly poultry. The detection of mcr-1/mcr-2 co-carriage in lamb meat, though rare, highlights the need for broader surveillance. These findings underscore the need for integrated monitoring and prudent antimicrobial use in food animals. The use of antibiotics as growth promoters is prohibited in T & uuml;rkiye, and therapeutic applications require a veterinary prescription; however, stronger enforcement remains essential to limit the dissemination of multidrug-resistant bacteria in the food chain.
Citation - WoS: 112
Citation - Scopus: 138
Comparative Analysis of Topsis, Vikor and Copras Methods for the Covid-19 Regional Safety Assessment
(ELSEVIER SCIENCE LONDON, 2021) Hezer, Seda; Gelmez, Emel; Özceylan, Eren
COVID-19, which emerged in December 2019, has affected the entire world. Therefore, COVID-19 has been a subject of research in various disciplines, especially in the field of health. One of these studies was the report made by the Deep Knowledge Group (DKG) consortium in which safe regions for COVID19 were determined. In the report, the main criteria of quarantine efficiency, government efficiency of risk management, monitoring and detection, health readiness, regional resilience, and emergency preparedness are used in the evaluation of countries and regions (alternatives). As the data and research structure used in this report are based on multi-criteria, the purpose of this study is to evaluate and analyse the safety levels of 100 regions in the world in terms of COVID-19 using Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), Vise Kriterijumsa Optimizacija I Kompromisno Resenje (VIKOR) and Complex Proportional Assessment (COPRAS) methods. The data and information required in the methods were obtained from a report prepared by the DKG. The results of the methods were compared with the ranking results presented in a report of the DKG. Accordingly, it has been observed that the method that provides the closest results to the results of the report is the COPRAS method, and the method that gives the most distant results is the VIKOR method. (c) 2021 The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).
Citation - WoS: 36
Citation - Scopus: 43
Comparison of Advanced Biological Treatment and Nature-Based Solutions for the Treatment of Pharmaceutically Active Compounds (phacs): a Comprehensive Study for Wastewater and Sewage Sludge
(ELSEVIER, 2021) Nas, Bilgehan; Dolu, Taylan; Argun, Mehmet Emin; Yel, Esra; Ateş, Havva; Koyuncu, Serdar
Passing of pharmaceutical residues into environment in an uncontrolled manner as a result of continuous increase in drug consumption across the globe has become a threatening problem for the ecosystems and almost all living creatures. In this study, diclofenac (DCF), carbamazepine (CBZ), 17 beta-estradiol (17 beta-E2) and 17 alpha ethynylestradiol (EE2) belonging to different therapeutic classes were investigated simultaneously in advanced biological treatment and nature-based treatments during 12-months sampling campaign. In this context, behavior patterns of pharmaceutically active compounds (PhACs) throughout the both wastewater and sludge lines in advanced biological wastewater treatment plant (WWTP), wastewater stabilization pond (WSP) and constructed wetland (CW) were discussed in detail based on each treatment processes seasonally. Furthermore, statistically evaluated data obtained in full-scale WWTPs were compared with each other in order to determine the valid removal mechanisms of these pharmaceutical compounds. While DCF and CBZ were detected very intensively both in the wastewater and sludge lines of the investigated WWTPs, steroid hormones,17 beta-E2 and EE2, were determined below the LOQ value in general. Annual average removal efficiencies achieved in studied WWTPs for DCF ranged between & minus;23.3% (in CW) and 75.2% (in WSP), while annual average removal rates obtained for CBZ varied between & minus;20.7% (in advanced biological treatment) and 10.0% (in CW). It has been found that DCF was highly affected by different wastewater treatment processes applied in the WWTPs compared to CBZ which showed extraordinary resistance to all different treatment processes. Although calculated in different rates for each compounds, biodegradation/biotransformation and sorption onto sewage sludge were determined as the main removal mechanisms for PhACs in plants. Although showed a similar behavior in the sludge dewatering unit (decanter) present in the advanced biological WWTP, quite different behaviors ob-served in the anaerobic digester for DCF (up to 15% decrease) and CBZ (up to 95% increase). Sorption and desorp-tion behaviors of DCF and CBZ were also evaluated in the sludge treatment processes found in advanced biological WWTP. Percentages of originated extra annual average of pharmaceutical loads were calculated as 0.64% and 0.90% for DCF and CBZ, respectively in the advanced biological WWTP due to the sidestream caused by the sludge dewatering unit. (c) 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 20
Citation - Scopus: 20
Comparison of Microbiota and Volatile Organic Compounds in Milk From Different Sheep Breeds
(Elsevier Inc., 2021) Yusuf, B.; Ezgi, T.A.; Gonca, S.; Telli, Nihat; Gürkan, U.
In this study, we compared the microbiota and volatile organic compounds (VOC) present in the milk obtained from 3 different sheep breeds, namely Merino, Lacaune, and Assaf. Udder milk was collected from 21 animals, 7 from each breed. Bacterial microflora was determined metagenomically by extracting the DNA from the milk and analyzing the V3-V4 region of the 16S rRNA gene. Headspace solid-phase microextraction gas chromatography-mass spectrometry method was used to analyze VOC. The metagenomic analysis revealed (for Merino, Lacaune, and Assaf milk, respectively) Firmicutes (66.32, 69.36, and 57.08%), Actinobacteria (19.09, 7.67, and 19.40%), Proteobacteria (13.76, 21.06, and 22.19%), and Bacteroidetes (0.84, 1.91, and 1.33%) phyla in the milk samples. Lactobacillus was highly abundant in the milk of 3 breeds (29.64, 43.50, and 18.70%). The genera constituting more than 2% of all bacteria in all groups were Jeotgalicoccus (7.19, 5.34, and 10.77%), Enterococcus (5.18, 9.78, and 3.64%), and Corynebacterium (4.08, 3.00, and 13.44%). A total of 32 different VOC were identified by headspace solid-phase microextration analysis with 9, 30, and 24 different compounds from Merino, Lacaune, and Assaf breeds, respectively. Although ketone was the most abundant compound in Merino milk (71.84%), hydrocarbons were the most detected in Lacaune and Assaf milk (37.18% and 55.42%, respectively). A positive correlation was found between acetone, which was detected at the highest level in all groups, with Salinicoccus, Alloiococcus, Psychrobacter, and Dietzia. In addition, a negative correlation was found between the Lactobacillus genus, detected at the highest level in all groups, with methyl cyclopentane, 3-methylheptane, octane, decane, 3,3-dimethyloctane, and dodecane. Thus, differences were observed in the bacterial microflora and VOC in the sheep milk from different breeds under different feeding and breeding conditions. © 2021 American Dairy Science Association
Citation - WoS: 3
Citation - Scopus: 4
A Comprehensive Evaluation of Oversampling Techniques for Enhancing Text Classification Performance
(Nature Portfolio, 2025) Taskiran, Salimkan Fatma; Turkoglu, Bahaeddin; Kaya, Ersin; Asuroglu, Tunc
Class imbalance is a common and critical challenge in text classification tasks, where the underrepresentation of certain classes often impairs the ability of classifiers to learn minority class patterns effectively. According to the "garbage in, garbage out" principle, even high-performing models may fail when trained on skewed distributions. To address this issue, this study investigates the impact of oversampling techniques, specifically the Synthetic Minority Over-sampling Technique (SMOTE) and thirty of its variants, on two benchmark text classification datasets: TREC and Emotions. Each dataset was vectorized using the MiniLMv2 transformer model to obtain semantically rich representations, and classification was performed using six machine learning algorithms. The balanced and imbalanced scenarios were compared in terms of F1-Score and Balanced Accuracy. This work constitutes, to the best of our knowledge, the first large-scale, systematic benchmarking of SMOTE-based oversampling methods in the context of transformer-embedded text classification. Furthermore, statistical significance of the observed performance differences was validated using the Friedman test. The results provide practical insights into the selection of oversampling techniques tailored to dataset characteristics and classifier sensitivity, supporting more robust and fair learning in imbalanced natural language processing tasks.
Citation - WoS: 40
Citation - Scopus: 43
Compressive Behavior of Pultruded Gfrp Boxes With Concentric Openings Strengthened by Different Composite Wrappings
(MDPI, 2022) Aksoylu, Ceyhun; Özkılıç, Yasin Onuralp; Madenci, Emrah; Safonov, Alexander
Web openings often need to be created in structural elements for the passage of utility ducts and/or pipes. Such web openings reduce the cross-sectional area of the structural element in the affected region, leading to a decrease in its load-carrying capacity and stiffness. This paper experimentally studies the effect of web openings on the response of pultruded fiber-reinforced polymer (PFRP) composite profiles under compressive loads. A number of specimens have been processed to examine the behavior of PFRP profiles strengthened with one or more web openings. The effects of the size of the web opening and the FRP-strengthening scheme on the structural performance of PFRP profiles with FRP-strengthened web openings have been thoroughly analyzed and discussed. The decrease in load-carrying capacity of un-strengthened specimens varies between 7.9% and 66.4%, depending on the diameter of the web holes. It is observed that the diameter of the hole and the type of CFRP- or GFRP-strengthening method applied are very important parameters. All CFRP- and GFRP-strengthening alternatives were successful in the PFRP profiles, with diameter-to-width (D/W) ratios between 0.29 and 0.68. In addition, the load-carrying capacity after reinforcements made with CFRP and GFRP increased by 3.1-30.2% and 1.7-19.7%, respectively. Therefore, the pultruded profiles with openings are able to compensate for the reduction in load-carrying capacity due to holes, up to a D/W ratio of 0.32. The capacity significantly drops after a D/W ratio of 0.32. Moreover, the pultruded profile with CFRP wrapping is more likely to improve the load-carrying capacity compared to other wrappings. As a result, CFRP are recommended as preferred composite materials for strengthening alternatives.
Citation - WoS: 93
Citation - Scopus: 123
Covid-19 Diagnosis Using State-Of Cnn Architecture Features and Bayesian Optimization
(Pergamon-Elsevier Science Ltd, 2022) Aslan, Muhammet Fatih; Sabancı, Kadir; Durdu, Akif; Ünlerşen, Muhammed Fahri
The coronavirus outbreak 2019, called COVID-19, which originated in Wuhan, negatively affected the lives of millions of people and many people died from this infection. To prevent the spread of the disease, which is still in effect, various restriction decisions have been taken all over the world. In addition, the number of COVID-19 tests has been increased to quarantine infected people. However, due to the problems encountered in the supply of RTPCR tests and the ease of obtaining Computed Tomography and X-ray images, imaging-based methods have become very popular in the diagnosis of COVID-19. Therefore, studies using these images to classify COVID-19 have increased. This paper presents a classification method for computed tomography chest images in the COVID-19 Radiography Database using features extracted by popular Convolutional Neural Networks (CNN) models (AlexNet, ResNet18, ResNet50, Inceptionv3, Densenet201, Inceptionresnetv2, MobileNetv2, GoogleNet). The determination of hyperparameters of Machine Learning (ML) algorithms by Bayesian optimization, and ANN-based image segmentation are the two main contributions in this study. First of all, lung segmentation is performed automatically from the raw image with Artificial Neural Networks (ANNs). To ensure data diversity, data augmentation is applied to the COVID-19 classes, which are fewer than the other two classes. Then these images are applied as input to five different CNN models. The features extracted from each CNN model are given as input to four different ML algorithms, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), Naive Bayes (NB), and Decision Tree (DT) for classification. To achieve the most successful classification accuracy, the hyperparameters of each ML algorithm are determined using Bayesian optimization. With the classification made using these hyperparameters, the highest success is obtained as 96.29% with the DenseNet201 model and SVM algorithm. The Sensitivity, Precision, Specificity, MCC, and F1-Score metric values for this structure are 0.9642, 0.9642, 0.9812, 0.9641 and 0.9453, respectively. These results showed that ML methods with the most optimum hyperparameters can produce successful results.

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