Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

Browse

Now showing 1 - 20 of 134

Citation - Scopus: 3
Solving Optimization Problem With Particle Swarm Optimization: Solving Hybrid Flow Shop Scheduling Problem With Particle Swarm Optimization Algorithm
(Springer, 2021) Madenoğlu, Fatma Selen
The flow shop scheduling problem is widely discussed in the literature since it is frequently applied in real industry. This paper presents a variant of flow shop scheduling problem with parallel machines. The proposed problem includes multistage and identical parallel machines at each stage, and the sequence-dependent setup time and transportation time are considered. The objective function is minimization of makespan. The particle swarm optimization algorithm (PSO) is addressed to solve the problem and compared with genetic algorithm and heuristics. The benchmark instances are generated to demonstrate the performance of the PSO. The numerical results show that the PSO significantly outperforms the comparison set. © 2021 Elsevier B.V., All rights reserved.
Apatinib Sensitizes Human Breast Cancer Cells Against Navitoclax and Venetoclax Despite Up-Regulated Bcl-2 and Mcl-1 Gene Expressions
(Kare Publ, 2021) Kavakcioglu Yardimci, Berna; Ozgun Acar, Ozden; Semiz, Asli; Sen, Alaattin
OBJECTIVE Defects in apoptotic cell death which restrict the success of conventional cytotoxic therapies have pivotal roles in a number of pathological conditions including cancer. However, a novel drug class targeting pro-survival Bcl-2 protein family members has been developed with the understanding of the structures and interactions of Bcl-2 proteins. Within this new class, Bcl-2/Bcl-xL inhibitor Navitoclax and Bcl-2 specific inhibitor Venetoclax have been shown to demonstrate strong anticancer activities on several types of cancers. But their low affinity to other anti-apoptotic proteins limits their clinical usage. Here, we investigated the cytotoxic and apoptotic effects of Navitoclax/Venetoclax and their combinations with specific tyrosine kinase inhibitor Apatinib on estrogen receptor (ER)-positive MCF-7 and ER-negative MDA-MB-231 breast cancer cell lines. METHODS MTT assay was used for the evaluation of the inhibition of cancer cell proliferation. ELISA test and Quantitative real-time PCR assay was performed to determine the role of caspase-3, Bak, Bax, Bcl-2, Bcl-xL and Mcl-1 proteins in the inhibition of cell proliferation triggered by the tested agents. RESULTS We found that aggressive MDA-MB-231 cell line was more sensitive to all tested agents. Apatinib significantly enhanced Navitoclax/Venetoclax mediated inhibition of cell viability in both cancer cell lines despite up-regulation in the expression levels of Bcl-2 and Mcl-1 genes. We further demonstrated significant Bak/Bax and caspase-3 expression in less aggressive MCF-7 cells. CONCLUSION Our findings have impacts on Navitoclax/Venetoclax plus Apatinib based therapy for breast adenocarcinoma. On the other hand, further studies should be conducted to elucidate the mechanisms underlying synergistic effects of Navitoclax/Venetoclax plus Apatinib combinations.
Text Classification Experiments on Contextual Graphs Built by N-Gram Series
(Springer International Publishing AG, 2025) Sen, Tarik Uveys; Yakit, Mehmet Can; Gumus, Mehmet Semih; Abar, Orhan; Bakal, Gokhan
Traditional n-gram textual features, commonly employed in conventional machine learning models, offer lower performance rates on high-volume datasets compared to modern deep learning algorithms, which have been intensively studied for the past decade. The main reason for this performance disparity is that deep learning approaches handle textual data through the word vector space representation by catching the contextually hidden information in a better way. Nonetheless, the potential of the n-gram feature set to reflect the context is open to further investigation. In this sense, creating graphs using discriminative ngram series with high classification power has never been fully exploited by researchers. Hence, the main goal of this study is to contribute to the classification power by including the long-range neighborhood relationships for each word in the word embedding representations. To achieve this goal, we transformed the textual data by employing n-gram series into a graph structure and then trained a graph convolution network model. Consequently, we obtained contextually enriched word embeddings and observed F1-score performance improvements from 0.78 to 0.80 when we integrated those convolution-based word embeddings into an LSTM model. This research contributes to improving classification capabilities by leveraging graph structures derived from discriminative n-gram series.
Citation - WoS: 3
Citation - Scopus: 3
Template Scoring Methods for Protein Torsion Angle Prediction
(Springer-Verlag Berlin, 2015) Aydin, Zafer; Baker, David; Noble, William Stafford
Prediction of backbone torsion angles provides important constraints about the 3D structure of a protein and is receiving a growing interest in the structure prediction community. In this paper, we introduce a three-stage machine learning classifier to predict the 7-state torsion angles of a protein. The first two stages employ dynamic Bayesian and neural networks to produce an ab-initio prediction of torsion angle states starting from sequence profiles. The third stage is a committee classifier, which combines the ab-initio prediction with a structural frequency profile derived from templates obtained by HHsearch. We develop several structural profile models and obtain significant improvements over the Laplacian scoring technique through: (1) scaling templates by integer powers of sequence identity score, (2) incorporating other alignment scores as multiplicative factors (3) adjusting or optimizing parameters of the profile models with respect to the similarity interval of the target. We also demonstrate that the torsion angle prediction accuracy improves at all levels of target-template similarity even when templates are distant from the target. The improvement is at significantly higher rates as template structures gradually get closer to target.
Citation - WoS: 1
Citation - Scopus: 2
Experimental Study on Increase of Bonding Strength of FRP Reinforcement in Concrete
(Springer-Verlag Singapore Pte Ltd, 2022) Taskin, Furkan; Ciftci, Cihan
In the last two decades, the use of fiber-reinforced polymer (FRP) bars is of great interest to reinforce concrete beam structures due to its high specific strength, effective corrosion resistance, and low cost fabrication. Therefore, the flexural performance of these reinforced concrete beams containing FRP bars has been investigated by researchers for years with great interest. According to these investigations, one of the major problems is weak bonding strength between these bars and concrete material. Since, this major problem causes low flexural capacity, high deflection, and high crack widths for the reinforced concrete beams. Hence, the use of FRP bars by engineers does not sufficiently become widespread and also the engineering applications of these useful materials are still limited today. In this study, it is aimed to present an applicable solution regarding the bonding failures of the FRP bars in structurally reinforced concrete beams. For this solution, reinforced concrete beam samples were produced by using FRP materials on which knotted structures were formed. Then these samples were tested under 3-point bending tests. Furthermore, smooth-surfaced FRP bars and traditional deformed steel rebars were also used as reinforcing materials in the concrete beam samples for the comparison of the flexural capacities of each sample in order to investigate the effects of the reinforcing materials on the bonding strength. To conclude, the knotted FRP bars provide a significant contribution on the flexural capacity due to the increase of the bonding strength between the reinforcing material and the concrete in the beams.
Normal Mixture Model-Based Clustering of Data Using Genetic Algorithm
(Springer International Publishing AG, 2020) Gogebakan, Maruf; Erol, Hamza
In this study, a new algorithm was developed for clustering multivariate big data. Normal mixture distributions are used to determine the partitions of variables. Normal mixture models obtained from the partitions of variables are generated using Genetic Algorithms (GA). Each partition in the variables corresponds to a clustering center in the normal mixture model. The best model that fits the data structure from normal mixture models is obtained by using the information criteria obtained from normal mixture distributions.
Acoustic Transformation of Rock-Cut Caves Into Performance Spaces
(European Acoustics Association, EAA, 2023) Aslan, Ahmet; Şaher, Konca; Tozoğlu, Ahmet Erdem
Cappadocia Region in Turkey is a center of attention as a tourism destination with its rock-cut caves, some of which are being used as performance spaces for concerts, festivals and local entertainment activities. However, these spaces are not fully investigated for their acoustic performance before being transformed into performance venues. This paper reports on the findings of an initial survey which presents a systematic mapping of the rock-cut caves used as performance spaces to locate, explore and document a sample of structures scattered in this historic district. A typological classification based on volume, size, type of tuff rock material and historical original use has been proposed and an acoustic analysis of some selected rock-cut caves has been carried out. The acoustic analysis included reverberation time calculations and simulations based on apparent volume, and tuff stone absorption characteristics, which were studied by other researchers in the area. © 2024 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Electricity Load Forecasting Using Deep Learning and Novel Hybrid Models
(Sakarya University, 2022) Sutcu, Muhammed; Şahi̇n, Kübra Nur; Koloğlu, Yunus; Çelikel, Mevlüt Emirhan; Gulbahar, Ibrahim Tümay
Load forecasting is an essential task which is executed by electricity retail companies. By predicting the demand accurately, companies can prevent waste of resources and blackouts. Load forecasting directly affect the financial of the company and the stability of the Turkish Electricity Market. This study is conducted with an electricity retail company, and main focus of the study is to build accurate models for load. Datasets with novel features are preprocessed, then deep learning models are built in order to achieve high accuracy for these problems. Furthermore, a novel method for solving regression problems with classification approach (discretization) is developed for this study. In order to obtain more robust model, an ensemble model is developed and the success of individual models are evaluated in comparison to each other. © 2025 Elsevier B.V., All rights reserved.
Citation - WoS: 4
Citation - Scopus: 4
Differential in Vitro Anti-Leukemic Activity of Resveratrol Combined With Serine Palmitoyltransferase Inhibitor Myriocin in FMS-Like Tyrosine Kinase 3-Internal Tandem Duplication (FLT3-LTD) Carrying AML Cells
(Springer, 2022) Ersoz, Nur Sebnem; Adan, Aysun
Treatment of FMS-like tyrosine kinase 3 (FLT3)-internal tandem duplication (ITD) AML is restricted due to toxicity, drug resistance and relapse eventhough targeted therapies are clinically available. Resveratrol with its multi-targeted nature is a promising chemopreventive remaining limitedly studied in FLT3-ITD AML regarding to ceramide metabolism. Here, its cytotoxic, cytostatic and apoptotic effects are investigated in combination with serine palmitoyltransferase (SPT), the first enzyme of de novo pathway of ceramide production, inhibitor myriocin on MOLM-13 and MV4-11 cells. We assessed dose-dependent cell viability, flow cytometric cell death and cell cycle profiles of resveratrol in combination with myriocin by MTT assay, annexin-V/PI staining and PI staining respectively. Resveratrol's dose-dependent effect on SPT protein expression was also checked by western blot. Resveratrol decreased cell viability in a dose- dependent manner whereas myriocin did not affect cell proliferation effectively in both cell lines after 48h treatments. Although resveratrol induced both apoptosis and a significant S phase arrest in MV4-11 cells, it triggered apoptosis and non-significant S phase accumulation in MOLM-13 cells. Co-administrations reduced cell viability. Increased cytotoxic effect of co-treatments was further proved mechanistically through induction of apoptosis via phosphatidylserine relocalization. The cell cycle alteration in co-treatment was significant with an S phase arrest in MV4-11 cells, however, it was not effective on cell cycle progression of MOLM-13 cells. Resveratrol also increased SPT expression. Overall, modulation of SPT together with resveratrol might be the possible explanation for resveratrol's action. It could be an integrative medicine for FLT3-ITD AML after investigating its detailed mechanism of action in relation to de novo pathway of ceramide production.
Citation - Scopus: 3
Türkiye’de Yapılan Kuraklık Analiz Çalışmaları Üzerine Bir Derleme
(Ankara University, 2022) Deniz Öztürk, Yasemin; Ünlü, Ramazan
Drought has become one of the most studied disaster issues by scientists, especially after the 2000s, with the importance of climate change. Many scientific publications on drought have been produced, due to many different methods on drought and the study of drought by many disciplines of science. In the study, theses, national and international articles, which include drought analysis by using any statistical method over meteorological data in Turkey, were compiled. A total of 270 studies, including 73 master's and Ph.D. theses, 107 national articles, and 90 international articles, written between 1943-2021 were examined. These studies were classified according to the year of publication, the drought analysis methods used, in publication, the scientific field of the first author, and the region examined in the study, and their frequency distributions were revealed. The main conclusions of this study are as follows: Although the first published studies on drought analysis in Turkey were made in 1943, 1956, and 1965, studies on drought started to increase after 2000 and the total number of publications reached 37 in 2019, 43 in 2020, and 64 in 2021. Publications in the period of 2019-2021 correspond to 53% of all publications. This rapid increase in recent years has led to a logarithmic increase in the number of publications. Although 63 different methods are used in drought analysis in the studies, the standardized precipitation index is the dominant method with a usage rate of 56%. Most of the studies were carried out on the basins (113). In 41 studies, the whole of Turkey was examined. Other studies were carried out for geographical regions, provinces, and smaller settlements. According to the scientific fields, it is seen that the Civil Engineering (131 units) and Geography (41 units) departments are the scientific fields that carry out the most drought analysis studies. © 2025 Elsevier B.V., All rights reserved.
Manganzı Demir Cevherinden Manganın Çözündürülmesinde Farklı İndirgeme Maddelerinin Etkisi
(Chamber of Mining Engineers of Turkey, 2022) Top, S.; Altiner, Mahmut; Kursunoglu, Sait
IIn this paper, the manganese extraction from a manganiferous iron ore was investigated using reductive leaching. Various chemicals were used as a reducing agent to leach manganese selectively from the ore in the presence of sulfuric acid (H2SO4) solution. Firstly, optimum dissolution values were determined for selective manganese dissolution without using a reducing agent. As it was aimed at the selective extraction of manganese from the ore, the reductive leaching tests were conducted by adding the reducing agents under the following optimal parameters: a leaching time of 1 h, a stirring speed of 300 rpm, a temperature of 70°C, a sulfuric acid concentration of 1 M where the ore was leached with an extraction ratio of 11.54% Mn and 2.16% Fe. Manganese was dissolved with high efficiencies (up to 97.46%) from the ore by using different organic compounds (tartaric acid (C4H6O6), oxalic acid (C2H2O4), citric acid (C6H8O7), glucose (C6H12O6), sucrose (C12H22O11), and maleic acid (C4H4O4)) as the reducing agents. © 2022 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Data-Driven Discovery and DFT Modeling of Fe4H on the Atomistic Level
(Elsevier B.V., 2024) Zagorac, Dejan; Zagorac, Jelena; Djukic, Milos B.; Bal, Burak; Schön, Johann Christian
Since their discovery, iron and hydrogen have been two of the most interesting elements in scientific research, with a variety of known and postulated compounds and applications. Of special interest in materials engineering is the stability of such materials, where hydrogen embrittlement has gained particular importance in recent years. Here, we present the results for the Fe-H system. In the past, most of the work on iron hydrides has been focused on hydrogen-rich compounds since they have a variety of interesting properties at extreme conditions (e.g. superconductivity). However, we present the first atomistic study of an iron-rich Fe4H compound which has been predicted using a combination of data mining and quantum mechanical calculations. Novel structures have been discovered in the Fe4H chemical system for possible experimental synthesis at the atomistic level. © 2024 Elsevier B.V., All rights reserved.
Citation - Scopus: 5
Extraction of Lanthanum and Cerıum from a Bastnasite Ore By Direct Acidic Leaching
(Chamber of Mining Engineers of Turkey, 2020) Kursunoglu, Sait; Top, S.; Hussaini, Shokrullah; Gokcen, H. S.; Altiner, Mahmut; Ozsarac, Safak; Kaya, Muammer
The extraction of lanthanum (La) and cerium (Ce) from a bastnasite ore by direct acidic leaching was investigated. The effects of acid concentration and leaching temperature on the extraction of La and Ce from the ore were tested. Using nitric (NHO3), more than 85% of the La and Ce were simultaneously extracted into leach solution whereas the La and Ce dissolutions were determined as less than 85% by using sulfuric acid (H2SO4). The La dissolution exceeded 90% by using hydrochloric acid (HCl); however, the Ce dissolution remained below 85% under the following conditions: solid-to-liquid ratio of 20% (w/v), the acid concentration of 20%, leaching temperature of 25°C and leaching time of 1 h. The result revealed that HNO3 could be used as a solvent for the maximum simultaneous extraction of the La and Ce from the bastnasite ore. The leaching temperature had no crucial effect on the dissolution of La and Ce when HNO3 or HCl solutions were preferred as a solvating agent. However, the leaching temperature had a slight positive effect on the dissolutions of La and Ce when H2SO4 was used as a solvent. © 2023 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Correlation of PAPP-A Values With Maternal Characteristics, Biochemical and Ultrasonographic Markers of Pregnancy
(Marmara Univ, Fac Medicine, 2021) Kaymakcalan, Hande; Uzut, Ommu Gulsum; Harkonen, Juho; Bakir Gungor, Burcu
Objective: Our aim is to investigate whether there is a correlation of pregnancy-associated plasma protein A (PAPP-A) values with other variables in pregnancy and maternal characteristics. Materials and Methods: We retrospectively analyzed the relation between the PAPP-A levels, demographics, biochemical and ultrasonographic markers of the first trimester screening of 11,842 pregnant women seen at a tertiary hospital between November 2002 and November 2008. Results: A significant difference between PAPP-A values of the diabetic and non-diabetic pregnant women were observed (p=0.0005, Mann-Whitney U test). In terms of weight, crown-rump length, Beta-hCG values, significant differences were observed between low and medium level PAPP-A subgroups and between low and high level PAPP-A subgroups. PAPP-A levels were found to differ significantly between the pregnant women of Caucasian origin and other racial origins. Conclusions: Pregnant women with different ethnic and medical backgrounds have different PAPP-A values and other markers of the aneuploidy screening. 'lb make patient specific risk predictions, understanding these interactions and differences is important. Future studies are needed to understand the pathopyhsiology behind these differences.
Preface of the Symposium on: Advances in Analytical, Analytical Approximate, Numerical and Asymptotic Analysis of Sturm-Liouville Problems With the Applications in Engineering
(American Institute of Physics Inc. subs@aip.org, 2018) Atay, Mehmet Tarik; Erdogan, Hakan H.
Citation - Scopus: 5
Distribution Automation Effects on Reliability During Major Contingencies
(IEEE Computer Society help@computer.org, 2018) Yoldaş, Yeliz; Onen, Ahmet; Alan, İrfan; Broadwater, Robert P.
Distribution automation affects reliability by providing faster restoration ability. In this study, the effect of distribution automation on radial distribution circuits during substation failures at peak load is investigated. The ultimate goal is to compare circuit automation to manual operation, where the comparison evaluates planning criteria reliability for customer interruption hours. The results show that distribution automation can improve reliability measurements such as SAIDI, SAIFI and CAIDI. © 2018 Elsevier B.V., All rights reserved.
Use of Confocal Microscopy to Monitor Structural Transformations in Nanopillars Based on DNA and CdSe/CdZnSe Quantum Dots
(Springer, 2023) Motevich, I. G.; Erdem, T.; Akrema, A.; Maskevich, S. A.; Strekal, N. D.
Chip system prototypes in the form of nanopillars were created from DNA complexes with CdSe/CdZnSe/ZnS quantum dots immobilized on a plasmonic gold fi lm by the use of vacuum deposition technology and inorganic synthesis. The design and presence of terminal DNA labeled with Cy3 cyanine dyes makes it possible to carry out the hybridization reaction of this terminal strand with complementary DNA and to control the process by variation of the giant Raman scattering (GRS) and the fluorescence signal. The effect of molecular recognition of complementary DNA is accompanied by a change in the GRS spectrum, a 20-fold increase in the fluorescence intensity, and a decrease in the duration of fluorescence decay.
Anticancer Effect of Ethanolic Yellow Hawthorn Extract on Chronic Myeloid Leukemia Cells and Acute Myeloid Leukemia Cells
(Ondokuz Mayis Universitesi, 2025) Arslan, Ayşe Nur; Akçok, Ismail
Cancer is a disease characterized by abnormal cell growth and invasion and metastasis of these cells to other tissues or organs of the body. Natural products have been used for centuries as drugs or in drug development, especially for the treatment of cancer. Besides, extracting natural products with several bioactive compounds has a promising effect on cancer treatment. In this study, we aimed to investigate the anticancer effect of the ethanolic extract of yellow hawthorn fruits on K562 (Chronic Myeloid Leukemia) and MOLM-13 (Acute Myeloid Leukemia) cell lines. The antiproliferative effect of the ethanolic extract of yellow hawthorn fruits was investigated in time-and dose-dependent manners. The Annexin-V/Propidium Iodide (PI) double staining was used to examine the apoptosis. Furthermore, cell cycle analysis is conducted by PI staining. The cell viability of K562 and MOLM-13 cell lines was significantly reduced by the ethanolic extract of yellow hawthorn fruits with IC50 values of 9144 µg/mL and 3515 µg/mL in 48-hour incubation time, respectively. Moreover, the results showed that the ethanolic extract of yellow hawthorn fruits caused an increased apoptosis by 12.7-and 8.87-fold changes in K562 and MOLM-13 cell lines compared to control groups, respectively. Ethanolic extract of yellow hawthorn fruit has reduced cell proliferation, induced apoptosis and arrested the cell cycle at G0/G1 phase by 71% in MOLM-13 and at G2/M phase by 80.3% and G0/G1 phase by 38.2 % in K562 cells. Further studies should be conducted to elucidate the mechanism of the effect of yellow hawthorn fruit on these cancer cells. © 2025 Elsevier B.V., All rights reserved.
Citation - Scopus: 2
Evaluating the Microbial Growth Kinetics and Artificial Gastric Digestion Survival of a Novel Pichia Kudriavzevii FOL-04
(Field Crops Central Research Institute, 2022) Gumustop, Ismail; Ortakci, Fatih
Present study aims to explore Pichia kudriavzevii FOL-04 (FOL-04)’s: i) survival against artificial gastric juice (AGJ) and artificial bile juice (ABJ), ii) growth kinetics in shake flask (SF) and fed-batch trials (FBT). Survival of FOL-04 as measured by relative cell density (RCD) against AGJ and ABJ was screened at four different pH-levels (control, 3, 2, 1.5) and ox-bile concentrations (control, 0.2%, 1%, 2%), respectively. Growth kinetics was calculated by periodic measurement of OD600 in SF (225 rpm, 30°C) or in FBT using exponential feeding regimen where pH, dissolved-oxygen and temperature were controlled at 5.5, 21%, and 30°C, respectively. The doubling-time, maximum specific growth rate, and final cell densities achieved for SF and FBT were 81.7min, 1.67, 11.79 and 170.4 min, 4.75, 37.95, respectively. RCDs calculated were similar for pH=3 and control vs both were significantly higher(p<0.05) than pH=1.5 and 2 with the latter two pH-levels were not significantly different(p>0.05). RCDs were similar across control, 0.2%, and 1% ox-bile levels(p>0.05). However, 2% ox-bile yielded significantly lower RCD (p<0.05) compared to all except 1%. FOL-04 is a potential probiotic candidate showing robustness against AGJ and ABJ and remarkable biomass increase was achieved when grown under FBT which could pave the way for developing a yeast-based probiotic using this strain. © 2023 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Measurement of Autophagic Activity in Cancer Cells With Flow Cytometric Analysis Using Cyto-Id Staining
(Humana Press Inc., 2025) Şansaçar, Merve; Gencer Akçok, Emel Başak
Autophagy is an evolutionarily conserved process providing the energy that cells need to survive, especially in stress situations, through catabolic processes. Considering the dual role of autophagy in cancer cells depending on the cellular context, it is crucial to comprehend the effect of drug candidates put forward to prevent cancer through the autophagy pathway. The CYTO-ID® Autophagy Detection Kit allows a rapid, specific and quantitative measurement of autophagic activity at the cellular level using a 488 nm-excitable green fluorescent detection reagent via flow cytometer. In this chapter, we present the CYTO-ID® Autophagy Detection method with a stepwise protocol to monitor the autophagy flux after the application of any compound to suspension cancer cell lines with flow cytometric analysis. © 2025 Elsevier B.V., All rights reserved.

Browse

Browsing Scopus İndeksli Yayınlar Koleksiyonu by Scopus Q "Q4"