Scopus İndeksli Yayınlar Koleksiyonu

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Citation - WoS: 1
Citation - Scopus: 1
The Associations Between Deviation From the Balanced Time Perspective and Depression and Anxiety: The Moderator Role of Mindfulness in a Two-Wave Study
(Sage Publications inc, 2025) Altan-Atalay, Ayse; Ranjbar, Hamed Abdollahpour; Altintas, Seda
Deviation from the balanced time perspective (DBTP) refers to difficulties in switching between different time frames in a flexible way by considering the situational demands. DBTP is associated with higher levels of depression and anxiety. Mindfulness acts as a protective mechanism against depression and anxiety. The current study examined the moderator role of mindfulness in the relationship between DBTP and psychological distress. The participants were 243 university students (53.09% women) between ages 18 and 29 (M = 19.88, SD = 1.42) who answered self-report measures of time perspective, mindfulness, anxiety, and depression at two-time points with a five-week time interval. The results showed that the interaction between DBTP and mindfulness measured at time one could prospectively predict both anxiety and depression measured at time two. Mindfulness plays a significant moderating role in the relationship between DBTP and anxiety and depression. The data indicate that for individuals with low levels of DBTP, those with higher mindfulness experience significantly lower anxiety and depression compared to those with lower mindfulness. However, as DBTP increases, anxiety and depression levels in the high mindfulness group rise significantly, ultimately converging with those observed in the low mindfulness group. This indicates that while high mindfulness offers buffering effects against anxiety and depression, these effects diminish under increased DBTP.
Citation - WoS: 27
Citation - Scopus: 26
New Biological and Chemical Evidences of Two Lamiaceae Species (thymbra Capitata and Thymus Sipyleus Subsp. Rosulans): in Vitro, in Silico and Ex Vivo Approaches
(Mdpi, 2022) Llorent-Martinez, Eulogio J.; Ruiz-Medina, Antonio; Zengin, Gokhan; Ak, Gunes; Jugreet, Sharmeen; Mahomoodally, Mohamad Fawzi; Emre, Gizem
In this study, the methanolic and infusion extracts of two species, Thymbra capitata and Thymus sipyleus subsp. rosulans, were tested for their chemical composition and biological abilities (antioxidant, enzyme inhibitory and anti-inflammatory effects). The extracts yielded total phenolic and flavonoid contents in the range of 83.43-127.52 mg GAE/g and 9.41-46.34 mg RE/g, respectively. HPLC analysis revealed rosmarinic acid to be a major component of the studied extracts (15.85-26.43%). The best ABTS radical scavenging ability was observed in the methanol extract of T. capitata with 379.11 mg TE/g, followed by in the methanol extract of T. sipylus (360.93 mg TE/g). In the CUPRAC assay, the highest reducing ability was also found in the methanol extract of T. capitata with 802.22 mg TE/g. The phosphomolybdenum ability ranged from 2.39 to 3.61 mmol TE/g. In terms of tyrosinase inhibitory effects, the tested methanol extracts (83.18-89.66 mg KAE/g) were higher than the tested water extracts (18.74-19.11 mg KAE/g). Regarding the BChE inhibitory effects, the methanol extracts were active on the enzyme while the water extracts showed no inhibitory effect on it. Overall, the methanolic extracts showed better enzyme inhibition compared to the infusion extracts. Molecular docking also showed the selected exhibited potential binding affinities with all enzymes, with a preference for cholinesterases. Additionally, the extracts were effective in attenuating the LPS-induced increase in COX-2 and IL-6 gene expression in isolated colon, thus indicating promising anti-inflammatory effects. The preliminary results of this study suggest that these species are good natural sources of antioxidants and also provide some scope as enzyme inhibitors, most likely due to their bioactive contents such as phenolic acids, and thus can be exploited for different applications related to health promotion and disease prevention.
A Methodological Approach to the Computational Problems in the Estimation of Adjusted PIN Model
(Routledge, 2025) Ersan, O.; Ghachem, M.
It is well documented that computational problems may lead to large biases in the estimation of probability of informed trading (PIN) models. The complexity of the AdjPIN model [Duarte, J. and Young, L., Why is PIN priced? J. Financ. Econ., 2009, 91, 119–138.], an extension of the conventional PIN model, exacerbates further these computational issues due to its larger parameter set. We introduce a dual approach to improve estimation reliability: a logarithmic factorization of the likelihood function and a strategic algorithm for generating initial parameter sets. The logarithmic factorization addresses floating point exceptions and numerical instability, while the algorithm significantly reduces the likelihood of converging to local maxima. We show that our methodology outperforms existing best practices and it enables accurate estimation of the AdjPIN model. We, therefore, strongly suggest its use in future studies. © 2025 Informa UK Limited, trading as Taylor & Francis Group.
Citation - Scopus: 7
Gastrointestinal: Epiploic appendagitis
(Blackwell Publishing, 2005) Kantarci,M.; Duran,C.; Sirvanci,M.
[No abstract available]
Citation - WoS: 5
Citation - Scopus: 5
Temperature Dependence of Oxygen Diffusion Into Clay-Doped Ps Films
(John Wiley & Sons Inc, 2010) Uğur, Şaziye; Yargı, Önder; Pekcan, Önder
Fluorescence technique was employed for the measurement of the diffusion coefficient of oxygen into polystyrene (PS) latex/modified Na-activated bentonite (MNaLB) clay composite films. Three different MNaLB content (0 5 and 20 wt%) composite films were prepared from PS/MNaLB mixtures by annealing them at 200 degrees C above the glass transition temperature of PS for 10 min. To determine the diffusivity of oxygen in PS/MNaLB composite films diffusion measurements were performed over the temperature range from 25 to 70 degrees C. Pyrene (P) was used as the fluorescent agent. The diffusion coefficients (D) of oxygen were determined by combining the fluorescence quenching method with Fickian transport model and were found as a function of temperature for each MNaLB content film. The results showed that D values are strongly dependent on both temperature and clay content in composite film. It was also observed that D coefficients obey Arrhenius behavior from where diffusion activation energies were measured. POLYM. COMPOS. 31:77-82 2010. (C) 2009 Society of Plastics Engineers
Citation - WoS: 14
Citation - Scopus: 17
A New Design of a Digital Filter for an Efficient Field Programmable Gate Array Using Quantum Dot Technology
(Elsevier, 2024) Taghavirashidizadeh, Ali; Ahmadpour, Seyed-Sajad; Ahmed, Suhaib; Navimipour, Nima Jafari; Kassa, Sankit Ramkrishna; Yalcin, Senay
Digital filtering algorithms are most frequently used to implement generic-based Field-programmable gate arrays (FPGAs) chips, which are used for higher sampling rates. In the filtering structure, delay and occupied areas play a vital role. Since the existing structures suffered from shortcomings such as high delay and high occupied area, implementing a high-performance digital filter circuit with high speed and low occupied area based on unique technology can significantly improve the performance of whole FPGA structures. One of the best technologies to implement this vital structure to solve these shortcomings is quantum-dot cellular automata (QCA) technology. This paper presents several new efficient full adders for digital filter applications based on quantum technology, including a multiplier, AND gate, and accumulator. The QCADesigner 2.0.3 tool is used to create and validate the suggested designs. According to the results, all designed circuits have simple structures with few quantum cells, low area, and low latency.
Citation - WoS: 4
Citation - Scopus: 4
Sensitivity of computational fluid dynamics simulations against soft errors
(Springer Wien, 2021) Yetkin, E. Fatih; Piskin, Senol
Computational capabilities of the largest high performance computing systems have increased by more than 100 folds in the last 10 years and keep increasing substantially every year. This increase is made possible mostly by multi-core technology besides the increase in clock speed of CPUs. Nowadays, there are systems with more than 100 thousand cores installed and available for processing simultaneously. Computational simulation tools are always in need of more than available computational sources. This is the case for especially complex, large scale flow problems. For these large scale problems, the soft error tolerance of the simulation codes should also be encountered where it is not an issue in relatively small scale problems due to the low occurrence probabilities. In this study, we analyzed the reaction of an incompressible flow solver to randomly generated soft errors at several levels of computation. Soft errors are induced into the final global assembly matrix of the solver by manipulating predetermined bit-flip operations. Behaviour of the computational fluid dynamics (CFD) solver is observed after iterative matrix solver, flow convergence and CFD iterations. Results show that the iterative solvers of CFD matrices are highly sensitive to customized soft errors while the final solutions seem more intact to bit-flip operations. But, the solutions might still differ from the real physical results depending on the bit-flip location and iteration number. So, the next generation computing platforms and codes should be designed to be able to detect bit-flip operations and be designed bit-flip resistant.
Citation - WoS: 1
Citation - Scopus: 1
Little Aleppo: the Neighbourhood Experiences of Syrian Refugees in Adana, Turkey, 'poor To Poor, Peer To Peer'
(Sage Publications Ltd, 2023) Akcali, Emel
The current refugee regimes (national/international and EUropean) present significant limitations in the ways they deal with refugee flows. However, both refugees and the host societies are able to develop their own agencies and strategies against such confines. This article pieces together the place-making and reterritorialisation efforts of Syrian refugees, the impact of their arrival on and interaction with the local population in the neighbourhoods of Adana in Turkey that has hosted the largest number of Syrian refugees and have become known as 'Little Aleppo'. The analysis of Syrians' experiences that emerge in their new settlements sheds new light on the ways in which urban refugees are able to increase their own agency and choose the solution(s) most appropriate to their own particular circumstances by establishing 'poor-to-poor, peer-to-peer' contacts, rather than depending on the few choices offered to them through refugee regimes. The locals, in return, are motivated by the newcomers' presence to reassess their own socio-economic positions and choices in the land of nation states, even though encounters with the refugees may at times elicit negative feelings.
Citation - WoS: 57
Citation - Scopus: 73
Drug Design for Cns Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3d-Qsar and Virtual Screening Methodologies
(Frontiers Media Sa, 2016) Nikolic, Katarina; Mavridis, Lazaros; Djikic, Teodora; Vucicevic, Jelica; Agbaba, Danica; Yelekçi, Kemal; Mitchell, John B. O.
The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer's disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug discovery programs. A probabilistic method, the ParzenRosenblatt Window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D-1-R/D-2-R/5-HT2A-R/H-3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs.
Four-Searchable Biconnected Outerplanar Graphs
(Elsevier, 2022) Diner, Oznur Yasar; Dyer, Danny; Yang, Boting
This paper deals with constructing obstruction sets for two subclasses of 4-searchable graphs. We first characterize the 4-searchable biconnected outerplanar graphs by listing all graphs that cannot be their minors; we then give a constructive characterization of such graphs. We also characterize the 4-searchable biconnected generalized wheel graphs by listing all graphs that cannot be their minors. Crown Copyright (C) 2021 Published by Elsevier B.V. All rights reserved.
Citation - WoS: 44
Citation - Scopus: 46
Software for Brain Network Simulations: A Comparative Study
(Frontiers Media Sa, 2017) Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.
Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with simplified neural and synaptic models and a small network with detailed models. These two case studies allow us to avoid any bias toward a particular software package. The results indicate that BRIAN provides the most concise language for both cases considered. Furthermore, as expected, NEST mostly favors large network models, while NEURON is better suited for detailed models. Overall, the case studies reinforce our general observation that simulators have a bias in the computational performance toward specific types of the brain network models.
Citation - WoS: 5
Citation - Scopus: 6
Integrating Technology Acceptance Model With Utaut To Increase the Explanatory Power of the Effect of Hci on Students' Intention To Use E-Learning System and Perceive Success
(Institute of Electrical and Electronics Engineers Inc., 2025) Al-Sayid, F.; Kirkil, G.
This study aimed to investigate the potential human-computer interaction factors (HCI) affecting students' behavioural intentions (BI) to use the e-learning system and perceive success. This paper proposes a comprehensive model, integrating the technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT). The data were collected via an online survey conducted on 232 students utilizing the Khas Learn system of Kadir has University in Turkey. The proposed hypotheses were tested by multi-linear regression. The results illustrated that the main predictors of students' success (SS) are behaviour intention, ease of use, usefulness, visual design, and learner interface interactivity which explained 53.6% of perceived success in using the system. While, the main predictors of BI are facilitating condition, effort expectancy, ease of use, and usefulness which explained 71% of the variance in continuance intentions to use e-learning. Therefore, the empirical findings provide strong backing to the technological-social-psychological dimensions extended by HCI main factors, which showed a high explanatory power in accepting e-learning technology and leads to enhance the SS, where five of the model's goodness-of-fit values meet five criteria of structural equation modeling (SEM). © 2013 IEEE.
Citation - WoS: 32
Citation - Scopus: 32
A Nano-Scale Arithmetic and Logic Unit Using a Reversible Logic and Quantum-Dots
(Springer, 2023) Navimipour, Nima Jafari; Ahmadpour, Seyed-Sajad; Yalcin, Senay
The arithmetic and logic unit (ALU) is a key element of complex circuits and an intrinsic part of the most widely recognized complex circuits in digital signal processing. Also, recent attention has been brought to reversible logic and quantum-dot cellular automata (QCA) because of their intrinsic capacity to decrease energy dissipation, which is a crucial need for low-power digital circuits. QCA will be the preferred technology for developing the subsequent generation of digital systems. These technologies played a substantial role in the design of the ALU for operations such as multiplication, subtraction, and division. In developing reversible logic and QCA technologies, the ALU is frequently studied as a central unit. Implementing an efficient ALU with low quantum cost and a small number of cells based on an efficient reversible block can solve all previous issues. Therefore, this research constructs a Feynman gate, a Fredkin gate, and full adder circuits using reversible logic and QCA technology. Using all of the specified circuits, a 20-operation ALU is constructed. The power consumption of the proposed ALU under various energy ranges demonstrated significant improvements over earlier designs.
Citation - WoS: 11
Citation - Scopus: 17
Mental Disorder and Suicidal Ideation Detection From Social Media Using Deep Neural Networks
(Springernature, 2024) Ezerceli, Ozay; Dehkharghani, Rahim
Depression and suicidal ideation are global reasons for life-threatening injury and death. Mental disorders have increased especially among young people in recent years, and early detection of those cases can prevent suicide attempts. Social media platforms provide users with an anonymous space to interact with others, making them a secure environment to discuss their mental disorders. This paper proposes a solution to detect depression/suicidal ideation using natural language processing and deep learning techniques. We used Transformers and a unique model to train the proposed model and applied it to three different datasets: SuicideDetection, CEASEv2.0, and SWMH. The proposed model is evaluated using the accuracy, precision, recall, and ROC curve. The proposed model outperforms the state-of-the-art in the SuicideDetection and CEASEv2.0 datasets, achieving F1 scores of 0.97 and 0.75, respectively. However, in the SWMH data set, the proposed model is 4% points behind the state-of-the-art precision providing the F1 score of 0.68. In the real world, this project could help psychologists in the early detection of depression and suicidal ideation for a more efficient treatment. The proposed model achieves state-of-the-art performance in two of the three datasets, so they could be used to develop a screening tool that could be used by mental health professionals or individuals to assess their own risk of suicide. This could lead to early intervention and treatment, which could save lives.
Citation - WoS: 2
Citation - Scopus: 2
A Novel Hybrid Coil Design and Implementation for Wireless Power Transfer Systems
(Edp Sciences S A, 2024) Pashaei, Ali; Aydin, Emrullah; Ozdemir, Mehmet Akif; Kosesoy, Yusuf; Aydemir, Mehmet Timur
Wireless Power Transfer (WPT) has been drawing a lot of attention in the last ten years parallel with the market increase in electric vehicles. Although conductive charging methods are still the preferred ones, WPT-based charging systems are used as clean and flexible alternatives. At the center of these systems are the transmitting and receiving coils, and different coil types have been proposed in the literature. This study proposes a square-hexagonal hybrid coil structure to increase magnetic coupling by shaping the magnetic field. In addition, this design aims to minimize the coupling coefficient variation for misaligned coils which is one of the most significant problems in WPT systems. A 3D model of the coils was created and analyzed using ANSYS, Maxwell software. Compared to the conventional square coil structure the coupling coefficient of the proposed structure is less affected by misalignment on the x and y axes, and as a result, it has a better efficiency. In addition, a WPT system operating at 50 W, 85-kHz is designed and tested in a laboratory environment. The FEA analyses and experimental application results largely overlap, and accordingly, the coil-to-coil efficiency of our WPT system was 93.5% and the overall efficiency of the system was 87%.
Citation - WoS: 12
Citation - Scopus: 12
Which Extraction Solvents and Methods Are More Effective in Terms of Chemical Composition and Biological Activity of Alcea Fasciculiflora From Turkey?
(Mdpi, 2022) Ozturk, Refiye Beyza; Zengin, Gokhan; Sinan, Kouadio Ibrahime; Montesano, Domenico; Zheleva-Dimitrova, Dimitrina; Gevrenova, Reneta; Uba, Abdullahi Ibrahim
The bioactive content, antioxidant properties, and enzyme inhibition properties of extracts of Alcea fasciculiflora from Turkey prepared with different solvents (water, methanol, ethyl acetate) and extraction methods (maceration, soxhlet, homogenizer assisted extraction, and ultrasound assisted extraction) were examined in this study. UHPLC-HRMS analysis detected or annotated a total of 50 compounds in A. fasciculiflora extracts, including 18 hydroxybenzoic and hydroxycinnamic acids, 7 Hexaric acids, 7 Coumarins, 15 Flavonoids, and 3 hydroxycinnamic acid amides. The extracts had phenolic and flavonoid levels ranging from 14.25 to 24.87 mg GAE/g and 1.68 to 25.26 mg RE/g, respectively, in the analysis. Both DPPH and ABTS tests revealed radical scavenging capabilities (between 2.63 and 35.33 mg TE/g and between 13.46 and 76.27 mg TE/g, respectively). The extracts had reducing properties (CUPRAC: 40.38-78 TE/g and FRAP: 17.51-42.58 TE/g). The extracts showed metal chelating activity (18.28-46.71 mg EDTAE/g) as well as total antioxidant capacity (phosphomolybdenum test) (0.90-2.12 mmol TE/g). DPPH, ABTS, FRAP, and metal chelating tests indicated the water extracts to be the best antioxidants, while the ethyl acetate extracts had the highest overall antioxidant capacity regardless of the extraction technique. Furthermore, anti-acetylcholinesterase activity was identified in all extracts (0.17-2.80 mg GALAE/g). The water extracts and the ultrasound-assisted ethyl acetate extract were inert against butyrylcholinesterase, but the other extracts showed anti-butyrylcholinesterase activity (1.17-5.80 mg GALAE/g). Tyrosine inhibitory action was identified in all extracts (1.79-58.93 mg KAE/g), with the most effective methanolic extracts. Only the ethyl acetate and methanolic extracts produced by maceration and homogenizer aided extraction showed glucosidase inhibition (0.11-1.11 mmol ACAE/g). These findings showed the overall bioactivity of the different extracts of A. fasciculiflora and provided an overview of the combination of solvent type and extraction method that could yield bioactive profile and pharmacological properties of interest and hence, could be a useful reference for future studies on this species.
Citation - WoS: 2
Citation - Scopus: 3
Seismic Assessment and Retrofit of Pre-Northridge High Rise Steel Moment Resisting Frame Buildings with Bilinear Oil Dampers
(Mdpi, 2023) Akcelyan, Sarven; Lignos, Dimitrios G.
This paper presents quantitative information on the effectiveness of seismic retrofit solutions using bilinear oil dampers for seismically deficient existing tall steel buildings. For this purpose, a benchmark 40-story steel space moment-resisting frame building is studied that represents 1970s design practice in North America. Rigorous seismic performance assessment based on ASCE 41 recommendations reveals a high collapse risk for the existing building. The local engineering demand parameters are comprehensively assessed to quantify the impact of seismic retrofit on steel columns and column splices, which are particularly vulnerable due to the time of construction. Multiple retrofit schemes are explored with numerous damping levels and vertical damping distribution methods. The dampers are designed via a recently developed multi-degree-of-freedom performance curves method. A new balanced vertical damping method is proposed to account for the effects of frame inelasticity. This strongly depends on the supplemental damping level, and it determines the effectiveness of the employed vertical damping distribution method. The results indicate that the proposed retrofit strategies can minimize the collapse risk of the tall building. It is shown that the balanced vertical damping distribution method provides the most uniform drift distribution along the building height. Despite the reduction in story drift ratios, the axial force demand in exterior columns remains relatively high in the bottom stories regardless of the seismic retrofit solution. On the other hand, bilinear oil dampers produce relative constant forces despite exhibiting higher velocity demands than expected.
Citation - WoS: 21
Citation - Scopus: 25
Posterior vitrectomy under topical anesthesia
(Elsevier, 2007) Bahçecioğlu, Halil Ibrahim; Ünal, Mustafa; Artunay, Özgür; Rasier, Rifat; Sarıcı, Ahmet Murat
Background: To determine the safety and efficacy of topical anesthesia in posterior vitrectomy. Methods: A total of 93 patients (93 eyes) with various vitreoretinal diseases not needing scleral buckling and with short predicted duration of surgery underwent posterior vitrectomy under topical (49 eyes) or retrobulbar (44 eyes) anesthesia. Patients in the topical group were sedated with neuroleptic anesthesia. Postoperatively patients were shown a visual analogue pain scale (VAPS) from 0 (no pain) to 10 (unbearable pain) to rate the levels of pain. The main outcome measures were overall and worst intraoperative pain scores duration of surgery and pain score during the administration of the retrobulbar anesthetic agent. Results: Mean surgical time was 57.9 minutes in the topical group and 56.6 minutes in the retrobulbar group (p > 0.05). The pain scores were not significantly different. Mean overall pain scores were 1.71 (SD 1.04 range 0-5) in the topical group and 1.38 (SD 1.04 range 0-3) in the retrobulbar group (p > 0.05). Mean worst pain scores were 3.20 (SD 1.30 range 1-7) and 2.95 (SD 0.73 range 1-4) respectively (p > 0.05). There was no significant correlation between duration of surgery and overall pain score in either group (r = 0.146 p = 0.356 and r = 0.174 p = 0.385 respectively). No patient required additional injection anesthesia in the topical group. Interpretation: Topical anesthesia combined with systemic sedation and analgesia in posterior vitrectomy procedures provided sufficient analgesic effects in selected patients needing no scleral buckling and with short predicted surgery time.
Citation - WoS: 22
Citation - Scopus: 25
Concept Selection With Hesitant Fuzzy Anp-Promethee Ii
(Taylor & Francis Ltd, 2021) Samanlıoğlu, Funda; Ayag, Zeki
An integrated approach is given for the assessment and ranking of concepts as part of the new product development (NPD) process. Selection of the best concept in NPD involves multiple criteria decision-making (MCDM) since there are numerous possibly competing criteria to consider. Here, hesitant fuzzy Analytic Network Process (H-F-ANP) and hesitant fuzzy Preference Ranking Organization Method for Enriching Evaluations II (H-F-PROMETHEE II) are integrated to assess the concepts and determine the best. In the hesitant fuzzy ANP-PROMETHEE II (H-F-ANP-PROMETHEE II), H-F-ANP is applied to calculate criteria weights, taking into consideration inner and outer dependence and feedback interactions between criteria and H-F-PROMETHEE II is implemented to rank concept alternatives, employing the calculated criteria weights. A demonstrative example is given where five concepts are evaluated by three decision makers (DMs) to exhibit the applicability. For comparison, H-F-ANP-VIKOR is utilized.
Citation - WoS: 16
Citation - Scopus: 20
Does Intuitive Mindset Influence Belief in God? a Registered Replication of Shenhav, Rand and Greene (2012)
(SOC Judgment & Decision Making, 2020) Sarıbay, S. Adil; Yılmaz, Onurcan; Körpe, Gülay Gözde
In 2012, two independent groups simultaneously demonstrated that intuitive mindset enhances belief in God. However, there is now some mixed evidence on both the effectiveness of manipulations used in these studies and the effect of mindset manipulation on belief in God. Thus, this proposal attempted to replicate one of those experiments (Shenhav, Rand & Greene, 2012) for the first time in a high-powered experiment using an under-represented population (Turkey). In line with the intuitive belief hypothesis, a negative correlation between reflectiveness and religious belief emerged, at least in one of the experimental conditions. In contrast to that hypothesis, however, the results revealed no effect of the cognitive style manipulation on religious belief. Although a self-report measure (Faith in Intuition) provided evidence that the manipulation worked as intended, it did not influence actual performance (Cognitive Reflection Test), suggesting a demand effect problem. Overall, the results failed to provide support for the intuitive belief hypothesis in our non-WEIRD sample, despite generally following the predicted patterns, and suggest that using stronger manipulation techniques are warranted in future studies.

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