PubMed İndeksli Yayınlar Koleksiyonu

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Citation - WoS: 2
Citation - Scopus: 6
A robotic system to prepare IV solutions
(Elsevier Ireland Ltd, 2018) Mehmet Suleyman Ünlütürk; Özgür Tamer; Semih Utku; Unluturk, Mehmet S.; Tamer, Ozgur; Utku, Semih
Drugs need to be used regularly and correctly in order to be effective. When medicines are used correctly negativities that threaten human health and life can be avoided but they can cause unwanted situations that can occur until the end of life when they are used incorrectly. The most common drug administration errors in hospitals are: The wrong dosage of the drug given to the patient the timing and / or the method of administration the wrong drug given to the patient the drug given to the wrong patient or even not given. Furthermore the information about the drug that is administered to the patient may not be registered at all. In this research a robotic drug preparation system and a communication server accepting prescription orders have been developed. Component engineering methodology is further utilized in the design of the Drug Preparation System to maximize reuse increase product reliability reduce design code and test efforts. The IV Robotic Drug Preparation Robot is composed of a robotic work station and a Cartesian carrier to carry the work station to the desired location. The robotic work station has several grippers to handle syringes to pull the piston of the syringe and to lock the closed system connector to the vial. The IV Robotic Drug Preparation System and communication server are developed and being used in the hospitals. Due to this system medicines left unused in vials can be used and a great amount of savings is obtained from the drug purchases. © 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 3
A stochastic approach for the assessment of suspended sediment concentration at the Upper Rhone River basin- Switzerland
(SPRINGER HEIDELBERG, 2022) Babak Vaheddoost; Saeed Vazifehkhah; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Vazifehkhah, Saeed; Safari, Mir Jafar Sadegh
This study addresses the link between suspended sediment concentration precipitation streamflow and direct runoff components. This is important since suspended sediment concentration in the streamflow has invaluable importance in the management of the river basin. For this the daily streamflow time series in five consecutive stations at Upper Rhone River Basin a relatively large basin in the Alpine region of Switzerland daily precipitation at one station and the twice a week suspended sediment concentration records at the most downstream station between January 1981 and October 2020 are used. Initially the base flow and the direct runoff associated with streamflow time series are obtained using the sliding interval method. Elasticity analyses between streamflow and suspended sediment concentration together with correlation autocorrelation partial autocorrelation stationarity and homogeneity are examined by the Augmented Dickey-Fuller and Pettitt's tests respectively. Then various stochastic scenarios are generated using the autoregressive moving average exogenous method (ARMAX). It is concluded that the precipitation and direct runoff have fewer effects on the suspended sediment concentration at downstream of the river. Hence the cumulative effect of the glacier or snowmelt and channel erosion may exceed the effect of rain blown washouts on the suspended sediment concentration at the Port du Scex station. It is found that the ARMAX model results are satisfactory and can be suggested for further application.
Citation - WoS: 1
Citation - Scopus: 2
Aggregation for Computing Multi-Modal Stationary Distributions in 1-D Gene Regulatory Networks
(IEEE COMPUTER SOC, 2018) Neslihan Avcu; Nihal Pekergin; Ferhan Pekergin; Cuneyt Guzelis; Pekergin, Nihal; Pekergin, Ferhan; Avcu, Neslihan; Guzelis, Cuneyt
This paper proposes aggregation-based three-stage algorithms to overcome the numerical problems encountered in computing stationary distributions and mean first passage times for multi-modal birth-death processes of large state space sizes. The considered birth-death processes which are defined by Chemical Master Equations are used in modeling stochastic behavior of gene regulatory networks. Computing stationary probabilities for a multi-modal distribution from Chemical Master Equations is subject to have numerical problems due to the probability values running out of the representation range of the standard programming languages with the increasing size of the state space. The aggregation is shown to provide a solution to this problem by analyzing first reduced size subsystems in isolation and then considering the transitions between these subsystems. The proposed algorithms are applied to study the bimodal behavior of the lac operon of E. coli described with a one-dimensional birth-death model. Thus the determination of the entire parameter range of bimodality for the stochastic model of lac operon is achieved.
Citation - Scopus: 2
Analysis of inoculation strategies during COVID-19 pandemic with an agent-based simulation approach
(Elsevier Ltd, 2025) Oray Kulaç; Ayhan Özgür Toy; Kamil Erkan Kabak; Toy, Ayhan Özgür; Kabak, Kamil Erkan; Kulaç, Oray
Background: The severity of recent Coronavirus (COVID-19) pandemics has revealed the importance of development of inoculation strategies in case of limited vaccine availability. Authorities have implemented inoculation strategies based on perceived risk factors such as age and existence of other chronic health conditions for survivability from the disease. However various other factors can be considered for identifying the preferred inoculation strategies depending on the vaccine availability and disease spread levels. This study explores the effectiveness of inoculating different groups of population in case of various vaccine availabilities and disease spread levels by means of some performance metrics namely: Attack Rate (AR) Death Rate (DR) and Hospitalization Rate (HR). Method: In this study we have implemented a highly detailed Agent-Based Simulation (ABS) model that extends classical SEIR Model by including five more additional states: Asymptomatic (A) Quarantine (Q) Hospitalized (H) Dead (D) and Immune (M) which can be used as a decision support tool to prioritize the groups of the population inoculated. The approach employs the modelling of daily mobility of individuals their interactions and transmission of virus among individuals. The population is heterogeneously clustered according to age family size work status transportation and leisure preferences with 17 different groups in order to find the most appropriate one to inoculate. Three different Disease Spread Levels (DSL) (low mid high) are experimented with four different Vaccine Available Percentages (VAP) (25% 50% 75% and 85%) with a total of 84 scenarios. Results: As the benchmark under the No Vaccine case Attack Rate Hospitalization Rate and Death Rate goes as high as 99.53% 16.96% and 1.38% respectively. Corresponding highest performance metrics (rates) are 72.33% 15.95% and 1.35% for VAP = 25%, 50.25% 9.55% and 0.94% for VAP = 50%, 24.53% 2.62% and 0.25% for VAP = 75%, and 11.51% 0.002% and 0.08% for VAP = 85%. The results of our study shows that the common practice of inoculation based on the age of individual does not yield the best outcome in terms of performance metrics across all DSL and VAP values. The groups containing workers and students that represent highly interactive individuals i.e. Group (9 10) Group (9 11 10‾) and Group (9 10 11 12‾) emerge as a commonly recommended choice for inoculation in the majority of cases. As expected we observe that the higher is the VAP levels the more is the number of alternative inoculation groups. Conclusions: Findings of this study present that: (i) inoculation considerably decreases the number of infected individuals the number of deaths and the number of hospitalized individuals due to the disease (ii) the best inoculation group/groups with respect to performance metrics varies depending on the vaccine availability percentages and disease spread levels (iii) simultaneous implementation of both inoculation and precautions like lock-down social distances and quarantines yields a stronger impact on disease spread and its consequences. © 2025 Elsevier B.V. All rights reserved.
Citation - WoS: 15
Citation - Scopus: 14
Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease
(John Wiley and Sons Ltd, 2014) Fatih Şendaǧ; Burak Zeybek; Ali Osman Akdemir; Banu Ozgurel; Kemal Öztekin; Akdemir, Ali; Ozgurel, Banu; Oztekin, Kemal; Zeybek, Burak; Sendag, Fatih
Background: The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease. Methods: Thirty-six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age BMI operating time set-up time docking time uterine weight blood loss intraoperative complications postoperative complications conversions to laparotomy and length of hospital stay. Results: The mean operating set-up and docking times were 169±54.5 52.9±12.4 and 7.8±7.6min respectively. The learning curve analysis revealed a decrease in both docking and operating times with both curves plateauing after case 9. Conclusions: The learning curve analysis revealed a decrease in docking time and operating time after case 9 suggesting that there might be a fast learning curve for experienced laparoscopic surgeons to master robotic hysterectomy and that the docking process does not have a significant negative influence on the overall operating time. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 10
Automated personnel-assets-consumables-drug tracking in ambulance services for more effective and efficient medical emergency interventions
(ELSEVIER IRELAND LTD, 2016) Semih Utku; Mehmet Hilal Ozcanhan; Mehmet Suleyman Unluturk; Unluturk, Mehmet Suleyman; Utku, Semih; Özcanhan, Mehmet Hilal
Patient delivery time is no longer considered as the only critical factor in ambulatory services. Presently five clinical performance indicators are used to decide patient satisfaction. Unfortunately the emergency ambulance services in rapidly growing metropolitan areas do not meet current satisfaction expectations, because of human errors in the management of the objects onboard the ambulances. But human involvement in the information management of emergency interventions can be reduced by electronic tracking of personnel assets consumables and drugs (PACD) carried in the ambulances. Electronic tracking needs the support of automation software which should be integrated to the overall hospital information system. Our work presents a complete solution based on a centralized database supported by radio frequency identification (RFID) and bluetooth low energy (BLE) identification and tracking technologies. Each object in an ambulance is identified and tracked by the best suited technology. The automated identification and tracking reduces manual paper documentation and frees the personnel to better focus on medical activities. The presence and amounts of the PACD are automatically monitored warning about their depletion non-presence or maintenance dates. The computerized two way hospital-ambulance communication link provides information sharing and instantaneous feedback for better and faster diagnosis decisions. A fully implemented system is presented with detailed hardware and software descriptions. The benefits and the clinical outcomes of the proposed system are discussed which lead to improved personnel efficiency and more effective interventions. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
BUYER SELLER NEGOTIATIONS: A COMPARISON OF DOMESTIC AND INTERNATIONAL CONDITIONS IN A PILOT STUDY WITH INTERNATIONAL BUSINESS STUDENTS
(SAGE PUBLICATIONS INC, 2010) Guelcimen Yurtsever; Gizem Kurt; Gungor Hacioglu; Hacioglu, Gungor; Yurtsever, Guelcimen; Kurt, Gizem
This study examined the differences and similarities between domestic and international negotiations using Kelley's Negotiation Game to measure the profit achieved. There were 58 participants in the international negotiation sample 29 Turkish and 29 European students. There were 62 Turkish students in the domestic negotiations. All participants studied business or related topics at a university in Izmir. Student t tests indicated statistically significant differences in scores on misrepresentation of information interpersonal attraction peer evaluation of misrepresentation information and satisfaction between domestic and international negotiations.
Citation - WoS: 6
Citation - Scopus: 6
Child Abuse and Neglect Among Children Who Drop Out of School: A Study in Izmir- Turkey
(ROUTLEDGE JOURNALS TAYLOR & FRANCIS LTD, 2016) Zeynep Sofuoglu; Gorkem Sariyer; Fulya Aydin; Sinem Cankardas; Birsu Kandemirci; Sariyer, Görkem; Aydin, Fulya; Cankardeş, Sinem; Cankardas, Sinem; Sofuoğlu, Zeynep; Kandemirci, Birsu
Child abuse and neglect (CAN) and dropping out of school have long been recognized as pervasive social problems globally and Turkey is no exception. This study aims to explore the prevalence and incidence of CAN in children who drop out of school of Turkey using the ISPCAN Child abuse Screening Tool Children's Version which is an appropriate tool for multinational comparisons. Data from a convenience sample of children who drop out of school age 11 13 and 16 from Izmir were collected either by interviews or by self-completion. The results show that compared to children who do not drop out of school children who drop out of school have higher rates of psychological and physical abuse and neglect within the family. This study not only highlights the need for preventive laws for CAN and dropping out of school but also points to direction for future research.
Citation - WoS: 29
Citation - Scopus: 33
Circular dairy supply chain management through Internet of Things-enabled technologies
(Springer Science and Business Media Deutschland GmbH, 2022) Yigit Kazancoglu; Melisa Ozbiltekin-Pala; Muruvvet Deniz Sezer; Anil Kumar; Sunil Luthra; Ozbiltekin-Pala, Melisa; Sezer, Muruvvet Deniz; Kumar, Anil; Luthra, Sunil; Kazancoglu, Yigit
Internet of Things-enabled technologies help to collect data and make it understandable especially in supply chain processes thus minimizing the problems that may arise in supply chains. It is extremely important to support this process with Internet of Things-enabled technologies especially in supply chains that are vulnerable to disruptions such as the dairy supply chain. Moreover dairy supply chains are the type of supply chains where the most waste is generated, evaluating this waste is very beneficial to the circular economy. Therefore monitoring data in dairy supply chains and using Internet of Things-enabled technologies prevent losses, it is critical to have Internet of Things-enabled circular dairy supply chains in operation. The aim of this study is to determine the success factors of Internet of Things-enabled circular dairy supply chains based on the various stages of these chains, we hope to match each dairy supply chain stage with a success factor of Internet of Things-enabled technology and determine a ranking for these factors. Hence six success factors of Internet of Things-enabled circular supply chains are weighted for each stage of the chain, Internet of Things-enabled digital technologies are then matched with each stage of the chain and the success factor is determined. The ranking of factors can then be drawn up through the integration of Step Wise Weight Assessment Ratio Analysis (SWARA) and Technique for Order Preference Similar to Ideal Solution (TOPSIS). The outcome of this study will provide managers and policy makers with insights into Internet of Things-enabled circular dairy supply chains. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 45
Citation - Scopus: 50
Classification of EEG recordings by using fast independent component analysis and artificial neural network
(Springer, 2008) Yücel Koçyig̃it; Ahmet Alkan; Halil Erol; Alkan, Ahmet; Kocyigit, Yucel; Erol, Halil
Since there is no definite decisive factor evaluated by the experts visual analysis of EEG signals in time domain may be inadequate. Routine clinical diagnosis requests to analysis of EEG signals. Therefore a number of automation and computer techniques have been used for this aim. In this study we aim at designing a MLPNN classifier based on the Fast ICA that accurately identifies whether the associated subject is normal or epileptic. By analyzing a data set consisting of 100 normal and 100 epileptic EEG time series we have found that the MLPNN classifier based on the Fast ICA achieved and sensitivity rate of 98% and specificity rate of 90.5%. The results demonstrate that the testing performance of the neural network diagnostic system is found to be satisfactory and we think that this system can be used in clinical studies. Since the time series analysis of EEG signals is unsatisfactory and requires specialist clinicians to evaluate this application brings objectivity to the evaluation of EEG signals. © 2007 Springer Science+Business Media LLC. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Citation - Scopus: 71
Comparison of AR and Welch methods in epileptic seizure detection
(2006) Ahmet Alkan; Mahmut Kemal Kıymık; Alkan, Ahmet; Kiymik, M. Kemal
Brain is one of the most critical organs of the body. Synchronous neuronal discharges generate rhythmic potential fluctuations which can be recorded from the scalp through electroencephalography. The electroencephalogram (EEG) can be roughly defined as the mean electrical activity measured at different sites of the head. EEG patterns correlated with normal functions and diseases of the central nervous system. In this study EEG signals were analyzed by using autoregressive (parametric) and Welch (non-parametric) spectral estimation methods. The parameters of autoregressive (AR) method were estimated by using Yule-Walker covariance and modified covariance methods. EEG spectra were then used to compare the applied estimation methods in terms of their frequency resolution and the effects in determination of spectral components. The variations in the shape of the EEG power spectra were examined in order to epileptic seizures detection. Performance of the proposed methods was evaluated by means of power spectral densities (PSDs). Graphical results comparing the performance of the proposed methods with that of Welch technique were given. The results demonstrate consistently superior performance of the covariance methods over Yule-Walker AR and Welch methods. © 2006 Springer Science+Business Media Inc. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Citation - WoS: 5
Citation - Scopus: 4
Computer based classification of MR scans in first time applicant Alzheimer patients
(Bentham Science Publ Ltd, 2012) Fatma Eksi Polat; Selçuk Orhan Demirel; Ömer Kitiş; Fatma Şimşek; Damla İşman Haznedaroǧlu; Kerry Lee Coburn; Emre Kumral; Ali Saffet Gönül; Simsek, Fatma; Kitis, Omer; Demirel, Selcuk Orhan; Gonul, Ali Saffet; Haznedaroglu, Damla Isman; Coburn, Kerry; Polat, Fatma
In this study we aimed to classify MR images for recognizing Alzheimer Disease (AD) in a group of patients who were recently diagnosed by clinical history and neuropsychiatric exams by using non-biased machine-learning techniques. T1 weighted MRI scans of 31 patients with probable AD and 31 age- and gender-matched cognitively normal elderly were analyzed with voxel-based morphometry and classified by support vector machine (SVM) a machine learning technique. SVM could differentiate patients from controls with accuracy of 74 % (sensitivity: 70 % and specificity: 77 %) when the whole brain was included the analyses. The classification accuracy was increased to 79 % (sensitivity: 65 % and specificity: 93 %) when the analyses restricted to hippocampus. Our results showed that SVM is a promising tool for diagnosis of AD but needed to be improved. © 2012 Bentham Science Publishers. © 2013 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Citation - WoS: 54
Citation - Scopus: 65
Cultural Bases for Self-Evaluation: Seeing Oneself Positively in Different Cultural Contexts
(SAGE Publications Inc. claims@sagepub.com, 2014) Maja Becker; Vivian L. Vignoles; Ellinor Owe; Matthew J. Easterbrook; Rupert James Brown; Peter Bevington Smith; Michael Harris Bond; Camillo Regalia; Claudia Manzi; Maria Brambilla; Easterbrook, Matthew J.; Vignoles, Vivian L.; Koller, Silvia H.; Brown, Rupert; Owe, Ellinor; Smith, Peter B.; Becker, Maja
Several theories propose that self-esteem or positive self-regard results from fulfilling the value priorities of one's surrounding culture. Yet surprisingly little evidence exists for this assertion and theories differ about whether individuals must personally endorse the value priorities involved. We compared the influence of four bases for self-evaluation (controlling one's life doing one's duty benefitting others achieving social status) among 4852 adolescents across 20 cultural samples using an implicit within-person measurement technique to avoid cultural response biases. Cross-sectional and longitudinal analyses showed that participants generally derived feelings of self-esteem from all four bases but especially from those that were most consistent with the value priorities of others in their cultural context. Multilevel analyses confirmed that the bases of positive self-regard are sustained collectively: They are predictably moderated by culturally normative values but show little systematic variation with personally endorsed values. © 2014 by the Society for Personality and Social Psychology Inc. © 2019 Elsevier B.V. All rights reserved.
Citation - WoS: 30
Citation - Scopus: 35
Determining a continuous marker for sleep depth
(Pergamon-Elsevier Science Ltd, 2007) Musa Hakan Asyali; Richard Barnett Berry; Michael C.K. Khoo; Ayşe Asyali Altinok; Khoo, Michael C.K.; Asyali, Musa H.; Berry, Richard B.; Altinok, Ayse
Detection and quantification of sleep arousals is an important issue as the frequent arousals are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep staging electroencephalograph (EEG) is the core signal and based on the visual inspection of the frequency content of EEG non-rapid eye movement sleep is staged into four somewhat rough categories. In this study we aimed at developing a continuous marker based on a more rigorous spectral analysis of EEG to measure or quantify the depth of sleep. In order to develop such a marker we obtained the time-frequency map of two EEG channels around sleep arousals and identified the frequency bands that show the most change during arousals. We then evaluated classification performance of the potential signals for representing the depth of sleep using receiver operating characteristic analysis. Our comparisons based on the area under the curve values revealed that the sum of absolute powers in alpha and beta bands is a good continuous marker to represent the depth of sleep. Higher values of this marker indicate low-quality sleep and vice versa. We believe that use of this marker will lead to a better quantification of sleep quality. © 2007. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Citation - WoS: 4
Citation - Scopus: 7
Drivers for circular economy development: making businesses more environmentally friendly
(SPRINGER HEIDELBERG, 2023) Antonio Eiti Kurita; Maximilian Espuny; Thalita Laua Reis Campos; Yigit Kazancoglu; Jayakrishna Kandsamy; Otavio Jose de Oliveira; Campos, Thalita Láua Reis; Kandsamy, Jayakrishna; Kurita, Antonio Eiti; Espuny, Maximilian; de Oliveira, Otávio José; Kazançoğlu, Yiğit
Stakeholders have been pressuring companies to develop more environmentally friendly strategic and operational solutions. In this sense companies are seeking alternatives that reduce the negative impacts of organizational activities Circular Economy (CE) is one of the solutions with the greatest potential for success. Thus the goal of this paper is to provide drivers for organizations' transition from a linear to a CE. For this reason content analysis was used as the scientific method for being appropriate for the interpretation of qualitative data and the identification clustering and systematization of themes in a given field of knowledge. In the case of this work a set of 30 articles with information related to the implementation and development of CE were analyzed allowing the identification of 19 key elements of CE. These key elements were then grouped and systematized into four drivers: decision-making, capacity and training, sustainable practices, and green supply chain. Scientifically this work contributes to the improvement and increase of the block of knowledge about the CE because the drivers can be used to advance the state of the art and as a starting point for the development of new research. In an applied way the drivers proposed in this article provide a range of actions for managers to make their companies greener and improve their organizational performance thus contributing environmentally and socially to the planet.
Citation - WoS: 2
Citation - Scopus: 1
Effect of AI-Related Patents, Energy Transition, Environmental Policy Stringency, Income, and Energy Consumption Sub-Types on the Environmental Sustainability: Evidence from China by KRLS Approach
(Academic Press Ltd- Elsevier Science Ltd, 2025) Taşkın, Dilvin; Kim, Eonsoo; Mukhtarov, Shahriyar; Kirikkaleli, Derviş; Kılıç Depren, Serpil; Park, Jinsu; Depren, Serpil Kilic; Kartal, Mustafa Tevfik
Due to the increasing negative effects on humanity, searching for potential solutions to combat environmental problems has been developing. Accordingly, the study examines the effect of a set of critical factors on environmental sustainability (ES) proxied by ecological footprint (EFP) and load capacity factor (LCF) in China. In this context, the study considers AI-related patents, energy transition, environmental policy stringency (EPS), income, and energy consumption (EC) sub-types and applies the Kernel Regularized Least Squares (KRLS) approach on data from 2000 to 2020 within the context of marginal effect analysis. The outcomes show that (i) AI-related patents and energy transition are completely ineffective to ensure ES; (ii) EPS are marginally effective only at 0.25th and 0.75th percentiles to support ES; (iii) economic growth as well as oil, gas, and coal EC are not good for ES across all percentiles; (iv) nuclear EC is only helpful at 0.25th percentiles, whereas renewable EC is completely unbeneficial; (v) KRLS approach presents successful prediction outcomes around 99.7 % (vi) some variables (i.e., nuclear and renewable EC as well as EPS); have marginal and varying effects across percentiles, whereas some others have not. Thus, the study empirically demonstrates the inefficiency of AI-related patents and energy transition on the ES, whereas EPS and nuclear EC can be helpful to develop ES in the Chinese case.
Citation - WoS: 12
Citation - Scopus: 13
Effect of Aldehyde and Carboxyl Functionalities on the Surface Chemistry of Biomass-Derived Molecules
(American Chemical Society service@acs.org, 2017) Başar Ca̧ǧlar; J. W.Hans Niemantsverdriet; C. J. Weststrate; Weststrate, C.J.; Caglar, Basar; Niemantsverdriet, J.W.
The adsorption and decomposition of acetaldehyde and acetic acid were studied on Rh(100) to gain insight into the interaction of aldehyde and carboxyl groups of biomass-derived molecules with the surface. Temperature-programmed reaction spectroscopy (TPRS) was used to monitor gaseous reaction products whereas Reflection absorption infrared spectroscopy (RAIRS) was used to determine the nature of surface intermediates and reaction paths. The role of adsorbate interactions in oxygenate decomposition chemistry was also investigated by varying the surface coverage. Acetaldehyde adsorbs in an η2(C O) configuration for all coverages where the carbonyl group binds to the surface via the C and O atoms. Decomposition occurs below room temperature (180-280 K) via C-H and C-C bond breaking which releases CO H and CHx species on the surface. At low coverage CHx dehydrogenation dominates and surface carbon is produced alongside H2 and CO. At high coverage about 60% of the CHx hydrogenates to form methane whereas only 40% of the CHx decomposes further to surface carbon. Acetic acid adsorbs dissociatively on the Rh(100) surface via O-H bond scission forming a mixture of mono- and bidentate acetate. The decomposition of acetate proceeds via two different pathways: (i) deoxygenation via C-O and C-C bond scissions and (ii) decarboxylation via C-C bond scission. At low coverage the decarboxylation pathway dominates a process that occurs at slightly above room temperature (280-360 K) and produces CO2 and CHx where the latter decomposes further to surface carbon and H2. At high coverage both decarboxylation and deoxygenation occur slightly above room temperature (280-360 K). The resulting O adatoms produced in the deoxygenation path react with surface hydrogen or CO to form water and CO2 respectively. The CHx species dehydrogenate to surface carbon for all coverages. Our findings suggest that oxygenates with a C=O functionality and an alkyl end react on the Rh(100) surface to produce synthesis gas and small hydrocarbons whereas CO2 and synthesis gas are produced when oxygenates with a COOH functionality and an alkyl end react with the Rh(100) surface. For both cases carbon accumulation occurs on the surface. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Effective health communication depends on the interaction of message source and content: two experiments on adherence to COVID-19 measures in Türkiye
(TAYLOR & FRANCIS LTD, 2024) Fatih Bayrak; Bengi Aktar; Berke Aydas; Onurcan Yilmaz; Sinan Alper; Ozan Isler; Aydas, Berke; Isler, Ozan; Aktar, Bengi; Yilmaz, Onurcan; Alper, Sinan; Bayrak, Fatih
ObjectiveFollowing the COVID-19 outbreak authorities recommended preventive measures to reduce infection rates. However adherence to calls varied between individuals and across cultures. To determine the characteristics of effective health communication we investigated three key features: message source content and audience.MethodsUsing a pre-test and two experiments we tested how message content (emphasizing personal or social benefit) audience (individual differences) message source (scientists or state officials) and their interaction influence adherence to preventive measures. Using fliers advocating preventive measures Experiment 1 investigated the effects of message content and examined the moderator role of individual differences. Experiment 2 presented the messages using news articles and manipulated sources.ResultsStudy 1 found decreasing adherence over time with no significant impact from message content or individual differences. Study 2 found messages emphasizing 'protect yourself' and 'protect your country' to increase intentions for adherence to preventive measures. It also revealed an interaction between message source and content whereby messages emphasizing personal benefit were more effective when they came from healthcare professionals than from state officials. However message source and content did not affect vaccination intentions or donations for vaccine research.ConclusionEffective health communication requires simultaneous consideration of message source and content.
Citation - WoS: 31
Citation - Scopus: 42
Effects of Environment Social and Governance (ESG)disclosures on ESGscores: Investigating therole ofcorporategovernance forpubliclytraded Turkishcompanies
(Academic Press, 2024) Mustafa Tevfik Kartal; Dilvin Taşkın; Muhammad Shahbaz; Serpil Kılıç Depren; Ugur Korkut Pata; Taşkın, Dilvin; Korkut Pata, Ugur; Pata, Ugur Korkut; Kılıç Depren, Serpil; Shahbaz, Muhammad; Depren, Serpil Kilic; Kartal, Mustafa Tevfik
The world has experienced climate-related issues which increase the importance of ESG disclosures and corporate governance (CG) of companies which take place at the heart of economies. Therefore improving ESG disclosures and CG practices becomes significant to combat climate change at the company level. Considering that Türkiye restructured ESG disclosures in 2022 this study investigates the role of CG on the nexus between ESG scores of publicly traded companies (PTC) and ESG reports. So the study analyzes 102 PTC (full sample) 51 PTC in Borsa Istanbul Corporate Governance Index (in-sample) and the remaining 51 PTC (out-sample) using ESG disclosures of 2022 and applying novel super learner (SL) algorithm. Our results show that (i) SL has a higher prediction performance reaching ∼94.3%, (ii) the environment (governance) layer has the highest (lowest) total relative importance (contribution) to ESG scores in all samples, (iii) C8 S6 and E5 are the most important ESG principles in the full sample in-sample and out-sample respectively, (iv) the contribution of each ESG principles to the total ESG scores varies by sample, (v) CG plays a smoothing role for the relative importance of each ESG principle while the relative importance in the out-sample shows much higher volatility. Overall the study reveals the non-linear contributions of ESG principles on ESG scores and suggests that PTC should prioritize highly important ESG principles consider the moderating role of CG on the link between ESG scores and ESG disclosures and use ESG disclosures as a strategic tool to develop ESG scores and disclosures. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Effects of Pre and Post-Rigor Marinade Injection on Some Quality Parameters of Longissimus Dorsi Muscles
(KOREAN SOC FOOD SCIENCE ANIMAL RESOURCES, 2018) Eylem Ezgi Fadiloglu; Meltem Serdaroglu; Fadiloglu, Eylem Ezgi; Serdaroglu, Meltem
This study was conducted to evaluate the effects of pre and post-rigor marinade injections on some quality parameters of Longissimus dorsi (LD) muscles. Three marinade formulations were prepared with 2% NaC1 2% NaC1+0.5 M lactic acid and 2% NaC1+0.5 M sodium lactate. In this study marinade uptake pH free water cooking loss drip loss and color properties were analyzed. Injection time had significant effect on marinade uptake levels of samples. Regardless of marinate formulation marinade uptake of pre-rigor samples injected with marinade solutions were higher than post rigor samples. Injection of sodium lactate increased pH values of samples whereas lactic acid injection decreased pH. Marinade treatment and storage period had significant effect on cooking loss. At each evaluation period interaction between marinade treatment and injection time showed different effect on free water content. Storage period and marinade application had significant effect on drip loss values. Drip loss in all samples increased during the storage. During all storage days lowest CIE L* value was found in pre-rigor samples injected with sodium lactate. Lactic acid injection caused color fade in pre-rigor and post-rigor samples. Interaction between marinade treatment and storage period was found statistically significant (p < 0.05). At day 0 and 3 the lowest CIE b* values obtained pre-rigor samples injected with sodium lactate and there were no differences were found in other samples. At day 6 no significant differences were found in CIE b* values of all samples.

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