Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Kaygusuz, Abdullah(35)
- Sipahi, Ferkan(35)
- Karsli, Orhan(34)
- Dokuz, Abdurrahman(30)
- Duran, Celal(30)
- Kandemir, Raif(29)
- Ozdes, Duygu(28)
- Maden, Nafiz(27)
- Uzun, Sevda(27)
- Merdan, Mehmet(26)
- Vural, Alaaddin(26)
- Öztürk, Serkan(25)
- Araz, Onur(24)
- Kulakaç, Nurşen(24)
- Ashyralyyev, Charyyar(23)
- Yildiz, Salih(23)
- Yilmaz, Ozgur(23)
- Doğan, Kadir Caner(21)
- Arslan, Mehmet(20)
- Aydin, Faruk(20)
- Doğru, Bülent(20)
- Bayraktar, Alemdar(19)
- Kankal, Murat(19)
- Ayaydin, Hasan(18)
- Baltaci, Cemalettin(18)
- Yolcu, Halil(18)
- Cakir, Tufan(17)
- Cengiz, Ekrem(17)
- Demir, Selim(17)
- Gücer, Mehmet Ali(17)
- Akaryali, Enver(16)
- Artan, Seyfettin(16)
- Hayaloğlu, Pınar(16)
- Kaya, Afşin Ahmet(16)
- Tosunoğlu, Büşra(16)
- Uysal, Ibrahim(16)
- Kurt, Kemal(15)
- Ozturk, Samet(15)
- Reis, Hatice Catal(15)
- Aksakal, Vecihi(14)
Yayınlar
- MakaleYalnız künye2024Scopus SJRQ3Assessment of Anticholinergic and Antidiabetic Properties of Some Natural and Synthetic Molecules: An In Vitro and In Silico Approach
Çomaklı, Veysel; Aygül, İmdat; Sağlamtaş, Rüya; Kuzu, Müslüm; Demirdağ, Ramazan; Akincioğlu, Hülya; Adem, Şevki; Gülçin, İlhami
Introduction: This study aimed to determine the in vitro and in silico effects of some natural and synthetic molecules on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and α-glucosidase enzymes. Background: Alzheimer's disease (AD) and Type II diabetes mellitus (T2DM) are considered the most important diseases of today’s world. However, the side effects of therapeutic agents used in both diseases limit their use. Therefore, developing drugs with high therapeutic efficacy and better pharmacological profile is important. Objectives: This study sets out to determine the related enzyme inhibitors used in treating AD and T2DM, considered amongst the most important diseases of today’s world. Methods: In the current study, the in vitro and in silico effects of dienestrol, hesperetin, L-thyroxine, 3,3',5-Triiodo-L-thyronine (T3) and dobutamine molecules on AChE, BChE and α-glycosidase enzyme activities were investigated. Results: All the molecules showed an inhibitory effect on the enzymes. The IC50 and Ki values of the L-Thyroxine molecule, which showed the strongest inhibition effect for the AChE enzyme, were determined as 1.71 µM and 0.83 ± 0.195 µM, respectively. In addition, dienestrol, T3, and dobutamine molecules showed a more substantial inhibition effect than tacrine. The dobutamine molecule showed the most substantial inhibition effect for the BChE enzyme, and IC50 and Ki values were determined as 1.83 µM and 0.845 ± 0.143 µM, respectively. The IC50 and Ki values for the hesperetin molecule, which showed the strongest inhibition for the α-glycosidase enzyme, were determined as 13.57 µM and 12.33 ± 2.57 µM, respectively. Conclusion: According to the results obtained, the molecules used in the study may be considered potential inhibitor candidates for AChE, BChE and α-glycosidase.
AtıfScopus8WoS7OpenAlex8
İncele - MakaleYalnız künye2024Scopus SJRQ1Comparison of histogram-curve fitting-based and global threshold methods for cloud detection
Günen, M. Akif
The goal of this research is fit the best curve to the image histogram using polynomial (i.e., linear, quadratic, cubic, and quartic), Fourier and Gaussian with two different term numbers, and Bezier functions, and then compare their performance with nine automatic state-of-the-art thresholding methods: Shanbhag, Triangle, Huang, Intermode, IsoData, Li's, Maximum entropy, Moment, and Otsu. The visible bands of the Landsat-9, Landsat-8, and Sentinel 2 satellite images are averaged to create an index map, which was used to perform the cloud detection. Since many satellites system only has visible bands, the average index map was used. Three different images which include various cloud types were clipped from each satellite imaging. Thresholding methods were evaluated using statistical tools such as structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and universal image quality index (UIQI), accuracy, Cohen's kappa, precision, recall, F-Measure, and G-Mean. The histogram-based approaches that performed the best after Li's method were Bezier (96.71% accuracy and 99.83% SSIM), 2nd Gaussian (97.62% precision), Quartic (80.56% kappa, 16.16% PSNR, 82.45% F-Measure, and 89.52%), and 2nd Fourier (81.08% recall and 89.27% G-Mean), according to the average statistics of all images. Additionally, methods other than Shanbhag yielded favorable results (more than 90% accuracy).
AtıfScopus19WoS16OpenAlex19İncele - MakaleYalnız künye2024Scopus SJRQ2The Impact of Video-Based Simulation Training on Perioperative Process in Nursing Students: A Randomized Controlled Study
Kulakaç, Nurşen; Koçan, Sema; Aktuğ, Cemile
This study was conducted to explore the effect of video-based simulation training on postoperative patient care, clinical decision-making, and the competency levels of nursing students. The study was conducted as a randomized controlled trial. The sample of the study consisted of students (n=87) attending the nursing department of the health sciences faculty of a state university located in the Eastern Black Sea Region of Turkey. The data were collected with the “Student Information Form”, the “Postoperative Patient Care Knowledge Test”, the “Clinical Decision-Making in Nursing Scale (CDMNS)”, and the “Competency Inventory of Nursing Students (CINS)”. The postoperative patient care knowledge test scores of the experimental group students were statistically significantly higher than those of the control group (p<0.001). The CDMNS scores of the experimental group students were statistically significantly higher than those of the control group (p=0.024). There was no statistically significant difference between the CINS scores of the experimental and control groups. The results showed that the use of video simulation contributed positively to students' postoperative patient care and clinical decision-making.
AtıfScopus6WoS6OpenAlex7İncele - Kitap BölümüYalnız künye2024Behavioral economics and Monetary Wisdom across 32 cultures: Good apples enjoy a good quality of life in good barrels
Tang, Thomas Li-Ping; Sutarso, Toto; Ansari, Mahfooz A.; Lim, Vivien Kim Geok; Teo, Thompson Sian Hin; Arias-Galicia, Fernando; Garber, Ilya E.; Chiu, Randy Ki-Kwan; Charles-Pauvers, Brigitte; Luna-Arocas, Roberto
Monetary Wisdom asserts that individuals apply their deep-rooted values (ardent monetary aspirations) to frame critical concerns in the immediate-proximal and omnibus-distal contexts and strategically maximize expected utility (achieve financial goals) and ultimate serenity (happiness). This study explores the bright side of Monetary Wisdom and behavioral economics, frames money attitude in the context of pay and life satisfaction, and controls money at the micro and individual level (Z income within each country) and the macro and national and global level (GDP per capita). We theorize: Managers with low love of money motive but high stewardship behavior will have high subjective well-being: pay satisfaction and quality of life. Data collected from 6586 managers in 32 cultures across 6 continents support our theory. Interestingly, GDP per capita is related to life satisfaction, but not to pay satisfaction. Individual income is related to both life and pay satisfaction. Neither GDP nor income is related to the Happiness construct (money makes people happy). For the whole sample, low motives, high stewardship behaviors, and high cognitions identify the latent Monetary Wisdom (MW), which, in turn, leads to higher pay satisfaction than life satisfaction. Results of our formative model challenge the notion that motives and cognitions are consistent in predict outcomes. Our theoretical model across three GDP groups (high, medium, and low GDP levels) offers additional innovative discoveries: In high GDP (rich) entities, “high income” not only reduces aspirations—“Rich, Motivator, and Power,” but also promotes stewardship behavior—“Factors Budget, Give/Donate, and Contribute” and cognitive meaning, “Factor Achievement.” After controlling income, we demonstrate the bright side of Monetary Wisdom: Low love of money motive but high stewardship behavior define Monetary Wisdom, which contributes to higher life satisfaction than pay satisfaction. “Good apples enjoy a good quality of life in good barrels”. This notion adds another explanation to managers’ low magnitude of dishonesty in entities with high Corruption Perceptions Index (CPI) (risk aversion for gains in the high probability context). In medium GDP countries, high income is negatively related to Factors Motivator (motive), Budget (behavior), and Power (cognition). Managers enjoy higher life satisfaction than pay satisfaction. However, in low GDP (poor) entities, high income is related to poor Budgeting skills and escalated Happiness. Interestingly, income leads to the notion of high Happiness (cognition) for managers in low GDP countries only. Managers experience equal satisfaction with pay and life. Results of Monetary Wisdom add a new vocabulary to the conversation of monetary aspirations, intelligence, income, GDP, happiness, subjective well-being, good and bad apples, good and bad barrels, corruption, and behavioral ethics.
- MakaleYalnız künye2024Scopus SJRQ3Development of a New and Facile Carrier Element-Free Coprecipitation Procedure for Separation, Preconcentration and Sensitive Determination of Cu(II) and Cd(II) Ions in Water and Vegetable Samples
Duran, Celal; Ozdes, Duygu; Mentese, Emre; Bektas, Hakan
A facile and sensitive method predicated on carrier element free coprecipitation (CEFC) using 2-(2-(2-(4-bromobenzyl)-1H-benzo[d]imidazole-1-yl)acetyl)-N-ethylhydrazine-1-carbothioamide (BIMANEC) is reported for trace determination of Cu(II) and Cd(II) in vegetables and water. BIMANEC was used for the first time for the quantitative determination of these trace heavy metals. Flame atomic absorption spectrometer (FAAS) was used for quantitation. The preconcentration conditions were optimized with respect to pH (8.0), BIMANEC mass (4.0 mg), volume of sample (100 mL), standing time (5 min), and centrifugation time and rate (3 min and 2500 rpm). The influence of potentially interfering ions was scrutinized for the recovery of analyte ions. Under the optimum conditions, the limits of detection (LODs) were 0.51 and 2.28 µg L−1 for Cu(II) and Cd(II), respectively. The relative standard deviations were < 5% for both. The recoveries from the spiked vegetable samples were from 94.9 to 102.8% and from the spiked water samples between 93.2 and 101.6%. Consequently the developed new, facile, rapid, and highly efficient CEFC process was employed for the trace determination of Cu(II) and Cd(II).
AtıfScopus6WoS8OpenAlex7İncele - Kitap BölümüYalnız künye2024Behavioral economics and Monetary Wisdom: The Enron Effect—Love of money, Corporate Ethical Values, Corruption Perceptions Index (CPI), and dishonesty across 31 geopolitical entities
Tang, Thomas Li-Ping; Sutarso, Toto; Ansari, Mahfooz A.; Lim, Vivien Kim Geok; Teo, Thompson Sian Hin; Arias-Galicia, Fernando; Garber, Ilya E.; Chiu, Randy Ki-Kwan; Charles-Pauvers, Brigitte; Luna-Arocas, Roberto
Monetary Wisdom asserts that individuals apply their deep-rooted values (the love of money attitudes, avaricious monetary aspirations) to frame critical concerns in the immediate-proximal and omnibus-distal contexts and strategically select certain options to maximize expected utility and ultimate serenity across context, people, and time at the individual, organizational, and national-global levels. This study explores the dark side of decision-making, e.g., avaricious monetary aspirations and corruption (dishonesty). Corruption involves greed, money, and risky decision-making. It is a risky prospect, involving a cost-benefit analysis of self-interest. We frame good or bad barrels in the environmental context as a proxy of high or low probability of getting caught for dishonesty, respectively. We theorize: Two levels of the subjective norm—perceived Corporate Ethical Values at the micro level (CEV, Level 1) and Corruption Perceptions Index at the macro level (CPI, Level 2), collected from multiple sources, jointly impact the magnitude and intensity of the relationships between love of money and dishonesty. Based on 6382 managers in 31 geopolitical entities across 6 continents, our cross-level three-way interaction effect illustrates the following discoveries: As expected, managers in good barrels (high CEV/high CPI), mixed barrels (low CEV/high CPI or high CEV/low CPI), and bad barrels (low CEV/low CPI) display a low, medium, and high magnitude of dishonesty, respectively. Context matters. With high CEV, the intensity is the same across cultures. With low CEV, the intensity of dishonesty is the highest in high CPI entities (risk seeking in the high probability context)—the Enron Effect, but the lowest in low CPI entities (risk aversion in the low probability context). Interestingly, CPI has a strong impact on the magnitude of dishonesty, whereas CEV has a strong impact on the intensity of dishonesty. We demonstrate dishonesty in light of monetary values and two frames of social norms, revealing critical implications to the field of business ethics. This chapter makes robust theoretical and practical contributions to Monetary Wisdom and business ethics.
AtıfScopus2OpenAlex1İncele - MakaleYalnız künye2024Scopus SJRQ2Hydrocarbon migration and structural reservoir traps in the Western Black Sea Basin: evidence from satellite-derived gravity tensor data
Maden, Nafiz; Doğru, Fikret
The Black Sea, situated between Türkiye, Bulgaria, Romania, Ukraine, and Russia, is tectonically separated into two different sub-basins: Eastern and Western Black Sea. These two sub-basins have been a target of interest for oil and gas exploration for several decades. Although the participation of the Black Sea Basin in the global oil market is very small compared to the Caspian Sea, this basin is considered a potential hydrocarbon deposit since both areas have similar characteristics in terms of source rock. In this study, satellite-derived Bouguer and free-air gravity data were interpreted to disclose the prospective hydrocarbon reservoirs and gas hydrate deposits within the Western Black Sea Basin. The locations of the maxima identified in the I2 invariants map were assessed as five substantial hydrocarbon prospective zones three of which are in the Turkish Exclusive Economic Zone. Numerous oil and gas seeps are evidence of lateral and vertical hydrocarbon migration from the source rock through major faults in the WBSB where the maximum I2 anomalies are observed.
AtıfScopus1WoS1OpenAlex2İncele - MakaleYalnız künye2024Scopus SJRQ1Evaluating country performance in preventing industrial accidents: A multi-criteria decision analysis approach
Şimşek, Ahmet Bahadır; Köse, Gülüstan; Göktekin, Zekiye
This study presents a methodology that adopts a multi-criteria decision analysis (MCDA) approach to evaluate countries' performance in preventing industrial accidents, using accident records and combining three MCDA techniques (TOPSIS, Electre II, and CoCoSo) to create a robust ranking. Applied to OECD countries, the methodology provides valuable insights into countries' commitment to industrial accident prevention. It highlights the impact of European Union legislation, variations in the ranks of G7 economies, and identifies role models like Spain and Italy while shedding light on the neglect of regulations in developing countries like Hungary and Turkey. In a world where industrial accidents have far-reaching consequences, this study emphasizes the importance of sincerity and dedication in accident prevention efforts.
AtıfScopus7WoS5OpenAlex8İncele - MakaleYalnız künye2024Scopus SJRQ1Influence of post processing on the mechanical properties and wear behavior of selective laser melted Co-Cr-Mo-W alloys
Varol, Temel; Aksa, Hüseyin Can; Yıldız, Fatih; Akçay, Serhatcan Berk; Kaya, Gürkan; Beder, Murat
In the study, the effect of laser energy density and post-processes (sintering, cold rolling, and hot rolling) on the properties of Co-Cr-Mo-W alloys fabricated by selective laser melting (SLM) are investigated. The samples are fabricated at 83, 125, and 167 J/mm3 of laser energy density to compare their properties. XRD results show that the samples in which ε-Co martensitic phase dominates γ-Co phase are the samples exposed to hot rolling. The highest hardness values obtained with the hot rolling applied after SLM. The hardness for SLM1hr, SLM2hr and SLM3hr is 489.2, 500.4 and 509.8 HV, respectively. The lowest wear rate values are also obtained after the hot rolling post-process, where the highest hardness values and lowest average COFs were obtained.
AtıfScopus16WoS15OpenAlex18İncele - MakaleYalnız künye2024Scopus SJRQ2Three novel 1,2,3-triazole-fused compounds: Syntheses, structural and spectroscopic characterizations with molecular modeling
Ejder, Esengül; Onur, Sultan; Yıldırım, Arzu Özek; Yıldırım, Muhammet Hakkı; Tümer, Ferhan
In this study, we report syntheses, structural and spectroscopic characterizations, and molecular modeling of three novel triazole fused compounds: 4-((4-methoxyphenoxy)methyl)-1-(4-methoxyphenyl)-1H-1,2,3-triazole, 1-(4-isopropylphenyl)-4-((4-methoxyphenoxy)methyl)-1H-1,2,3-triazole, and 1-(4-fluorophenyl)-4-((4-methoxyphenoxy)methyl)-1H-1,2,3-triazole. Their molecular structures and intermolecular interactions were elucidated using single-crystal X-ray crystallography. The compounds crystallize in the P-1 and P21/c space groups with weak C−H∙∙∙N and C-H∙∙∙O interactions. Hirshfeld surface analyses revealed the complex network of intermolecular interactions, determining that in all three compounds, an average of 13 % of the packing interactions were due to hydrogen bonds, and an average of 25 % were due to C-H···π interactions. Since the compounds differ from each other by only one substituent (methoxy, isopropyl, and fluorine) in their phenyl ring, their experimental infrared spectra were clarified by comparing them with the calculated ones. NMR spectroscopy was employed to examine the behavior of the compounds in solution. Conformational scans revealed that the energy differences between conformers are low, indicating potential conformations in which compounds could exist in solution. Nonlinear optical properties were calculated to evaluate the potential of the compounds for optical applications, particularly emphasizing the significantly larger values seen for two compounds compared to a reference compound. Finally, molecular electrostatic potential maps were generated to visualize the charge distribution and potential electrophilic and nucleophilic attack regions.
AtıfScopus8WoS7OpenAlex8İncele - MakaleYalnız künye2024Scopus SJRQ1Past, present, and future scene of influencer marketing in hospitality and tourism management
Polat, Eray; Çelik, Fatih; Ibrahim, Blend; Gursoy, Dogan
This paper reviews influencer marketing (IM)-research in the tourism and hospitality (H&T) field to provide a state-of-the-art of the past, present, and future of IM-research. It identifies research themes, theoretical underpinnings, and methodologies utilized in IM-research. Seventy-five studies are examined through co-citation, bibliographic coupling and content analysis based on the TCCM (theory/context/characteristics/methodology) framework. Co-citation analysis reveals that IM-research focused on travel blogs, vlogs, celebrity endorsement, influencer authenticity. An assessment of recent studies through bibliographic coupling indicates a partial shift toward the study of more contemporary issues. This field-discipline-focused hybrid-review contributes to literature and practice by presenting the past, present, and future of IM-research.
AtıfScopus80WoS69OpenAlex73İncele - MakaleYalnız künye2024Scopus SJRQ2A New Approach for Ground Filtering of Airborne Laser Scanning Data Using PointNet++
Akbulut, Zeynep; Karsli, Fevzi; Dihkan, Mustafa
Ground filtering is an essential process that separates ground and non-ground points for generating digital elevation models (DEMs) from airborne laser scanning (ALS) point cloud data. Traditionally, ground filtering was carried out using rule-based approaches, but with the advancements in deep learning networks, ground filtering can now be performed using these methods. Deep neural networks (DNNs) require large amounts of training samples to reveal key information within the dataset. OpenGF is a new ultra-large-scale dataset which has nearly half a billion points from nine different scenes ranging from highly dense urban areas to steep vegetation covered mountains for ground filtering task. In this study, PointNet++ architecture was employed for ground filtering on the OpenGF dataset. Firstly, we slightly modified PointNet++ architecture’s sampling strategy to decrease the number of duplicate points in the batching process. We proposed a new adaptive tiling strategy based on input point cloud density to cope with highly varying point sampling of the OpenGF dataset. Modified PointNet++ architecture was trained with both adaptive tiling strategy and original OpenGF tiles to investigate the advantages and drawbacks of the proposed strategy on the ground filtering task. To evaluate the performance of the proposed strategy, the results for different test areas were compared with those obtained using the original PointNet++ and rule-based cloth simulation filtering (CSF) algorithms. Despite using fewer epochs, the proposed data collection strategy achieved up to 13% higher accuracy on test scenes with the modified PointNet++ architecture compared to the network trained with original OpenGF tiles.
AtıfScopus2WoS1OpenAlex2İncele - MakaleYalnız künye2024Scopus SJRQ2Earthquakes as a natural occurrence and disaster: A qualitative research from the perspective of chaos theory
Yildiz, Eyyüp; Bostan, Sedat
A concept that inspired social sciences as well as many other fields of science was developed from chaos theory. Disaster researchers are also trying to approach, understand, explain and manage disasters with this new concept. However, it has been observed that studies investigating disasters from this perspective do not focus on disaster sources. With this starting point, in this research, the chaotic factors that prepare the disaster formation were investigated with the example of earthquake. The study was carried out with the qualitative method. Data were collected by semi-structured online interview. Participants were selected by purposive sampling method. The interview data obtained from a total of 10 participants were managed with the MAQXDA 2018 software package using the traditional content analysis method. All codes were classified into three themes and 11 categories. According to the findings, earthquakes can be dealt with in three different chaotic periods: a natural event, a natural event that turns into a disaster, and disaster response and recovery. Future research is recommended to explain the dynamics of occurrence of other disasters such as floods, storms, explosions, and epidemics. It is recommended that disaster management practitioners integrate the chaos management approach into disaster management. With this, it is hoped that disaster management will shift from a linear, bureaucratic, command-control approach to a community-based, flexible, continuous planning approach in which even the smallest occurrences are carefully monitored.
AtıfScopus4WoS3OpenAlex4İncele - MakaleYalnız künye2024Scopus SJRQ2Fast building detection using new feature sets derived from a very high-resolution image, digital elevation and surface model
Günen, Mehmet Akif
Detecting building rooftops with very high-resolution (VHR) images is an important issue in many fields, including disaster management, urban planning, and climate change research. Buildings with varying geometrical features are challenging to detect accurately from VHR image due to complicated image scenes containing spectrally similar objects, illumination, occlusions, viewing angles, and shadows. This study aims to detect building rooftops with high accuracy using a new framework that includes VHR image, visible band difference vegetation index, digital surface and elevation models, the terrain ruggedness and the topographic position index. Five distinct feature sets were generated in order of importance by exposing the ten related stacking features to a feature selection procedure using the maximum relevance minimum redundancy method. Then, Auto-Encoder, k-NN, decision tree, RUSBoost, and random forest machine learning algorithms were utilized for binary classification. Random forest yielded the highest accuracy (97.2% F-score, 98.72% accuracy) when all features (F10) were used, while decision tree was the least successful (59.16% F-score, 83.56% accuracy) for RGB feature set (FRGB). It was revealed that classification of F10 with random forest increased F-score by about 23% compared to classification with FRGB. Additionally, McNemar’s tests showed no statistically significant difference between random forest vs k-NN and decision tree vs RUSBoost.
AtıfScopus19WoS16OpenAlex17İncele - MakaleYayıncıda açık erişim2024Scopus SJRQ3Control moment gyroscope recoil stabiliser including LQR controller for two-wheeled robot
Çetin, Gökhan; Ünker, Faruk
The control moment gyroscope’s (CMG) success in emerging damping control under impact load is of great interest for new technical applications. This paper explores the potential use of a two-wheeled robot with an independent weapon, such as an automatic cannon robot, and considers employing CMG with LQR control as a weapon recoil stabiliser for the robot. Cannon turret firing accuracy is crucial for optimising LQR control parameters and enhancing weapon-robot performance. CMG with LQR control effectively reduces the recoil impact loads of the overhead weapon while compensating angular momentum to ensure safety for robot in firing. The precession motion of the gimbal from several milliradians to tens of milliradians is one of some contradictions for describing the effect of the recoil force on robot–gyroscope performance. This paper uses computational methods, combined with CAE software, to study the impact of increasing angular momentum on recoil-induced weapon vibrations.
AtıfScopus3WoS2İncele - MakaleYalnız künye2024Scopus SJRQ1The effect of maternal functional and postpartum depression status on breastfeeding self-efficacy of the mothers: A cross-sectional study
Palancı AY, Özge; Aktaş, Songül
In this study, the researchers investigated the effect of maternal functioning and postpartum depression status on breastfeeding self-efficacy of mothers. The study was conducted with 254 mothers with babies aged 2-6 months old. The total mean scores of the mothers were found to be 57.201 ± 7.612 on the breastfeeding self-efficacy scale, 8.516 ± 5.304 on the postpartum depression scale, and 74.055 ± 11.738 on the maternal functioning scale. 21.3% of mothers had a risk of postpartum depression. A negative relationship was found between breastfeeding self-efficacy and postpartum depression scores (p < 0.001), and a positive relationship was seen between breastfeeding self-efficacy and maternal functioning scores (p < 0.001). Maternal functioning and postpartum depression status were found to have a cumulative effect of 31.5% on maternal breastfeeding self-efficacy (F = 59.086 R2=0.315).
AtıfScopus18WoS21OpenAlex25İncele - MakaleYalnız künye2024Scopus SJRQ1Waste Heat and Mass Recovery from Boiler Exhaust Gases in a New Generation District Heating System: Energy and Exergy Analysis
Terhan, Meryem
The study performs energy and exergy analyses for each component such as boilers, buildings, distribution networks and heat exchangers of a new generation district heating system. Energy and exergy efficiencies are compared for all system components, and energy and exergy losses are presented using Sankey and Grassman diagrams. Three flue gas condensers with finned bundles are designed for different capacities of boilers that intend to recover water and heat from the waste flue gas in the district heating system due to high flue gas energy losses. Colburn-Hougen and one-dimensional finite difference methods are used to design the flue gas condensers with the MATLAB program. The exergy analysis showed that the exergy input to the system is lost by 4.52% from the distribution networks, 4.15% from all buildings and 2.18% from the flue gas. In the system, the energy and exergy efficiencies of the boilers are calculated to be 87.23% and 17.32%, respectively, and the heat loss from the flue gas is found to be 12%. The design results show that the values of mass convection coefficient (km) for all flue gas condensers decrease from 0.0706 at the inlet condensation zone to 0.0354 towards the outlet. The total condensation rate and condensation efficiency are found to be 86 kg/h and 60%, respectively, for the 2500 kW boiler.
AtıfScopus3WoS3OpenAlex3İncele - MakaleYayıncıda açık erişim2024Scopus SJRQ1HIJACKING OF STATE POWER ON RELIGIOUS FREEDOM BY COMMUNITY ORGANIZATIONS IN INDONESIA
Prianto, Andi Luhur; Karimullah, Suud Sarim; Idri; Ibrahim, Zumiyati Sanu; Nugraha, Aat Ruchiat; Gönan, Yavuz
This study aims to reveal the failure of the state to use its authority to ensure the fulfilment of religious freedom for all its citizens maximally and adequately because, in practice, the state sometimes takes refuge behind the slogan of neutrality when it sees the majority group committing violent practices against minority groups. This study uses a discourse analysis method with a phenomenological approach to understanding the meaning of various events and human interactions. Meanwhile, the data was collected through literature study, media study, and observation using content analysis and discourse analysis methods in processing the data. Then this research results in the finding that opening the state accommodation gap to the demands of the majority religious group will provide space for them to take advantage of the similarities in their religious ideology with state actors and then attempt to dictate state policy. The inability of the state to be neutral in solving the problems of its people, at the same time, has given rise to the impression that a handful of certain social classes have controlled the state. Even this research results also show that tendencies of intolerance and discrimination arise in the community.
AtıfScopus5OpenAlex3İncele - MakaleYalnız künye2024Scopus SJRQ2Selective Hydrogenation of Croton Aldehyde on Pt Nanoparticles Controlled by Tailoring Fraction of Well-Ordered Facets Under Different Pretreatment Conditions
Sarıbıyık, Oğuz Y.; Resasco, Daniel E.
This study focuses on the influence of pretreatment conditions and surface structures of well-tuned Pt nanoparticles on the selective hydrogenation of α-β unsaturated crotonaldehyde. The surface binding site preferences of the reactant during catalytic conversions are strongly influenced by the configuration of the nanoparticles’ surface fraction exposed. Since the orientation of the well-ordered surfaces are significantly affected by the pretreatment conditions, we have attempted to obtain relationships between morphology changes and catalytic activity by controlling the fraction of facets with ordered structures. Pt nanoparticles exhibit different types of exposed surfaces, namely Cubic (Cub) (100) and Cuboctahedra (CubOc) (111) + (100). These different surface structures play a crucial role in the preferential hydrogenation of the model molecule. Additionally, we investigated the impact of the pretreatment condition on the catalytic selectivity of the well-shaped nanoparticles. We employed various techniques such as high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), transmission electron microscopy (TEM), and room temperature carbon monoxide adsorption Fourier transform infrared spectroscopy (RT-CO-FTIR) to determine the reconstructions of the particles under different pretreatment conditions. The results indicate that both the well-ordered surface fraction and pretreatment conditions of Pt nanoparticles had a moderate influence on both catalytic activity and selectivity. Overall, this study highlights the importance of analyzing the surface morphology and pretreatment conditions of nanoparticles in order to optimize catalytic activity and selectivity in reactions involving well-tuned surface structures. Graphical Abstract: (Figure presented.).
AtıfScopus4WoS5OpenAlex5İncele - MakaleYayıncıda açık erişim2024Scopus SJRQ1Potato leaf disease detection with a novel deep learning model based on depthwise separable convolution and transformer networks
Catal Reis, Hatice; Turk, Veysel
Early diagnosis of plant diseases is essential in reducing economic losses for farmers and increasing production efficiency. Therefore, Computer-Aided Diagnosis (CAD) systems supported by artificial intelligence technologies can be developed to help diagnose diseases quickly and accurately by examining the symptoms and signs in plant leaves. In this study, Multi-head Attention Mechanism Depthwise Separable Convolution Inception Reduction Network (MDSCIRNet) architecture, an image-based deep convolutional neural network, is proposed for classifying potato leaf diseases. The main components of the MDSCIRNet architecture are depthwise separable convolution (DSC) and a multi-head attention mechanism. The proposed architecture has been compared with modern algorithms developed with DSC technology, such as Xception, MobileNet, and deep learning algorithms, such as ResNet101, InceptionV3, and EfficientNetB2, to evaluate its performance in the classification process. In addition, hybrid methods developed with the classical machine learning algorithms Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), Adaptive Boosting (AdaBoost), and MDSCIRNet model, integrated deep learning model, hard voting ensemble learning model. Suggested methods such as these were also used in the experimental process. Moreover, techniques such as Contrast Limited Adaptive Histogram Equalization (CLAHE), Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN), and Hypercolumn were used to improve the image quality of the data set. In the experimental process, the MDSCIRNet deep learning architecture achieved 99.24% accuracy in the study using the original dataset. While a 99.11% accuracy rate was achieved with the integrated deep learning model and hard voting ensemble learning model, the highest success rate of 99.33% was performed in the study conducted with the MDSCIRNet + SVM method. This study contributes to developing new and effective strategies in the agricultural industry for the early diagnosis and control of potato plant diseases. Machine learning-based approaches offer the potential to minimize economic losses and increase productivity in production by allowing farmers to intervene early.
AtıfScopus111WoS75OpenAlex83İncele