Hydrogen is one of the most clean energy carrier and the best alternative for fossil fuels. In this study, thermodynamic analysis of modified Organic Rankine Cycle (ORC) integrated with Parabolic ...Trough Collector (PTC) for hydrogen production is investigated. The integrated system investigated in this study consists of a parabolic trough collector, a modified ORC, a single effect absorption cooling system and a PEM electrolyzer. By using parabolic trough collector, solar energy is converted heat energy and then produced heat energy is used in modified ORC to produce electricity. Electricity is then used for hydrogen production. The outputs of this integrated system are electricity, cooling and hydrogen. By performing a parametric study, the effects of design parameters of PTC, modified ORC and PEM electrolyzer on hydrogen production is evaluated. According to the analysis results, solar radiation is one of the most important factor affecting system exergy efficiency and hydrogen production rate. As solar radiation increases from 400 W/m2 to 1000 W/m2, exergy efficiency of the system increases 58%–64% and hydrogen production rate increases from 0.1016 kg/h to 0.1028 kg/h.
•Hydrogen production via solar energy.•Thermodynamic efficiency analysis of an integrated system.•Effects of reference temperature on energetic and exergetic efficiency.•Effects of solar radiation change on hydrogen production rate.
Why do voters vote for undemocratic politicians in a democracy? My chief contention is that affective polarization has become a primary factor driving support for undemocratic politicians. Once ...partisan identification turns into a salient identity in the hierarchy of group affiliations, it has the potential to widen inter-party distances. Such a political environment fosters positive beliefs of their preferred party and negative beliefs of the other party, which promote political cynicism, intolerance and increase partisan loyalty. As a result, crossing party lines becomes costly, even when incumbents violate democratic principles or incumbents' economic policies do not appeal to supporters' interests. This tradeoff enables undemocratic politicians to evade electoral sanctions for undemocratic behaviour. I created an extended version of Reiljan's affective polarization application. The new dataset covers affective polarization scores of 53 countries calculated over 170 national election surveys. I find that increasing affective polarization is highly correlated with democratic backsliding, less accountability, less freedom, fewer rights, and less deliberation in democracies. However, ideological polarization has shown no correlation.
We developed a general method for the selective photochemical homo- and heterodimerization of cinnamic acid derivatives with the use of commercially available 1,8-dihydroxynaphthalene as a covalent ...template. A variety of symmetrical and unsymmetrical β-truxinic acids were obtained in high yields and as single diastereomers. The use of a template not only provides the alignment of the two olefins with suitable proximity (<4.2 Å) but also allows the heterodimerization of two different cinnamic acids, leading to unsymmetrical β-truxinic acid products.
The COVID-19 epidemic, in which millions of people suffer, has affected the whole world in a short time. This virus, which has a high rate of transmission, directly affects the respiratory system of ...people. While symptoms such as difficulty in breathing, cough, and fever are common, hospitalization and fatal consequences can be seen in progressive situations. For this reason, the most important issue in combating the epidemic is to detect COVID-19(+) early and isolate those with COVID-19(+) from other people. In addition to the RT-PCR test, those with COVID-19(+) can be detected with imaging methods. In this study, it was aimed to detect COVID-19(+) patients with cough acoustic data, which is one of the important symptoms. Based on these data, features were obtained from traditional feature extraction methods using empirical mode decomposition (EMD) and discrete wavelet transform (DWT). Deep features were also obtained using pre-trained ResNet50 and pre-trained MobileNet models. Feature selection was applied to all obtained features with the ReliefF algorithm. In this case, the highest 98.4% accuracy and 98.6% F1-score values were obtained by selecting the EMD + DWT features using ReliefF. In another study in which deep features were used, features obtained from ResNet50 and MobileNet using scalogram images were used. For the features selected using the ReliefF algorithm, the highest performance was found with support vector machines-cubic as 97.8% accuracy and 98.0% F1-score. It has been determined that the features obtained by traditional feature approaches show higher performance than deep features. Among the chaotic measurements, the approximate entropy measurement was determined to be the highest distinguishing feature. According to the results, a highly successful study is presented with cough acoustic data that can easily be obtained from mobile and computer-based applications. We anticipate that this study will be useful as a decision support system in this epidemic period, when it is important to correctly identify even one person.
•Detection of COVID-19(+) patients based on cough acoustic signals has been realized.•The performances of EMD and DWT methods were analyzed.•The performances of the deep features obtained from 2D Scalogram images were investigated.•ReliefF algorithm was applied as feature selection method.•High detection accuracy (98.4%) was obtained using traditional features with EMD + DWT.
Abstract The enhancement of flexibility, energy efficiency, and environmental friendliness constitutes a widely acknowledged trend in the development of urban infrastructure. The proliferation of ...various types of transportation vehicles exacerbates the complexity of traffic regulation. Intelligent transportation systems, leveraging real-time traffic status prediction technologies, such as velocity estimation, emerge as viable solutions for the efficacious management and control of urban road networks. The objective of this project is to address the complex task of increasing accuracy in predicting traffic conditions on a big scale using deep learning techniques. To accomplish the objective of the study, the historical traffic data of Paris and Istanbul within a certain timeframe were used, considering the impact of variables such as speed, traffic volume, and direction. Specifically, traffic movie clips based on 2 years of real-world data for the two cities were utilized. The movies were generated with HERE data derived from over 100 billion GPS (Global Positioning System) probe points collected from a substantial fleet of automobiles. The model presented by us, unlike the majority of previous ones, takes into account the cumulative impact of speed, flow, and direction. The developed model showed better results compared to the well-known models, in particular, in comparison with the SR-ResNet model. The pixel-wise MAE (mean absolute error) values for Paris and Istanbul were 4.299 and 3.884 respectively, compared to 4.551 and 3.993 for SR-ResNET. Thus, the created model demonstrated the possibilities for further enhancing the accuracy and efficacy of intelligent transportation systems, particularly in large urban centres, thereby facilitating heightened safety, energy efficiency, and convenience for road users. The obtained results will be useful for local policymakers responsible for infrastructure development planning, as well as for specialists and researchers in the field. Future research should investigate how to incorporate more sources of information, in particular previous information from physical traffic flow models, information about weather conditions, etc. into the deep learning framework, as well as further increasing of the throughput capacity and reducing processing time.
In this paper, the thermodynamic study of a combined geothermal power-based hydrogen generation and liquefaction system is investigated for performance assessment. Because hydrogen is the energy of ...future, the purpose of this study is to produce hydrogen in a clear way. The results of study can be helpful for decision makers in terms of the integrated system efficiency. The presented integrated hydrogen production and liquefaction system consists of a combined geothermal power system, a PEM electrolyzer, and a hydrogen liquefaction and storage system. The exergy destruction rates, exergy destruction ratios and exergetic performance values of presented integrated system and its subsystems are determined by using the balance equations for mass, energy, entropy, energy and exergy and evaluated their performances by means of energetic and exergetic efficiencies. In this regard, the impact of some design parameters and operating conditions on the hydrogen production and liquefaction and its exergy destruction rates and exergetic performances are investigated parametrically. According to these parametric analysis results, the most influential parameter affecting system exergy efficiency is found to be geothermal source temperature in such a way that as geothermal fluid temperature increases from 130 °C to 200 °C which results in an increase of exergy efficiency from 38% to 64%. Results also show that, PEM electrolyzer temperature is more effective than reference temperature. As PEM electrolyzer temperature increases from 60 °C to 85 °C, the hydrogen production efficiency increases from nearly 39% to 44%.
•Geothermal energy based hydrogen production and liquefaction system is suggested.•Exergy analysis and performance assessment of combined system components are given.•Energetic and exergetic performance of combined system are investigated.•Effects of design variables on power and hydrogen generation are investigated.
In bacterial cellulose (BC) production, we developed a new static cultivation system named series static culture (SSC) to eliminate air limitation problem encountered in conventional static culture ...(CSC). In SSC system, the fermentation broth at the bottom of BC pellicle produced in initial culture medium is transferred to the next empty sterile culture medium at the end of a certain fermentation period. This procedure was performed until BC production ceased. Fermentation experiments were carried out using Gluconacetobacter xylinus NRRL B-759 and sugar beet molasses at 30 °C and initial pH 5. Also, some quality parameters of produced BC pellicles were determined. Final pH at the stages of SSC system was higher that of the initial pH due to sugar content (sucrose) of molasses and microorganism used. Total BC production increased with increasing sugar concentration in SSC. As a result, an increase of 22.02 % in BC production was achieved using developed SSC. FT-IR spectra of all BC pellicles produced were typical spectra. The absorption bands at the relevant wavenumbers identify the mode of vibrations of the created chemical bonds arising at the BC surface such as OH, CH, H-O-H, C-O-C, and C-OH. XRD analyses showed that the crystallinity index values of BC obtained from CCS and SSC were high. The form of produced all BC pellicles is generally Cellulose I. Removal of surface moisture and depolymerisation of carbon skeleton were determined from TGA-DTA thermograms. SEM images showed that the BC samples produced had nano-sized cellulose fibrils which were aggregated in fermentation media containing molasses. Finally, the BC samples, especially in molasses media, having high mechanical strength and WHC were found.
•A novel static culture was developed (SSC) in BC production•Compared to conventional static culture, BC yield was increased using developed SSC (22 %)•pHs of fermantation broth in the stages of SSC increased•According to quality parameters, produced BC pellicles in the SSC had typical properties.
New-generation technologies on vehicles provide many advantages in terms of cost, time, and the environment in the transportation, logistics, freight, and delivery service sectors. This study aimed ...to measure the effect of using e-scooter vehicles in mail delivery on the energy cost and delivery time in Turkey. Considering the number of test drives in e-scooter applications of potential regions, the amount of energy consumption and driving time data were used. The number of test drives for each e-scooter was assumed as a package or postal delivery amount. The methodology of this study consisted of measuring the effect of input parameters on output variables using the linear response optimization regression method and minimizing the amount of energy consumed and delivery time. The nine input variables and two output variables based on the test drive were analyzed in this study. The distance to the delivery address, region where the delivery address was located, and temperature were found to be statistically significant predictors of the amount of energy required for delivery. The statistical significance levels of time zone, distance, temperature, rainfall, and region factors were calculated as 0.053, 0.001, 0.0033, 0.044, and 0.042, respectively. Driver age, data time zone, distance, wind speed, and delivery region factors affected the time required for delivery with an e-scooter. The statistical significance levels of these factors were calculated as 0.02, 0.001, 0.001, 0.043, and 0.001, respectively. Additionally, N (p; 0.042), NE (p; 0.030), and W (p; 0.057) wind directions directly influenced the delivery time. SE (p; 0.017) was the only wind direction that statistically significantly affected energy consumption. The objective functions were estimated by calculating the optimum values of the input parameters for the minimum energy consumption and delivery time. The optimum values of both input and output variables were calculated based on the desirability values of the optimization models, which were in the optimum solution set. The average data of the optimum values of the objective functions were computed as 2.83 for the number of tests and TRY 0.021 (per 0.098 km) for the energy cost required for delivery. The necessity of using e-scooters, which are more environmentally friendly, economical, and time-saving than traditional delivery vehicles, in postal delivery service is among the prominent suggestions of this study.
Current energy infrastructure is not sustainable due to highly dependence to fossil fuels. Increasing energy usage obliges people to find new, economic, environmental friendly and safe energy ...options. Recent studies indicate that there are many alternative ways for fossil fuels such as solar, geothermal, wind and biomass. By using these renewable sources in tri-generation or multigeneration energy systems, the desired energy infrastructure can be set. On the other hand, hydrogen is seen as future energy carrier because of its advantages. There are many options to benefit from hydrogen such as fuel cells, direct combustion, or store as gas or liquid. However, awareness of society of the renewable energy usage and also hydrogen as energy carrier is not sufficient. In order to increase the awareness of the society, teachers have high responsibility. In this study, views of elementary science teacher candidates on hydrogen as future energy carrier are evaluated by using qualitative phenomenological research. Ten students from elementary science teacher department in Afyon Kocatepe University are selected for semi structured interview. The results of these interviews are analyzed by using content analysis method.
•The views of elementary science teacher candidates on hydrogen energy are investigated.•Case study a type of qualitative research is performed.•Views of science teacher candidates are coded in themes and later analyzed.
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