Aromatic sulfonated polymers as a suitable candidate for Nafion membrane in proton exchange membrane fuel cells are the subject of many research activities. It has proved that these polymers need higher ion exchange capacities to reach the same proton conductivities compared to the Nafion membrane, which is a result of their different microstructures. Accordingly, to compensate different microstructures in the Nafion and sulfonated aromatic substitutions, several composite blend membranes of poly(ether sulfone) (PES) and poly(ether ether ketone) (PEEK), including electrospun fibers of highly-sulfonated/non-sulfonated PEEK and PES polymers have prepared. For comparison, two membranes with a routine solution-casting technique also have been made. The membrane-electrode assemblies are tested in H2/O2 single-cell. Before that, characterization measurements have performed for all membranes. To select the best sample between prepared membranes, multi-criteria decision-making (MCDM) have used, and to achieve more reliable results, four techniques of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), COmplex PRoportional ASsessment of alternatives (COPRAS), and VIekriterijumsko KOmpromisno Rangiranje (VIKOR) have applied. According to the experiments and MCDM methods, composite blend membrane containing sulfonated electrospun fibers of PEEK in non-sulfonated PES matrix gains the best rank among all membranes.
The identification of knowledge graph entity mentions in textual content has already attracted much attention. The major assumption of existing work is that entities are explicitly mentioned in text and would only need to be disambiguated and linked. However, this assumption does not necessarily hold for social content where a significant portion of information is implied. The focus of our work in this paper is to identify whether textual social content include implicit mentions of knowledge graph entities or not, hence forming a two-class classification problem. To this end, we adopt the systemic functional linguistic framework that allows for capturing meaning expressed through language. Based on this theoretical framework we systematically introduce two classes of features, namely syntagmatic and paradigmatic features, for implicit entity recognition. In our experiments, we show the utility of these features for the task, report on ablation studies, measure the impact of each feature subset on each other and also provide a detailed error analysis of our technique.
Quantum computing is a vital research field in science and technology. One of the fundamental questions hardly known is how quantum computing research is developing to support scientific advances and the evolution of path-breaking technologies for economic, industrial, and social change. This study confronts the question here by applying methods of computational scientometrics for publication analyses to explain the structure and evolution of quantum computing research and technologies over a 30-year period. Results reveal that the evolution of quantum computing from 1990 to 2020 has a considerable average increase of connectivity in the network (growth of degree centrality measure), a moderate increase of the average influence of nodes on the flow between nodes (little growth of betweenness centrality measure), and a little reduction of the easiest access of each node to all other nodes (closeness centrality measure). This evolutionary dynamics is due to the increase in size and complexity of the network in quantum computing research over time. This study also suggests that the network of quantum computing has a transition from hardware to software research that supports accelerated evolution of technological pathways in quantum image processing, quantum machine learning, and quantum sensors. Theoretical implications of this study show the morphological evolution of the network in quantum computing from a symmetric to an asymmetric shape driven by new inter-related research fields and emerging technological trajectories. Findings here suggest best practices of innovation management based on R&D investments in new technological directions of quantum computing having a high potential for growth and impact in science and markets.
Background and purpose: Recent research suggests that obese people are up to 80 times more likely to develop type 2 diabetes than those with a normal BMI. Besides, obesity, inadequate physical activity, and unhealthy diets are the main causes of this metabolic disease. The purpose of this study was to investigate the effect of six weeks of high-intensity interval training on muscle expression of Fat mass and obesity-associated protein (FTO) and Peroxisome proliferator activator receptor gamma (PPAR-γ) in obese diabetic rats. Material and methods: This experimental study was carried out on 12 male Wistar rats (220±20 g bodyweight and 10 weeks old). Animals received a high-fat diet within six weeks, and then in order to induce type 2 diabetes, an intraperitoneal injection of a single dose of 30 mg/kg freshly prepared streptozotocin (STZ) (Sigma, USA) solved in citrate buffer (pH 4.5) was performed. Diabetic rats were divided into two (High-Intensity Interval Training and control) groups randomly. HIIT program included five sessions of 30 minutes per week. 48 hours after the last training session, the outcomes were measured. The muscle expression of FTO and PPAR-γ was measured using the real-time PCR method. Independent samples t-test and Analysis of covariance (ANCOVA) were applied to compare the means. Results: The expression of FTO (P<0.01), fasting blood sugar (P<0.001), weight (P<0.001) and HOMA-IR (P<0.004) significantly decreased after six weeks of high-intensity interval training, whilst PPAR-γ expression (P<0.007) significantly increased. Conclusion: Regarding the results of this study, it can be stated that a six-week HIIT program can improve glucose metabolism and insulin sensitivity. It can also increase the expression of diabetes- and obesity-associated genes (e.g., PPAR-γ and FTO), and thereby plays a prominent role in the control and treatment of type 2 diabetes in obese patients.
This paper has scrutinized the process of testing market efficiency, data generation process and the feasibility of market prediction with a detailed, coherent and statistical approach. Furthermore, attempts are made to extract knowledge from S&P 500 market data with an emphasize on feature engineering. As such, different data representations are provided through different procedures, and their performance in knowledge extraction is discussed. Amongst the neural networks, Long Short-Term Memory has not been adequately experimented. LSTM, because of its intrinsic, considers the long-term and short-term memory in its computations. Thus, in this paper LSTM is further examined in return prediction and different preprocessing methods are tested to improve its accuracy. This study is conducted on market data during September-2000 to February-2021. In order to extend the amount of knowledge extracted from financial time series, and to select the best input features, the advantage of Principal Component Analyze, Random Forest, Wavelet and the LSTM’s own deep feature extraction procedure are taken, and 4 models are compiled. Subsequently, to validate the performance of the models, MAE, MSE, MAPE, CSP and CDCP are calculated. Results from Diebold Mariano test implied that although LSTM neural network has gained a lot of attention recently, it does not significantly perform better than the benchmark method in S&P 500 index return prediction. Yet, results from Wilcoxon signed rank test showed the significance of improvement in the predictions performed by the combination of Principal component analysis and LSTM.
Despite the substantial growth of research on teachers’ beliefs and practices in the past decades, little research has examined the impact of teacher education on in-service teachers’ grammar beliefs and practices. The present study aimed to fill part of this gap in relation to two Iranian novice EFL teachers. Data were collected before and after a grammar-oriented teacher education course from semi-structured interviews and classroom observations. The findings showed that the course influenced the teachers’ beliefs to move from a more teacher-fronted approach toward an approach that marked attention to the importance of learners’ socioemotional states. Moreover, the teachers’ practices after the course featured more attention to the collaborative and pragmatic aspects of grammar instruction. Based on the findings, we provide several implications for teacher education, which highlight the role of sociocultural and personal dimensions in programs that are structured around grammar instruction.
The environmental planning of cities and rural regions is associated with monitoring the performance of several services, including solid waste management. This study proposes a new framework for the comparative assessment of the performance of integrated municipal solid waste management. The framework includes the fuzzy MACBETH multi-criteria decision-making model used to investigate the uncertainties and inefficiencies associated with solid waste management systems. The model consists of all major stages in solid waste management and its environmental impact. The applicability of the model was examined in the South European region. According to the global fuzzy values of the criteria weights, the most influential reported criteria were GHG emission (0.113,0.157,0.202), the waste generation growth rate (0.034,0.063,0.141), and waste generation (0.034,0.054,0.127). The other results indicated that Italy (47.26) and France (42.67) had shown a better performance , only to be followed by Spain (37.68), whereas Greece (15.77) and Portugal (12.85) had received the lowest score. In the context of promoting the circular economy in Europe, having a higher recycling rate and less landfilling is beneficial for Greece and Portugal. In addition to this, all these countries should make efforts on decoupling the waste generation-GDP correlation. Furthermore, the applicability of the model depends on an appropriate scale and criteria. The model can be replicated to other developed societies with a few modifications. However, it is necessary to modify the criteria for assessing developing societies based on local conditions.
Hydrogen as an energy carrier can play a significant role in reducing environmental emissions if it is produced from renewable energy resources. This research aims to assess hydrogen production from wind energy considering environmental, economic, and technical aspect for the East Azerbaijan province of Iran. The economic assessment is performed by calculation of payback period, levelized cost of hydrogen, and levelized cost of electricity. Since uncertainty in the power output of wind turbines may affect the payback period, all calculations are performed for four different turbine degradation rates. While it is common in the literature to choose the wind turbine based on a single criterion, this study implements Multi-Criteria Decision-Making (MCDM) techniques for this purpose. The results of Step-wise Weight Assessment Ratio Analysis illustrates that economic issue is the most important criterion for this research. The results of Weighted Aggregated Sum Product Assessment shows that Vestas V52 is the most suitable wind turbine for Ahar and Sarab cities, while Eovent EVA120 H-Darrieus is a better choice for other stations. The most suitable location for wind power generation is found to be Ahar, where it is estimated to annually generate 2914.8 kWh of electricity at the price of 0.045 $/kWh, and 47.2 tons of hydrogen at the price of 1.38 $/kg, which result in 583 tons of CO2 emission reduction.
Nowadays, the production of stone paper, in addition to its widespread utilization in various fields, does not require water consumption, cutting down trees, and stone paper products are easily recyclable and recoverable. Due to the importance of developing and using stone paper and paying attention to environmental matters, Closed-Loop Supply Chain Network Design (CLSCND) is very important for stone paper products. Moreover, due to epistemic, randomness uncertainties, the uncertainties in Objective Function (OF), and the flexible constraints for CLSCND in the real world, this paper introduces a novel Mixed Robust Stochastic, Possibilistic, and Flexible Programming (MRSPFP) approach based on credibility theory. The different attitudes of the Decision-Makers (DMs) are addressed by a more flexible measurement of the optimistic and pessimistic parameters using the criterion of credibility. In the study, a comprehensive procedure is proposed for stone paper CLSCND, to minimize costs, increase responsiveness by minimizing transit time between different facilities, and regarding environmental concerns into account through minimizing carbon emissions. The model is solved utilizing an interactive fuzzy programming solution procedure and the Best-Worst Method (BWM). The results of sensitivity analysis, the effect of changing the problem parameters, and the performance of the proposed model are investigated and compared. The results show that the MRSPFP model has a better performance compared to other previous models. The MRSPFP model performs better in strategic decisions that require high investment costs due to the minimization of the absolute deviation of OF from its mean. Also, the applied results of the study show that CLSCND has a good capability and potential for sustainable development in the field of stone paper.
Today, by increasing public awareness about environmental issues and pressures from governments and other stakeholders, companies have dealt with environmental challenges more than ever. This paper focuses on environmentally sustainable performance using an integrated methodology based on meta-synthesis, Delphi, and structural equation modeling (SEM) techniques which are utilized in different phases. In the first phase, an in-depth review of green human resources management (GHRM) literature is conducted based on the meta-synthesis method, and as a result, 38 codes are extracted. Next, to adapt and customize the codes with the nature of the construction industry, 2 rounds of Delphi method are implemented to extract the expert judgment from a panel of 15 industry professionals, resulting in 21 codes in 7 categories. To validate the developed methodology, a dataset from 33 Iranian construction companies are collected along with 15 factors in 5 categories determined using SEM. The findings reveal that among 9 main GHRM components extracted from the literature, just 5 components including green recruitment and selection, green performance management, green-reward, green-based employee empowerment, and green training have significant and positive relationships with GHRM. Finally, managerial insights, limitations, and future research directions are discussed.
Due to the high rate of comorbidity of social anxiety disorder and major depressive disorder, this study aimed to examine the mediation effect of depressive symptoms on the association between emotion regulation, negative self-evaluation, and social anxiety symptoms. The population of this study consisted of all students of the Faculty of Architecture, Islamic Azad University. The sample included 284 of the students based on convenience sampling method. Depressive symptoms were measured by Beck Depression Inventory-II (Beck et al., 1996), emotion regulation was measured by Cognitive Emotion Regulation Questionnaire (Garnefski et al., Personality and Individual Differences, 30(8), 1311–1327, 2001), social anxiety was measured by Social Phobia Inventory (Connor et al., Depression and Anxiety, 14(2), 137–140, 2001) and, negative self-evaluation was measured by Consequences of Negative Social Events Questionnaire (Wilson and Rapee, Journal of Anxiety Disorders, 19(3), 245–274, 2005). We used Path analysis to test the significance of mediation. The result of the study indicated that the direct and indirect effects of all maladaptive emotion regulation strategies, negative self-evaluation and evaluation from the others’, and depression components on social anxiety symptoms components was positive and significant.From these results, we conclude that high levels of depressive symptoms accompanied by high levels of maladaptive emotion regulation and high levels of negative self-evaluation can lead to increased social anxiety symptoms. The theoretical and practical issues have been discussed.
Global warming and environmental pollution are concepts that are more or less encountered in the news and newspapers today. Protecting the environment is crucial to the survival of humanity and the many plant and animal species that inhabit the planet. Lack of control of greenhouse gases can increase the average surface temperature and lead to floods and serious damage in the near future. On the other hand, overproduction of plastics by factories can lead to environmental pollution and the destruction of many food cycles on Earth. In this study, in order to sustainability integrate issues in supply chain network design decisions, a multiobjective optimization model is presented, which is a two-level routing location problem and optimizes economic and environmental goals. The first level is decisions related to the selection of operating facilities from a set of potential facilities (manufacturers and distribution centers), and the second level is related to determining the number of products from distribution centers to retailers and from manufacturers to distribution centers. The objective function is also of the minimization type, which is related to minimizing fixed and variable costs, and minimizing the environmental effects of the whole chain, which includes reducing the costs of greenhouse gas and carbon emissions.
One of the most important issues is to achieve maximum production of energy from a particular energy source, which ensures the complete protection of the environment. The current paper as the first application of flexible and powerful semi-disposability approach, performs an empirical technical and environmental efficiency analysis for 39 natural gas and gasoline power plants, including governmental and private property, during the years 2011–2016. Different scenarios for environmental analysis, namely, weak disposability, strong disposability and semi-disposability with different returns to scale assumptions are performed in the analysis. The primary results of multivariate assessment based on constant returns to the scale shows that 7 power plants with state ownership and 8 power plants with private ownership were among the most efficient power plants from the technical-environmental perspective. Parametric and non-parametric tests are performed and the result shows better performance of private power plants compared with governmental power plants.
Background The effect of the Posterior X Taping (PXT) used for subjects with Tibiofemoral Varus Malalignment (TFRV) aimed to control excessive tibiofemoral rotations is still unclear. Further, it is critical to use evidence-based therapeutic exercises to prevent non-contact injuries, especially in repetitive movements. Objective To investigate whether the PXT and real-time feedback (RTF) interventions would improve lower extremity functions during the pedaling task in subjects with TFRV. Methods Twenty-four male recreational athletes with TFRV participated in this study; Kinematic and muscle activity were synchronously recorded on ten consecutive pedal cycles during the last 30 s of 2-min pedaling. Results The present study indicated that the subjects at the post-intervention of the RTF group exhibited significant decreased hip adduction and internal rotation, significant decreased tibiofemoral external rotation between 144 and 216° of crank angle, significant increased vastus medialis activity between 144 and 288° of crank angle, and significant increased gluteus medius activity between 180 and 144° of crank angle; In contrast, the subjects at the post-intervention of the PXT group exhibited significant decreased tibiofemoral external rotation and increased ankle external rotation at all the crank angles. No between-group differences were observed in pre-and post-intervention. Significance These results suggest that the PXT and RTF interventions are recommended to immediately improve the functional defects of the subjects with TFRV during the pedaling task.
For the first time in the tourism and environment literature, this study investigates the CO 2 emissions effect of the market diversification of tourist arrivals. Theoretically, tourism market diversification has two opposite potential effects on CO 2 emissions, depending on its scale and composition effect. It may increase CO 2 emissions by expanding the scale of tourism-related activities or decrease CO 2 emissions by expanding the share of developed/less-polluted source countries in the destination. By utilizing the econometrics of time series data, we tested the impact of tourism market diversification on CO 2 emissions in Australia over the period 1976-2019. Our findings show that tourism market diversification has pro-CO 2 emissions effects in the long run for Australia. These findings contribute to our understanding of the environmental impacts of tourism market diversification and help in policy formulations in Australia. ARTICLE HISTORY
This study examined the relationship between pathological narcissism, narcissistic grandiosity, narcissistic vulnerability and the five-factor model of personality. Participants consisted of 290 undergraduate students from four universities in three different cities in Iran, recruited by available sampling, Instruments, including, Pathological Narcissism Inventory (PNI) and the NEO Five-Factor Inventory (NEO-FFI) were also completed for the participants. Hierarchical regression analysis showed that narcissistic grandiosity was positively associated with extraversion and openness, while narcissistic vulnerability and overall pathological narcissism were positively associated with neuroticism and negatively related to agreeableness and openness (only for narcissistic vulnerability). The results are consistent with prior research in Western cultures (e.g., United States, Germany) and revealed that neuroticism is a common factor in narcissistic vulnerability and pathological narcissism which suggested pathological narcissism may be a distinct dimension from normal narcissism. Also, there were various contributors of personality traits for narcissistic grandiosity and narcissistic vulnerability which can be considered as a support for the distinction of two phenotypes of pathological narcissism.
Most activities of FinTech companies in the real world are limited to a variety of banking services such as payment and funds transfer, while the scope of banking services is much broader than the current activities of FinTech companies. In recent years, extensive research has also been conducted on how FinTech companies contribute to the provision of banking services. The present study identifies ideas for new and innovative areas of FinTech companies’ activity by reviewing the relevant literature. These areas are categorized using the Banking Industry Architecture Network (BIAN) service landscape and are identified and described through thematic analysis. The outcome of this study is a model which reveals that the main service domains belong to the “banking operations and execution,” “sales and services,” “risk and compliance,” “business support,” and “reference data.” According to the findings of the present research, FinTech companies have the capability to provide banking services in 22 domains out of 36 BIAN domains. Theoretical contributions and comparative analysis are discussed.
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