Critical Factors in Competitive Advantage of Islamic Banking

This research focuses on determining the impact of service quality, customer satisfaction, and loyalty programs on customers’ loyalty in the banking sector of Malaysia. It is obvious that customers are important stakeholders in organisations, and their satisfaction is a priority to the management. Customer satisfaction has been a subject of great interest to organisations and researchers alike. In recent years, organisations are obliged to render additional services on top of their offers. The quality of service has become an aspect of customer satisfaction

Relation of the chondromalatia patellae to proximal tibial anatomical parameters, assessed with MRI

Magnetic resonance imaging (MRI) is a non-invasive highly sensitive tool for diagnosing chondromalacia patellae in the early stages. Many studies have evaluated patellar and trochlear morphology with different radiologic indices. We aimed to assess the discriminative power of tibial, patellar, and femoral indices in MRI for chondromalacia patellae. 100 cases of chondromalacia, as well as 100 age-matched controls among the patients who underwent knee MRI between February 2017 and March 2019, were included. The standard protocol of knee MRI was applied and the diagnosis of chondromalacia was made on MRI findings. Chondromalacia subjects were also classified as grade 1 to 4 according to the Modified Outerbridge's MRI grading system. We measured 25 MRI parameters in the knee and adjacent structures to determine the relation between chondromalacia patellae and anatomical MRI parameters. Tibial slope, trochlear depth, lateral trochlear inclination, and lateral patellar tilt angle had significant correlation with chondromalacia. Any increase in lateral trochlear inclination and lateral patellar tilt angle could increase the probability of the disease (Odds ratio OR 1.15, 1.13; 95% CI: 1.03-1.30; 1.02-1.26, respectively), while any increase in medial tibial slope and trochlear depth could decrease the probability of chondromalacia (OR 0.85, 0.06; 95% CI: 0.73-0.98, 0.02-0.17, respectively). We also designed a model for the severity of disease by using the patellar height index (relative odds ratio: 75.9). The result of this study showed the novelty role of tibial anatomy in developing chondromalacia and its mechanism. We also concluded that patellar height might be an important factor in defining disease severity. © 2020 2020 Mohammadreza Tabary, Azadehsadat Esfahani, Mehdi Nouraie, Mohammad Reza Babaei, Ali Reza Khoshdel, Farnaz Araghi, Mostafa Shahrezaee, published by Sciendo

Using Discrete Wavelet Transform for Trend Analysis and Oscillatory Patterns Identification of Temperature (Case Study: Mashhad Synoptic Station)

Introduction: Studying long-term trend changes of meteorological parameters is one of the routine methods in atmospheric studies, especially in the climate change subject. Among the meteorological parameters, temperature is always considered as one of the most atmospheric elements and studying it in order to gain a better understanding of the climate change phenomenon, has been effective. In addition to identifying trends, extraction of oscillatory patterns in the atmospheric phenomena and parameters occurrence can be an applicable and reliable method to explore the complex relations between atmospheric-oceanic cycles and short term or long term consequences of meteorological parameters. Materials and Methods: In this paper, monthly average temperature time series in Mashhad synoptic station in 55 years period (from 1956 to 2010) in monthly, seasonal, annual and seasons separately (winter, spring, summer and autumn) have been analyzed. Discrete wavelet transform and Mann-Kendall trend test were the main methods for performing this research. Wavelet transform is a powerful method in signal processing and it is an advanced version of short time Fourier transforms. Moreover, it has many improvements and more capabilities compared with Fourier transform. In the first step, temperature time series in various time scales (which was mentioned above) have been decomposed via discrete wavelet transforms into approximation (A) and detail (D) components. For the second step, Mann-Kendall trend test was applied to the various combinations of these decomposed components. For detecting the most dominant periodic component for each of the time scales datasets, results of Mann-Kendall test for the original time series and the decomposed components were compared to each other. The nearest value indicated the most dominant periodicity based on the D component’s level. To detect the similarity between results of the Mann-Kendall test, relative error method was employed. Additionally, it must be noted that before applying Mann-Kendall test, time series has to be assessed for its autocorrelation status. If there are seasonality patterns in the studied time series or lag-1 autocorrelation coefficient of data is significant, then some modified versions of the Mann-Kendall test have to be employed. Results and Discussion: Results of this study showed that the temperature trend at every time scaled dataset (monthly, seasonal, annual and seasons separately) is positive and significant. Autocorrelation coefficients indicated that only seasonal time series and winter datasets did not have significant ACFs. On the other hand, monthly and seasonal datasets had seasonality pattern. Based on these results, Hirsch and Slack’s modified version of Mann-Kendall test was employed for monthly and seasonal time series and for the winter temperature data, the original version of the Mann-Kendall test was applied. For the remaining time series, the Hamed and Rao’s modified version of the Mann-Kendall trend test was employed. Dominant periodicities in monthly, seasonal and annual, confirmed the oscillatory behavior of each other. However, in the seasons, it seems that periodic patterns with the same temperature ranges are more similar. On the other hand, due to the greater similarity between the results of the Mann-Kendall test in the warmer seasons and the data with monthly, seasonal and annual time scale, it seems that yearly warm period has more noticeable impacts on the positive and significant trend of temperature in the study area. It must be noted that in any of the studied time series, results of the Mann-Kendall test for detail (D) component was not significant and after adding approximation (A) component, Mann-Kendall statistics turned to a significant value. This happens because the long term variations or trends appear in approximation components in most of the time series. Conclusion: In this study, a powerful signal processing method called wavelet transform was employed to detect the most dominant periodic components in temperature time series in various time scales, in Mashhad synoptic station. Results showed that using frequency-time analysis methods has more benefits compared with the use of only classic statistical methods, since one can explore any time series with more accuracy. Because most of the meteorological variables have periodic structures, it seems that using advanced signal processing methods like wavelet for analysis of these variables can have many advantages compared with linear-based methods. It can be suggested for future studies to use and employ signal processing methods for exploring the large scaled phenomena (e.g. ENSO, NAO, etc.) and discovering the relationship between these phenomena and climate change in recent decades. Keywords: Discrete wavelet transforms, Mann-Kendall test, Oscillatory pattern, Tren

Controlling Differentiation of Stem Cells for Developing Personalized Organ-on-Chip Platforms

Organ-on-chip (OOC) platforms have attracted attentions of pharmaceutical companies as powerful tools for screening of existing drugs and development of new drug candidates. OOCs have primarily used human cell lines or primary cells to develop biomimetic tissue models. However, the ability of human stem cells in unlimited self-renewal and differentiation into multiple lineages has made them attractive for OOCs. The microfluidic technology has enabled precise control of stem cell differentiation using soluble factors, biophysical cues, and electromagnetic signals. This study discusses different tissue- and organ-on-chip platforms (i.e., skin, brain, blood-brain barrier, bone marrow, heart, liver, lung, tumor, and vascular), with an emphasis on the critical role of stem cells in the synthesis of complex tissues. This study further recaps the design, fabrication, high-throughput performance, and improved functionality of stem-cell-based OOCs, technical challenges, obstacles against implementing their potential applications, and future perspectives related to different experimental platforms