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There is a developing interest in flexible sensors, especially in the new and intelligent generation of textiles. The purpose of this paper is to fabricate a flexible capacitive sensor on a PET fabric and to investigate some affecting factor on its performance.

PET fabric, coated with graphite or with graphite/PEDOT:PSS, was applied as electrodes. Two types of electrospun nanoweb layers from polyamide and polyvinyl alcohol polymers were used as dielectrics. Some factors including electrode area, fabric conductivity, fabric roughness, dielectric thickness, dielectric insulation type and vertical pressure were considered as independent variables. The capacity of the sensor and its detection threshold considered as the outcome (response) variables. Control samples were fabricated by using aluminum plates and cellulosic layer as electrodes and dielectric, respectively.

Results showed that post-coating with PEDOT:PSS would improve the conductivity of electrodes up to 300 Ω in comparison with just graphite-coated samples. It was also found that either by improving the conductivity or increasing the area of electrode plates the sensitivity of sample would be increased in pressure stimulating tests.

The fabric sensor showed remarkable response toward pressure with a lower detection threshold of 30mN/cm² (obtained capacity ~ 4×104 pF) in comparison with aluminum electrode sensors.

During 2008 Olympics, Michael Phelps had a record-breaking performance. One contributing factor to his success was the full-body swimsuit he was wearing. Cases like these were the reason for the initiation of study and research for improvement in the new generation of sport gears. The purpose of this paper is to show that drag force plays a significant role in swimmers’ speed through the water; thus, using swimsuit with minimized drag force becomes imperative for Olympians like Michael Phelps.

This paper shows a comparative evaluation of hydrodynamics of three PET fabrics with different finishings that have hydrophobic behavior over a range of Reynolds number 1.0218×10³ and 1.365×10³ in the air medium at 20°C ambient temperature, and Reynolds number ranging from 15.68856×10³ to 20.958×10³ in the water medium at 20°C ambient temperature under stable stretch conditions.

The results show that hydrophobic finishing reduces the drag force by 1.5 percent at the angles of attack of 0 and 90 degrees.

If all the factors are considered to be stable for the swimmer, the drag force reduces by 1.5 percent, thereby increasing the speed of swimmer by 1.22 percent, which means that the record of the swimmer improves by 0.819 seconds.

This paper is based on the simulation of wind tunnel experiment for better understanding and predicting the behavior of PET fabric in the wind tunnel. This software calculates the drag force of fabric, illustrates pressure in the surrounding of airfoil and velocity of wind in the tunnel during different angles of attack (0°, 45° and 90°). The paper aims to discuss these issues.

The sol-gel method was applied for the synthesis of silica nano particles. So, PET fabric was coated with precursor (Tetra ethyl ortho silicate) solution first and the process continued on PET fabric. The morphology of obtained hydrophobic fabric samples and their surface roughness was observed and determined by atomic microscopes (AFM and SEM). Experimental data were used for simulation and modeling, and then results were interpreted.

It was concluded that the surface roughness and its amount can play a significant role in the drag reduction of PET fabric, and surface roughness can change the boundary layer from laminar to turbulent.

At 45 degrees angle of attack, larger boundary layer separation results in a large increase in the drag force. This model is useful for predicting flow behavior in the experimental wind tunnel.

The purpose of the paper is to investigate the extent to which a model based on financial and non-financial variables predicts auditors' decisions to issue qualified audit reports in the case of companies listed on the Tehran Stock Exchange (TSE).

The authors utilized data from the financial statements of 96 Iranian firms as the sample over a period of five years (2012–2016). A total of 480 observations were analysed using a probit model through 11 primary financial ratios accompanying non-financial variables, including the type of audit firm, auditor turnover and corporate performance, which affect the issuance of audit reports.

The results demonstrated high explanatory power of financial ratios and type of audit firm (the national audit organization vs other local audit firms) in explaining qualifications through audit reports. The predictive accuracy of the estimated model is evaluated using a regression model for the probabilities of qualified and clean opinions. The model is reliable, with 72.9% accuracy in classifying the total sample correctly to explain changes in the auditor's opinion.

This study contains some limitations. First, it is likely that similar researches in developed countries set a large sample (e.g. over 1,000 firms) including more years, but the authors cannot follow such a trend due to data access restrictions. Second, banks and financial institutions, investment and holding firms are removed from the sample, because their financial structure is diverse. The third limitation of the study represents the different economic and cultural conditions of Iran compared to other countries. Future studies could focus on internal control material weaknesses or earnings management to predict audit opinion in emerging economies including Iran.

The paper has practical implications and can assist auditors in identifying factors motivating audit report qualifications, mainly in emerging economies.

The paper contributes to auditing research, since very little is known about the determinants of audit opinion in emerging markets including Iran; it also constitutes an addition to previous knowledge about audit opinion in the context of TSE. The paper is one of the rare studies predicting auditor opinions using both financial variables and non-financial metrics.