ABSTRACT
Background: The presence of gluten proteins in rice flour leads to some problems for patients of celiac; a digestive autoimmune disease. Consumption of a non-gluten regime can decrease the effects of this disease. The aim of this study was to produce a non-gluten cake with an appropriate quality and high nutritional value by using rice flour, quinoa flour, Persian gums, and Tragacanth
Methods: The effect of addition of Persian gums, Tragacanth, and a combination of both of these compounds at levels of 0.5, 1, and 1.5% on texture, color, and sensory characteristics of these cakes was evaluated in this study
Results: The results showed that solidity and viscosity factors were elevated by addition of gum to cake. Using of gums in cakes leads to moisture maintenance inside the cake texture and thus improves mastication property. Furthermore, the results of porosity evaluation showed that addition of Persian gums and Tragacanth decreases the size and increases the number of gas cells inside the cake texture and improves porosity. The best porosity was related to the sample containing 1.5% Persian gum and Tragacanth. The treatment that contained 0.75% Persian gum and 0.75% Tragacanth had the highest acceptability among consumers
Conclusions: Results showed that Persian and Tragacanth gums, whether used independently or in combination, can improve the quality and organoleptic characteristics of gluten-free cakes
ABSTRACT
Background: Nowadays, the health work decision makers need to analyze a huge amount of data and consider many conflicting evaluation criteria and sub-criteria. Therefore, an ergonomic evaluation in the work environment in order to the control occupational disorders is considered as the Multi Criteria Decision Making [MCDM] problem. In this study, the ergonomic risks factors, which may influence health, were evaluated in a manufacturing company in 2014. Then entropy method was applied to prioritize the different risk factors
Methods: This study was done with a descriptive-analytical approach and 13 tasks were included from total number of employees who were working in the seven halls of an ark opal manufacturing [240]
Required information was gathered by the demographic questionnaire and Assessment of Repetitive Tasks [ART] method for repetitive task assessment. In addition, entropy was used to prioritize the risk factors based on the ergonomic control needs
Results: The total exposure score based on the ART method calculated was equal to 30.07+/-12.43. Data analysis illustrated that 179 cases [74.6% of tasks] were in the high level of risk area and 13.8% were in the medium level of risk. ART- entropy results revealed that based on the weighted factors, higher value belongs to grip factor and the lowest value was related to neck and hand posture and duration
Conclusions: Based on the limited financial resources, it seems that MCDM in many challenging situations such as control procedures and priority approaches could be used successfully. Other MCDM methods for evaluating and prioritizing the ergonomic problems are recommended
ABSTRACT
Background: Major injuries and death in accidents have roots in drowsiness. Sleepiness is a main result of insufficient sleep. It is vital to explore drowsiness and its level. There are various sorts of methods in the forms of subjective and objective approaches. The goal of this study was to detect the association of subjective and interpretive drowsiness with facial dynamic changes
Methods: This experimental study was conducted in the Virtual Reality Lab, in Khaje-Nasir Toosi University of Technology, Tehran Iran on 40 drivers in 2015. Facial Dynamic changes [eyes, mouth and eyebrows], Karolinska Sleepiness Scale [KSS] and Observer Rating of Drowsiness [ORD] were applied. The neural network and Viola-Jones were utilized for facial characteristics detection. Statistical analyses were conducted using SPSS version 21
Result: Thirty-four drivers got drowsy during the test. They were selected randomly among suburban drivers at the age in a range of 26 to 60 yr old. Descriptive statistics of the dynamic changes in eyebrows, mouth and eyes showed that these features were of meaningful changes with respect to the level of drowsiness during driving. A relationship between the dynamic changes of facial features and ORD was recognized. Moreover, there was a significant relationship between facial expression and drowsiness [P<0.05]
Conclusions: Results of KSS and ORD illustrated that there were dynamic changes in eyes and mouth and eyebrow parameters while driver felt sleepy. This research is helpful in a way that specific changes in elements of face could be effective to provide tools to predict drowsiness