Azade Tahernejad; Reza Mostafavi; Somaye Tahernejad; Matin Rostami
Abstract
Objective: The occurrence of crises such as the outbreak of the new coronavirus (COVID-19) showed that the availability of a mask that fits the face is of great importance for individuals. The present study was performed to design a tool to assess the facial fitness of the mask based on face dimensions. ...
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Objective: The occurrence of crises such as the outbreak of the new coronavirus (COVID-19) showed that the availability of a mask that fits the face is of great importance for individuals. The present study was performed to design a tool to assess the facial fitness of the mask based on face dimensions. Methods: A hybrid method is introduced which consists of modeling of a fuzzy system using a neural network, so that with only one-time training of this neuro-fuzzy system, ANFIS, it is possible to easily determine the fit of N95 respiratory mask only by applying the anthropometric dimensions of the face. Six anthropometric dimensions of the face were assigned as the inputs and respiratory mask fitness was assigned as the output of the ANFIS model. Results: The proposed neuro-fuzzy system, ANFIS, is designed in such a way that by specifying the input parameters for each individual, the fitness of the mask to the face can be predicted. Conclusion: According to the results of the probability predicted by the neuro-fuzzy system, using the data of the six dimensions of the face, in about 75 percent of the cases the fitness of the mask to the face of individuals can be predicted accurately; therefore, the designed ANFIS network can be used instead of the fitness test to predict the fitness of the respiratory mask to the face using the anthropometric data of the face of the individuals only when it is not possible to perform the fit testing.
Mohsen Kalantari; Qasem Asgari; Khadijeh Rostami; Shahrbano Naderi; Iraj Mohammadpour; Masoud Yousefi; Mohammad Hassan Davami; Kourosh Azizi
Abstract
Background: Anti-Toxoplasma antibodies were identified in female university students referred to Valie-Asr hospital of Mamasani from Azad and Payame-Noor Universities, using serological and molecular methods. Methods: Based on the prevalence and characteristics method, 504 serum samples were collected ...
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Background: Anti-Toxoplasma antibodies were identified in female university students referred to Valie-Asr hospital of Mamasani from Azad and Payame-Noor Universities, using serological and molecular methods. Methods: Based on the prevalence and characteristics method, 504 serum samples were collected from female university students, during 2015, and evaluated by Enzyme-Linked Immun-Sorbent Assay (ELISA), Modified Agglutination Test (MAT), and Polymerase Chain Reaction (PCR) based on B1 gene for detection of Toxoplasma gondii. The data were analyzed using SPSS 19 software. Results: Out of 504 studied female students, 27 (5.36%) and 36 (7.14%) cases were found to be positive for anti-Toxoplasma IgG antibodies by MAT and ELISA, respectively. Moreover, 5 (0.99%) cases were found to be positive for anti-Toxoplasma IgM. PCR detected the Toxoplasma DNA in 58 out of 504 (11.51%) samples. Conclusions: Findings of the current study revealed that Toxoplasma was a common infection among female university students in Mamasani district in Fars province. Seronegative individuals are at risk for the disease, as well as congenital toxoplasmosis in later stages of their life. Preventive measures should be taken to reduce the rate of infection.
