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Fulltext Artificial neural network modeling of p-cresol photodegradation

Abdollahi Y, Zakaria A, Abbasiyannejad M, Masoumi HR, Moghaddam MG, Matori KA, et al.

Chem Cent J, 2013;7(1):96.
PMID: 23731706 DOI: 10.1186/1752-153X-7-96

The complexity of reactions and kinetic is the current problem of photodegradation processes. Recently, artificial neural networks have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the non-linear relationships between variables in complex systems. In this study, an artificial neural network was applied for modeling p-cresol photodegradation. To optimize the network, the independent variables including irradiation time, pH, photocatalyst amount and concentration of p-cresol were used as the input parameters, while the photodegradation% was selected as output. The photodegradation% was obtained from the performance of the experimental design of the variables under UV irradiation. The network was trained by Quick propagation (QP) and the other three algorithms as a model. To determine the number of hidden layer nodes in the model, the root mean squared error of testing set was minimized. After minimizing the error, the topologies of the algorithms were compared by coefficient of determination and absolute average deviation.
Family Physicians' satisfaction with factors affecting the dynamism of the urban family physician program in the Fars and Mazandaran provinces of Iran

Kabir MJ, Hassanzadeh-Rostami Z, Ashrafian Amiri H, Nasrollapour Shirvani SD, Keshavarzi A, Hosseini S

Malays Fam Physician, 2019;14(3):28-36.
PMID: 32175038

Background and objective: A successful family physician program needs ongoing and full cooperation between people and the organizations in charge. Ensuring the satisfaction of family physicians through improvement of the underlying factors could motivate them to provide high-quality services. This study aimed to determine the family physicians' satisfaction level with the factors affecting the dynamism of the urban family physicians program in the Fars and Mazandaran provinces of Iran.
Method: This cross-sectional study was carried out in urban areas in the Fars and Mazandaran provinces in 2016. The sample consisted of 143 and 96 family physicians, respectively, in Fars and Mazandaran provinces and was selected using the stratified random sampling method. Data were collected using a questionnaire and included both sociodemographic variables and factors assessing the family physicians' satisfaction levels. Each factor was scored based on a Likert scale from 0 to 5 points, and any satisfaction level higher than 3 out of 5 was equated with being satisfied.
Results: The overall satisfaction levels among family physicians in Fars and Mazandaran provinces were 2.77±0.53 and 3.37±0.56, respectively, revealing a statistically significant difference between provinces (p<0.001). Moreover, the mean satisfaction scores for the performances of healthcare centers, insurance companies, specialists, healthcare workers, and the population covered were 2.78±0.1, 2.54±0.9, 2.52±0.8, 4.24±0.07, and 2.96±0.8, respectively. The family physicians' levels of satisfaction were significantly correlated with population size (p=0.02, r= -0.106), and willingness to stay in an urban family physician program (p<0.001, r= +0.398).
Conclusion: This study revealed that family physicians exhibited a low level of satisfaction with the urban family physician program. Given the direct association between family physicians' satisfaction levels and retention in the program, it is expected that family physicians will no longer stay in the program, and it is likely to have subsequent executive problems.

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