Showing 44 results for Hosseini
Mr Mohsen Shamsi, Mr Ali Kulivand, Mr Mohammadjavad Ghannadzadeh, Ms Mahboobeh Khorsandi, Mr Seyedhamed Mirhosseini, Mr Amir Almasi-Hashiani, Mr Behrooz Karimi, Mr Seyednadali Alavi Bakhtiarvand, Ms Masoume Naderi Noreyni,
Volume 25, Issue 4 (October & November 2022)
Abstract
Introduction: Today, with the increase in population, the per capita production of waste materials and the subsequent threat and destruction of the environment is an increasing process, and waste management by the people of a society can play an essential role in reducing this problem. Therefore, the aim of this study was determine of predicting the waste management behaviors of households in Arak city in 2022.
Methods: This is a cross-sectional and analytical study that was carried out on 600 mothers of households in Arak city, who were selected by multi-stage sampling. The data collection tool was a valid and reliable researcher-made questionnaire that included demographic characteristics, knowledge, attitude and behavior of households in the field of waste management. Data were analyzed using SPSS software and t-test, chi-square and regression tests. This study was approved by the research ethics committee of Arak University of Medical Sciences (Code: IR.ARAKMU.REC.1401.040).
Results: The average age of the studied was 39±11 years and the number of family members was 3.6. In terms of type of housing, most of them lived in apartments (44%) and a smaller number lived in complexes (14%). 65 percent of the people had not received the training on the waste separation plan from the source, and among the effective training methods, the majority (38 percent) of the people had overestimated the effectiveness of the training through the Internet. The mean and standard deviation of knowledge was 66±19, attitude was 84±11 and performance was 73±18. The majority of the people studied had a good level of awareness and attitude. The regression analysis model showed that the greatest impact on the waste management behavior of the samples was the age of the people, their knowledge and attitude, which predicted a total of 33% of the waste management behavior.
Conclusions: Considering the favorable state of awareness and attitude of households in Arak city, it seems that for better waste management, other environmental factors should be emphasized, including sources of waste production at the source. Also, based on the prediction model, it is still important to inform and change the attitude of households in Arak city for better performance at younger ages.
Ali Jadidi, Soleiman Zand, Mr Ali Khanmohamadi Hezave, Negin Hosseini,
Volume 27, Issue 1 (3-2024)
Abstract
Introduction: Quality of life is one of the most influential issues that can encourage a person to continue a happy and healthy life. On the other hand, spiritual health is one of the dimensions of health and a sense of harmonious connection between oneself, others, nature, and beyond, and leads to understanding the ultimate purpose and meaning in life. The purpose is to determine the relationship between spiritual health and quality of life in university students in Arak. The results of this study can be used to formulate strategic plans improve spiritual health and the quality of students' lives.
Methods: First, the population of each university in Arak city was measured, and taking into account their population and establishing a ratio between the sample size of the study and the population of each university, people who had the characteristics of entering the study were included in the study. The sample size was 400 people and was conducted on students who have been studying at the university for at least six months. After obtaining the consent of the participants, the researchers filled out the questionnaire through interviews with the students. The questionnaires included two instruments: a spiritual health questionnaire and a quality of life questionnaire with 36 questions.
Results: No significant relationship was observed between spiritual health and demographic variables. Likewise, spiritual health had no statistically significant relationship with demographic variables. The analysis of the study data showed that there is a positive correlation between the quality of life and spiritual health of students. (P < 0.05).
Conclusions: According to the horoscope results, there is a relationship between the quality of life and the spiritual health of the students of Arak universities. By improving the quality of students' lives, we can increase their spiritual health, and even by increasing their spiritual health, we can witness the improvement of students' quality of life.
Seyed Sadegh Hosseini, Mohammad Reza Yamaghani,
Volume 27, Issue 4 (10-2024)
Abstract
Introduction: Nowadays, the use of artificial intelligence and machine learning has impacted all fields of study. Utilizing these methods for identifying individuals' emotions through integrating audio, text, and image data has shown higher accuracy than conventional methods, presenting various applications for psychologists and human-machine interaction. Identifying human emotions and individuals' reactions is crucial in psychology and psychotherapy. Emotional identification has traditionally been conducted individually and by analyzing facial expressions, speech patterns, or handwritten responses to stimuli and events. However, depending on the subject's conditions or the analyst's circumstances, this approach may lack the required accuracy. This paper aimed to achieve high-precision emotional recognition from audio, text, and image data using artificial intelligence and machine learning methods.
Methods: This research employs a correlation-based approach between emotions and input data, utilizing machine learning methods and regression analysis to predict a criterion variable based on multiple predictor variables (the emotional category as the criterion variable and the features, audio, image, and text variables as predictors). The statistical population of this study is the IEMOCAP dataset, and the data type of this research is a mixed quantitative-qualitative approach.
Results: The results indicated that combining audio, image, and text data for multi-modal emotional recognition significantly outperformed the recognition of emotions from each data alone, exhibiting a precision of 82.9% in the baseline dataset.
Conclusions: The results demonstrate a considerably acceptable precision in identifying human emotions through audio integration, text, and image data compared to individual data when using machine learning and artificial intelligence methods.
Rahmatallah Fatahian, Behnaz Karimi, Seyed Reza Hosseini, Kianoush Forouhar Majd, Ayatallah Hatempour ,
Volume 28, Issue 3 (8-2025)
Abstract
Introduction: The study discusses the impact of thiamine on the kidney tissue of rats that have been exposed to copper oxide nanoparticles. The research examined how thiamine correlates with the level of kidney damage caused by the intrusion of nanoparticles.
Methods: In this experimental study, forty male Wistar rats were randomly divided into four groups (10 rats per group). Two groups of rats were used as the control group (I) and the thiamine group (II). Rats of group III were administered an intraperitoneal injection of 25 mg/kg body weight of copper oxide nanoparticles for 14 days. Rats in group IV received the same dose of copper oxide nanoparticles along with thiamine (30 mg/kg body weight).
Results: The histopathological findings showed disruption of the arrangement of convoluted tubules and their disintegration and widening of the tubular lumen, cell separation and tubular necrosis in the majority of the renal tubules in-group III. In the group treated with copper oxide nanoparticles along with thiamine (IV), the pathological changes were slight and the majority of the tubules had retained normal structure. Statistically significant differences in the levels of some serum biochemical parameters (catalase, superoxide dismutase, TBARS, and TAC) were observed in groups III and IV on day 14 when compared to the control group.
Conclusions: This study demonstrated that thiamine can be utilized as an effective compound to reduce the damage caused by nanoparticles to kidney tissue and may lead to significant improvement in the health of kidney tissue in individuals suffering from damage caused by these nanoparticles.
