فهرست مطالب adel karami

The yield of the wheat crop is affected by the climate and soil parameters such as moisture and nutrients, plant pests and diseases. The main objective of this research is the feature level fusion of multiple effective criteria on the wheat yields using linear and machine learning regression models. The effects of vegetation condition, moisture, nutrients and pests on wheat yield are represented by spectral indices those are extracted from remotely sensed data. Optimum spectral indices are selected as the input features to each of the multiple linear and machine learning regression models such as decision tree, support vector regression and generalized regression neural network. The evaluation of the experimental results in eight wheat fields indicates that the wheat yield prediction based on spectral features fusion show the mean improvement of 0.81 in RMSE comparing with considering only one vegetation index in all regression models. Moreover, all investigated machine learning regression models have about 0.03 more performance than the multiple linear regression model as indicated by R2 coefficient. The generalized regression neural network model with the least RMSE error 0.0063 has the best results compared with other machine learning regression models and MLR.

Emotions are constitutive elements of temperament. The aim of this study was to investigate the relationship between primary emotional traits and symptoms of borderline personality disorder (BPD) and also the predicting role of these traits in BPD symptoms. This cross-sectional study was carried out in Tehran, Iran 2017. The research population included 197 university students. They were recruited using convenience sampling based on the study inclusion/exclusion criteria. The participants completed the Persian version of Affective Neuroscience Personality Scale-2.4 (ANPS 2.4) and Borderline Personality Inventory (BPI). All statistical analyses were carried out in SPSS V16. The findings showed a significant positive correlation between BPD symptoms and playfulness (r=0.17, p=0.001), anger (r=0.32, p=0.001), and sadness (r=0.19, p=0.001). We found a negative relationship between seeking and BPD symptoms (r=-0.22, p=0.001). It was also found that 28% of the total variance of BPD symptoms were explained by primary emotional traits. Anger, playfulness, seeking, and sadness were significant predictors of BPD symptoms. This study confirmed emotional traits of personality. Findings also help to illustrate the possible emotional profiles of people with BPD symptoms. Hence, affective neuroscience approach could be used in diagnosis and treatment of BPD symptoms.

Background and purpose: The Fifth Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) offers an alternative model of personality disorders (PD) in section III alongside the categorical model in section II. In the alternative model of PD the presence of impairment in personality functioning (criterion A) and maladaptive personality traits (criterion B) are essential for diagnosis. There are no official tools for evaluating personality functioning and some current tools developed in Western cultures are taking considerable time. Therefore, this study aimed to develop a Brief Semi-Structured Interview for DSM-5 Personality Functioning (BSSIDPF) according to Iranian culture and evaluating its psychometric propertis. This cross-sectional research was conducted in preliminary and final stages in 34 and 346 individuals, respectively. Participants were selected by convenience sampling in Tehran, Iran 2015-2016. Data were collected using Semi-Structured Interview-Breif Form for DSM-5 Personality Functioning (BSSIDPF), SCID-II-PQ, and NEO-FFI. Data were then and analyzed applying t-test, Cronbach's alpha, and correlation. The scores for inter-rater reliability in personality functioning, identity, self-direction, intimacy, and empathy were 0.94, 0.96, 0.84, and 0.81, respectively (P= 0.01). The Cronbach alpha ranged from 0.81 (intimacy) to 0.89 (self-direction). Brief semi-structured interview for DSM-5 personality functioning was found to have good psychometric properties which could be used in clinical and research settings in Iranian population.

The main aim of this study was to examine the cognitive emotion regulation strategies among prisoners with Borderline Personality Disorder (BPD) and compare those with the normal population, by achieving the patterns of the implemented strategies between the BPD prisoners.
Ninety prisoners with BPD and 92 non-clinical individuals participated in this study. A Structured Clinical Interview (SCID-II) was used to diagnosis of BPD, and the cognitive emotion regulation strategies were evaluated by the Cognitive Emotion Regulation Questionnaire (CERQ). The data were analyzed by independent t test and correlation coefficient via SPSS-16 software.
Independent t-test and correlations analyses showed that cognitive emotion regulation strategies differed in BPD as compared to normal samples, and also showed that self-blame, catastrophization, other blames and rumination strategies exhibited the largest associations with BPD (rs=0.40, 0.38, 0.34 and 0.33, respectively).
The findings showed that the cognitive emotion regulation strategies, especially maladaptive cognitive emotion regulation strategies, had significant relation with BPD symptoms. So, these maladaptive cognitive-emotional components may, therefore, play an essential role in the interventional strategies

The purposes of this study was to examine the relationships between personality traits, cognitive emotion regulation strategies and impulsive behaviors of borderline personality disorder, and to explore which personality traits and cognitive emotion regulation strategies can better predict and explain the impulsive behaviors in borderline personality disorder. This study was a cross-sectional study design. The participants consisted of 78 patients with borderline personality disorder. Patients were recruited from health and medical centers in Tehran, Iran. The Sample was selected based on judgmental sampling. The SCID-II-PQ, Structured Clinical Interview for DSM-IV Axis II (SCID-II), NEO-PI-R, Cognitive Emotion Regulation Questionnaire (CERQ) and Impulsive Behaviors checklist were used for diagnosis and assessment. Pearson Correlation and Multivariate Regression Analysis has been used for data analysis. All statistical analyses were performed using the SPSS 16. Findings indicate that neuroticis m and openness significantly correlated with impulsive behaviors (r = 0.312 and 0.280 respectively, P< 0.001, P< 0.05), and can predict impulsive behaviors in borderline personality disorder. The results also showed that, self-blame, other blame and positive refocus positively correlate with impulsive behaviors (r= 0.32, 0.31 and 0.27 respectively, P< 0.001, P< 0.05). Also significant beta weights were positive for self-blame and other-blame. Those results partially confirm existing studies. Overall, findings showed that neuroticis m, openness, self-blame and other blame are significant predictors of impulsive behaviors in borderline personality disorder.