Effectiveness of Acceptance and Commitment Therapy on Cognitive Emotion Regulation in Men under Methadone Treatment

Introduction: Today, third wave therapy in psychotherapy puts special emphasis on the individuals’ awareness  as well as their emotional and cognitive acceptance rather than challenging the cognitions. Therfore, this study aimed to investigate the effectiveness of acceptance and commitment therapy on cognitive emotion regulation in the addicted men under Methadone treatment. Method: The study population consisted of all the addicted men under Methadone treatment referring to an addiction treatment clinic in Isfahan in 2014-2015, out of which 24 addicted men were selected via convenience sampling method, and then were appointed randomly into two experimental and control groups (n= 12). Both groups filled Cognition Emotion Regulation Questionnaire. The therapeutic interventions based on aacceptance and commitment therapy were held for the experimental group for 8 sessions of one hour once a week. Ultimately, the collected data were analyzed applying SPSS software via ANCOVA method . Result: The findings of the present study demonstrated a significant positive impact of acceptance and commitment  therapy on reduction of self blame, rumination, catastrophizing as well as blaming others. Moreover, a significant increase was observed in regard with the acceptance, positive refocus, refocus on planning, positive reappraisal and positive perspective. Conclusion: It was concluded that acceptance and commitment therapy seems to be beneficial to enhancing the emotion regulation of addicted men under Methadone treatment, which can be related to training the referrents to accept their thoughts and conditions

Determining the Effectiveness of Lactobacillus Casei in Camel Milk on Lipid and Sugar Parameters in Type 1 Diabetic Rats

Introduction: Nutritional interventions are one of the most effective methods of diabetes prevention and control. Along with usual treatments, camel milk has had positive effects on the blood sugar of diabetic patients. The present study was conducted with the aim of investigating the effect of lactobacillus casei present in camel milk on the sugar and lipid profile of type 1 diabetic rats. Methods: This was of an intervention study and carried out by an experimental trial method. 32 mice were randomly divided into four groups of eight. After making diabetic, the rats were gavage with 2cc of the product prepared for each group every other day. Evaluations (weight, serum concentrations of glucose, FBS, urea, creatinine, uric acid, LDL, HDL, TG, cholesterol, as well as liver enzymes AST, ALT, and ALP) were performed after 30 days of receiving gavage. In order to analyze the data, SPSS16 software was used. Results: The mean weight and serum concentration of LDL in the treatment group with standard and native Lactobacillus casei probiotics was significantly lower than the diabetic control group (P0.05). Conclusion: It seems that lactobacillus casei probiotics from camel milk may be able to improve weight loss and improve lipid profile (increase in HDL, decrease in LDL and LDL/HDL ratio) in type 1 diabetic rats, which requires more extensive studies in this field

Analysis of the performance of a crude-oil desalting system based on historical data

Our study is keyed to the development of a methodological approach to assess the workflow and performance associated with the operation of a crude-oil desalting/demulsification system. Our analysis is data-driven and relies on the combined use of (a) Global Sensitivity Analysis (GSA), (b) machine learning, and (c) rigorous model discrimination/identification criteria. We leverage on an extensive and unique data-set comprising observations collected at a daily rate across a three-year period at an industrial plant where crude oil is treated through a combination of demulsification/desalting processes. Results from GSA enable us to quantify the system variables which are most influential to the overall performance of the industrial plant. Machine learning is then applied to formulate a set of candidate models whose relative skill to represent the system behavior is quantified upon relying on model identification criteria. The integrated approach we propose can then effectively assist to (a) modern and reliable interpretation of data associated with performances of the crude oil desalting process and (b) robust evaluation of future performance scenarios, as informed by historical data