Comparison of the effectiveness of medicinal and non-medicinal therapy on the control of primary nocturnal enuresis of school-age children

Background and aims: Enuresis is one of the most common disorders and problematic. Diagnosis of enuresis occurs when the urine is given 2 times in a week, for at least 3 consecutive months. This study was performed to compare the effectiveness of medicinal and non-medicinal therapy to control primary nocturnal enuresis of school-age children. Methods: This study is the one blind clinical trial which has been done on 64 children suffering from enuresis in the 6-12-year-old children in school-age reffered to the Urology Specialized Clinic in Golestan hospital, Ahvaz Jundishapur University of Medical Sciences. Children were divided parochial randomized in two groups of medicinal therapy (n=32) and non-medicinal therapy (n=32). Data collection tools include demographic questionnaire, diary note and check list. The data analysis was used from descriptive and inferential statistical tests(T-test and K2) and SPSS software. Results: The results of the present study showed that the level of improvement during intervention (one and two months) had a statistically significant difference between two groups, pharmacological and non-medicinal treatment groups (P=0.001, P=0.005), respectively. Recovery level in the group of medicinal therapy was higher than the non-medicinal treatment one. After three months from the start intervention stage, statistically significant difference was not observed between two groups (P=0.112); But in the stage of one month after the end of intervention, statistically significant difference was observed between the two groups of medicinal and non-medicinal treatment and the rate of improvement was higher in the non-medicinal al therapy (P=0.009). Conclusion: Due to the effect of duration on the results of the present study, effectiveness of non-medicinal therapy has been more than medicinal therapy. So, it is recommended, non-medicinal therapy in order to effect on the enuresis control of children to be performed in the longer term and continuous follow-up

COMPARATIVE STUDY OF ANN AND ANFIS MODELS FOR PREDICTING TEMPERATURE IN MACHINING

The Mechanism of heat generation at the cutting region (tool-workpiece interface) during machining processes is a highly complicated phenomenon and depends on many process parameters. Elevated temperature during the machining process is a root cause of residual stress on the machined part as well as a cause of rapid tool wear. Although several methods have been developed to measure the temperature in machining, the in-situ application of these methods has many technical problems and restrictions. As a result, the utilization of computational methods to predict temperature in machining is very demanding. In this paper, the artificial intelligent models known as Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) were used to model and predict the temperature in machining. Several experiments were conducted to validate these models. These experiments were carried out on thin-walled AL7075 work pieces to investigate the effect of different machining parameters on temperature in turning. A thermal imaging Infrared (IR) camera was used to measure the temperature of the cutting area during machining. With respect to experimental data, the ANN and ANFIS models were developed and the results obtained from those models were then compared to the experimental results to evaluate the performance of the models. According to the results, the ANFIS model is superior to the ANN model in terms the accurate and reliable prediction of temperature in machining

Computer simulation of a novel pharmaceutical silicon nanocarrier

Saeed Soltani, Soroush Sardari, Sima Azadi SororDrug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, IranAbstract: We show the potential of the nanosilicon structure of the frustules of a typical diatom, Cymatopleura sp., as a new vehicle for drugs. The basic diatom nanostructure is a lattice of SiO2, and computerized methods in a dock project have identified the most likely and the best drug types to load into such a structure.Keywords: diatom, docking, artificial neural network, simulation, computerized method

Comparative study of ann and anfis models for predicting temperature in machining

The Mechanism of heat generation at the cutting region (tool-workpiece interface) during machining processes is a highly complicated phenomenon and depends on many process parameters. Elevated temperature during the machining process is a root cause of residual stress on the machined part as well as a cause of rapid tool wear. Although several methods have been developed to measure the temperature in machining, the in-situ application of these methods has many technical problems and restrictions. As a result, the utilization of computational methods to predict temperature in machining is very demanding. In this paper, the artificial intelligent models known as Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) were used to model and predict the temperature in machining. Several experiments were conducted to validate these models. These experiments were carried out on thin-walled AL7075 work pieces to investigate the effect of different machining parameters on temperature in turning. A thermal imaging Infrared (IR) camera was used to measure the temperature of the cutting area during machining. With respect to experimental data, the ANN and ANFIS models were developed and the results obtained from those models were then compared to the experimental results to evaluate the performance of the models. According to the results, the ANFIS model is superior to the ANN model in terms the accurate and reliable prediction of temperature in machining

An in Silico Approach for Prioritizing Drug Targets in Metabolic Pathway of Mycobacterium Tuberculosis

There is an urgent need to develop novel Mycobacterium tuberculosis (Mtb) drugs that are active against drug resistant bacteria but, more importantly, kill persistent bacteria. Our study structured based on integrated analysis of metabolic pathways, small molecule screening and similarity Search in PubChem Database. Metabolic analysis approaches based on Unified weighted used for potent target selection. Our results suggest that pantothenate synthetase (panC) and and 3-methyl-2-oxobutanoate hydroxymethyl transferase (panB) as a appropriate drug targets. In our study, we used pantothenate synthetase because of existence inhibitors. We have reported the discovery of new antitubercular compounds through ligand based approaches using computational tools

Resilience and sustainable supply chain network design by considering renewable energy

Nowadays, using renewable energy (RE) is faster growing by each country. The managerial and designer of supply chain network design (SCND) have to plan to apply RE in pillars of supply chain (SC). This research indicates resilience and sustainable SCND by considering RE (RSSCNDRE) for the first time. A two-stage new robust stochastic optimization is embedded for RSSCNDRE. The first stage locates facility location and RE and the second stage defines flow quantity between SC components. We solve the model by GAMS-CPLEX solver to locate components of SC and RE. Effects of changing conservative coefficient and demand are investigated and by increasing 20% for conservative coefficient, the cost function increase by 0.5%. Also, when demand is high, activating RE is economically feasible and we cannot buy and supply energy by the government power network and have to supply energy by RE. After activating RE, by increasing 20% for demand, the cost function increases by 6%. We contribute fix-and-optimize strategy to define the upper bound for a large-scale problem. The proposed upper bound for the main model is less than 10% and appropriate for estimating the cost of large-scale problems. This research suggested to equip SC by RE that SC becomes resilient against demand fluctuation and sustainable energy resource compatible with sustainable development goal (SGD7)

Marital Relationship and Its Associated Factors in Veterans Exposed to High Dose Chemical Warfare Agents

Objective: The aim of this study was to determine the associates of marital relationship in mustard exposed veterans. Materials and Methods: Two hundred ninety two married Iranian mustard exposed veterans, who had been exposed to single high dose mustard gas in Iraq-Iran war, were assessed for marital adjustment with Revised Dyadic Adjustment Scale (RDAS). Census sampling was done. The patients' quality of life (SF-36), spirometric measures and war related data were also extracted. Results: A total of 189 subjects (65%) completed our study. The mean (±SD) of the RDAS Total score, RDAS Dyadic Consensus , RDAS Affectional Expression, RDAS Dyadic Satisfaction , and RDAS Dyadic Cohesion were 50.61 (8.16), 16.67 (2.77), 7.62 (1.84), 14.76 (3.39), and 11.54 (3.79), respectively. RDAS Dyadic satisfaction was correlated with SF-36 and all its sub-scores (p<0.05). RDAS total score showed significant correlation with SF-36 total score and most of its sub-scores (p<0.05). RDAS affective expression was significantly correlated with role limitation, social function, general mental health, vitality, General health perceptions, physical composite score (PCS) and mental composite score (MCS) (p<0.05). RDAS dyadic consensus was not correlated with any SF-36 sub-scores. Conclusion: Veterans health team including physicians, psychologists and/or psychiatrists should know that poorer marital satisfaction is linked with lower quality of life scores, late after mustard exposure, although marital relationship is independent of spirometric findings, age, duration from exposure and comorbidity score

How Much Importance Do We Give to Target Audiences in Article Writing?

Objectives: Writing papers can be used as a means to convey amessage. Knowledge transfer is also about conveying the rightmessage to the right target audience. The aim of this study was todetermine the proportion of articles that had mentioned a clearmessage and the target audience in the abstract and the article as awhole, and also to examine their association with different determinantfactors.Methods: Articles published from 2001 to 2006 that were basedon clinical and health system research conducted on Iranian populationsand on maternal care, diabetes and tuberculosis weresearched systematically in domestic and international databases.Eventually checklists (Additional file 1) were completed for 795articles.Results: Overall, 98.5% of articles had a clear message, whereas12.5% had addressed the direct target audience. Presence of a clearmessage in formatted abstracts were seen 3.6 times more (CI95%:1.5-8.7) than in articles without formatted abstracts (p = 0.005).Addressing of the direct target audience was seen twice as much inhealth system research articles as compared to clinical studies,odds ratio was 2.3 (CI95%: 1.47-3.48 ,p<0.001).Conclusions: Creating a format for journal abstracts seems to bean effective intervention for presenting the message in articles