Prevalence of Cannabis Lifetime Use in Iranian High School and College Students: A Systematic Review, Meta-Analyses,and Meta-Regression

Cannabis is the most widely used substance in the world. This study aimed to estimate the prevalence of cannabis lifetime use (CLU) in high school and college students of Iran and also to determine factors related to changes in prevalence. A systematic review of literature on cannabis use in Iran was conducted according to MOOSE guideline. Domestic scientific databases, PubMed/Medline, ISI Web of Knowledge, and Google Scholar, relevant reference lists, and relevant journals were searched up to April, 2014. Prevalences were calculated using the variance stabilizing double arcsine transformation and confidence intervals (CIs) estimated using the Wilson method. Heterogeneity was assessed by Cochran's Q statistic and I-2 index and causes of heterogeneity were evaluated using meta-regression model. In electronic database search, 4,000 citations were retrieved, producing a total of 33 studies. CLU was reported with a random effects pooled prevalence of 4.0 (95 CI = 3.0 to 5.0). In subgroups of high school and college students, prevalences were 5.0 (95 CI = 3.0 to -7.0) and 2.0 (95 CI = 2.0 to -3.0), respectively. Meta-regression model indicated that prevalence is higher in college students (beta = 0.089, p < .001), male gender (beta = 0.017, p < .001), and is lower in studies with sampling versus census studies (beta = -0.096, p < .001). This study reported that prevalence of CLU in Iranian students are lower than industrialized countries. In addition, gender, level of education, and methods of sampling are highly associated with changes in the prevalence of CLU across provinces

Prevalence of Cannabis Lifetime Use in Iranian High School and College Students: A Systematic Review, Meta-Analyses,and Meta-Regression

Cannabis is the most widely used substance in the world. This study aimed to estimate the prevalence of cannabis lifetime use (CLU) in high school and college students of Iran and also to determine factors related to changes in prevalence. A systematic review of literature on cannabis use in Iran was conducted according to MOOSE guideline. Domestic scientific databases, PubMed/Medline, ISI Web of Knowledge, and Google Scholar, relevant reference lists, and relevant journals were searched up to April, 2014. Prevalences were calculated using the variance stabilizing double arcsine transformation and confidence intervals (CIs) estimated using the Wilson method. Heterogeneity was assessed by Cochran's Q statistic and I-2 index and causes of heterogeneity were evaluated using meta-regression model. In electronic database search, 4,000 citations were retrieved, producing a total of 33 studies. CLU was reported with a random effects pooled prevalence of 4.0 (95 CI = 3.0 to 5.0). In subgroups of high school and college students, prevalences were 5.0 (95 CI = 3.0 to -7.0) and 2.0 (95 CI = 2.0 to -3.0), respectively. Meta-regression model indicated that prevalence is higher in college students (beta = 0.089, p < .001), male gender (beta = 0.017, p < .001), and is lower in studies with sampling versus census studies (beta = -0.096, p < .001). This study reported that prevalence of CLU in Iranian students are lower than industrialized countries. In addition, gender, level of education, and methods of sampling are highly associated with changes in the prevalence of CLU across provinces

Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

The choroid layer is a vascular layer in human retina and its main function is to provide oxygen and support to the retina. Various studies have shown that the thickness of the choroid layer is correlated with the diagnosis of several ophthalmic diseases. For example, diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. Despite contemporary advances, automatic segmentation of the choroid layer remains a challenging task due to low contrast, inhomogeneous intensity, inconsistent texture and ambiguous boundaries between the choroid and sclera in Optical Coherence Tomography (OCT) images. The majority of currently implemented methods manually or semi-automatically segment out the region of interest. While many fully automatic methods exist in the context of choroid layer segmentation, more effective and accurate automatic methods are required in order to employ these methods in the clinical sector. This paper proposed and implemented an automatic method for choroid layer segmentation in OCT images using deep learning and a series of morphological operations. The aim of this research was to segment out Bruch’s Membrane (BM) and choroid layer to calculate the thickness map. BM was segmented using a series of morphological operations, whereas the choroid layer was segmented using a deep learning approach as more image statistics were required to segment accurately. Several evaluation metrics were used to test and compare the proposed method against other existing methodologies. Experimental results showed that the proposed method greatly reduced the error rate when compared with the other state-of-the art methods

Learning Abstract Concepts of Modern Physics Applied Laser Areas to Help

The focus of this study was to clarify the degree of relationship between field Transfer of Learning by means of application in the modern physics (laser) and common field. To achieve this goal an intact group of 85 students in introductory level college in Shahreray zone in Tehran in Iran participated in test. The major objectives of the test were to investigate students’ transfer of physics learning from their experiences of watching laser applications to the provided physical models, from one model to the other and from the models to the modern physics (laser) problems. To find the degree of relationship between tow variables point- biserial correlation coefficient was used. To compare the mean scores of the tow variables the independent T-test technique was used. The result of the statistical analyses revealed that in the knowledge domain that was significant difference between the control and the experimental groups

The compensatory effect of regular exercise on long-term memory impairment in sleep deprived female rats

Previous studies have been shown that exercise can improve short-term spatial learning, memory and synaptic plasticity impairments in sleep deprived female rats. The aim of the present study was to investigate the effects of treadmill exercise on sleep deprivation (SD) induced impairment in hippocampal dependent long-term memory in female rats. Intact and ovariectomized female rats were used in the current study. Exercise protocol was 4 weeks treadmill running. Twenty four hour SD was induced by using multiple platform apparatus after learning phase. Spatial learning and long-term memory was examined by using the Morris Water Maze (MWM) test. Our results indicated that sleep deprivation impaired long term memory in the intact and ovariectomized female rats, regardless of reproductive status (p<0.05) and treadmill exercise compensated this impairment (p<0.05). In conclusion the results of the current study confirmed the negative effect of SD on cognitive functions and regular exercise seems to protect rats from these factors, however more investigations need to be done

Review of Experimental Observations of Intermodal Nonlinearities in a Few-Mode Fiber

We review the measurements of inter-modal nonlinear effects performed on a 4.7-km few-mode fiber where both inter-modal cross-phase modulation and inter-modal four-wave mixing were observed

Validation of optical low coherence reflectometry retinal and choroidal biometry

To compare measurements of retinal thickness (RT) and choroidal thickness (ChT) obtained with an optical low coherence reflectometry (OLCR) biometer (Lenstar LS 900) with those obtained with a spectral domain optical coherence tomographer (SD OCT) (Copernicus SOCT HR) in young normal subjects

Mode-Equalized Distributed Raman Amplification in 137-Km Few-Mode Fiber

We experimentally demonstrate 8 dB of mode-equalized distributed Raman gain using a backward pumping scheme. The equivalent noise figure of the amplifier is -1.5 dB, and the amplifier was successfully employed to demonstrate 6-channel mode-multiplexed MIMO transmission over 137-km few-mode fiber