Social network sites as educational factors

Background: In this present era, the technology development has established certain type of communication. Nowadays education as the fundamental principle in transferring cognition to the learners has found various methods. Recently the concept that social networks could be effective tool in easing the achievement to the educational goals has been under attention. Therefore, this investigation is trying to find out whether, the social networks could play role on the process of education among students? Materials and Methods: This cross sectional descriptive study was performed on 1000 students from 7 medical universities in 2015. The data collection tool was questionnaire that was approved Cronbach's alpha was 0.85. Meanwhile its validity was confirmed too. The obtained data were analyzed by the descriptive statistic, ANOVA, Turkey and used X2 SPSS-19. Results: In this investigation, 940 subjects were under study. 85 used daily the social network. The highest usage was attributed to the Telegram. 52 preferred image suitable for transferring of information. Even though, 73 believed that these networks have significant effects on coordinating of students with in university charges. Conclusion: Considering the findings of the present study, it is proposed that the universities integrate the social networks in the education programs and recognize it as the awareness factor, therefore benefit it in the educational affairs. © 2016 Alireza Ebrahimpour, Farnaz Rajabali, Fatemeh Yazdanfar, Reza Azarbad, Majid Rezaei Nodeh, Hasan Siamian, Mohammad Vahedi

Comparative Study of the Effectiveness of sub mucosal Partial Inferior Turbinectomy and Out fracture of Inferior Turbinate in the Nasal Respiratory Function of Rhinoplasty Patients

INTRODUCTION: The inferior turbinate is a critical and dynamic structure during rhinoplasty in the internal valve. Many surgeons try to preventively reduce its resistance against the path in the post-rhinoplasty period. To this end, the two methods of "sub mucosal partial inferior turbinectomy" and "inferior turbinate out fracture" are compared in the present study. METHODS: In this clinical study, 110 rhinoplasty candidates were randomly divided into two groups, namely sub mucosal partial inferior turbinectomy and out fracture of the inferior turbinate. To assess the complications, the Sino-Nasal Outcome Test (SNOT-22) was used prior to surgical intervention, and 1, 2, 3, 6, and 12 months following the rhinoplasty procedures. RESULTS: Based on the results of this clinical study and according to the SNOT-22 questionnaire, there was no significant difference between the two groups prior to surgery and a month following the surgery (P > 0.05). However, the average SNOT-22 score for the sub mucosal partial inferior turbinectomy group was significantly lower than that of the group with the out fracture of the inferior turbinate, 2, 3, 6, and 12 months following the surgery. CONCLUSION: Both "sub mucosal partial inferior turbinectomy" and "out fracture of inferior turbinate" are effective methods in improving the respiratory function of rhinoplasty patients, yet the former method is more effective than the latter as regards improving the respiratory function of patients

Genetics of intellectual disability in consanguineous families

Autosomal recessive (AR) gene defects are the leading genetic cause of intellectual disability (ID) in countries with frequent parental consanguinity, which account for about 1/7th of the world population. Yet, compared to autosomal dominant de novo mutations, which are the predominant cause of ID in Western countries, the identification of AR-ID genes has lagged behind. Here, we report on whole exome and whole genome sequencing in 404 consanguineous predominantly Iranian families with two or more affected offspring. In 219 of these, we found likely causative variants, involving 77 known and 77 novel AR-ID (candidate) genes, 21 X-linked genes, as well as 9 genes previously implicated in diseases other than ID. This study, the largest of its kind published to date, illustrates that high-throughput DNA sequencing in consanguineous families is a superior strategy for elucidating the thousands of hitherto unknown gene defects underlying AR-ID, and it sheds light on their prevalence

How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?

Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition

A Stable Biologically Motivated Learning Mechanism for Visual Feature Extraction to Handle Facial Categorization

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task

Risk factors for moderate and severe persistent pain in patients undergoing total knee and hip arthroplasty : a prospective predictive study

Persistent post-surgical pain (PPSP) is a major clinical problem with significant individual, social and health care costs. The aim of this study was to examine the joint role of demographic, clinical and psychological risk factors in the development of moderate and severe PPSP after Total Knee and Hip Arthroplasty (TKA and THA, respectively). This was a prospective study wherein a consecutive sample of 92 patients were assessed 24 hours before (T1), 48 hours after (T2) and 4-6 months (T3) after surgery. Hierarchical logistic regression analyses were performed to identify predictors of moderate and severe levels of PPSP. Four to six months after TKA and THA, 54 patients (58.7%) reported none or mild pain (Numerical Rating Scale: NRS 3). In the final multivariate hierarchical logistic regression analyses, illness representations concerning the condition leading to surgery (osteoarthritis), such as a chronic timeline perception of the disease, emerged as a significant predictor of PPSP. Additionally, post-surgical anxiety also showed a predictive role in the development of PPSP. Pre-surgical pain was the most significant clinical predictive factor and, as expected, undergoing TKA was associated with greater odds of PPSP development than THA. The findings on PPSP predictors after major joint arthroplasties can guide clinical practice in terms of considering cognitive and emotional factors, together with clinical factors, in planning acute pain management before and after surgery.This work was supported by a Project grant (PTDC/SAU-NEU/108557/2008) and by a PhD grant (SFRH/BD/36368/2007) from the Portuguese Foundation of Science and Technology, COMPETE and FEDER. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

The XMM Cluster Survey: Exploring scaling relations and completeness of the Dark Energy Survey Year 3 redMaPPer cluster catalogue

We cross-match and compare characteristics of galaxy clusters identified in observations from two sky surveys using two completely different techniques. One sample is optically selected from the analysis of three years of Dark Energy Survey observations using the redMaPPer cluster detection algorithm. The second is X-ray selected from XMM observations analysed by the XMM Cluster Survey. The samples comprise a total area of 57.4 deg$^2$, bounded by the area of 4 contiguous XMM survey regions that overlap the DES footprint. We find that the X-ray selected sample is fully matched with entries in the redMaPPer catalogue, above $\lambda>$20 and within 0.1$< z <$0.9. Conversely, only 38\% of the redMaPPer catalogue is matched to an X-ray extended source. Next, using 120 optically clusters and 184 X-ray selected clusters, we investigate the form of the X-ray luminosity-temperature ($L_{X}-T_{X}$), luminosity-richness ($L_{X}-\lambda$) and temperature-richness ($T_{X}-\lambda$) scaling relations. We find that the fitted forms of the $L_{X}-T_{X}$ relations are consistent between the two selection methods and also with other studies in the literature. However, we find tentative evidence for a steepening of the slope of the relation for low richness systems in the X-ray selected sample. When considering the scaling of richness with X-ray properties, we again find consistency in the relations (i.e., $L_{X}-\lambda$ and $T_{X}-\lambda$) between the optical and X-ray selected samples. This is contrary to previous similar works that find a significant increase in the scatter of the luminosity scaling relation for X-ray selected samples compared to optically selected samples.Comment: Accepted for publication to MNRA