Factors Affecting the Learning of Fixed Prosthodontics Course by Students at Kermanshah University of Medical Sciences

AIM: The objective of this study was to investigate the factors affecting the learning of fixed prosthodontics course from the viewpoint of students and faculty members of Kermanshah Dentistry School. MATERIAL AND METHODS: This research was a descriptive-analytical study conducted using the convenient sampling method. A total of 72 students and 5 faculty members were included in the study. Data were collected using a researcher-made questionnaire containing two sections. The first section consists of demographic information, and the second section consists of 14 questions to evaluate the factors affecting the learning of the fixed prosthodontics course. RESULTS: From the students’ point of view, there was a significant relationship between the effect of using clinical points during a teaching on the learning efficacy of the fixed prosthodontics course and gender (P = 0.028). There was a statistically significant relationship between the level of professor's knowledge regarding the modern educational methods on the learning of fixed prosthodontics course (P = 0.034). The factor of displaying and implementing practical work on the real patient was considered important by students, and having knowledge about modern educational methods was considered important by faculty members. CONCLUSIONS: It is recommended that appropriate educational planning be implemented to enhance students’ practical work on the real patient and increase professors’ knowledge about modern educational methods

Cloud detection based on high resolution stereo pairs of the geostationary meteosat images

Due to the considerable impact of clouds on the energy balance in the atmosphere and on the earth surface, they are of great importance for various applications in meteorology or remote sensing. An important aspect of the cloud research studies is the detection of cloudy pixels from the processing of satellite images. In this research, we investigated a stereographic method on a new set of Meteosat images, namely the combination of the high resolution visible (HRV) channel of the Meteosat-8 Indian Ocean Data Coverage (IODC) as a stereo pair with the HRV channel of the Meteosat Second Generation (MSG) Meteosat-10 image at 0° E. In addition, an approach based on the outputs from stereo analysis was proposed to detect cloudy pixels. This approach is introduced with a 2D-scatterplot based on the parallax value and the minimum intersection distance. The mentioned scatterplot was applied to determine/detect cloudy pixels in various image subsets with different amounts of cloud cover. Apart from the general advantage of the applied stereography method, which only depends on geometric relationships, the cloud detection results are also improved because: (1) The stereo pair is the HRV bands of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor, with the highest spatial resolution available from the Meteosat geostationary platform; and (2) the time difference between the image pairs is nearly 5 s, which improves the matching results and also decreases the effect of cloud movements. In order to prove this improvement, the results of this stereo-based approach were compared with three different reflectance-based target detection techniques, including the adaptive coherent estimator (ACE), constrained energy minimization (CEM), and matched filter (MF). The comparison of the receiver operating characteristics (ROC) detection curves and the area under these curves (AUC) showed better detection results with the proposed method. The AUC value was 0.79, 0.90, 0.90, and 0.93 respectively for ACE, CEM, MF, and the proposed stereo-based detection approach. The results of this research shall enable a more realistic modelling of down-welling solar irradiance in the future

Motivated forgetting increases the recall time of learnt items: Behavioral and event related potential evidence

International audienc

Opposite effect of motivated forgetting on sleep spindles during stage 2 and slow wave sleep

International audienceMemories selectively benefit from sleep. In addition to the importance of the consolidation of relevant memories, the capacity to forget unwanted memories is also crucial. We investigated the effect of suppressing unwanted memories on electroencephalography activity of subsequent sleep using a motivated forgetting (MF) paradigm as compared with a control non-forgetting task. Subjects were randomly assigned to nap or no-nap groups. We used a modified version of the think/no-think paradigm with dominant number of no-think words cued to be forgotten and included only subjects capable of suppressing unwanted memories by performing an initial subject inclusion experiment. In both groups and conditions, the performance of the subjects in recalling the word pairs learned in the beginning of the day was evaluated in a final recall test. We found that both nap and no-nap groups recalled significantly less no-think words in the MF condition compared to the control condition. Moreover, for the nap group, in the MF compared to the control condition, spindle power and density increased during stage 2 (S2) whereas they decreased during slow wave sleep (SWS). Interestingly, recall performance of no-think words was negatively correlated with spindle power during S2 whereas it was positively correlated with spindle power during SWS. These results indicate that sleep spindles are sensitive to the previous MF experiences and suggest a differential role of sleep spindles during S2 and SWS in memory processing during sleep

Obtaining Thickness Maps of Corneal Layers Using the Optimal Algorithm for Intracorneal Layer Segmentation

Optical Coherence Tomography (OCT) is one of the most informative methodologies in ophthalmology and provides cross sectional images from anterior and posterior segments of the eye. Corneal diseases can be diagnosed by these images and corneal thickness maps can also assist in the treatment and diagnosis. The need for automatic segmentation of cross sectional images is inevitable since manual segmentation is time consuming and imprecise. In this paper, segmentation methods such as Gaussian Mixture Model (GMM), Graph Cut, and Level Set are used for automatic segmentation of three clinically important corneal layer boundaries on OCT images. Using the segmentation of the boundaries in three-dimensional corneal data, we obtained thickness maps of the layers which are created by these borders. Mean and standard deviation of the thickness values for normal subjects in epithelial, stromal, and whole cornea are calculated in central, superior, inferior, nasal, and temporal zones (centered on the center of pupil). To evaluate our approach, the automatic boundary results are compared with the boundaries segmented manually by two corneal specialists. The quantitative results show that GMM method segments the desired boundaries with the best accuracy

Human exposure to aerosol from indoor gas stove cooking and the resulting nervous system responses

Our knowledge of the effects of exposure to indoor ultrafine particles (sub-100 nm, #/cm3) on human brain activity is very limited. The effects of cooking ultrafine particles (UFP) on healthy adults were assessed using an electroencephalograph (EEGs) for brain response. Peak ultrafine particle concentrations were approximately 3 × 105 particle/cm3, and the average level was 1.64 × 105 particle/cm3. The average particle number emission rate (S) and the average number decay rate (a+k) for chicken frying in brain experiments were calculated to be 2.82 × 1012 (SD = 1.83 × 1012, R2 = 0.91, p = 0.0013) particles/min, 0.47 (SD = 0.30, R2 = 0.90, p < 0.0001) min−1, respectively. EEGs were recorded before and during cooking (14 min) and 30 min after the cooking sessions. The brain fast-wave band (beta) decreased during exposure, similar to people with neurodegenerative diseases. It subsequently increased to its pre-exposure condition for 70% of the study participants after 30 min. The brain slow-wave band to fast-wave band ratio (theta/beta ratio) increased during and after exposure, similar to observed behavior in early-stage Alzheimer's disease (AD) patients. The brain then tended to return to its normal condition within 30 min following the exposure. This study suggests that chronically exposed people to high concentrations of cooking aerosol might progress toward AD

Human exposure to aerosol from indoor gas stove cooking and the resulting nervous system responses

Our knowledge of the effects of exposure to indoor ultrafine particles (sub-100 nm, #/cm3) on human brain activity is very limited. The effects of cooking ultrafine particles (UFP) on healthy adults were assessed using an electroencephalograph (EEGs) for brain response. Peak ultrafine particle concentrations were approximately 3 × 105 particle/cm3, and the average level was 1.64 × 105 particle/cm3. The average particle number emission rate (S) and the average number decay rate (a+k) for chicken frying in brain experiments were calculated to be 2.82 × 1012 (SD = 1.83 × 1012, R2 = 0.91, p = 0.0013) particles/min, 0.47 (SD = 0.30, R2 = 0.90, p < 0.0001) min−1, respectively. EEGs were recorded before and during cooking (14 min) and 30 min after the cooking sessions. The brain fast-wave band (beta) decreased during exposure, similar to people with neurodegenerative diseases. It subsequently increased to its pre-exposure condition for 70% of the study participants after 30 min. The brain slow-wave band to fast-wave band ratio (theta/beta ratio) increased during and after exposure, similar to observed behavior in early-stage Alzheimer's disease (AD) patients. The brain then tended to return to its normal condition within 30 min following the exposure. This study suggests that chronically exposed people to high concentrations of cooking aerosol might progress toward AD

Human exposure to aerosol from indoor gas stove cooking and the resulting nervous system responses.

Our knowledge of the effects of exposure to indoor ultrafine particles (sub-100 nm, #/cm3 ) on human brain activity is very limited. The effects of cooking ultrafine particles (UFP) on healthy adults were assessed using an electroencephalograph (EEGs) for brain response. Peak ultrafine particle concentrations were approximately 3 × 105 particle/cm3, and the average level was 1.64 × 105 particle/cm3 . The average particle number emission rate (S) and the average number decay rate (a+k) for chicken frying in brain experiments were calculated to be 2.82 × 1012 (SD = 1.83 × 1012 , R2  = 0.91, p = 0.0013) particles/min, 0.47 (SD = 0.30, R2  = 0.90, p < 0.0001) min-1 , respectively. EEGs were recorded before and during cooking (14 min) and 30 min after the cooking sessions. The brain fast-wave band (beta) decreased during exposure, similar to people with neurodegenerative diseases. It subsequently increased to its pre-exposure condition for 70% of the study participants after 30 min. The brain slow-wave band to fast-wave band ratio (theta/beta ratio) increased during and after exposure, similar to observed behavior in early-stage Alzheimer's disease (AD) patients. The brain then tended to return to its normal condition within 30 min following the exposure. This study suggests that chronically exposed people to high concentrations of cooking aerosol might progress toward AD