Development of tunable high pressure CO2 laser for lidar measurements of pollutants and wind velocities

The problem of laser energy extraction at a tunable monochromatic frequency from an energetic high pressure CO2 pulsed laser plasma, for application to remote sensing of atmospheric pollutants by Differential Absorption Lidar (DIAL) and of wind velocities by Doppler Lidar, was investigated. The energy extraction principle analyzed is based on transient injection locking (TIL) at a tunable frequency. Several critical experiments for high gain power amplification by TIL are presented

Survey on enrichment of Artemia urmiana nauplii with oxolinic acid and determination of its accumulation rate in different dosages and times

The nauplii of Artemia urmiana was enriched with oxolinic acid and the accumulation rate of this antibacterial drug in different times and dosages was determined. The nauplii which were hatched out of cysts from Urmia Lake's Artemia were incubated in the antibiotic/ seawater suspension with dosages of 25, 50, 75 and 100mg/l of oxolinic acid, in intervals of 2, 4, 6 and 8 hours. All factors including salinity, pH, aeration, dosage and enrichment time were kept the same for all treatments. Each treatment was repeated three times. After enrichment, the concentration of oxolinic acid per sample was determined by high performance liquid chromatography (HPLC). One way ANOVA and Duncan's tests were implemented to analyze the data

Evaluation of the potential of aerial thermal imagery to generate 3D point clouds

This research evaluates the ability of thermal images obtained from aerial platforms to produce 3D point clouds. In this study, the thermal camera is first calibrated. Then, in order to avoid data redundancy, the key frames of the obtained thermal video are separated from other frames. Afterwards, the point clouds are generated and then the thermal ortho image is created from the key frames. The evaluation is done using visible orthophoto, ground control points and the linearity of the edges of buildings extracted from thermal images. The results of this study show that the thermal ortho image matches the visible ortho image with a good accuracy in the study area. Moreover, the standard deviation of the edges of the buildings has been calculated for a number of reconstructed buildings in thermal ortho with proper dispersion. 77% of the measurements taken from the edges of the buildings coincide with a straight line with an accuracy of better than two pixels, and about half of these values are extracted with an accuracy of better than a pixel

Effect of gamma irradiation on fatty acid composition of rainbow trout (Oncorhynchus mykiss) fillets

The present study was conducted to evaluate the effect of low-dose gamma irradiation (0, 1, 3 and 5 kGy) on fatty acid composition of Rainbow trout (Oncorhynchus mykiss) fillet. Among all of the fatty acids, oleic acid (C18:1) (with mean 33.50±3.02 g/100 g fatty acids) and myristoleic acid (C14:1) (with mean 0.41±0.26 g/100 g fatty acids) were the most predominant and the lowest fatty acids in all irradiated and non-irradiated samples, respectively. Statistical analysis showed that there were no significant differences (P>0.05) in level of all fatty acids, saturated fatty acids (SFA), unsaturated fatty acids (USFA), mono unsaturated fatty acids (MUFA) and poly unsaturated fatty acids (PUFA) between Rainbow trout fillet control and irradiated in 1, 3 and 5 kGy. Therefore irradiation process and different doses of irradiation in this study (1, 3 and 5 kGy) had no significant effect (P>0.05) on fatty acid composition

Improving semantic segmentation of high-resolution remote sensing images using Wasserstein generative adversarial network

Semantic segmentation of remote sensing images with high spatial resolution has many applications in a wide range of problems in this field. In recent years, the use of advanced techniques based on fully convolutional neural networks have achieved high and impressive accuracies. However, the labels of different classes are estimated independently in this method. In general, the segmentation effect is too coarse to take the relationship between pixels into account. On the other hand, due to the use of convolution filters and limitations of calculations, the field of view information of these filters will be limited in deep layers. In this study, a method based on generative adversarial network (GAN) is proposed to strengthen spatial vicinity in the output segmentation map. The segmentation model receive assistance from the GAN model in the form of a higher order potential loss. Furthermore, for better stability and performance in model training the Wasserstein GAN is used for optimization of the model. We successfully show an increase in semantic segmentation accuracy using the challenging ISPRS Vaihingen benchmark dataset

EFFECT OF KEYFRAMES EXTRACTION FROM THERMAL INFRARED VIDEO STREAM TO GENERATE DENSE POINT CLOUD OF THE BUILDING'S FACADE

Keyframes extraction is required and effective for the 3D reconstruction of objects from a thermal video sequence to increase geometric accuracy, reduce the volume of aerial triangulation calculations, and generate the dense point cloud. The primary goal and focus of this paper are to assess the effect of keyframes extraction from the thermal infrared video sequence on the geometric accuracy of the dense point cloud generated. The method of keyframes extraction of thermal infrared video presented in this paper consists of three basic steps. (A) The ability to identify and remove blur frames from non-blur frames in a sequence of recorded frames. (B) The ability to apply the standard baseline condition between sequence frames to establish the overlap condition and prevent the creation of degeneracy conditions. (C) Evaluating degeneracy conditions and keyframes extraction using Geometric Robust Information Criteria (GRIC). The performance evaluation criteria for keyframes extraction in the generation of the thermal infrared dense point cloud in this paper are to assess the increase in density of the generated three-dimensional point cloud and reduce reprojection error. Based on the results and assessments presented in this paper, using keyframes increases the density of the thermal infrared dense point cloud by about 0.03% to 0.10% of points per square meter. It reduces the reprojection error by about 0.005% of pixels (2 times)

Enhancement of Kerr nonlinearity via multi-photon coherence

We propose a new method of resonant enhancement of optical Kerr nonlinearity using multi-level atomic coherence. The enhancement is accompanied by suppression of the other linear and nonlinear susceptibility terms of the medium. We show that the effect results in a modification of the nonlinear Faraday rotation of light propagating in an Rb87 vapor cell by changing the ellipticity of the light.Comment: 4 pages, 3 figures Submitted to Optics Letter

Velocity-selective resonance dips in the probe absorption spectra of Rb D2 transitions induced by a pump laser

We report experimental observation of velocity-selective resonances in the Doppler-broadened probe absorption spectra of 85Rb and 87Rb D2 transitions in the presence of a strong copropagating pump laser locked to a frequency within the Doppler profile of the transition. The set of three dips having the separation of allowed hyperfine transitions can be moved along the Doppler profile by tuning the pump laser frequency indicating a resonance between the pump laser frequency and the velocity shifted probe laser frequency.Comment: 7 pages, 4 figure

The study of heavy metals (Lead and Iron) contamination in cultured Oncorhynchus mykiss of Guilan province

This study was carried out in three farmed rainbow trout (Oncorhynchus mykiss) of Guilan Province. Heavy metals (Iron and Lead) were measured using Atomic absorption spectrometry in food, water and fish muscles of farms. The amounts of Iron and Lead (Mean ±SD) in all water samples from studied farms were 55.29±2.71 and 2.066±0.714 µg/L, respectively. The amounts of Iron and Lead (Mean± SD) in consumed feed of studied farms were 494.51± 89.18 and 3.494± 1.462 mg/kg, respectively. Also, the amounts of Iron and lead in fish muscle of studied farms were measured as 7.715± 1.050 and 0.39970± 0.073 mg/kg, respectively. The obtained results revealed the existence of higher amounts of iron in fish muscle above Codex standard, 2001 and lower amounts of lead levels from the mentioned standard in studied farms. The obtained data showed no significant differences in water, food and muscle of fish in studied areas (p>0.05)

Can public-private partnership (PPP) improve hospitals' performance indicators?

Background: This study was conducted to compare the main performance indicators of Hasheminejad hospital before and after implementing PPP model. Methods: This cross sectional study was conducted in Iran in 2015. Performance indicators of Hasheminejad hospital, the only Iranian unit that implemented PPP model, were applied. Data were collected based on a researcher-designed checklist after ensuring its validity and reliability. Data were analyzed applying SPSS21, and the Shapiro-Wilk test was used to examine the relevant data normalization. After confirming the normality of the data, descriptive statistics and paired t test were used to analyze the data at a significant level of 0.05. Results: Dramatic variations were observed in the status of the studied indicators after the implementation of PPP in Hasheminejad hospital, and the changes were statistically significant in all these indicators (p < 0.05). Conclusion: It seems that implementing PPP in Hasheminejad hospital can be considered as a successful experience in Iran's health sector. The significant improvement in this hospital's performance indicators can emphasize the effective role of PPP in administration of this hospital. However, service quality and patient satisfaction should be considered as qualitative indicators, along with the present quantitative indicators because better judgment about the changes was achieved in this hospital after implementing PPP. © Iran University of Medical Sciences