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The ladybird beetle, Hippodamia variegata (Goeze) (Coleoptera: Coccinellidae) is one of the most important natural enemies of the common pistachio psylla, Agonoscena pistaciae Burckhardt and Lauterer (Hemiptera: Psyllidae). The effects of hexaflumuron and spirodiclofen were investigated on development and carbohydrates and total lipid contents of 4^th instar larvae of H. variegata. The insecticides had significant effects on the mortality of eggs, but no significant effects on mortality of larvae or pupae. Hexaflumuron significantly increased the length of development of eggs (2.89 days) and first instar larvae (3.28 days), but had no significant effects on other instars or pupae. Spirodiclofen had no significant effects on developmental stages of H. variegata. Glycogen content was significantly reduced by spirodiclofen (17.42 mg/g fresh body weight) and hexaflumuron (16.07 mg/g fresh body weight). Trehalose content in hexaflumuron (1.89 mg/g fresh body weight) and spirodiclofen-treated larvae (2.02 mg/g fresh body weight) was significantly lower than control (8.01 mg/g fresh body weight). Glucose content in spirodiclofen-treated larvae (0.96 mg/g fresh body weight) was significantly higher than in hexaflumuron-treated larvae (0.24 mg/g fresh body weight) and control (0.15 mg/g fresh body weight). Significant reduction in the amount of lipid was observed in spirodiclofen-treated larvae (5.29 mg/g fresh body weight), but not in hexaflumuron-treated larvae (7.11 mg/g fresh body weight). These results suggest that substantial physiological events in the life of larvae are affected in response to the action of the tested insecticides.  

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Research subject: The use of scrap tires to recover energy and their compounds is an effective way to protect the environment and recover energy and materials.
Research approach: In this research, the aim is to investigate the process of tire pyrolysis as well as the simultaneous pyrolysis (co-pyrolysis) process of tire and fuel oil. Here, the effect of different operating conditions such as temperature, volumetric nitrogen gas, heating rate and tire parts size on the physical quantities and physical properties of the products manufactured by these processes have been investigated.
Main results: The optimal operating conditions for these experiments are 420C, the volumetric gas flow rate is 100 ml / min and the heating rate is           3 C / min. The volume of the reactor used is 500 ml and the amount of mazut in the coprolysis process is 30 wt%. The highest amount of liquid produced in the process of pyrolysis of used tire was achieved using feed with a particle size of 4×2×0.5cm³, which is 43.3% by weight. In contrast, the largest liquid product produced in the simultaneous pyrolysis process of the tire and mazut was obtained using tire parts with a size of 4×4×0.5cm³, which is 52.3% by weight. In this study, the physical properties of liquid products produced by two processes of pyrolysis of tire and co-pyrolysis of tire and mazut, such as kinematic viscosity, density and refractive index, have been investigated.

 

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Backgrounds: Reinfection among COVID-19 patients is still a challenging issue in the medical literature. Therefore, the current meta-analysis was conducted to estimate the pooled incidence rate of reinfection among COVID-19 patients.
Materials & Methods: A comprehensive search was conducted in PubMed, Web of Science, and Scopus databases from July 1 to October 1, 2021. Original studies which estimated the incidence rate of COVID-19 reinfection were included. CASP (Critical Appraisal skills program) was used to assess the quality of studies. Data were analyzed by STATA statistical software Version 15 (StataCorp, College Station, TX, USA).
Findings: A total of 3803 articles were found, of which 16 articles remained after title, abstract, and full text screening. The minimum and maximum incidence rates of reinfection were 0.001 and 0.73%, respectively. The pooled estimated incidence rate of COVID-19 reinfection was 0.11% (95% confidence interval: 0.02-0.20, p< .001, I² = 100.0). The highest pooled estimated incidence rate of reinfection was observed in people <50 years old (0.14%) (95% CI: 0.001-0.34, p<.001, I² = 100). Regarding the time elapsed after the first infection, the highest reinfection rate occurred four months after the first infection (0.12%) (95% CI: 0.001-0.27, p< .001, I² = 100).
Conclusion: The incidence rate of reinfection among COVID-19 patients is expected to be high. However, it seems that the influence of factors including the age of patients and the time elapsed after the first infection must be considered.

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Operation manner in most of the conventional classification algorithms in remote sensing is based on pixels spectral information.Classification of these data ignore information obtained from adjacent pixels. In additional to with increasing of spatial resolution in satellites , increase harmful information( noise) and spectral similarity between classes , consequently increase internal variance of classes and finally decrease classification accuracy. To remove or decrease this problems , the proper incorporation and use of spectral and contextual information can efficiently help distinguish land-uses which are similar spectrally. In this study, effectiveness of incorporating structural information with classification procedures have been investigated. The technique is based on the use of edge-density information generated from the classified data. “ Maximum Likelihood ”(ML) , “ Minimum Distance to Means ”(MD) and “ Mahalanobis ” classification procedures have been used to classify data together with the edge-density information as an additional band. The performance of using edge-density data has been evaluated using the data of SPOT-XS and aerial photographs of the Anzali Wetlands ( Anzali Talab ) located in Gilan province north of Iran. This region is very heterogeneous. Results show that use of the structural information leads to increases in accuracy of some classes particularly those with low spectral separabilities. Mahalanobis classifier using spatial and spectral information in rural-urban ( 74.60) and river and channel ( 66.87) classes show 14.06 and 6.57 percent increases respectively in accuracies as compared to the spectral classification of satellite data. Application of this approach also in aerial photographs for patches of trees , river , agricultural and residential classes show 11.78 , 36.61 , 28.09 and 53.29 percent increases in accuracies respectively. Result show that considering the complex environmental conditions of the study site, the proper incorporation and use of spectral and spatial information can result in more efficient discrimination of some spectrally similar classes. The information of edge-density seems to be more promising in high resolution imagery and heterogeneous classes such as urban features.

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Difference in pixel size between multi-spectral and pan images, is one of the main effective factors on the spectral and spatial performance of image fusion methods. In this research, after producing simulated images with different pixel sizes of 8, 12, 16, 44 meters from IKONOS multi-spectral images and 4 meters from IKONOS pan image,by using four different fusion algorithms (i.e. Brovey, PCA, wavelet and combination of PCA and wavelet algorithms),all the simulated multi-spectral and pan derived images were fused.Correlation coefficient index and entropy were used to assess the spatial and spectral quality of the fused images, respectively. The results showed that the effect of increasing of multi-spectral images resolution difference compared with pan image on spectral and spatial quality of the fused images is related to the methods used for image fusion. Among the methods used for image fusion, Brovey transform and PCA-wavelet transform methods have the lowest and highest sensivity respectively, in respect to the variations of resolution difference. Also the relationship between spectral and spatial quality changes of the fused images with respect to the increasing of difference in pixel sizes of multi-spectral and pan images is non-linear.

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Quality of coastal water is of great importance in environment and other applications. Therefore, studying the quality of this water is quite vital. Traditional methods of water quality studies are time consuming processes that lead to pixel-based information and also impose a great deal of costs. Using stelllite images and remote sensing can play an important role in enhancing the outcome of these studies. In this research, by field sampling of secchi depth, simultaneous to the satellite pass; an experimental statistic-mathematical model was fitted for the acquired data in the field and the processed images of the IRS-LISS-III sensor. The results indicated good relations between the Secchi depth and the radiance received by the sensor. The fitted model can be used to map Secchi depth in coastal areas.

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Abstract In Hydrocarbon resources exploration process several geological, geochemical, and geophysical maps are required. Furthermore, According to the capabilities of Geographic Information System, and with the widespread use of multi criteria decision making methods in GIS, this method seems a proper method for hydrocarbon resources potential suitability mapping. Also, in order to understand the behavior of the model, a GIS based multi-criteria decision making with sensitivity analysis process seems to be necessary. Therefore, in this paper, a sensitivity analysis approach is presented for measuring the dependency of the model output to input criteria weights, and identifying sensitive criteria to weight changes. The 1:25000 sheet of Ahvaz which contains great oil fields, was selected to implement the model. For this purpose, GIS data layers including Total organic carbon indicator, potential yield for hydrocarbon generation indicator, Tmax indicator, proximity to anticline axes, and presence or proximity to high residual Bouguer Gravity anomaly areas were used. The results demonstrate that presence or proximity to high residual Bouguer Gravity anomaly areas has the highest sensitivity and Tmax indicator has the lowest among all criteria. The final suitability map classified about 82 percent of the known reserves in very suitable and suitable classes in total.

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electrical discharge coating (EDC) is the simplest way to deposit a thin or thick coating on the surface of a substrate to change the properties of this undesirable layer. In the EDC process, the molten pool produced due to sparking in electrical discharge is combined with material particles from the loosely bonded compacted electrode (green compacted) and then rapidly cooled to form a coated layer. Extensive methods for coating the surface of the substrate exist such as electroplating, electroless plating, vapor deposition methods, thermal spraying and many others. These processes have disadvantages such as high capital costs, complexity, higher setup complexity and space requirements that limit their implementation to some extent. Among all coating methods, EDC has advantages over other coating methods. For EDC, there is no need to set up any equipment to create a vacuum or isolation environment around the bed. Also, only by changing the different variables of the machine, the thickness can be changed and the characteristics of the coating layer can be controlled. This study focuses on chrome ceramic coatings formed in the EDC process on stainless steel substrates (ST37) with process parameters with 8 amp current and 100 µs on time. The results showed that the hardness of stainless steel coated with chromium and copper increased to 1284 (HV) in electrical discharge.