Aim: Investigating the relationship between land surface temperature and urban land uses can be used for urban management. However, one of the main problems in this field is the low spatial resolution of thermal images. This research aims to evaluate and select the best existing algorithm for achieving a high spatial resolution of thermal images to investigate and analyze changes in land surface temperature in Region 4 of Ahvaz. Material & method: For this purpose, the split window algorithm was used as one of the most common suitable algorithms to calculate land surface temperature, and SFIM and T sharp DisTrade algorithms in urban areas were applied to improve spatial resolution. Finding: Results show that the spatial resolution of the output image obtained by Split Window, T Sharp DisTrade, and SFIM algorithms is 30, 100, and 45 meters, respectively. The T Sharp DisTrade algorithm presented the output images with very good resolution so that different land uses could be separated according to their surface temperature. Split Window and SFIM algorithms did not provide acceptable results in land use evaluation. Also, the average land surface temperature values obtained from T Sharp DisTrade, Split Window algorithm, and SFIM are equal to 17.5, 23.5, and 28.25 degrees Celsius, respectively. This temperature difference of these algorithms is due to utilizing the fusion process. Conclusion: As a result, T Sharp DisTrade algorithm was more effective in improving the spatial resolution of thermal images. Innovation: Innovations of this research are: - simultaneous use of three mentioned algorithms for increasing spatial resolution of thermal images and discovering the best algorithm in this field, which has not been investigated in previous research, - improving spatial resolution of thermal images for evaluating urban land uses by using T Sharp DisTrade algorithm, and detail investigation of surface temperature changes.

Due to technical limitations, most satellites cannot simultaneously collect images with high spatial, temporal, and spectral resolution. In this paper, the possibility of using DisTrade and TsHARP downscaling methods and STI-FM method in order to achieve high spatial resolution for MODIS and Landsat8 images was investigated. The RMSE value for sharpened images of 1 km to 30 meters was less than 3. 93 °,C. In this study, the surface energy balance algorithm (SEBAL) was investigated to estimate the actual evapotranspiration distribution using a combination of Landsat 7 and MODIS satellite images based on the T-Sharp downscale method. The results showed that the integration of satellite images improved the accuracy of estimating actual evapotranspiration compared to Landsat 7 images. The mean squared error of estimated evapotranspiration during the growth period was determined in comparison with lysimetric data for Modis images of 1. 24-2. 91 mm / day and for integrated images of 0. 81-1. 1 mm / day. In general, the results of this study showed that the estimation of evapotranspiration using SEBAL algorithm and based on the combination of images with different temporal and spatial accuracy can provide acceptable results.

In this paper, an ultra-wide stopband microstrip low pass filter with sharp roll-off and compact size is designed and fabricated. To provide very small dimensions, T-shaped and stepped impedance have been used. The cut off frequency at-3 dB is 3. 1 GHz. In the proposed structure, the insertion loss is lower than 0. 12 dB and the return loss is greater than 15 dB. In order to achieve a-20dB attenuation level in the stopband, a modified L-shaped structure is utilized. This filter has an ultra-wide stopband that is expanded from 3. 37 GHz to 37. 5 GHz. Also the suppression level is greater than-20dB. The fabricated LPF has a size about 16. 6 × 13. 5 mm2 which is equal to 0. 28ƛ g × 0. 22ƛ g, where ƛ g is the guided wavelength at 3. 1 GHz, which is very small. The proposed filter is designed, simulated, optimized, fabricated and measured and we can see a good agreement between the simulations and measured results.

Technical limitations in image capturing usually impose defect, such as contrast degradation. There are different approaches to improve the contrast of an image. Among the exiting approaches, un-sharp masking is a popular method due to its simplicity in implementation and computation. There is an important parameter in un-sharp masking, named gain factor, which affects the quality of the enhanced image. In this paper, a new adaptive un-sharp masking method is proposed. In the proposed method gradient variation of the image is used to estimate the gain factor for un-sharp masking. Gradient variation of an image can provide information about the image contrast. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed un-sharp masking methods. The experimental results show the superiority of the proposed method compared to the existing methods in image enhancing using un-sharp masking.

Background: Globalised and industrialised food systems contribute to human and planetary health challenges, such as food insecurity, malnutrition, and climate change. International trade and investment can serve as a barrier or enabler to food system transformations that would improve health and environmental outcomes. Methods: This article used health impact assessment (HIA) to analyse what we know, what we don’ t know, and what we don’ t know we don’ t know about the role that trade and investment might play in food system transformations to improve human and planetary health. Results: Evidence exists for the link between trade and investment and the spread of unhealthy food commodities, efforts to impede nutrition labelling, and increased concentration of ultra-processed food and beverage product companies. The role of trade and investment in the reduction of animal sources in human diets is emerging and may include challenging measures that restrict the use of terms like ‘ milk’ and ‘ burger’ in plant-based alternatives and the promotion of plantbased foods through non-tariff barriers and targeted efforts at regulatory harmonisation. Trade disputes may serve as the forum for battles around state discrepancies in the safety and acceptability of technological innovation in the food supply, as was the case with hormone treated beef between the European Union (EU) and the United States. Corporate social responsibility (CSR) obligations are unambitious but represent welcome progress in balancing public and private interests. Finally, introducing greater policy flexibility, transparency, and participation provides opportunities to shape a modern trade and investment system that can respond to future food system challenges in a timely fashion. Conclusion: Research at the intersection of trade and investment and food systems should address emergent food systems issues, particularly those that intersect health and climate, while policy efforts should be future-proofing the flexibility of the trade and investment system to enable food system design that supports improved human and planetary health outcomes.

The present study on politeness is an attempt to examine (dis)agreeing strategies utilized by EFL learners while chatting on the internet. Subjects of the study were forty male and thirty-three female Iranian natives whose internet relay chat (IRC) interactions, composed of 400 excerpts, were collected between December 2007 and September 2008. Data analysis was based on the general taxonomy of politeness strategies suggested by Brown and Levinson (1987) which is the baseline of many politeness studies today. The results indicate that IRC is a mode of communication whose characteristics are typically different from face-to-face and real-life conversational settings. Some common face threatening acts (FTAs) like ‘direct disagreements’ are performed widely in chat channels. Furthermore, gender-oriented differences were found not to be statistically significant on the internet.

Un-sharp masking method improves the images contrast without requiring any prior knowledge. In this method, a sharper image can be achieved by empowering the high frequency components of the input image. Un-sharp masking has a parameter named gain factor which has a high effect on the enhanced image quality. In this paper, an approach is proposed to adaptively estimate the appropriate value of this parameter in order to effectively enhance an image with local blur, or an image with non-uniform blur. In proposed method, first, the input image is segmented into blur and non-blur regions. Then the gain factor is estimated for each region adaptively. In this approach, the influence of the image blurriness on its gradient information is used to estimate the value for the gain factor. The image quality assessments are applied to evaluate the performance of proposed un-sharp masking method in image enhancement. Experimental results demonstrate that the performance of our proposed method is better than the performance of existing un-sharp masking methods in image enhancement.