In the last two decades electricity shortage has hampered the economic growth of Pakistan. To overcome these crises, thermal power plants were commissioned to bridge the supply and demand gap. Deployment of thermal power generation resulted in an unsustainable energy mix with the higher cost of generation. In the last decade, policymakers have shown considerable interest in deploying renewable energy generally and wind energy particularly. Therefore, this paper evaluates some important drivers and barriers to wind power generation. SWOT-Delphi approach with Relative Importance Index (RII) analysis has been applied. The results show that the deployment of wind power can enhance energy security and environmental sustainability. Major barriers to wind energy are the presence of competitive energy resources, policy implications, and poor grid infrastructure. With this contrasting environment, the evaluation of drivers and barriers of wind power are insightful for formulating sustainable energy planning strategies for future generation mix.

Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues. These challenges are increasing the interest in the quality of medical images. Recent research has proven that the rapid progress in convolutional neural networks (CNNs) has achieved superior performance in the area of medical image super-resolution. However, the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance (MR) images, adding extra noise in the models and more memory consumption. Furthermore, conventional deep CNN approaches used layers in series-wise connection to create the deeper mode, because this later end layer cannot receive complete information and work as a dead layer. In this paper, we propose Inception-ResNet-based Network for MRI Image Super-Resolution known as IRMRIS. In our proposed approach, a bicubic interpolation is replaced with a deconvolution layer to learn the upsampling filters. Furthermore, a residual skip connection with the Inception block is used to reconstruct a high-resolution output image from a low-quality input image. Quantitative and qualitative evaluations of the proposed method are supported through extensive experiments in reconstructing sharper and clean texture details as compared to the state-of-the-art methods.

Water is a prerequisite for the existence of life on earth. Rapid growth in the global population and industrialization have created a dearth of freshwater resources. Escalating water scarcity suggests that the use of passive solar stills is the most suitable and viable option in the arid and semi-arid areas around the world. In this study, the yield of wick type floating solar still is experimentally investigated for different wick materials. Capillary rise and absorbency of two different absorbers are considered as performance parameters for analysis of the research. Based on results, crepe paper with absorbency (1.8s) and capillary rise (112mm/h) proved a better absorber for higher productivity of the still. The efficiency of still with crepe paper was observed to be 16.68% higher than that of glass fiber sheet when applied in still during the investigation. The maximum internal temperature and the productivity of still were 9.1°C and 0.8 L/day respectively higher when crepe paper was used instead of a glass fiber sheet as a wicking material.

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