Bacillus sp. ZBP10 is an amylase producing strain isolated from a soil sample collected from a potato cultivation field in Sakarya. In this study, culture conditions were optimized for Bacillus sp. ZBP10 in order to increase amylase production using submerged fermentation. The effects of temperature (30-40°C), fermentation time (24-72 h), initial medium pH (6.0-9.0), carbon sources (soluble, wheat, rice and corn starches) and substrate concentration (5-30 g/L) on the production of amylase were determined. According to the results, the bacterium produced maximum amount of amylase, when the initial pH of the medium was 7.0, at 33°C, and within 48 h. Soluble starch was the best substrate among the starches tested. Optimum substrate concentration was 20 g/L for enzyme production with which 3.57±0.19 U/mL enzymatic activity was obtained.

Giving machines the ability to imagine possible new objects or scenes from linguistic descriptions and produce their realistic renderings is arguably one of the most challenging problems in computer vision. Recent advances in deep generative models have led to new approaches that give promising results towards this goal. In this paper, we introduce a new method called DiCoMoGAN for manipulating videos with natural language, aiming to perform local and semantic edits on a video clip to alter the appearances of an object of interest. Our GAN architecture allows for better utilization of multiple observations by disentangling content and motion to enable controllable semantic edits. To this end, we introduce two tightly coupled networks: (i) a representation network for constructing a concise understanding of motion dynamics and temporally invariant content, and (ii) a translation network that exploits the extracted latent content representation to actuate the manipulation according to the target description. Our qualitative and quantitative evaluations demonstrate that DiCoMoGAN significantly outperforms existing frame-based methods, producing temporally coherent and semantically more meaningful results.