No abstract

As is well known, carbohydrate is the most appropriate organic material for hydrogen fermentation, and its hydrogen yield is significantly larger than that of protein. The fermentation of protein began with hydrogen production followed by hydrogen consumption, which helps overall hydrogen recovery. Both carbohydrate and protein are basic components of organic material, and yet carbohydrate is known to be a better substrate than protein in terms of hydrogen yield during hydrogen fermentation. This study used multiple substrates containing different ratios of glucose and peptone as multiple substrates to investigate the roles played by carbohydrate and protein in hydrogen fermentation. The experimental results demonstrated that suitable ratios of glucose and peptone improved the growth of hydrogen producing bacteria. Additionally, a maximum hydrogen yield of 6.4 mmole-H2/g-COD was obtained from the multiple substrate containing 40% peptone and 60% glucose. Most of the produced hydrogen came from fermentation of glucose, not peptone. During hydrogen fermentation, the pH dropped by 1.0 and 1.9 units in 80% and 20% of peptone content in the substrate. Ammonia produced due to peptone degradation neutralized the acids produced from hydrogen fermentation.

No abstract

In order to improve the image quality of BLADE magnetic resonance imaging (MRI) using the index tensor solvers and to evaluate MRI image quality in a clinical setting, we implemented BLADE MRI reconstructions using two tensor solvers (the least-squares solver and the L1 total-variation regularized least absolute deviation (L1TV-LAD) solver) on a graphics processing unit (GPU). The BLADE raw data were prospectively acquired and presented in random order before being assessed by two independent radiologists. Evaluation scores were examined for consistency and then by repeated measures analysis of variance (ANOVA) to identify the superior algorithm. The simulation showed the structural similarity index (SSIM) of various tensor solvers ranged between 0.995 and 0.999. Inter-reader reliability was high (Intraclass correlation coefficient (ICC) = 0.845, 95% confidence interval: 0.817, 0.87). The image score of L1TV-LAD was significantly higher than that of vendor-provided image and the least-squares method. The image score of the least-squares method was significantly lower than that of the vendor-provided image. No significance was identified in L1TV-LAD with a regularization strength of λ= 0.4–1.0. The L1TV-LAD with a regularization strength of λ= 0.4–0.7 was found consistently better than least-squares and vendor-provided reconstruction in BLADE MRI with a SENSitivity Encoding (SENSE) factor of 2. This warrants further development of the integrated computing system with the scanner.