Adsorption of Lactic Acid from Fermentation Broth and Aqueous Solutions on Zeolite Molecular Sieves

The recovery of lactic acid from fermentation broth and aqueous solutions was studied by adsorption on Silicalite molecular sieves. Batch experiments were used to measure the adsorption isotherms of the lactic acid on Silicalite. A linear correlation was found for both solutions. Silicalite showed a higher adsorptive capacity in the case of the aqueous solution than that of the fermentation broth. Henry’s constants were estimated as Formula Not Shown and Formula Not Shown for the aqueous and broth solutions, respectively. The effect of temperature on adsorption was also studied in batch mode. Henry’s constant dependency on temperature was derived from Van’t Hoff’s equation. The heat of adsorption was calculated as ( Formula Not Shown )kJ/mol. The kinetics of adsorption was investigated in column studies where the breakthrough and elution curves were measured. The adsorption process was controlled by the internal diffusion in the Silicalite pellets rather than the diffusion through the fluid film around the pellet. The fluid phase resistance was estimated as 21% of the overall resistance. The glucose presence in the fermentation broth had a negligible effect on lactic acid breakthrough curve in the studied range

A Reference High-Pressure CO2\u3c/sub\u3e Adsorption Isotherm for Ammonium ZSM-5 Zeolite: Results of an Interlaboratory Study

© 2018, The Author(s). This paper reports the results of an international interlaboratory study led by the National Institute of Standards and Technology (NIST) on the measurement of high-pressure surface excess carbon dioxide adsorption isotherms on NIST Reference Material RM 8852 (ammonium ZSM-5 zeolite), at 293.15 K (20 °C) from 1 kPa up to 4.5 MPa. Eleven laboratories participated in this exercise and, for the first time, high-pressure adsorption reference data are reported using a reference material. An empirical reference equation nex=d(1+exp[(-ln(P)+a)/b])c, [nex-surface excess uptake (mmol/g), P-equilibrium pressure (MPa), a = −6.22, b = 1.97, c = 4.73, and d = 3.87] along with the 95% uncertainty interval (Uk = 2 = 0.075 mmol/g) were determined for the reference isotherm using a Bayesian, Markov Chain Monte Carlo method. Together, this zeolitic reference material and the associated adsorption data provide a means for laboratories to test and validate high-pressure adsorption equipment and measurements. Recommendations are provided for measuring reliable high-pressure adsorption isotherms using this material, including activation procedures, data processing methods to determine surface excess uptake, and the appropriate equation of state to be used

A SOM-based Chan–Vese model for unsupervised image segmentation

Active Contour Models (ACMs) constitute an efficient energy-based image segmentation framework. They usually deal with the segmentation problem as an optimization problem, formulated in terms of a suitable functional, constructed in such a way that its minimum is achieved in correspondence with a contour that is a close approximation of the actual object boundary. However, for existing ACMs, handling images that contain objects characterized by many different intensities still represents a challenge. In this paper, we propose a novel ACM that combines—in a global and unsupervised way—the advantages of the Self-Organizing Map (SOM) within the level set framework of a state-of-the-art unsupervised global ACM, the Chan–Vese (C–V) model. We term our proposed model SOM-based Chan– Vese (SOMCV) active contourmodel. It works by explicitly integrating the global information coming from the weights (prototypes) of the neurons in a trained SOM to help choosing whether to shrink or expand the current contour during the optimization process, which is performed in an iterative way. The proposed model can handle images that contain objects characterized by complex intensity distributions, and is at the same time robust to the additive noise. Experimental results show the high accuracy of the segmentation results obtained by the SOMCV model on several synthetic and real images, when compared to the Chan–Vese model and other image segmentation models

Efficacy of coeliac plexus and splanchnic nerve blockades in body and tail located pancreatic cancer pain

Palliative treatment, pain therapy and quality of life (QOL) are very important in pancreatic cancer patients. We evaluated the pain relieving efficacy, side effects and effects on QOL of neurolytic coeliac plexus blockade (NCPB) and splanchnic nerves neurolytic blockade (SNB) in body and tail located pancreatic cancer