다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Fibroblasts can condense a hydrated collagen lattice to a tissue-like structure 1/28th the area of the starting gel in 24 hr. The rate of the process can be regulated by varying the protein content of the lattice, the cell number, or the con- centration of an inhibitor such as Colcemid. Fibroblasts of high population doubling level propagated in vitro, which have left the cell cycle, can carry out the contraction at least as efficiently as cycling cells. The potential uses of the system as an immu- nologically tolerated "tissue" for wound hea ing and as a model for studying fibroblast function are discussed.

Production of a tissue-like structure by contraction of collagen lattices by human fibroblasts of different proliferative

http://bioprocesos.unq.edu.ar/Biopro%20II/Paper%20escalado.pdf

Bioreactor scale-up and oxygen transfer rate in microbial processes: An overview

The rising cost of crude oil combined with the depletion of the resources, political instability in oil producing countries, and the desire to reduce the current dependence on imported oil are some of the reasons that have motivated the different waves of interest for renewable and sustainable fuels. In addition to bioethanol and biodiesel, biobutanol is attracting significant interest as a biofuel mainly due to the recent advances in biotechnology for its production. Biobutanol has lower water miscibility, flammability, and corrosiveness than ethanol, and has the enviable advantage to be able to directly replace gasoline in car engines without requiring modifications. Butanol can be produced from a wide variety of waste biomass feedstock which does not compete with food. In butanol bioproduction, the most widely used microorganisms for acetonebutanol–ethanol (ABE) fermentation are anaerobic bacteria such as the solventogenic Clostridia including Clostridium acetobutylicum and Clostridium beijerinckii. However, the production of biobutanol via fermentation is facing significant engineering challenges due to the very low final concentration and low yield due to the severe butanol toxicity to microorganisms. It is therefore important to find an efficient separation technique to recover butanol at the end of fermentation or during the fermentation to reduce the level of toxicity and prolong the fermentation. In this article, the main butanol separation techniques such as adsorption, gas stripping, liquid–liquid extraction (LLE), perstraction, reverse osmosis (RO) and pervaporation were discussed. It was concluded that adsorption and pervaporation are the separation techniques that offer the most potential for butanol separation from dilute solutions.

Separation techniques in butanol production: Challenges and developments

Rheological characteristics of non-Newtonian nanofluids: Experimental investigation

This article presents an introduction to the use of neural network computational algorithms for the dynamic modeling of bioprocesses. The dynamic neural model is used for the prediction of key fermentation variables. This relatively hew method is compared with a more traditional prediction technique to judge its performance for prediction. Illustrative simulation results of a continuous stirred tank fermentor are used for this comparison. It is shown that neural network models are accurate with a certain degree of noise immunity. They offer the distinctive ability over more traditional methods to learn very naturally complex relationships without requiring the knowledge of the model structure.

Jules Thibault

Papers

Separation techniques in butanol production: Challenges and developments

Rheological characteristics of non-Newtonian nanofluids: Experimental investigation

On-line prediction of fermentation variables using neural networks

Thermal conductivity of non-Newtonian nanofluids: Experimental data and modeling using neural network

Dynamic modelling of the activated sludge process: Improving prediction using neural networks