The utilization of microencapsulated phase change material wallboards for energy saving

Wallboards with micro encapsulated phase changing material (micro PCM) were used to investigate the performance and the energy saving characteristics as building materials in winter and summer climate conditions. The test house consisted of a boiler with under floor heating system, an air conditioner, micro PCM wallboard room and conventional wallboard room. The outer temperature of the rooms could be artificially controlled at the temperature range of −12 to 35 °C. Micro PCM content in wallboards was 0–4 kg/m². The melting temperature and latent heat of Micro PCM are 23 °C and 211 J/g. Also, micro PCM shows stable mechanical strength under 500 psi. As micro PCM content increased, the temperature fluctuations decreased. In case of micro PCM wallboard, temperature profiles in the room show stable and comfortable ranges. The optimum amount of micro PCM in wallboard to maximize energy saving efficiency was around 3 kg/m².     

Sequential hydrolysis of hemicellulose and lignin in lignocellulosic biomass by two-stage percolation process using dilute sulfuric acid and ammonium hydroxide

To obtain the total fractionation and pretreatment of the corn stover, two-stage percolation process was investigated. This process consists of two steps: use of 0.07 wt% sulfuric acid for hemicellulose recovery in first stage and ARP (ammonia recycled percolation) in the following stage for lignin recovery. Among tested conditions, the best conditions of two-stage process were as follows: 1^st stage; 170 °C, 2.5 ml/min, 30 minutes using 0.07 wt% sulfuric acid and 2^nd stage; 170 °C, 5.0 ml/min, 60minutes using 15 wt% ammonium hydroxide. At above two-stage treatment conditions, the hemicellulose in corn stover was easily hydrolyzed (95%) and recovered with high yields (86%) and the extent of the lignin removal was 81%. After two-stage process, the treated biomass contained nearly pure glucan (85%). Two-stage treatment brought about enzymatic digestibility of 90% and 89% with 60 and 15 FPU/g glucan cellulase enzyme loadings, respectively.     

Hypoxia Suppresses Spontaneous Mineralization and Osteogenic Differentiation of Mesenchymal Stem Cells via IGFBP3 Up-Regulation

Hypoxia has diverse stimulatory effects on human adipose-derived stem cells (ASCs). In the present study, we investigated whether hypoxic culture conditions (2% O₂) suppress spontaneous mineralization and osteogenic differentiation of ASCs. We also investigated signaling pathways and molecular mechanisms involved in this process. We found that hypoxia suppressed spontaneous mineralization and osteogenic differentiation of ASCs, and up-regulated mRNA and protein expression of Insulin-like growth factor binding proteins (IGFBPs) in ASCs. Although treatment with recombinant IGFBPs did not affect osteogenic differentiation of ASCs, siRNA-mediated inhibition of IGFBP3 attenuated hypoxia-suppressed osteogenic differentiation of ASCs. In contrast, overexpression of IGFBP3 via lentiviral vectors inhibited ASC osteogenic differentiation. These results indicate that hypoxia suppresses spontaneous mineralization and osteogenic differentiation of ASCs via intracellular IGFBP3 up-regulation. We determined that reactive oxygen species (ROS) generation followed by activation of the MAPK and PI3K/Akt pathways play pivotal roles in IGFBP3 expression under hypoxia. For example, ROS scavengers and inhibitors for MAPK and PI3K/Akt pathways attenuated the hypoxia-induced IGFBP3 expression. Inhibition of Elk1 and NF-κB through siRNA transfection also led to down-regulation of IGFBP3 mRNA expression. We next addressed the proliferative potential of ASCs with overexpressed IGFBP3, but IGFBP3 overexpression reduced the proliferation of ASCs. In addition, hypoxia reduced the osteogenic differentiation of bone marrow-derived clonal mesenchymal stem cells. Collectively, our results indicate that hypoxia suppresses the osteogenic differentiation of mesenchymal stem cells via IGFBP3 up-regulation.     

Training Algorithm with Incomplete Data for Feed-Forward Neural Networks

A new algorithm is developed to train feed-forward neural networks for non-linear input-to-output mappings with small incomplete data in arbitrary distributions. The developed Training-EStimation-Training (TEST) algorithm consists of 3 steps, i.e., (1) training with the complete portion of the training data set, (2) estimation of the missing attributes with the trained neural networks, and (3) re-training the neural networks with the whole data set. Error back propagation is still applicable to estimate the missing attributes. Unlike other training methods with missing data, it does not assume data distribution models which may not be appropriate for small training data. The developed TEST algorithm is first tested for the Iris benchmark data. By randomly removing some attributes from the complete data set and estimating the values latter, accuracy of the TEST algorithm is demonstrated. Then it is applied to the Diabetes benchmark data, of which about 50% contains missing attributes. Compared with other existing algorithms, the proposed TEST algorithm results in much better recognition accuracy for test data.     

Cytotoxic Petrosiacetylenes from the Marine Sponge Petrosia sp.

A novel petrosiacetylene analog (petrosiacetylene E) has been isolated from the Korean marine sponge Petrosia sp., along with petrosiacetylene A, B and C. Their structures were elucidated on the basis of spectroscopic methods and the stereochemistry of the new compound was determined by using the modified Mosher’s method. Petrosiacetylene E showed higher cytotoxicity against five human cancer cell lines than petrosiacetylene A and B, presumably due to the additional hydroxy group located at C-16.