An Inter-molecular Adaptive Collision Scheme for Chemical Reaction Optimization

Optimization techniques are frequently applied in science and engineering research and development. Evolutionary algorithms, as a kind of general-purpose metaheuristic, have been shown to be very effective in solving a wide range of optimization problems. A recently proposed chemical-reaction-inspired metaheuristic, Chemical Reaction Optimization (CRO), has been applied to solve many global optimization problems. However, the functionality of the inter-molecular ineffective collision operator in the canonical CRO design overlaps that of the on-wall ineffective collision operator, which can potential impair the overall performance. In this paper we propose a new inter-molecular ineffective collision operator for CRO for global optimization. To fully utilize our newly proposed operator, we also design a scheme to adapt the algorithm to optimization problems with different search space characteristics. We analyze the performance of our proposed algorithm with a number of widely used benchmark functions. The simulation results indicate that the new algorithm has superior performance over the canonical CRO

Effects on the transcriptome upon deletion of a distal element cannot be predicted by the size of the H3K27Ac peak in human cells.

Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for colorectal cancer (CRC). A molecular understanding of the functional consequences of this genetic variation is complicated because most GWAS SNPs are located in non-coding regions. We used epigenomic information to identify H3K27Ac peaks in HCT116 colon cancer cells that harbor SNPs associated with an increased risk for CRC. Employing CRISPR/Cas9 nucleases, we deleted a CRC risk-associated H3K27Ac peak from HCT116 cells and observed large-scale changes in gene expression, resulting in decreased expression of many nearby genes. As a comparison, we showed that deletion of a robust H3K27Ac peak not associated with CRC had minimal effects on the transcriptome. Interestingly, although there is no H3K27Ac peak in HEK293 cells in the E7 region, deletion of this region in HEK293 cells decreased expression of several of the same genes that were downregulated in HCT116 cells, including the MYC oncogene. Accordingly, deletion of E7 causes changes in cell culture assays in HCT116 and HEK293 cells. In summary, we show that effects on the transcriptome upon deletion of a distal regulatory element cannot be predicted by the size or presence of an H3K27Ac peak

Test structure, circuits and extraction methods to determine the radius of infuence of STI and polysilicon pattern density

Advanced CMOS processes need new methodologies to extract, characterize and model process variations and their sources. Most prior studies have focused on understanding the effect of local layout features on transistor performance; limited work has been done to characterize medium-range (≈ 10μm to 2mm) pattern density effects. We propose a new methodology to extract the radius of influence, or the range of neighboring layout that should be taken into account in determining transistor characteristics, for shallow trench isolation (STI) and polysilicon pattern density. A test chip, with 130k devices under test (DUTs) and step-like pattern density layout changes, is designed in 65nm bulk CMOS technology as a case study. The extraction result of the measured data suggests that the local layout geometry, within the DUT cell size of 6μm × 8μm, is the dominant contributor to systematic device variation. Across-die medium-range layout pattern densities are found to have a statistically significant and detectable effect, but this effect is small and contributes only 2-5% of the total variation in this technology