Volterra Series identification Based on State Transition Algorithm with Orthogonal Transformation

A Volterra kernel identification method based on state transition algorithm with orthogonal transformation (called OTSTA) was proposed to solve the hard problem in identifying Volterra kernels of nonlinear systems. Firstly, the population with chaotic sequences was initialized by using chaotic strategy. Then the orthogonal transformation was used to finish the mutation operator of the selected individual. OTSTA was used on the identification of Volterra series, and compared with particle swarm optimization (called PSO) and state transition algorithm (STA). The simulation results showed that OTSTA has better identification precision and convergence than PSO and STA under non-noise interference. And when there is noise, the identification precision, convergence and anti-interference of OTSTA are also superior to PSO and STA

Motivating and Sustaining Women\u27s Digital Literacy through ICT Learning

Digital literacy is one of the most important issues that women confront today. Lacking of digital literacy excludes women from lifelong learning and development. Our two-phase, multi-method study attempted to examine how ICT literacy affects women and identifies the key factors that motivate adult females to acquire ICT skills. The first phase identified important theoretical constructs that affect and sustain ICT learning and usage among women, using a qualitative approach based on Social Cognitive and Social Capital Theories. In the second phase, a quantitative study was conducted to validate the research model. Our findings suggest that social capital and learning satisfaction contribute significantly to ICT usage, and that this in turn has a positive impact on the level of well-being

1,1′-Dimethyl-1,1′-(butane-1,4-di­yl)dipyrrolidinium dibromide methanol disolvate

In the title compound, C14H30N2 2+·2Br−·2CH3OH, two terminal C atoms of the butane chain are connected to two N atoms of the 1-methyl­pyrollidines, forming a linear diquaternary ammonium cation. The cation lies across a centre of inversion located between the two central C atoms of the butane chain. The asymmetric unit therefore comprises one half-cation, a bromide anion and a methanol solvent mol­ecule. In the crystal structure, the bromide anions are linked to the methanol solvent mol­ecules by O—H⋯Br hydrogen bonds

Fast Specimen Boundary Tracking and Local Imaging with Scanning Probe Microscopy

An efficient and adaptive boundary tracking method is developed to confine area of interest for high-efficiency local scanning. By using a boundary point determination criterion, the scanning tip is steered with a sinusoidal waveform while estimating azimuth angle and radius ratio of each boundary point to accurately track the boundary of targets. A local scan region and path are subsequently planned based on the prior knowledge of boundary tracking to reduce the scan time. Boundary tracking and local scanning methods have great potential not only for fast dimension measurement but also for sample surface topography and physical characterization, with only scanning region of interest. The performance of the proposed methods was verified by using the alternate current mode scanning ion-conductance microscopy, tapping, and PeakForce modulation atomic force microscopy. Experimental results of single/multitarget boundary tracking and local scanning of target structures with complex boundaries demonstrate the flexibility and validity of the proposed method

Multi-Omics Analyses Detail Metabolic Reprogramming in Lipids, Carnitines, and Use of Glycolytic Intermediates between Prostate Small Cell Neuroendocrine Carcinoma and Prostate Adenocarcinoma.

As the most common cancer in men, prostate cancer is molecularly heterogeneous. Contributing to this heterogeneity are the poorly understood metabolic adaptations of the two main types of prostate cancer, i.e., adenocarcinoma and small cell neuroendocrine carcinoma (SCNC), the latter being more aggressive and lethal. Using transcriptomics, untargeted metabolomics and lipidomics profiling on LASCPC-01 (prostate SCNC) and LNCAP (prostate adenocarcinoma) cell lines, we found significant differences in the cellular phenotypes of the two cell lines. Gene set enrichment analysis on the transcriptomics data showed 62 gene sets were upregulated in LASCPC-01, while 112 gene sets were upregulated in LNCAP. ChemRICH analysis on metabolomics and lipidomics data revealed a total of 25 metabolite clusters were significantly different. LASCPC-01 exhibited a higher glycolytic activity and lower levels of triglycerides, while the LNCAP cell line showed increases in one-carbon metabolism as an exit route of glycolytic intermediates and a decrease in carnitine, a mitochondrial lipid transporter. Our findings pinpoint differences in prostate neuroendocrine carcinoma versus prostate adenocarcinoma that could lead to new therapeutic targets in each type