Cooperative three- and four- player quantum games

A cooperative multi-player quantum game played by 3 and 4 players has been studied. Quantum superposed operator is introduced in this work which solves the non-zero sum difficulty in previous treatment. The role of quantum entanglement of the initial state is discussed in details.Comment: 7 pages with 3 figures. To appear in Physics Letters

Correlated Mutation Analysis on the Catalytic Domains of Serine/Threonine Protein Kinases

BACKGROUND:Protein kinases (PKs) have emerged as the largest family of signaling proteins in eukaryotic cells and are involved in every aspect of cellular regulation. Great progresses have been made in understanding the mechanisms of PKs phosphorylating their substrates, but the detailed mechanisms, by which PKs ensure their substrate specificity with their structurally conserved catalytic domains, still have not been adequately understood. Correlated mutation analysis based on large sets of diverse sequence data may provide new insights into this question. METHODOLOGY/PRINCIPAL FINDINGS:Statistical coupling, residue correlation and mutual information analyses along with clustering were applied to analyze the structure-based multiple sequence alignment of the catalytic domains of the Ser/Thr PK family. Two clusters of highly coupled sites were identified. Mapping these positions onto the 3D structure of PK catalytic domain showed that these two groups of positions form two physically close networks. We named these two networks as theta-shaped and gamma-shaped networks, respectively. CONCLUSIONS/SIGNIFICANCE:The theta-shaped network links the active site cleft and the substrate binding regions, and might participate in PKs recognizing and interacting with their substrates. The gamma-shaped network is mainly situated in one side of substrate binding regions, linking the activation loop and the substrate binding regions. It might play a role in supporting the activation loop and substrate binding regions before catalysis, and participate in product releasing after phosphoryl transfer. Our results exhibit significant correlations with experimental observations, and can be used as a guide to further experimental and theoretical studies on the mechanisms of PKs interacting with their substrates

Deep Neural Network for Robust Speech Recognition With Auxiliary Features From Laser-Doppler Vibrometer Sensor

Recently, the signal captured from a laser Doppler vibrometer (LDV) sensor been used to improve the noise robustness automatic speech recognition (ASR) systems by enhancing the acoustic signal prior to feature extraction. This study proposes another approach in which auxiliary features extracted from the LDV signal are used alongside conventional acoustic features to further improve ASR performance based on the use of a deep neural network (DNN) as the acoustic model. While this approach is promising, the best training data sets for ASR do not include LDV data in parallel with the acoustic signal. Thus, to leverage such existing large-scale speech databases, a regres- sion DNN is designed to map acoustic features to LDV features. This regression DNN is well trained from a limited size parallel signal data set, then used to form pseudo-LDV features from a massive speech data set for parallel training of an ASR system. Our experiments show that both the features from the limited scale LDV data set as well as the massive scale pseudo-LDV features are able to train an ASR system that significantly outperforms one using acoustic features alone, in both quiet and noisy environments

Proteome analysis of human colorectal cancer tissue using 2-D DIGE and tandem mass spectrometry for identification of disease-related proteins

Laser capture microdissection and two-dimensional difference gel electrophoresis were used to establish the proteomic profiles for tumor and matched adjacent tissues from 12 patients. Differential protein spots were identified by mass spectrometric analysis. The cDNA of the differential protein was transfected into colorectal cancer cells, and the biological behavior of these cells was observed. The proteomic profile in colorectal cancer tissues was significantly different from that in normal adjacent tissues. There was a 1.5-fold difference and 60 differential protein spots between cancer and adjacent tissues. Ten differential protein spots were analyzed. Among them, two protein spots were down-regulated and eight protein spots were up-regulated in the primary tumor tissues. After identification by mass spectrometry, the two down-regulated proteins were carbonic anhydrase II and protein disulfide isomerase, and these eight up-regulated proteins included APC-stimulated guanine nucleotide exchange factor, phosphoglycerate kinase 1, fumarate hydratase, aldolase A, activator protein 2B, glutathione S-transferase A3, Arginase and zinc finger protein 64 homolog. After been transfected with carbonic anhydrase II, the invasive ability, mobility and drug resistance of colon cancer lovo cells were significantly reduced. The proteomic profile was significantly different between colorectal cancer tissues and normal adjacent tissues. The down-regulation of carbonic anhydrase II and protein disulfide isomerase and up-regulation of APC-stimulated guanine nucleotide exchange facto, aldolase A, glutathione S-transferase A3 and arginase were correlated with the onset of colorectal cancer.Key words: Colorectal cancer, proteomics