A learning rule for local synaptic interactions between excitation and shunting inhibition

The basic requirement for direction selectivity is a nonlinear interaction between two different inputs in space-time. In some models, the interaction is hypothesized to occur between excitation and inhibition of the shunting type in the neuron's dendritic tree. How can the required spatial specificity be acquired in an unsupervised manner? We here propose an activity-based, local learning model that can account for direction selectivity in visual cortex based on such a local veto operation and that depends on synaptically induced changes in intracellular calcium concentration. Our biophysical simulations suggest that a model cell with our learning algorithm can develop direction selectivity organically after unsupervised training. The learning rule is also applicable to a neuron with multiple-direction-selective subunits and to a pair of cells with opposite-direction selectivities and is stable under different starting conditions, delays, and velocities

Tie-dye technique and pattern features

Relationship between tie-dye technique and image pattern has been studied. Based on digital image processing, average value of HSV (hue, saturation, value) tri-component of valid tie-dye area, proportion of incompletely dyed area in HSV color space and the Tamura first three texture features of digital tie-dye image have been extracted. Then, the repeated tests and analysis of variance (ANOVA) of rotation speed and concentration have been done. The results show the obvious impact of concentration and rotation speed on the color and texture feature of tie-dye pattern. Furthermore, back propagation neutral network is developed and partial pattern features with low correlation is used to forecast the tie-dye concentration and rotation speed. The experiment results show the 100% rate of forecast, which proves that pattern features can effectively achieve the technique forecast

From stateflow simulation to verified implementation: A verification approach and a real-time train controller design

Simulink is widely used for model driven development (MDD) of industrial software systems. Typically, the Simulink based development is initiated from Stateflow modeling, followed by simulation, validation and code generation mapped to physical execution platforms. However, recent industrial trends have raised the demands of rigorous verification on safety-critical applications, which is unfortunately challenging for Simulink. In this paper, we present an approach to bridge the Stateflow based model driven development and a well- defined rigorous verification. First, we develop a self- contained toolkit to translate Stateflow model into timed automata, where major advanced modeling features in Stateflow are supported. Taking advantage of the strong verification capability of Uppaal, we can not only find bugs in Stateflow models which are missed by Simulink Design Verifier, but also check more important temporal properties. Next, we customize a runtime verifier for the generated nonintrusive VHDL and C code of Stateflow model for monitoring. The major strength of the customization is the flexibility to collect and analyze runtime properties with a pure software monitor, which opens more opportunities for engineers to achieve high reliability of the target system compared with the traditional act that only relies on Simulink Polyspace. We incorporate these two parts into original Stateflow based MDD seamlessly. In this way, safety-critical properties are both verified at the model level, and at the consistent system implementation level with physical execution environment in consideration. We apply our approach on a train controller design, and the verified implementation is tested and deployed on a real hardware platform

Large-scale phosphoproteome analysis in seedling leaves of Brachypodium distachyon L.

BACKGROUND: Protein phosphorylation is one of the most important post-translational modifications involved in the regulation of plant growth and development as well as diverse stress response. As a member of the Poaceae, Brachypodium distachyon L. is a new model plant for wheat and barley as well as several potential biofuel grasses such as switchgrass. Vegetative growth is vital for biomass accumulation of plants, but knowledge regarding the role of protein phosphorylation modification during vegetative growth, especially in biofuel plants, is far from comprehensive. RESULTS: In this study, we carried out the first large-scale phosphoproteome analysis of seedling leaves in Brachypodium accession Bd21 using TiO(2) microcolumns combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and MaxQuant software. A total of 1470 phosphorylation sites in 950 phosphoproteins were identified, and these phosphoproteins were implicated in various molecular functions and basic cellular processes by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Among the 950 phosphoproteins identified, 127 contained 3 to 8 phosphorylation sites. Conservation analysis showed that 93.4% of the 950 phosphoproteins had phosphorylation orthologs in other plant species. Motif-X analysis of the phosphorylation sites identified 13 significantly enriched phosphorylation motifs, of which 3 were novel phosphorylation motifs. Meanwhile, there were 91 phosphoproteins with both multiple phosphorylation sites and multiple phosphorylation motifs. In addition, we identified 58 phosphorylated transcription factors across 21 families and found out 6 significantly over-represented transcription factor families (C3H, Trihelix, CAMTA, TALE, MYB_related and CPP). Eighty-four protein kinases (PKs), 8 protein phosphatases (PPs) and 6 CESAs were recognized as phosphoproteins. CONCLUSIONS: Through a large-scale bioinformatics analysis of the phosphorylation data in seedling leaves, a complicated PKs- and PPs- centered network related to rapid vegetative growth was deciphered in B. distachyon. We revealed a MAPK cascade network that might play the crucial roles during the phosphorylation signal transduction in leaf growth and development. The phosphoproteins and phosphosites identified from our study expanded our knowledge of protein phosphorylation modification in plants, especially in monocots. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-375) contains supplementary material, which is available to authorized users

Dietary Intake of Fatty Acids, Total Cholesterol, and Stomach Cancer in a Chinese Population.

To investigate the associations between dietary fatty acids and cholesterol consumption and stomach cancer (SC), we analyzed data from a population-based case-control study with a total of 1900 SC cases and 6532 controls. Dietary data and other risk or protective factors were collected by face-to-face interviews in Jiangsu Province, China, from 2003 to 2010. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multiple unconditional logistic regression models and an energy-adjusted method. The joint associations between dietary factors and known risk factors on SC were examined. We observed positive associations between dietary saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and total cholesterol and the development of SC, comparing the highest versus lowest quarters. Increased intakes of dietary SFAs (p-trend = 0.005; aOR, 1.11; 95% CI, 1.01-1.22 with a 7 g/day increase as a continuous variable) and total cholesterol (p-trend < 0.001; aOR, 1.13; 95% CI, 1.06-1.22 with a 250 mg/day increase as a continuous variable) were monotonically associated with elevated odds of developing SC. Our results indicate that dietary SFAs, MUFAs, and total cholesterol are associated with stomach cancer, which might provide a potential dietary intervention for stomach cancer prevention