Implementation of dynamical systems with plastic self-organising velocity fields

To describe learning, as an alternative to a neural network recently dynamical systems were introduced whose vector fields were plastic and self-organising. Such a system automatically modifies its velocity vector field in response to the external stimuli. In the simplest case under certain conditions its vector field develops into a gradient of a multi-dimensional probability density distribution of the stimuli. We illustrate with examples how such a system carries out categorisation, pattern recognition, memorisation and forgetting without any supervision. [Continues.

Down-Regulating Sphingolipid Synthesis Increases Yeast Lifespan

Knowledge of the mechanisms for regulating lifespan is advancing rapidly, but lifespan is a complex phenotype and new features are likely to be identified. Here we reveal a novel approach for regulating lifespan. Using a genetic or a pharmacological strategy to lower the rate of sphingolipid synthesis, we show that Saccharomyces cerevisiae cells live longer. The longer lifespan is due in part to a reduction in Sch9 protein kinase activity and a consequent reduction in chromosomal mutations and rearrangements and increased stress resistance. Longer lifespan also arises in ways that are independent of Sch9 or caloric restriction, and we speculate on ways that sphingolipids might mediate these aspects of increased lifespan. Sch9 and its mammalian homolog S6 kinase work downstream of the target of rapamycin, TOR1, protein kinase, and play evolutionarily conserved roles in regulating lifespan. Our data establish Sch9 as a focal point for regulating lifespan by integrating nutrient signals from TOR1 with growth and stress signals from sphingolipids. Sphingolipids are found in all eukaryotes and our results suggest that pharmacological down-regulation of one or more sphingolipids may provide a means to reduce age-related diseases and increase lifespan in other eukaryotes

Enhanced oxidation resistance of active nanostructures via dynamic size effect.

A major challenge limiting the practical applications of nanomaterials is that the activities of nanostructures (NSs) increase with reduced size, often sacrificing their stability in the chemical environment. Under oxidative conditions, NSs with smaller sizes and higher defect densities are commonly expected to oxidize more easily, since high-concentration defects can facilitate oxidation by enhancing the reactivity with O2 and providing a fast channel for oxygen incorporation. Here, using FeO NSs as an example, we show to the contrary, that reducing the size of active NSs can drastically increase their oxidation resistance. A maximum oxidation resistance is found for FeO NSs with dimensions below 3.2 nm. Rather than being determined by the structure or electronic properties of active sites, the enhanced oxidation resistance originates from the size-dependent structural dynamics of FeO NSs in O2. We find this dynamic size effect to govern the chemical properties of active NSs

Proteomic analysis of young leaves at three developmental stages in an albino tea cultivar

Abstract Background White leaf No.1 is a typical albino tea cultivar grown in China and it has received increased attention in recent years due to the fact that white leaves containing a high level of amino acids, which are very important components affecting the quality of tea drink. According to the color of its leaves, the development of this tea cultivar is divided into three stages: the pre-albinistic stage, the albinistic stage and the regreening stage. To understand the intricate mechanism of periodic albinism, a comparative proteomic approach based on two-dimensional electrophoresis (2-DE) and mass spectrometry was adopted first time to identify proteins that changed in abundance during the three developmental periods. Results The 2-DE results showed that the expression level of 61 protein spots varied markedly during the three developmental stages. To analyze the functions of the significantly differentially expressed protein spots, 30 spots were excised from gels and analyzed by matrix-assisted laser desorption ionization-time of flight-tandem mass spectrometry. Of these, 26 spots were successfully identified. All identified protein spots were involved in metabolism of carbon, nitrogen and sulfur, photosynthesis, protein processing, stress defense and RNA processing, indicating these physiological processes may play crucial roles in the periodic albinism. Quantitative real-time RT-PCR analysis was used to assess the transcriptional level of differentially expressed proteins. In addition, the ultrastructural studies revealed that the etioplast-chloroplast transition in the leaf cell of White leaf No. 1 was inhibited and the grana in the chloroplast was destroyed at the albinistic stage. Conclusions In this work, the proteomic analysis revealed that some proteins may have important roles in the molecular events involved in periodic albinism of White leaf No. 1 and identificated many attractive candidates for further investigation. In addition, the ultrastructural studies revealed that the change in leaf color of White leaf No. 1 might be a consequence of suppression of the etioplast-chloroplast transition and damage to grana in the chloroplast induced by temperature. These results provide much useful information to improve our understanding of the mechanism of albinism in the albino tea cultivar.</p

Direct structural identification of carbenium ions and investigation of host-guest interaction in the methanol to olefins reaction obtained by multinuclear NMR correlations

Probing and determining the intermediates formed during catalytic reactions in heterogeneous catalysis are strong challenges. Using C-13 labelling and two dimensional C-13-C-13 through-bond NMR correlations, we directly reveal the structures of a range of carbenium ion species formed during the conversion of methanol to olefins on acidic H-ZSM-5 zeolite by mapping the carbon-carbon bond connectivities. Additionally, we use C-13-Al-27 and Si-29-C-13 through-space NMR experiments to probe the interactions between the confined carbon species (including carbenium ions) and the framework of the zeolite, which quantitatively provide an estimate for the carbon-aluminium and carbon-silicon distances, respectively

Structures and growth pathways of AunCln+3-(n≤7) cluster anions

Gold chloride clusters play an important role in catalysis and materials chemistry. Due to the diversity of their species and isomers, there is still a dearth of structural studies at the molecular level. In this work, anions of AunCln+3- and AunCln+5- (n = 2–4) clusters were obtained by laser desorption/ionization mass spectrometry (LDI MS), and the most stable isomers of AunCln+3- were determined after a thorough search and optimization at the TPSSh/aug-cc-pVTZ/ECP60MDF level. The results indicate that all isomers with the lowest energy have a planar zigzag skeleton. In each species, there is one Au(III) atom at the edge connected with four Cl atoms, which sets it from the other Au(I) atoms. Four growth pathways for AunCln+3- (n = 2–7) clusters are proposed (labelled R1, R2, R3 and R4). They are all associated with an aurophilic contact and are exothermic. The binding energies tend to stabilize at ~ −41 kcal/mol when the size of the cluster increases in all pathways. The pathway R1, which connects all the most stable isomers of the respective clusters, is characterized by cluster growth due to aurophilic interactions at the terminal atom of Au(I) in the zigzag chains. In the pathway of R4 involving Au-Au bonding in its initial structures (n ≤ 3), the distance between intermediate gold atoms grows with cluster size, ultimately resulting in the transfer of the intermediate Au-Au bonding into aurophilic interaction. The size effect on the structure and aurophilic interactions of these clusters will be better understood based on these discoveries, potentially providing new insights into the active but elusive chemical species involved in the corresponding catalytic reactions or nanoparticle synthesis processes

Influence Pathway Discovery on Social Media

This paper addresses influence pathway discovery, a key emerging problem in today's online media. We propose a discovery algorithm that leverages recently published work on unsupervised interpretable ideological embedding, a mapping of ideological beliefs (done in a self-supervised fashion) into interpretable low-dimensional spaces. Computing the ideological embedding at scale allows one to analyze correlations between the ideological positions of leaders, influencers, news portals, or population segments, deriving potential influence pathways. The work is motivated by the importance of social media as the preeminent means for global interactions and collaborations on today's Internet, as well as their frequent (mis-)use to wield influence that targets social beliefs and attitudes of selected populations. Tools that enable the understanding and mapping of influence propagation through population segments on social media are therefore increasingly important. In this paper, influence is measured by the perceived ideological shift over time that is correlated with influencers' activity. Correlated shifts in ideological embeddings indicate changes, such as swings/switching (among competing ideologies), polarization (depletion of neutral ideological positions), escalation/radicalization (shifts to more extreme versions of the ideology), or unification/cooldown (shifts towards more neutral stances). Case-studies are presented to explore selected influence pathways (i) in a recent French election, (ii) during political discussions in the Philippines, and (iii) for some Russian messaging during the Russia/Ukraine conflict.Comment: This paper is accepted by IEEE CIC as an invited vision pape