Influence of reconstruction on the structure of self-assembled normal-alkane monolayers on Au(111) surfaces

Ordered normal-alkane monolayers of lamellar structures are found to form in the interface between alkane solutions and the reconstructed Au (111) surfaces. The boundaries of the lamellae may exhibit a zigzag shape. In the alkane monolayers, two kinds of packing of the alkane molecules are observed. The packing patterns are correlated to the structure of the gold surface and the molecular lengths of the alkanes. The orientation of alkane molecules is gently disturbed by the reconstructed gold ridges. Furthermore, the lamellar boundaries are located on the elbow positions of the reconstructed gold surfaces for long-chain alkanes. These results demonstrate that the structures of self-assembled monolayers of normal alkanes are sensitive to the structures of the Au (111) surfaces

Nanofluids Containing γ-Fe2O3 Nanoparticles and Their Heat Transfer Enhancements

Homogeneous and stable magnetic nanofluids containing γ-Fe2O3 nanoparticles were prepared using a two-step method, and their thermal transport properties were investigated. Thermal conductivities of the nanofluids were measured to be higher than that of base fluid, and the enhanced values increase with the volume fraction of the nanoparticles. Viscosity measurements showed that the nanofluids demonstrated Newtonian behavior and the viscosity of the nanofluids depended strongly on the tested temperatures and the nanoparticles loadings. Convective heat transfer coefficients tested in a laminar flow showed that the coefficients increased with the augment of Reynolds number and the volume fraction

Neural network model of the primary visual cortex: From functional architecture to lateral connectivity and back

The role of intrinsic cortical dynamics is a debatable issue. A recent optical imaging study (Kenet et al., 2003) found that activity patterns similar to orientation maps (OMs), emerge in the primary visual cortex (V1) even in the absence of sensory input, suggesting an intrinsic mechanism of OM activation. To better understand these results and shed light on the intrinsic V1 processing, we suggest a neural network model in which OMs are encoded by the intrinsic lateral connections. The proposed connectivity pattern depends on the preferred orientation and, unlike previous models, on the degree of orientation selectivity of the interconnected neurons. We prove that the network has a ring attractor composed of an approximated version of the OMs. Consequently, OMs emerge spontaneously when the network is presented with an unstructured noisy input. Simulations show that the model can be applied to experimental data and generate realistic OMs. We study a variation of the model with spatially restricted connections, and show that it gives rise to states composed of several OMs. We hypothesize that these states can represent local properties of the visual scene

Investigation on two abnormal phenomena about thermal conductivity enhancement of BN/EG nanofluids

The thermal conductivity of boron nitride/ethylene glycol (BN/EG) nanofluids was investigated by transient hot-wire method and two abnormal phenomena was reported. One is the abnormal higher thermal conductivity enhancement for BN/EG nanofluids at very low-volume fraction of particles, and the other is the thermal conductivity enhancement of BN/EG nanofluids synthesized with large BN nanoparticles (140 nm) which is higher than that synthesized with small BN nanoparticles (70 nm). The chain-like loose aggregation of nanoparticles is responsible for the abnormal increment of thermal conductivity enhancement for the BN/EG nanofluids at very low particles volume fraction. And the difference in specific surface area and aspect ratio of BN nanoparticles may be the main reasons for the abnormal difference between thermal conductivity enhancements for BN/EG nanofluids prepared with 140- and 70-nm BN nanoparticles, respectively

Mining Virulence Genes Using Metagenomics

When a bacterial genome is compared to the metagenome of an environment it inhabits, most genes recruit at high sequence identity. In free-living bacteria (for instance marine bacteria compared against the ocean metagenome) certain genomic regions are totally absent in recruitment plots, representing therefore genes unique to individual bacterial isolates. We show that these Metagenomic Islands (MIs) are also visible in bacteria living in human hosts when their genomes are compared to sequences from the human microbiome, despite the compartmentalized structure of human-related environments such as the gut. From an applied point of view, MIs of human pathogens (e.g. those identified in enterohaemorragic Escherichia coli against the gut metagenome or in pathogenic Neisseria meningitidis against the oral metagenome) include virulence genes that appear to be absent in related strains or species present in the microbiome of healthy individuals. We propose that this strategy (i.e. recruitment analysis of pathogenic bacteria against the metagenome of healthy subjects) can be used to detect pathogenicity regions in species where the genes involved in virulence are poorly characterized. Using this approach, we detect well-known pathogenicity islands and identify new potential virulence genes in several human pathogens

Efficient control of atmospheric sulfate production based on three formation regimes

The formation of sulfate (SO₄²⁻) in the atmosphere is linked chemically to its direct precursor, sulfur dioxide (SO₂), through several key oxidation paths for which nitrogen oxides or NO_x (NO and NO₂) play essential roles. Here we present a coherent description of the dependence of SO₄²⁻ formation on SO₂ and NO_x under haze-fog conditions, in which fog events are accompanied by high aerosol loadings and fog-water pH in the range of 4.7–6.9. Three SO₄²⁻ formation regimes emerge as defined by the role played by NO_x. In the low-NO_x regime, NO_x act as catalyst for HO_x, which is a major oxidant for SO₂, whereas in the high-NO_x regime, NO₂ is a sink for HO_x. Moreover, at highly elevated NO_x levels, a so-called NO₂-oxidant regime exists in which aqueous NO₂ serves as the dominant oxidant of SO₂. This regime also exists under clean fog conditions but is less prominent. Sensitivity calculations using an emission-driven box model show that the reduction of SO₄²⁻ is comparably sensitive to the reduction of SO₂ and NO_x emissions in the NO₂-oxidant regime, suggesting a co-reduction strategy. Formation of SO₄²⁻ is relatively insensitive to NO_x reduction in the low-NO_x regime, whereas reduction of NO_x actually leads to increased SO₄²⁻ production in the intermediate high-NO_x regime

A Bayesian view of murine seminal cytokine networks

It has long been established that active agents in seminal fluid are key to initiating and coordinating mating-induced immunomodulation. This is in part governed by the actions of a network of cytokine interactions which, to date, remain largely undefined, and whose interspecific evolutionary conservation is unknown. This study applied Bayesian methods to illustrate the interrelationships between seminal profiles of interleukin (IL)-1alpha, IL-1beta, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12 (p70), IL-13, IL-17, eotaxin, granulocyte-colony stimulating factor (G-CSF), granulocyte macrophage-colony stimulating factor (GM-CSF), interferon (IFN)-gamma, keratinocyte-derived chemokine (KC), monocyte chemoattractant protein (MCP-1), macrophage inflammatory protein (MIP-1) alpha, MIP-1beta, regulated on activation normal T cell expressed and secreted (RANTES), tumour necrosis factor (TNF)-alpha, leptin, inducible protein (IP)-10 and vascular endothelial growth factor (VEGF) in a rat model. IL-2, IL-9, IL-12 (p70), IL-13, IL-18, eotaxin, IFN-gamma, IP-10, KC, leptin, MCP-1, MIP-1alpha and TNF-alpha were significantly higher in serum, whilst IL-1beta, IL-5, IL-6, IL-10, IL-17, G-CSF and GM-CSF were significantly higher in seminal fluid. When compared to mouse profiles, only G-CSF was present at significantly higher levels in the seminal fluid in both species. Bayesian modelling highlighted key shared features across mouse and rat networks, namely TNF-alpha as the terminal node in both serum and seminal plasma, and MCP-1 as a central coordinator of seminal cytokine networks through the intermediary of KC and RANTES. These findings reveal a marked interspecific conservation of seminal cytokine networks