433 resultados para chemical interaction


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Towards Intuitive Interaction Theory Intuitive interaction, or intuitive use, or even ‘intuitivity’, have long been buzzwords used by designers and marketers but until recently there was no research about what this might entail and how designers could encourage it. This century, work on intuitive interaction has been gaining pace and this special issue showcases the state of the art in intuitive interaction research worldwide. This editorial is intended to introduce readers to the concept and definitions of intuitive interaction, briefly discuss the short history of work in this field and highlight and discuss some of the main issues raised by the papers in the issue.

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Background Little information exists regarding the interaction effects of obesity with long-term air pollution exposure on cardiovascular diseases (CVDs) and stroke in areas of high pollution. The aim of the present study is to examine whether obesity modifies CVD-related associations among people living in an industrial province of northeast China. Methods We studied 24,845 Chinese adults, aged 18 to 74 years old, from three Northeastern Chinese cities in 2009 utilizing a cross-sectional study design. Body weight and height were measured by trained observers. Overweight and obesity were defined as a body mass index (BMI) between 25–29.9 and ≥ 30 kg/m2, respectively. Prevalence rate and related risk factors of cardiovascular and cerebrovascular diseases were investigated by a questionnaire. Three-year (2006–2008) average concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxides (NO2), and ozone (O3) were measured by fixed monitoring stations. All the participants lived within 1 km of air monitoring sites. Two-level logistic regression (personal level and district-specific pollutant level) was used to examine these effects, controlling for covariates. Results We observed significant interactions between exposure and obesity on CVDs and stroke. The associations between annual pollutant concentrations and CVDs and stroke were strongest in obese subjects (OR 1.15–1.47 for stroke, 1.33–1.59 for CVDs), less strong in overweight subjects (OR 1.22–1.35 for stroke, 1.07–1.13 for CVDs), and weakest in normal weight subjects (OR ranged from 0.98–1.01 for stroke, 0.93–1.15 for CVDs). When stratified by gender, these interactions were significant only in women. Conclusions Study findings indicate that being overweight and obese may enhance the effects of air pollution on the prevalence of CVDs and stroke in Northeastern metropolitan China. Further studies will be needed to investigate the temporality of BMI relative to exposure and onset of disease.

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The stoned locus in Drosophila encodes two proteins StonedA (STNA) and StonedB (STNB), both of which have been suggested to act as adaptins in mediating synaptic vesicle recycling. A combination of immunological, genetic and biochemical studies have shown an interaction of STNA and STNB with the C2B domain of Synaptotagmin-I (SYT-1), an integral synaptic vesicle protein that mediates Ca2+-dependent exocytosis, as well as endocytosis. The C2B domain of SYT-1 contains an AP-2 binding site that controls the size of recycled vesicles, and a C-terminal tryptophan-containing motif that acts as an internalization signal. Investigation of SYT-1 mutations in Drosophila has shown that altering the Ca2+ binding region of the C2B domain, results in a reduction in the rate of vesicle recycling, implicating this region in SYT-I endocytosis. In this poster, we report the molecular dissection of the interactions between the STNA and STNB proteins and the C2B domain of SYT-1. Deletion of the AP-2 binding site decreased the binding of both STNA and STNB. However, C-terminal deletions of the C2B domain significantly increased STNB binding. In contrast, the same C-terminal deletions reduced the affinity of the C2B domain for STNA. The possible interactions of both STNB and STNA with the Ca2+ binding region of SYT-1 will be also investigated.

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The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

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With the aim of elucidating the seasonal behaviour of rare earth elements (REEs), surface and groundwaters were collected under dry and wet conditions in different hydrological units of the Teviot Brook catchment (Southeast Queensland, Australia). Sampled waters showed a large degree of variability in both REE abundance and normalised patterns. Overall REE abundance ranged over nearly three orders of magnitude, and was consistently lower in the sedimentary bedrock aquifer (18ppt<∑REE<477ppt) than in the other hydrological systems studied. Abundance was greater in springs draining rhyolitic rocks (∑REE=300 and 2054ppt) than in springs draining basalt ranges (∑REE=25 and 83ppt), yet was highly variable in the shallow alluvial groundwater (16ppt<∑REE<5294ppt) and, to a lesser extent, in streamwater (85ppt<∑REE<2198ppt). Generally, waters that interacted with different rock types had different REE patterns. In order to obtain an unbiased characterisation of REE patterns, the ratios between light and middle REEs (R(M/L)) and the ratios between middle and heavy REEs (R(H/M)) were calculated for each sample. The sedimentary bedrock aquifer waters had highly evolved patterns depleted in light REEs and enriched in middle and heavy REEs (0.17chemical processes in complex geological settings

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This thesis improves our insight towards the effects of using biodiesels on the particulate matter emission of diesel engines and contributes to our understanding of their potential adverse health effects. The novelty of this project is the use of biodiesel fuel with controlled chemical composition that enables us to relate changes of physiochemical properties of particles to specific properties of the biodiesel. For the first time, the possibility of a correlation of the volatility and the Reactive Oxygen Species concentration of the particles is investigated versus the saturation, oxygen content and carbon chain length of the fuel.

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Mathematics has been perceived as the core area of learning in most educational systems around the world including Sri Lanka. Unfortunately, it is clearly visible that a majority of Sri Lankan students are failing in their basic mathematics when the recent grade five scholarship examination and ordinary level exam marks are analysed. According to Department of Examinations Sri Lanka , on average, over 88 percent of the students are failing in the grade 5 scholarship examinations where mathematics plays a huge role while about 50 percent of the students fail in there ordinary level mathematics examination. Poor or lack of basic mathematics skills has been identified as the root cause.

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Efficient yet inexpensive electrocatalysts for oxygen reduction reaction (ORR) are an essential component of renewable energy devices, such as fuel cells and metal-air batteries. We herein interleaved novel Co3O4 nanosheets with graphene to develop a first ever sheet-on-sheet heterostructured electrocatalyst for ORR, whose electrocatalytic activity outperformed the state-of-the-art commercial Pt/C with exceptional durability in alkaline solution. The composite demonstrates the highest activity of all the nonprecious metal electrocatalysts, such as those derived from Co3O4 nanoparticle/nitrogen-doped graphene hybrids and carbon nanotube/nanoparticle composites. Density functional theory (DFT) calculations indicated that the outstanding performance originated from the significant charge transfer from graphene to Co3O4 nanosheets promoting the electron transport through the whole structure. Theoretical calculations revealed that the enhanced stability can be ascribed to the strong interaction generated between both types of sheets.

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High conductive graphene films can be grown on metal foils by chemical vapor deposition (CVD). We here analyzed the use of ethanol, an economic precursor, which results also safer than commonly-used methane. A comprehensive range of process parameters were explored in order to obtain graphene films with optimal characteristics in view of their use in optoelectronics and photovoltaics. Commercially-available and electro-polished copper foils were used as substrates. By finely tuning the CVD conditions, we obtained few-layer (2-4) graphene films with good conductivity (-500 Ohm/sq) and optical transmittance around 92-94% at 550 nm on unpolished copper foils. The growth on electro-polished copper provides instead predominantly mono-layer films with lower conductivity (>1000 Ohm/sq) and with a transmittance of 97.4% at 550 nm. As for the device properties, graphene with optimal properties as transparent conductive film were produced by CVD on standard copper with specific process conditions.

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In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the tau-leaping framework to past information. Using the theta-trapezoidal tau-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k >= 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.

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The aim of this study was to investigate the molecular basis of human IgE-allergen interaction by screening a phage-displayed peptide library with an allergen-specific human IgE-mimicking monoclonal antibody (mAb). A mAb that reacted with major grass pollen allergens was successfully identified and shown to inhibit human IgE-allergen interaction. Biopanning of a phage-displayed random peptide library with this mAb yielded a 12 amino acid long mimotope. A synthetic peptide based on this 12-mer mimotope inhibited mAb and human IgE binding to grass pollen extracts. Our results indicate that such synthetic peptide mimotopes of allergens have potential as novel therapeutic agents. © 2001 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

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Double diffusive Marangoni convection flow of viscous incompressible electrically conducting fluid in a square cavity is studied in this paper by taking into consideration of the effect of applied magnetic field in arbitrary direction and the chemical reaction. The governing equations are solved numerically by using alternate direct implicit (ADI) method together with the successive over relaxation (SOR) technique. The flow pattern with the effect of governing parameters, namely the buoyancy ratio W, diffusocapillary ratio w, and the Hartmann number Ha, is investigated. It is revealed from the numerical simulations that the average Nusselt number decreases; whereas the average Sherwood number increases as the orientation of magnetic field is shifted from horizontal to vertical. Moreover, the effect of buoyancy due to species concentration on the flow is stronger than the one due to thermal buoyancy. The increase in diffusocapillary parameter, w caus

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During their entire lives, people are exposed to the pollutants present in indoor air. Recently, Electronic Nicotine Delivery Systems, mainly known as electronic cigarettes, have been widely commercialized: they deliver particles into the lungs of the users but a “second-hand smoke” has yet to be associated to this indoor source. On the other hand, the naturally-occurring radioactive gas, i.e. radon, represents a significant risk for lung cancer, and the cumulative action of these two agents could be worse than the agents separately would. In order to deepen the interaction between radon progeny and second-hand aerosol from different types of cigarettes, a designed experimental study was carried out by generating aerosol from e-cigarette vaping as well as from second-hand traditional smoke inside a walk-in radon chamber at the National Institute of Ionizing Radiation Metrology (INMRI) of Italy. In this chamber, the radon present in air comes naturally from the floor and ambient conditions are controlled. To characterize the sidestream smoke emitted by cigarettes, condensation particle counters and scanning mobility particle sizer were used. Radon concentration in the air was measured through an Alphaguard ionization chamber, whereas the measurement of radon decay product in the air was performed with the Tracelab BWLM Plus-2S Radon daughter Monitor. It was found an increase of the Potential Alpha-Energy Concentration (PAEC) due to the radon decay products attached to aerosol for higher particle number concentrations. This varied from 7.47 ± 0.34 MeV L−1 to 12.6 ± 0.26 MeV L−1 (69%) for the e-cigarette. In the case of traditional cigarette and at the same radon concentration, the increase was from 14.1 ± 0.43 MeV L−1 to 18.6 ± 0.19 MeV L−1 (31%). The equilibrium factor increases, varying from 23.4% ± 1.11% to 29.5% ± 0.26% and from 30.9% ± 1.0% to 38.1 ± 0.88 for the e-cigarette and traditional cigarette, respectively. These growths still continue for long time after the combustion, by increasing the exposure risk.

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We find that visible light irradiation of gold–palladium alloy nanoparticles supported on photocatalytically inert ZrO2 significantly enhances their catalytic activity for oxidant-free dehydrogenation of aromatic alcohols to the corresponding aldehydes at ambient temperatures. Dehydrogenation is also the dominant process in the selective oxidation of the alcohols to the corresponding aldehydes with molecular oxygen. The alloy nanoparticles strongly absorb light and exhibit superior catalytic and photocatalytic activity when compared to either pure palladium or gold nanoparticles. Analysis with a free electron gas model for the bulk alloy structure reveals that the alloying increases the surface charge heterogeneity on the alloy particle surface, which enhances the interaction between the alcohol molecules and the metal NPs. The increased surface charge heterogeneity of the alloy particles is confirmed with density function theory applied to small alloy clusters. Optimal catalytic activity was observed with a Au : Pd molar ratio of 1 : 186, which is in good agreement with the theoretical analysis. The rate-determining step of the dehydrogenation is hydrogen abstraction. The conduction electrons of the nanoparticles are photo-excited by the incident light giving them the necessary energy to be injected into the adsorbed alcohol molecules, promoting the hydrogen abstraction. The strong chemical adsorption of alcohol molecules facilitates this electron transfer. The results show that the alloy nanoparticles efficiently couple thermal and photonic energy sources to drive the dehydrogenation. These findings provide useful insight into the design of catalysts that utilize light for various organic syntheses at ambient temperatures.

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Background Biochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need for numerical methods that are both fast and accurate. The Bulirsch-Stoer method is an established method for solving ordinary differential equations that possesses both of these qualities. Results In this paper, we present the Stochastic Bulirsch-Stoer method, a new numerical method for simulating discrete chemical reaction systems, inspired by its deterministic counterpart. It is able to achieve an excellent efficiency due to the fact that it is based on an approach with high deterministic order, allowing for larger stepsizes and leading to fast simulations. We compare it to the Euler τ-leap, as well as two more recent τ-leap methods, on a number of example problems, and find that as well as being very accurate, our method is the most robust, in terms of efficiency, of all the methods considered in this paper. The problems it is most suited for are those with increased populations that would be too slow to simulate using Gillespie’s stochastic simulation algorithm. For such problems, it is likely to achieve higher weak order in the moments. Conclusions The Stochastic Bulirsch-Stoer method is a novel stochastic solver that can be used for fast and accurate simulations. Crucially, compared to other similar methods, it better retains its high accuracy when the timesteps are increased. Thus the Stochastic Bulirsch-Stoer method is both computationally efficient and robust. These are key properties for any stochastic numerical method, as they must typically run many thousands of simulations.