991 resultados para sphere packing kissing number
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Norway is currently the only Western European state and ‘old’ NATO member that strongly relies on the traditional dimension of NATO's collective defence. It is also the only ally in Western Europe which perceives Russia as a threat to its military security, in the so-called High North. In order to successfully deal with the potential challenges and threats in the region, Norway has been pursuing a defence policy based on cooperation and deterrence. Cooperation means improving collaboration with Russia in cross-border relations, in the petroleum sector and in the military sphere. The deterrent measures include maintaining NATO’s credibility as a collective defence alliance; increasing military cooperation with the United States; building up Norway’s own military capabilities; and developing military cooperation across Northern Europe. The primary objective of Oslo’s defence policy is to minimise the likelihood of crises and conflicts emerging in the High North which could prove too ‘big’ for Norway but too ‘small’ for NATO.
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The ‘turn to the East’ proclaimed by Russia in 2010 has failed to bring about a fundamental breakthrough in her relations with Asian countries, nor has it produced impulses for the economic modernization of Russia’s Far Eastern territories. Although the energisation of Russian policy towards Asia which has taken place under this slogan has diversified Russian foreign policy somewhat, this diversification has two weak points: Firstly, it has occurred only in the political sphere. The share of Asian countries in Russia’s foreign economic relations has not risen significantly in comparison with the share of European and North American countries. Secondly, the ‘turn to the East’ has turned out primarily to be a turn towards China. In all spheres – diplomatic, economic, energy and military – it is Beijing that has become the most important Asian partner for Moscow. The result is that the policy that aimed to limit the excessive – in the Kremlin’s view – dependence of Russia on the West is likely to turn Russia into a ‘junior partner’ of the People’s Republic of China.
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The Eurasian Economic Union (EaEU), a project forced through by Russia which links it to Kazakhstan, Belarus, Armenia and Kyrgyzstan, is currently struggling with serious problems. The economic crisis in Russia – mainly caused by the fall in the price of oil on world markets and exacerbated by sanctions imposed by Western countries in connection with the Ukraine conflict – is affecting these uncompetitive post-Soviet economies which are dependent on Russia. This has resulted in increased economic and political tension among the members of the EaEU. From Russia’s point of view, however, the EaEU project remains useful, because it is not economic integration that is Moscow’s priority. The Union remains its most important instrument for implementing the Kremlin’s geo-political objectives, in particular maintaining its sphere of influence and preventing post-Soviet countries from integrating with the West, as well as restricting their rapprochement with China. Moscow is pushing for the EaEU to include new countries, strengthening its tools for political dominance within the Union, and promoting its project on the international stage. However, the future of this project will depend on both the continued determination of the Kremlin, and whether the other countries can change the rules for integration by taking advantage of the current crisis.
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Since gaining its independence Tajikistan has faced severe political, economic and social problems. The last several months has seen a clear increase in their intensity. This is in part caused by the deteriorating economic situation in Russia and the significant fall of remittances from the Tajik labour migrants in Russia, as well as by President Emomali Rahmon’s rising authoritarianism. Despite this intensification, qualitatively speaking Tajikistan’s problems have been unchanged for years. Besides the state’s structural weakness, the main cause is the ongoing neo-colonial dependence on Russia, which effectively limits Dushanbe’s room for political manoeuvre and keep Tajikistan in Russia’s sphere of control. This dependence on the one hand protects the country from collapsing, but on the other it precludes the development of the state, resulting in Tajikistan’s enduring stagnation. Similar processes also take place in other countries of post-Soviet Central Asia. However, in the case of Tajikistan the dependence and stagnation it causes are the strongest and their mechanisms most easily observed.
Resumo:
Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.
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In this paper, we evaluate the performance of the 1- and 5-site models of methane on the description of adsorption on graphite surfaces and in graphitic slit pores. These models have been known to perform well in the description of the fluid-phase behavior and vapor-liquid equilibria. Their performance in adsorption is evaluated in this work for nonporous graphitized thermal carbon black, and simulation results are compared with the experimental data of Avgul and Kiselev (Chemistry and Physics of Carbon; Dekker: New York, 1970; Vol. 6, p 1). On this nonporous surface, it is found that these models perform as well on isotherms at various temperatures as they do on the experimental isosteric heat for adsorption on a graphite surface. They are then tested for their performance in predicting the adsorption isotherms in graphitic slit pores, in which we would like to explore the effect of confinement on the molecule packing. Pore widths of 10 and 20 angstrom are chosen in this investigation, and we also study the effects of temperature by choosing 90.7, 113, and 273 K. The first two are for subcritical conditions, with 90.7 K being the triple point of methane and 113 K being its boiling point. The last temperature is chosen to represent the supercritical condition so that we can investigate the performance of these models at extremely high pressures. We have found that for the case of slit pores investigated in this paper, although the two models yield comparable pore densities (provided the accessible pore width is used in the calculation of pore density), the number of particles predicted by the I-site model is always greater than that predicted by the 5-site model, regardless of whether temperature is subcritical or supercritical. This is due to the packing effect in the confined space such that a methane molecule modeled as a spherical particle in the I-site model would pack better than the fused five-sphere model in the case of the 5-site model. Because the 5-site model better describes the liquid- and solid-phase behavior, we would argue that the packing density in small pores is better described with a more detailed 5-site model, and care should be exercised when using the 1-site model to study adsorption in small pores.
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We define Picard cycles on each smooth three-sheeted Galois cover C of the Riemann sphere. The moduli space of all these algebraic curves is a nice Shimura surface, namely a symmetric quotient of the projective plane uniformized by the complex two-dimensional unit ball. We show that all Picard cycles on C form a simple orbit of the Picard modular group of Eisenstein numbers. The proof uses a special surface classification in connection with the uniformization of a classical Picard-Fuchs system. It yields an explicit symplectic representation of the braid groups (coloured or not) of four strings.
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A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.
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Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.
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The measurement of submicrometre (< 1.0 m) and ultrafine particles (diameter < 0.1 m) number concentration have attracted attention since the last decade because the potential health impacts associated with exposure to these particles can be more significant than those due to exposure to larger particles. At present, ultrafine particles are not regularly monitored and they are yet to be incorporated into air quality monitoring programs. As a result, very few studies have analysed their long-term and spatial variations in ultrafine particle concentration, and none have been in Australia. To address this gap in scientific knowledge, the aim of this research was to investigate the long-term trends and seasonal variations in particle number concentrations in Brisbane, Australia. Data collected over a five-year period were analysed using weighted regression models. Monthly mean concentrations in the morning (6:00-10:00) and the afternoon (16:00-19:00) were plotted against time in months, using the monthly variance as the weights. During the five-year period, submicrometre and ultrafine particle concentrations increased in the morning by 105.7% and 81.5% respectively whereas in the afternoon there was no significant trend. The morning concentrations were associated with fresh traffic emissions and the afternoon concentrations with the background. The statistical tests applied to the seasonal models, on the other hand, indicated that there was no seasonal component. The spatial variation in size distribution in a large urban area was investigated using particle number size distribution data collected at nine different locations during different campaigns. The size distributions were represented by the modal structures and cumulative size distributions. Particle number peaked at around 30 nm, except at an isolated site dominated by diesel trucks, where the particle number peaked at around 60 nm. It was found that ultrafine particles contributed to 82%-90% of the total particle number. At the sites dominated by petrol vehicles, nanoparticles (< 50 nm) contributed 60%-70% of the total particle number, and at the site dominated by diesel trucks they contributed 50%. Although the sampling campaigns took place during different seasons and were of varying duration these variations did not have an effect on the particle size distributions. The results suggested that the distributions were rather affected by differences in traffic composition and distance to the road. To investigate the occurrence of nucleation events, that is, secondary particle formation from gaseous precursors, particle size distribution data collected over a 13 month period during 5 different campaigns were analysed. The study area was a complex urban environment influenced by anthropogenic and natural sources. The study introduced a new application of time series differencing for the identification of nucleation events. To evaluate the conditions favourable to nucleation, the meteorological conditions and gaseous concentrations prior to and during nucleation events were recorded. Gaseous concentrations did not exhibit a clear pattern of change in concentration. It was also found that nucleation was associated with sea breeze and long-range transport. The implications of this finding are that whilst vehicles are the most important source of ultrafine particles, sea breeze and aged gaseous emissions play a more important role in secondary particle formation in the study area.
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Having flexible notions of the unit (e.g., 26 ones can be thought of as 2.6 tens, 1 ten 16 ones, 260 tenths, etc.) should be a major focus of elementary mathematics education. However, often these powerful notions are relegated to computations where the major emphasis is on "getting the right answer" thus procedural knowledge rather than conceptual knowledge becomes the primary focus. This paper reports on 22 high-performing students' reunitising processes ascertained from individual interviews on tasks requiring unitising, reunitising and regrouping; errors were categorised to depict particular thinking strategies. The results show that, even for high-performing students, regrouping is a cognitively complex task. This paper analyses this complexity and draws inferences for teaching.
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Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.