499 research outputs found

    Qualitative assessment of the purity of multi-walled carbon nanotube samples using krypton adsorption

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    peer reviewedKrypton is a subcritical vapour at the nitrogen boiling temperature. As such, its adsorption on crystalline surfaces leads to condensation steps, typical of type VI isotherms according to IUPAC, while its adsorption on rough surfaces is BET-like. Based on this property of krypton adsorption at 77 K, a methodology is proposed to determine the purity of carbon nanotubes samples. The method is tested on model samples obtained by mixing mechanically purified multi-walled carbon nanotubes with various amounts of the same catalyst as used for their synthesis

    Agrometeorological forecasting

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    Agrometeorological forecasting covers all aspects of forecasting in agrometeorology. Therefore, the scope of agrometeorological forecasting very largely coincides with the scope of agrometeorology itself. All on-farm and regional agrometeorological planning implies some form of impact forecasting, at least implicitly, so that decision-support tools and forecasting tools largely overlap. In the current chapter, the focus is on crops, but attention is also be paid to sectors that are often neglected by the agrometeorologist, such as those occurring in plant and animal protection. In addition, the borders between meteorological forecasts for agriculture and agrometeorological forecasts are not always clear. Examples include the use of weather forecasts for farm operations such as spraying pesticides or deciding on trafficability in relation to adverse weather. Many forecast issues by various national institutions (weather, but also commodity prices or flood warnings) are vital to the farming community, but they do not constitute agrometeorological forecasts. (Modified From the introduction of the chapter: Scope of agrometeorological forecasting)JRC.H.4-Monitoring Agricultural Resource

    Density of States for a Specified Correlation Function and the Energy Landscape

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    The degeneracy of two-phase disordered microstructures consistent with a specified correlation function is analyzed by mapping it to a ground-state degeneracy. We determine for the first time the associated density of states via a Monte Carlo algorithm. Our results are described in terms of the roughness of the energy landscape, defined on a hypercubic configuration space. The use of a Hamming distance in this space enables us to define a roughness metric, which is calculated from the correlation function alone and related quantitatively to the structural degeneracy. This relation is validated for a wide variety of disordered systems.Comment: Accepted for publication in Physical Review Letter

    Значение традиционных нравственно-эстетических ценностей в формировании духовного мира ребенка в произведениях Эмиля Амита

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    Предлагаемый вниманию материал посвящён значению традиционных нравственно-эстетических ценностей в формировании духовного мира подрастающего поколения. Обращение к испокон веков ценимым ценностям под пером автора обретает особое звучание.Пропонований увазі матеріал присвячений проблемі еволюції морального ідеалу в творчості Е.Аміт. Традиційні споконвічні ціності під пером автора набувають особливого звучання.The material which is proposed to you dedicated to a problem of the evolution of the moral ideal in the creation of A Rmit

    Investigating the relationship between the inter-annual variability of satellite-derived vegetation phenology and a proxy of biomass production in the Sahel

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    In the Sahel region, moderate to coarse spatial resolution remote sensing time series are used in early warning monitoring systems with the aim of detecting unfavorable crop and pasture conditions and informing stakeholders about impending food security risks. Despite growing evidence that vegetation productivity is directly related to phenology, most approaches to estimate such risks do not explicitly take into account the actual timing of vegetation growth and development. The date of the start of the season (SOS) or of the peak canopy density can be assessed by remote sensing techniques in a timely manner during the growing season. However, there is limited knowledge about the relationship between vegetation biomass production and these variables at regional scale. This study describes a first attempt to increase our understanding of such a relationship through the analysis of phenological variables retrieved from SPOT-VEGETATION time series of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). Two key phenological variables (growing season length, GSL; timing of SOS) and the maximum value of FAPAR attained during the growing season (Peak) are analyzed as potentially related to a proxy of biomass production (CFAPAR, the cumulative value of FAPAR during the growing season). GSL, SOS and Peak all show different spatial patterns of correlation with CFAPAR. In particular, GSL shows a high and positive correlation with CFAPAR over the whole Sahel (mean r = 0.78). The negative correlation between delays in SOS and CFAPAR is stronger (mean r = -0.71) in the southern agricultural band of the Sahel, while the positive correlation between Peak FAPAR and CFAPAR is higher in the northern and more arid grassland region (mean r = 0.75). The consistency of the results and the actual link between remote-sensing derived phenological parameters and biomass production were evaluated using field measurements of aboveground herbaceous biomass of rangelands in Senegal. This study demonstrates the potential of phenological variables as indicators of biomass production. Nevertheless, the strength of the relation between phenological variables and biomass production is not universal and indeed quite variable geographically, with large scattered areas not showing a statistically significant relationship.JRC.H.4-Monitoring Agricultural Resource

    Farmers perceptions of climate change related events in Shendam and Riyom, Nigeria

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    Although agriculture in Nigeria is the major source of income for about 70% of the active population, the impact of agrarian infrastructure on boosting productivity and supporting livelihoods has increased. Climate change and the increasing trend of climate-related events in Nigeria challenge both the stability of agrarian infrastructure and livelihood systems. Based on case studies of two local communities in Plateau state in Nigeria, this paper utilizes a range of perceptions to examine the impacts of climate-related events on agrarian infrastructures and how agrarian livelihood systems are, in turn, affected. Data are obtained from a questionnaire survey (n = 175 farmers) and semi-structured interviews (n = 14 key informants). The study identifies local indicators of climate change, high risks climate events and the components of agrarian infrastructures that are at risk from climate events. Findings reveal that, changes in rainfall and temperature patterns increase the probability of floods and droughts. They also reveal that, although locational differences account for the high impact of floods on road transport systems and droughts on irrigation infrastructures, both have a chain of negative effects on agricultural activities, economic activities and livelihood systems. A binomial logistic regression model is used to predict the perceived impact levels of floods and droughts, while an in-depth analysis is utilized to corroborate the quantitative results. The paper further stresses the need to strengthen the institutional capacity for risk reduction through the provision of resilient infrastructures, as the poor conditions of agrarian infrastructure were identified as dominant factors on the high impact levels

    Microstructural Degeneracy associated with a Two-Point Correlation Function and its Information Content

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    Two-point correlation functions provide crucial yet incomplete characterization of microstructures because different microstructures may have the same correlation function. In an earlier Letter [Phys. Rev. Lett. 108, 080601 (2012)], we addressed the degeneracy question: What is the number of microstructures compatible with a specified correlation function? We computed this degeneracy, i.e., configurational entropy, in the framework of reconstruction methods, which enabled us to map the problem to the determination of ground-state degeneracies. Here, we provide a more comprehensive presentation and additional results. Since the configuration space of a reconstruction problem is a hypercube on which a Hamming distance is defined, we can calculate analytically an energy profile corresponding to the average energy of all microstructures at a given Hamming distance from a ground state. The steepness of this profile is a measure of the roughness of the energy landscape, which can be used as a proxy for ground-state degeneracy. The relationship between roughness metric and ground-state degeneracy is calibrated using a Monte Carlo algorithm for determining the degeneracy of a variety of microstructures, including hard disks and Poisson point processes as well as those with known degeneracies (single disks of various sizes and a particular crystalline microstructure). We show that our results can be expressed in terms of the information content of the two-point correlation functions. From this perspective, the a priori condition for a reconstruction to be accurate is that the information content, expressed in bits, should be comparable to the number of pixels in the unknown microstructure. We provide a formula to calculate the information content of any two-point correlation function, which makes our results broadly applicable to any field in which correlation functions are employed.Comment: Accepted for publication in Physical Review
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