159 resultados para TIR CO2 FIR O2 profili VMR lembo retrieval microwindows


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Phase behavior of CO2 confined in porous fractal silica with volume fraction of SiO2 φs = 0.15 was investigated using small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS) techniques. The range of fluid densities (0<(FCO2)bulk<0.977 g/cm3) and temperatures (T=22 °C, 35 and 60 °C) corresponded to gaseous, liquid, near critical and supercritical conditions of the bulk fluid. The results revealed formation of a dense adsorbed phase in small pores with sizes D<40 A° at all temperatures. At low pressure (P <55 bar, (FCO2)bulk <0.2 g/cm3) the average fluid density in pores may exceed the density of bulk fluid by a factor up to 6.5 at T=22 °C. This “enrichment factor” gradually decreases with temperature, however significant fluid densification in small pores still exists at temperature T=60°C, i.e., far above the liquid-gas critical temperature of bulk CO2 (TC=31.1 °C). Larger pores are only partially filled with liquid-like adsorbed layer which coexists with unadsorbed fluid in the pore core. With increasing pressure, all pores become uniformly filled with the fluid, showing no measurable enrichment or depletion of the porous matrix with CO2.

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We have applied X-ray and neutron small-angle scattering techniques (SAXS, SANS, and USANS) to study the interaction between fluids and porous media in the particular case of subcritical CO2 sorption in coal. These techniques are demonstrated to give unique, pore-size-specific insights into the kinetics of CO2 sorption in a wide range of coal pores (nano to meso) and to provide data that may be used to determine the density of the sorbed CO2. We observed densification of the adsorbed CO2 by a factor up to five compared to the free fluid at the same (p, T) conditions. Our results indicate that details of CO2 sorption into coal pores differ greatly between different coals and depend on the amount of mineral matter dispersed in the coal matrix: a purely organic matrix absorbs more CO2 per unit volume than one containing mineral matter, but mineral matter markedly accelerates the sorption kinetics. Small pores are filled preferentially by the invading CO2 fluid and the apparent diffusion coefficients have been estimated to vary in the range from 5 × 10-7 cm2/min to more than 10-4 cm2/min, depending on the CO2 pressure and location on the sample.

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Time- and position-resolved synchrotron small angle X-ray scattering data were acquired from samples of two Australian coal seams: Bulli seam (Bulli 4, Ro=1.42%, Sydney Basin), which naturally contains CO2 and Baralaba seam (Ro=0.67%, Bowen Basin), a potential candidate for sequestering CO2. This experimental approach has provided unique, pore-size-specific insights into the kinetics of CO2 sorption in the micro- and small mesopores (diameter 5 to 175 Å) and the density of the sorbed CO2 at reservoir-like conditions of temperature and hydrostatic pressure. For both samples, at pressures above 5 bar, the density of CO2 confined in pores was found to be uniform, with no densification in near-wall regions. In the Bulli 4 sample, CO2 first flooded the slit pores between polyaromatic sheets. In the pore-size range analysed, the confined CO2 density was close to that of the free CO2. The kinetics data are too noisy for reliable quantitative analysis, but qualitatively indicate faster kinetics in mineral-matter-rich regions. In the Baralaba sample, CO2 preferentially invaded the smallest micropores and the confined CO2 density was up to five times that of the free CO2. Faster CO2 sorption kinetics was found to be correlated with higher mineral matter content but, the mineral-matter-rich regions had lower-density CO2 confined in their pores. Remarkably, the kinetics was pore-size dependent, being faster for smaller pores. These results suggest that injection into the permeable section of an interbedded coal-clastic sequence could provide a viable combination of reasonable injectivity and high sorption capacity.

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Recently, the capture and storage of CO2 have attracted research interest as a strategy to reduce the global emissions of greenhouse gases. It is crucial to find suitable materials to achieve an efficient CO2 capture. Here we report our study of CO2 adsorption on boron-doped C60 fullerene in the neutral state and in the 1e−-charged state. We use first principle density functional calculations to simulate the CO2 adsorption. The results show that CO2 can form weak interactions with the BC59 cage in its neutral state and the interactions can be enhanced significantly by introducing an extra electron to the system.

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We present a study to understand the effect that negated terms (e.g., "no fever") and family history (e.g., "family history of diabetes") have on searching clinical records. Our analysis is aimed at devising the most effective means of handling negation and family history. In doing so, we explicitly represent a clinical record according to its different content types: negated, family history and normal content; the retrieval model weights each of these separately. Empirical evaluation shows that overall the presence of negation harms retrieval effectiveness while family history has little effect. We show negation is best handled by weighting negated content (rather than the common practise of removing or replacing it). However, we also show that many queries benefit from the inclusion of negated content and that negation is optimally handled on a per-query basis. Additional evaluation shows that adaptive handing of negated and family history content can have significant benefits.

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Relevation! is a system for performing relevance judgements for information retrieval evaluation. Relevation! is web-based, fully configurable and expandable; it allows researchers to effectively collect assessments and additional qualitative data. The system is easily deployed allowing assessors to smoothly perform their relevance judging tasks, even remotely. Relevation! is available as an open source project at: http://ielab.github.io/relevation.

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The top-k retrieval problem aims to find the optimal set of k documents from a number of relevant documents given the user’s query. The key issue is to balance the relevance and diversity of the top-k search results. In this paper, we address this problem using Facility Location Analysis taken from Operations Research, where the locations of facilities are optimally chosen according to some criteria. We show how this analysis technique is a generalization of state-of-the-art retrieval models for diversification (such as the Modern Portfolio Theory for Information Retrieval), which treat the top-k search results like “obnoxious facilities” that should be dispersed as far as possible from each other. However, Facility Location Analysis suggests that the top-k search results could be treated like “desirable facilities” to be placed as close as possible to their customers. This leads to a new top-k retrieval model where the best representatives of the relevant documents are selected. In a series of experiments conducted on two TREC diversity collections, we show that significant improvements can be made over the current state-of-the-art through this alternative treatment of the top-k retrieval problem.

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The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP’s limitations. All alternatives deviate from the PRP by incorporating dependencies. This results in a re-ranking that promotes or demotes documents depending upon their relationship with the documents that have been already ranked. In this paper, we compare and contrast the behaviour of state-of-the-art ranking strategies and principles. To do so, we tease out analytical relationships between the ranking approaches and we investigate the document kinematics to visualise the effects of the different approaches on document ranking.

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In this paper, we consider the problem of document ranking in a non-traditional retrieval task, called subtopic retrieval. This task involves promoting relevant documents that cover many subtopics of a query at early ranks, providing thus diversity within the ranking. In the past years, several approaches have been proposed to diversify retrieval results. These approaches can be classified into two main paradigms, depending upon how the ranks of documents are revised for promoting diversity. In the first approach subtopic diversification is achieved implicitly, by choosing documents that are different from each other, while in the second approach this is done explicitly, by estimating the subtopics covered by documents. Within this context, we compare methods belonging to the two paradigms. Furthermore, we investigate possible strategies for integrating the two paradigms with the aim of formulating a new ranking method for subtopic retrieval. We conduct a number of experiments to empirically validate and contrast the state-of-the-art approaches as well as instantiations of our integration approach. The results show that the integration approach outperforms state-of-the-art strategies with respect to a number of measures.

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In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

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While the Probability Ranking Principle for Information Retrieval provides the basis for formal models, it makes a very strong assumption regarding the dependence between documents. However, it has been observed that in real situations this assumption does not always hold. In this paper we propose a reformulation of the Probability Ranking Principle based on quantum theory. Quantum probability theory naturally includes interference effects between events. We posit that this interference captures the dependency between the judgement of document relevance. The outcome is a more sophisticated principle, the Quantum Probability Ranking Principle, that provides a more sensitive ranking which caters for interference/dependence between documents’ relevance.

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We consider the following problem: users in a dynamic group store their encrypted documents on an untrusted server, and wish to retrieve documents containing some keywords without any loss of data confidentiality. In this paper, we investigate common secure indices which can make multi-users in a dynamic group to obtain securely the encrypted documents shared among the group members without re-encrypting them. We give a formal definition of common secure index for conjunctive keyword-based retrieval over encrypted data (CSI-CKR), define the security requirement for CSI-CKR, and construct a CSI-CKR based on dynamic accumulators, Paillier’s cryptosystem and blind signatures. The security of proposed scheme is proved under strong RSA and co-DDH assumptions.

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A dynamic accumulator is an algorithm, which merges a large set of elements into a constant-size value such that for an element accumulated, there is a witness confirming that the element was included into the value, with a property that accumulated elements can be dynamically added and deleted into/from the original set. Recently Wang et al. presented a dynamic accumulator for batch updates at ICICS 2007. However, their construction suffers from two serious problems. We analyze them and propose a way to repair their scheme. We use the accumulator to construct a new scheme for common secure indices with conjunctive keyword-based retrieval.

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The mineral lomonosovite has been studied using a combination of scanning electron microscopy with energy dispersive X-ray analysis and vibrational spectroscopy. Qualitative chemical analysis gave Si, P, Na and Ti as the as major elements with small amounts of Mn, Ca, Fe and Al. The mineral lomonosovite has a formula Na5Ti2(Si2O7)(PO4)O2. Raman bands observed at 909, 925 and 939 cm−1 are associated with phosphate units. Raman bands found at 975, 999, 1070, 1080 and 1084 cm−1 are attributed to siloxane stretching vibrations. The observation of multiple bands in both the phosphate stretching and bending regions supports the concept that the symmetry of the phosphate anion in the structure of lomonosovite is significantly reduced. Infrared spectroscopy identifies bands in the water stretching and bending regions, thus suggesting that water is involved with the structure of lomonosovite either through adsorption on the surface or by bonding to the phosphate units.

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The Ar/O2plasma needle in the induction of A549 cancer cells apoptosis process is studied by means of real-time observation. The entire process of programmed cell death is observed. The typical morphological changes of A549 apoptosis are detected by 4′, 6-diamidino-2-phenylindole staining, for example, chromatin condensation and nuclear fragmentation. Cell viability is determined and quantified by neutral red uptake assay, and the survival rate of A549 from Ar/O2plasmas is presented. Further spectral analysis indicates the reactive species, including O and OH play crucial roles in the cell inactivation.