New prediction methods for CO2 evaporation inside tubes: Part I - A two-phase flow pattern map and a flow pattern based phenomenological model for two-phase flow frictional pressure drops

An updated flow pattern map was developed for CO2 on the basis of the previous Cheng-Ribatski-Wojtan-Thome CO2 flow pattern map [1,2] to extend the flow pattern map to a wider range of conditions. A new annular flow to dryout transition (A-D) and a new dryout to mist flow transition (D-M) were proposed here. In addition, a bubbly flow region which generally occurs at high mass velocities and low vapor qualities was added to the updated flow pattern map. The updated flow pattern map is applicable to a much wider range of conditions: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m(2) s, heat fluxes from 1.8 to 46 kW/m(2) and saturation temperatures from -28 to +25 degrees C (reduced pressures from 0.21 to 0.87). The updated flow pattern map was compared to independent experimental data of flow patterns for CO2 in the literature and it predicts the flow patterns well. Then, a database of CO2 two-phase flow pressure drop results from the literature was set up and the database was compared to the leading empirical pressure drop models: the correlations by Chisholm [3], Friedel [4], Gronnerud [5] and Muller-Steinhagen and Heck [6], a modified Chisholm correlation by Yoon et al. [7] and the flow pattern based model of Moreno Quiben and Thome [8-10]. None of these models was able to predict the CO2 pressure drop data well. Therefore, a new flow pattern based phenomenological model of two-phase flow frictional pressure drop for CO2 was developed by modifying the model of Moreno Quiben and Thome using the updated flow pattern map in this study and it predicts the CO2 pressure drop database quite well overall. (C) 2007 Elsevier Ltd. All rights reserved.

Assessing the evolution of sustainability reporting in the mining sector

Since the 1990s several large companies have been publishing nonfinancial performance reports. Focusing initially on the physical environment, these reports evolved to consider social relations, as well as data on the firm`s economic performance. A few mining companies pioneered this trend, and in the last years some of them incorporated the three dimensions of sustainable development, publishing so-called sustainability reports. This article reviews 31 reports published between 2001 and 2006 by four major mining companies. A set of 62 assessment items organized in six categories (namely context and commitment, management, environmental, social and economic performance, and accessibility and assurance) were selected to guide the review. The items were derived from international literature and recommended best practices, including the Global Reporting Initiative G3 framework. A content analysis was performed using the report as a sampling unit, and using phrases, graphics, or tables containing certain information as data collection units. A basic rating scale (0 or 1) was used for noting the presence or absence of information and a final percentage score was obtained for each report. Results show that there is a clear evolution in report`s comprehensiveness and depth. Categories ""accessibility and assurance"" and ""economic performance"" featured the lowest scores and do not present a clear evolution trend in the period, whereas categories ""context and commitment"" and ""social performance"" presented the best results and regular improvement; the category ""environmental performance,"" despite it not reaching the biggest scores, also featured constant evolution. Description of data measurement techniques, besides more comprehensive third-party verification are the items most in need of improvement.

Resource use pattern analysis for predicting resource availability in opportunistic grids

This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

Impacts of land-use pattern on soil water-content variability on the Loess Plateau of China

Long-term vegetation restoration carried out on the slopes of the Loess Plateau of China employed different spatial and temporal land-use patterns but very little is known about the effects of these patterns on soil water-content variability. For this study the small Donggou catchment was selected to investigate soil water-content distributions for three spatial scales, including the entire catchment area, sampling transects, and land-use systems. Gravimetric soil water contents were determined incrementally to a soil depth of 1.20 m, on 10 occasions from April to October, 2007, at approximately 20-day intervals. Results indicated that soil water contents were affected by the six land-use types, resulting in four distinct patterns of vertical distribution of soil moisture (uniform, increasing, decreasing, and fluctuating with soil depth). The soil water content and its variation were also influenced in a complex manner by five land-use patterns distributed along transects following the gradients of five similar slopes. These patterns with contrasting hydrological responses in different components, such as forage land (alfalfa)-cropland-shrubland or shrubland-grassland (bunge needlegrass)-cropland-grassland, showed the highest soil water-content variability. Soil water at the catchment scale exhibited a moderate variability for each measurement date, and the variability of soil water content decreased exponentially with increasing soil water content. The minimum sample size for accurate data for use in a hydrological model for the catchment, for example, required many more samples for drier (69) than for wet (10) conditions. To enhance erosion and runoff control, this study suggested two strategies for land management: (i) to create a mosaic pattern by land-use arrangement that located units with higher infiltration capacities downslope from those with lower soil infiltrabilities; and (ii) raising the soil-infiltration capacity of units within the spatial mosaic pattern where possible.

Spatial pattern of black spot incidence within citrus trees related to disease severity and pathogen dispersal

Guignardia citricarpa, the causal agent of citrus black spot, forms airborne ascospores on decomposing citrus leaves and water-spread conidia on fruits, leaves and twigs. The spatial pattern of diseased fruit in citrus tree canopies was used to assess the importance of ascospores and conidia in citrus black spot epidemics in Sao Paulo State, Brazil. The aggregation of diseased fruit in the citrus tree canopy was quantified by the binomial dispersion index (D) and the binary form of Taylor`s Power Law for 303 trees in six groves. D was significantly greater than 1 in 251 trees. The intercept of the regression line of Taylor`s Power Law was significantly greater than 0 and the slope was not different from 1, implying that diseased fruit was aggregated in the canopy independent of disease incidence. Disease incidence (p) and severity (S) were assessed in 2875 citrus trees. The incidence-severity relationship was described (R-2 = 88.7%) by the model ln(S) = ln(a) + bCLL(p) where CLL = complementary log-log transformation. The high severity at low incidence observed in many cases is also indicative of low distance spread of G. citricarpa spores. For the same level of disease incidence, some trees had most of the diseased fruit with many lesions and high disease severity, whereas other trees had most of the fruit with few lesions and low disease severity. Aggregation of diseased fruit in the trees suggests that splash-dispersed conidia have an important role in increasing the disease in citrus trees in Brazil.

Characterization of the electrocardiographic pattern of individuals with cerebral palsy

Background: Dentists of Lar Sao Francisco observed during dental treatment that children with cerebral palsy (CP) had increased heart rate (HR) and lower production of saliva. Despite the high prevalence of CP found in the literature (2.08-3.6/1000 individuals), little is known about the electrocardiographic (ECG) characteristics, especially HR, of individuals with CP. Objective: This study aimed to investigate the hypothesis that individuals with CP have a higher HR and to define other ECG characteristics of this population. Methods: Ninety children with CP underwent clinical examination and 12-lead rest ECG. Electrocardiographic data on rhythm, HR, PR interval, QRS duration, P/QRS/T axis, and QT, QTc and T(peak-end) intervals (minimum, mean, maximum, and dispersion) were measured and analyzed then compared with data from a control group with 35 normal children. Fisher and Mann-Whitney U tests were used, respectively, to compare categorical and continuous data. Results: Groups cerebral palsy and control did not significantly differ in age (9 +/- 3 x 9 +/- 4 years) and male gender (65% x 49%). Children with CP had a higher HR (104.0 +/- 20.6 x 84.2 +/- 13.3 beats per minute; P < .0001), shorter PR interval (128.8 +/- 15.0 x 138.1 +/- 15.1 milliseconds; P = .0018), shorter QRS duration (77.4 +/- 8.6 x 82.0 +/- 8.7 milliseconds; P = .0180), QRS axis (46.0 degrees +/- 26.3 degrees x 59.7 degrees +/- 24.8 degrees; P = .0024) and T-wave axis (34.3 degrees +/- 28.9 degrees x 42.9 degrees +/- 17.1 degrees; P = .034) more horizontally positioned, and greater mean QTc (418.1 +/- 18.4 x 408.5 +/- 19.4 milliseconds; P = .0110). All the electrocardiogram variables were within the reference range for the age group including those with significant differences. Conclusion: Children with CP showed increased HR and other abnormal ECG findings in the setting of this investigation. Further studies are needed to explain our findings and to correlate the increased HR with situations such as dehydration, stress, and autonomic nervous disorders. (C) 2011 Elsevier Inc. All rights reserved.

Conservation of dual-targeted proteins in Arabidopsis and rice points to a similar pattern of gene-family evolution

Gene duplication followed by acquisition of specific targeting information and dual targeting were evolutionary strategies enabling organelles to cope with overlapping functions. We examined the evolutionary trend of dual-targeted single-gene products in Arabidopsis and rice genomes. The number of paralogous proteins encoded by gene families and the dual-targeted orthologous proteins were analysed. The number of dual-targeted proteins and the corresponding gene-family sizes were similar in Arabidopsis and rice irrespective of genome sizes. We show that dual targeting of methionine aminopeptidase, monodehydroascorbate reductase, glutamyl-tRNA synthetase, and tyrosyl-tRNA synthetase was maintained despite occurrence of whole-genome duplications in Arabidopsis and rice as well as a polyploidization followed by a diploidization event (gene loss) in the latter.

The effect of storage on the solubilization pattern of bean hull non-starch polysaccharides

The storage of Carioca bean at 30 C and 75% relative humidity for eight months altered the solubilization pattern of hulls non-starch polysaccharides The polysaccharide physicochemical pattern changed resulting in a shift in the composition of water-soluble and water-insoluble polysaccharides caused by the insolubilization of galacturonans and xyloglucan Hulls make up 10% of whole beans which showed an increase of about 5% in water-insoluble polysaccharides and a decrease of about 1% in water-soluble polysaccharides with aging These values suggest that cotyledons and hulls together account for an increase of about 2 g of water-insoluble polysaccharides and a decrease of 1 5 g of water-soluble polysaccharides per 100 g of beans This change in the polysaccharide composition may produce a considerable difference in the dietary fiber profile The alterations observed in bean hull non-starch polysaccharide composition were similar to those previously observed in the cotyledon (C) 2010 Elsevier Ltd All rights reserved

Restoration of Pattern Recognition Receptor Costimulation to Treat Chromoblastomycosis, a Chronic Fungal Infection of the Skin

Chromoblastomycosis is a chronic skin infection caused by the fungus Fonsecaea pedrosoi. Exploring the reasons underlying the chronic nature of F. pedrosoi infection in a murine model of chromoblastomycosis, we find that chronicity develops due to a lack of pattern recognition receptor (PRR) costimulation. F. pedrosoi was recognized primarily by C-type lectin receptors (CLRs), but not by Toll-like receptors (TLRs), which resulted in the defective induction of proinflammatory cytokines. Inflammatory responses to F. pedrosoi could be reinstated by TLR costimulation, but also required the CLR Mincle and signaling via the Syk/CARD9 pathway. Importantly, exogenously administering TLR ligands helped clear F. pedrosoi infection in vivo. These results demonstrate how a failure in innate recognition can result in chronic infection, highlight the importance of coordinated PRR signaling, and provide proof of the principle that exogenously applied PRR agonists can be used therapeutically.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

Interference pattern with a dark center from two atoms driven by a coherent laser field

In a recent paper Meyer and Yeoman [Phys. Rev. Lett. 79, 2650 (1997)] have shown that the resonance fluorescence from two atoms placed in a cavity and driven by an incoherent field can produce an interference pattern with a dark center. We study the fluorescence from two coherently driven atoms in free space and show that this system can also produce an interference pattern with a dark center. This happens when the atoms are in nonequivalent positions in the driving: field, i.e., the atoms experience different intensities and phases of the driving field. We discuss the role of the interatomic interactions in this process and find that the interference pattern with a dark center results from the participation of the antisymmetric state in the dynamics of the driven two-atom system.

Interference pattern with a dark center in resonance fluorescence from two atoms driven by a squeezed vacuum field

We study the resonance fluorescence from two interacting atoms driven by a squeezed vacuum field and show that this system produces an interference pattern with a dark center. We discuss the role of the interatomic interactions in this process and find that the interference pattern results from an unequal population of the symmetric and antisymmetric states of the two-atom system. We also identify intrinsically nonclassical effects versus classical squeezed field effects, (C) 1998 Elsevier Science B.V. All rights reserved.

Knowledge discovery and data mining in biological databases

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.