An electrochemical investigation of the formation of CoSx and its effect on the anodic dissolution of iron in ammoniacal-carbonate solutions

It has been found that the co-presence of cobalt (II) and thiosulphate ions in ammoniacal-carbonate solutions promotes the passivation of iron, under conditions in which it would otherwise continue to dissolve anodically. Electrochemical experiments have shown a relationship between the immersion time required for passivation and the formation of a solid species on the iron surface, which is thought to be implicated in the mechanism of passivation, whilst not being itself the protective species. Based on a combination of electrochemical, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and grazing incidence X-ray diffraction (GIXRD) characterisation techniques, the said species has been identified as CoSx, resulting from the interaction of cobalt (II) and thiosulphate ions. It is thought to form as a product of the cathodic reactions taking place on the iron surface during its active dissolution. These findings are particularly relevant to the Caron process, in which the ammoniacal-carbonate solutions containing dissolved cobalt and thiosulphate ions are used to leach nickel and cobalt from pre-reduced laterite ores rich in metallic iron. Both the loss of cobalt into the CoSx layer and the passivation of iron and of its alloys with nickel and cobalt, are potential contributing factors to the low cobalt and nickel recoveries, which are typical of the Caron process. This study provides a better understanding of the conditions under which the CoSx layer forms and promotes the passivation of iron, and may therefore provide useful information to help minimise the effect this may have on the extraction efficiency of the process. In particular, at the cobalt and thiosulphate ion concentrations usually encountered at a Caron plant, the passivation of iron was found to be prevented by maintaining a high enough concentration of ammonia

Application of alternative lixiviants for secondary heap leaching of gold

Some preliminary results on the secondary leaching of previously heap leached gold ore are presented. Alternative lixiviants for gold comprising chlorine, thiourea and thiosulphate were compared with cyanide using bottle roll tests. Chlorine was subsequently selected for column leaching tests. Column tests at 1.0, 0.1 and 0.01 gL-1 Cl2 at pH 2 were conducted. The results indicated that about 23 per cent of the gold was leached over 45 days using 1 gL-1 Cl2 at pH 2. The experiments conducted proved that the chlorine/chloride system has good potential for further extraction of gold and silver from the existing cyanide heap leach residues and a process for secondary leaching of gold has been proposed. Further testwork is recommended to extend conditions, sample types, and the duration of leaching period

img2net: Automated network-based analysis of imaged phenotypes

Automated analysis of imaged phenotypes enables fast and reproducible quantification of biologically relevant features. Despite recent developments, recordings of complex, networked structures, such as: leaf venation patterns, cytoskeletal structures, or traffic networks, remain challenging to analyze. Here we illustrate the applicability of img2net to automatedly analyze such structures by reconstructing the underlying network, computing relevant network properties, and statistically comparing networks of different types or under different conditions. The software can be readily used for analyzing image data of arbitrary 2D and 3D network-like structures. img2net is open-source software under the GPL and can be downloaded from http://mathbiol.mpimp-golm.mpg.de/img2net/, where supplementary information and data sets for testing are provided.Comment: Bioinformatics, 2014, btu50

Do economic crises lead to health and nutrition behavior responses?: analysis using longitudinal data from Russia

Using longitudinal data on more than 2,000 Russian families spanning the period between 2007 and 2010, this paper estimates the impact of the 2009 global financial crisis on food expenditures, health care expenditures, and doctor visits in Russia. The primary estimation strategy adopted is the semi-parametric difference-in-difference with propensity score matching technique. The analysis finds that household health and nutritional behavior indicators do not vary statistically between households that were crisis-affected and households that were not affected by the crisis. However the analysis finds that crisis-affected poor families curtailed their out-of-pocket health expenditures during and after the crisis more than poor families that were not affected by the crisis did. In addition, crisis-affected vulnerable groups changed their health behavior. In particular, households with low educational attainment of household heads and households with more elderly people changed their health and nutrition behavior response when affected by the crisis. The results are invariant to the propensity score matching techniques and parametric fixed effects estimation models

Institutions and economic performance: What can be explained?

Institutions are now widely believed to be important in explaining performance. In this paper, we analyse whether commonly used measures of institutions have any significant, measurable impact on performance, whether of countries or firms. We look at three ‘levels’ of institutions and associated conjectures. The first concerns whether the political system affects performance. The second concerns whether the business and investment environment affects the performance of countries and the third concerns whether perceived business constraints directly affect the performance of firms. In all instances, we find little evidence of a robust link between widely used measures of institutions and our indicators of performance. We consider why this might be the case and argue that mis-measurement, mis-specification, complexity and non-linearity are all relevant factors.

Institutions and Economic Performance: What Can Be Explained?

Institutions are now widely believed to be important in explaining performance. In this paper, we analyze whether commonly used measures of institutions have any significant, measurable impact on performance, whether of countries or firms. We look at three 'levels' of institutions and associated conjectures. The first concerns whether the political system affects performance. The second concerns whether the business and investment environment affects the performance of countries and the third concerns whether perceived business constraints directly affect the performance of firms. In all instances, we find little evidence of a robust link between widely used measures of institutions and our indicators of performance. We consider why this might be the case and argue that mis-measurement, mis-specification, complexity and non-linearity are all relevant factors.institutions, growth

On the effects of alternative optima in context-specific metabolic model predictions

Recent methodological developments have facilitated the integration of high-throughput data into genome-scale models to obtain context-specific metabolic reconstructions. A unique solution to this data integration problem often may not be guaranteed, leading to a multitude of context-specific predictions equally concordant with the integrated data. Yet, little attention has been paid to the alternative optima resulting from the integration of context-specific data. Here we present computational approaches to analyze alternative optima for different context-specific data integration instances. By using these approaches on metabolic reconstructions for the leaf of Arabidopsis thaliana and the human liver, we show that the analysis of alternative optima is key to adequately evaluating the specificity of the predictions in particular cellular contexts. While we provide several ways to reduce the ambiguity in the context-specific predictions, our findings indicate that the existence of alternative optimal solutions warrant caution in detailed context-specific analyses of metabolism

Graph-theoretic Approach To Modeling Propagation And Control Of Network Worms

In today\u27s network-dependent society, cyber attacks with network worms have become the predominant threat to confidentiality, integrity, and availability of network computing resources. Despite ongoing research efforts, there is still no comprehensive network-security solution aimed at controling large-scale worm propagation. The aim of this work is fivefold: (1) Developing an accurate combinatorial model of worm propagation that can facilitate the analysis of worm control strategies, (2) Building an accurate epidemiological model for the propagation of a worm employing local strategies, (3) Devising distributed architecture and algorithms for detection of worm scanning activities, (4) Designing effective control strategies against the worm, and (5) Simulation of the developed models and strategies on large, scale-free graphs representing real-world communication networks. The proposed pair-approximation model uses the information about the network structure--order, size, degree distribution, and transitivity. The empirical study of propagation on large scale-free graphs is in agreement with the theoretical analysis of the proposed pair-approximation model. We, then, describe a natural generalization of the classical cops-and-robbers game--a combinatorial model of worm propagation and control. With the help of this game on graphs, we show that the problem of containing the worm is NP-hard. Six novel near-optimal control strategies are devised: combination of static and dynamic immunization, reactive dynamic and invariant dynamic immunization, soft quarantining, predictive traffic-blocking, and contact-tracing. The analysis of the predictive dynamic traffic-blocking, employing only local information, shows that the worm can be contained so that 40\% of the network nodes are not affected. Finally, we develop the Detection via Distributed Blackholes architecture and algorithm which reflect the propagation strategy used by the worm and the salient properties of the network. Our distributed detection algorithm can detect the worm scanning activity when only 1.5% of the network has been affected by the propagation. The proposed models and algorithms are analyzed with an individual-based simulation of worm propagation on realistic scale-free topologies

Employment Concentration and Resource Allocation: One-Company Towns in Russia

The paper looks at the effects of employment concentration on resource allocation with a particular focus on one-company towns in Russia defined as towns where a single company accounts for a significant share of total employment of the locality. Empirical analysis of firms' production functions indicates that companies located in one-company towns are characterised by lower marginal product of labour, higher marginal product of capital and lower overall productivity pointing towards significant labour hoarding. One-company town enterprises are also found to be financially more vulnerable. The paper argues that the dominance of natural resources in the Russian economy and employment concentration is closely linked.employment concentration, one-company towns, labour productivity, Russia

Determinants of diabetes in Kuwait: evidence from the World Health Survey

Diabetes is one of the most prevalent non-communicable diseases in the Middle East and North Africa (MENA) region, particularly among countries within the Gulf Cooperation Council (GCC). We analysed data from the World Health Organization’s World Health Survey conducted in Kuwait in 2013 in order to distil the main demographic and socio-economic determinants of diabetes. A subjective measure of diabetes was used given the low blood chemistry measurement response rates. An analysis of key risk factors indicated that obese, hypertensive and insufficiently active respondents were more likely to be diabetic. In addition, when examining the prevalence of multiple chronic conditions, our results showed that diabetic patients were more likely to have been diagnosed with two or more chronic conditions compared to non-diabetics. Finally, results from the multivariate logistic regression model indicated that people’s weight, age and employment status were the most significant predictors of diabetes. Although not the focus of this paper, similar results yield for the entire population (i.e. nationals and expatriates). Given the cost associated with diabetes and that diabetics were more likely to suffer from multiple chronic conditions, the government should devote more effort to preventive types of healthcare