233 resultados para metal-detecting


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Evidence for a two-metal ion mechanism for cleavage of the HH16 hammerhead ribozyme is provided by monitoring the rate of cleavage of the RNA substrate as a function of La3+ concentration in the presence of a constant concentration of Mg2+. We show that a bell-shaped curve of cleavage activation is obtained as La3+ is added in micromolar concentrations in the presence of 8 mM Mg2+, with a maximal rate of cleavage being attained in the presence of 3 microM La3+. These results show that two-metal ion binding sites on the ribozyme regulate the rate of the cleavage reaction and, on the basis of earlier estimates of the Kd values for Mg2+ of 3.5 mM and > 50 mM, that these sites bind La3+ with estimated Kd values of 0.9 and > 37.5 microM, respectively. Furthermore, given the very different effects of these metal ions at the two binding sites, with displacement of Mg2+ by La3+ at the stronger (relative to Mg2+) binding site activating catalysis and displacement of Mg2+ by La3+ at the weaker (relative to Mg2+) (relative to Mg2+) binding site inhibiting catalysis, we show that the metal ions at these two sites play very different roles. We argue that the metal ion at binding site 1 coordinates the attacking 2'-oxygen species in the reaction and lowers the pKa of the attached proton, thereby increasing the concentration of the attacking alkoxide nucleophile in an equilibrium process. In contrast, the role of the metal ion at binding site 2 is to catalyze the reaction by absorbing the negative charge that accumulates at the leaving 5'-oxygen in the transition state. We suggest structural reasons why the Mg(2+)-La3+ ion combination is particularly suited to demonstrating these different roles of the two-metal ions in the ribozyme cleavage reaction.

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Significant cleavage by hammerhead ribozymes requires activation by divalent metal ions. Several models have been proposed to account for the influence of metal ions on hammerhead activity. A number of recent papers have presented data that have been interpreted as supporting a one-metal-hydroxide-ion mechanism. In addition, a solvent deuterium isotope effect has been taken as evidence against a proton transfer in the rate-limiting step of the cleavage reaction. We propose that these data are more easily explained by a two-metal-ion mechanism that does not involve a metal hydroxide, but does involve a proton transfer in the rate-limiting step.

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It is very difficult to selectively oxidise stable compounds such as toluene and xylenes to useful chemicals with molecular oxygen (O 2) under moderate conditions. To achieve high conversion and less over-oxidised products, a new class of photocatalysts, metal hydroxide nanoparticles grafted with alcohols, is devised. They can efficiently oxidise alkyl aromatic compounds with O 2 using visible or ultraviolet light or even sunlight to generate the corresponding aldehydes, alcohols and acids at ambient temperatures and give very little over-oxidation. For example toluene can be oxidised with a 23% conversion after a 48-hour exposure to sunlight with 85% of the product being benzaldehyde, and only a trace of CO 2.The surface complexes grafted onto metal hydroxides can absorb light, generating free radicals on the surface, which then initiate aerobic oxidation of the stable alkyl aromatic molecules with high product selectivity. This mechanism is distinctly different from those of any known catalysts. The use of the new photocatalysts as a controlled means to generate surface radicals through light excitation allows us to drive the production of fine organic chemicals at ambient temperatures with sunlight. The process with the new photocatalysts is especially valuable for temperature-sensitive syntheses and a greener process than many conventional thermal reactions. © 2012 The Royal Society of Chemistry.

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In the context of increasing demand for potable water and the depletion of water resources, stormwater is a logical alternative. However, stormwater contains pollutants, among which metals are of particular interest due to their toxicity and persistence in the environment. Hence, it is imperative to remove toxic metals in stormwater to the levels prescribed by drinking water guidelines for potable use. Consequently, various techniques have been proposed, among which sorption using low cost sorbents is economically viable and environmentally benign in comparison to other techniques. However, sorbents show affinity towards certain toxic metals, which results in poor removal of other toxic metals. It was hypothesised in this study that a mixture of sorbents that have different metal affinity patterns can be used for the efficient removal of a range of toxic metals commonly found in stormwater. The performance of six sorbents in the sorption of Al, Cr, Cu, Pb, Ni, Zn and Cd, which are the toxic metals commonly found in urban stormwater, was investigated to select suitable sorbents for creating the mixtures. For this purpose, a multi criteria analytical protocol was developed using the decision making methods: PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) and GAIA (Graphical Analysis for Interactive Assistance). Zeolite and seaweed were selected for the creation of trial mixtures based on their metal affinity pattern and the performance on predetermined selection criteria. The metal sorption mechanisms employed by seaweed and zeolite were defined using kinetics, isotherm and thermodynamics parameters, which were determined using the batch sorption experiments. Additionally, the kinetics rate-limiting steps were identified using an innovative approach using GAIA and Spearman correlation techniques developed as part of the study, to overcome the limitation in conventional graphical methods in predicting the degree of contribution of each kinetics step in limiting the overall metal removal rate. The sorption kinetics of zeolite was found to be primarily limited by intraparticle diffusion followed by the sorption reaction steps, which were governed mainly by the hydrated ionic diameter of metals. The isotherm study indicated that the metal sorption mechanism of zeolite was primarily of a physical nature. The thermodynamics study confirmed that the energetically favourable nature of sorption increased in the order of Zn < Cu < Cd < Ni < Pb < Cr < Al, which is in agreement with metal sorption affinity of zeolite. Hence, sorption thermodynamics has an influence on the metal sorption affinity of zeolite. On the other hand, the primary kinetics rate-limiting step of seaweed was the sorption reaction process followed by intraparticle diffusion. The boundary layer diffusion was also found to limit the metal sorption kinetics at low concentration. According to the sorption isotherm study, Cd, Pb, Cr and Al were sorbed by seaweed via ion exchange, whilst sorption of Ni occurred via physisorption. Furthermore, ionic bonding is responsible for the sorption of Zn. The thermodynamics study confirmed that sorption by seaweed was energetically favourable in the order of Zn < Cu < Cd < Cr . Al < Pb < Ni. However, this did not agree with the affinity series derived for seaweed suggesting a limited influence of sorption thermodynamics on metal affinity for seaweed. The investigation of zeolite-seaweed mixtures indicated that mixing sorbents have an effect on the kinetics rates and the sorption affinity. Additionally, the theoretical relationships were derived to predict the boundary layer diffusion rate, intraparticle diffusion rate, the sorption reaction rate and the enthalpy of mixtures based on that of individual sorbents. In general, low coefficient of determination (R2) for the relationships between theoretical and experimental data indicated that the relationships were not statistically significant. This was attributed to the heterogeneity of the properties of sorbents. Nevertheless, in relative terms, the intraparticle diffusion rate, sorption reaction rate and enthalpy of sorption had higher R2 values than the boundary layer diffusion rate suggesting that there was some relationship between the former set of parameters of mixtures and that of sorbents. The mixture, which contained 80% of zeolite and 20% of seaweed, showed similar affinity for the sorption of Cu, Ni, Cd, Cr and Al, which was attributed to approximately similar sorption enthalpy of the metal ions. Therefore, it was concluded that the seaweed-zeolite mixture can be used to obtain the same affinity for various metals present in a multi metal system provided the metal ions have similar enthalpy during sorption by the mixture.

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Child abuse and neglect is prevalent and entails significant costs to children, families and society. Teachers are responsible for significant proportions of official notifications to statutory child protection agencies. Hence, their accurate and appropriate reporting is crucial for well-functioning child protection systems. Approximately one-quarter of Australian teachers indicate never detecting a case of child maltreatment across their careers, while a further 13-15% admit to not reporting suspected cases in some circumstances. The detection and reporting of child abuse and neglect are complex decision-making behaviors, influenced by: the nature of the maltreatment itself; the characteristics of the teacher; the school environment; and the broader legislative and policy environment. In this chapter, the authors provide a background to teachers’ involvement in detecting and reporting child abuse and neglect, and an overview of the role of teachers is provided. Results are presented from three Australian studies that examine the unique contributions of: case; teacher; and contextual characteristics to detection and reporting behaviors. The authors conclude by highlighting the key implications for enhancing teacher training in child abuse and neglect, and outline future research directions.

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The research study discussed in the paper investigated the influence of organic matter on heavy metal adsorption for different particle size ranges of build-up solids. Samples collected from road surfaces were assessed for organic matter content, mineral composition, particle size distribution and effective cation exchange capacity. It was found that the organic matter plays a key role in >75µm particles in the adsorption of Zinc, Lead, Nickel and Copper, which are generated by traffic activities. Clay forming minerals and metal oxides of Iron, Aluminium and Manganese was found to be important for heavy metal adsorption to <75µm particles. It was also found that heavy metals adsorbed to organic matter are strongly bound to particles and these metal ions will not be bio-available if the chemical quality of the media remains stable.

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The elastic properties of 1D nanostructures such as nanowires are often measured experimentally through actuation of the nanowire at its resonance frequency, and then relating the resonance frequency to the elastic stiffness using elementary beam theory. In the present work, we utilize large scale molecular dynamics simulations to report a novel beat phenomenon in [110]oriented Ag nanowires. The beat phenomenon is found to arise from the asymmetry of the lattice spacing in the orthogonal elementary directions of the [110] nanowire, i.e. the [-110] and [001] directions, which results in two different principal moments of inertia. Because of this, actuations imposed along any other direction are found to decompose into two orthogonal vibrational components based on the actuation angle relative to these two elementary directions, with this phenomenon being generalizable to <110> FCC nanowires of different materials (Cu, Au, Ni, Pd and Pt). The beat phenomenon is explained using a discrete moment of inertia model based on the hard sphere assumption, the model is utilized to show that surface effects enhance the beat phenomenon, while the effect is reduced with increasing nanowires cross-sectional size or aspect ratio. Most importantly, due to the existence of the beat phenomena, we demonstrate that in resonance experiments only a single frequency component is expected to be observed, particularly when the damping ratio is relatively large or very small. Furthermore, for a large range of actuation angles, the lower frequency is more likely to be detected than the higher one, which implies that experimental predictions of Young’s modulus obtained from resonance may in fact be under predictions. The present study therefore has significant implications for experimental interpretations of Young’s modulus as obtained via resonance testing.

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Approximate clone detection is the process of identifying similar process fragments in business process model collections. The tool presented in this paper can efficiently cluster approximate clones in large process model repositories. Once a repository is clustered, users can filter and browse the clusters using different filtering parameters. Our tool can also visualize clusters in the 2D space, allowing a better understanding of clusters and their member fragments. This demonstration will be useful for researchers and practitioners working on large process model repositories, where process standardization is a critical task for increasing the consistency and reducing the complexity of the repository.

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Reliable approaches for predicting pollutant build-up are essential for accurate urban stormwater quality modelling. Based on the in-depth investigation of metal build-up on residential road surfaces, this paper presents empirical models for predicting metal loads on these surfaces. The study investigated metals commonly present in the urban environment. Analysis undertaken found that the build-up process for metals primarily originating from anthropogenic (copper and zinc) and geogenic (aluminium, calcium, iron and manganese) sources were different. Chromium and nickel were below detection limits. Lead was primarily associated with geogenic sources, but also exhibited a significant relationship with anthropogenic sources. The empirical prediction models developed were validated using an independent data set and found to have relative prediction errors of 12-50%, which is generally acceptable for complex systems such as urban road surfaces. Also, the predicted values were very close to the observed values and well within 95% prediction interval.

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Chatrooms, for example Internet Relay Chat, are generally multi-user, multi-channel and multiserver chat-systems which run over the Internet and provide a protocol for real-time text-based conferencing between users all over the world. While a well-trained human observer is able to understand who is chatting with whom, there are no efficient and accurate automated tools to determine the groups of users conversing with each other. A precursor to analysing evolving cyber-social phenomena is to first determine what the conversations are and which groups of chatters are involved in each conversation. We consider this problem in this paper. We propose an algorithm to discover all groups of users that are engaged in conversation. Our algorithms are based on a statistical model of a chatroom that is founded on our experience with real chatrooms. Our approach does not require any semantic analysis of the conversations, rather it is based purely on the statistical information contained in the sequence of posts. We improve the accuracy by applying some graph algorithms to clean the statistical information. We present some experimental results which indicate that one can automatically determine the conversing groups in a chatroom, purely on the basis of statistical analysis.

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A suite of new materials, based on chemical modification of kaolins, has been successfully prepared via manipulation of the kaolin structure and subsequent intercalation by CaCl2 and MgCl2. A standard kaolinite(KGa-1)and a commercially available halloysite (New Zealand china clay) were used for this study. The kaolins are given several cycles of intercalation and deintercalation using a common intercalant such as potassium acetate. The number of cycles given depends on the type of kaolin. After this treatment, both kaolinite and halloysite hydrate show considerable broadening of the (00l) reflections which indicate extensive exfoliation of the layers. In the case of kaolinite, exfoliated layers roll to form tubes similar to proper halloysite. Kaolins modified by the above treatment readily intercalate MgCl2 and CaCl2 from saturated solutions of these salts. On intercalation with CaCl2 and MgCl2, kaolinite layers expand to 10A and 9.8A, and those of halloysite to 12.8A and 15.5A, respectively. To our knowledge, this is the first report of successful intercalation of alkaline-earth halides by kaolins.

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Our objective was to measure the prevalence of wife abuse in an urban teaching hospital family practice unit and compare this to the frequency of documentation by family physicians. A modified Conflicts Tactics Scale Questionnaire was administered to all female patients either married or common-law older than 16 years during the study period. The respective patients' charts were reviewed for documentation of wife abuse. Three hundred eighty-three charts were reviewed, and 275 surveys were completed (72% response rate). Physical and mental abuse were reported in 8% and 23%, respectively, of the respondents. Four percent of respondents had considered suicide. One percent of the charts had wife assault documented (p = 0.0001). Wife abuse is reported in at least 8% of our patients. There appear to be significant health risks to these women, including homicide, suicide, and rape. Family physician documentation of wife abuse was poor.

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Smartphones become very critical part of our lives as they offer advanced capabilities with PC-like functionalities. They are getting widely deployed while not only being used for classical voice-centric communication. New smartphone malwares keep emerging where most of them still target Symbian OS. In the case of Symbian OS, application signing seemed to be an appropriate measure for slowing down malware appearance. Unfortunately, latest examples showed that signing can be bypassed resulting in new malware outbreak. In this paper, we present a novel approach to static malware detection in resource-limited mobile environments. This approach can be used to extend currently used third-party application signing mechanisms for increasing malware detection capabilities. In our work, we extract function calls from binaries in order to apply our clustering mechanism, called centroid. This method is capable of detecting unknown malwares. Our results are promising where the employed mechanism might find application at distribution channels, like online application stores. Additionally, it seems suitable for directly being used on smartphones for (pre-)checking installed applications.

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Transition metal-free magnetism and half-metallicity recently has been the subject of intense research activity due to its potential in spintronics application. Here we, for the first time, demonstrate via density functional theory that the most recently experimentally realized graphitic carbon nitride (g-C4N3) displays a ferromagnetic ground state. Furthermore, this novel material is predicted to possess an intrinsic half-metallicity never reported to date. Our results highlight a new promising material toward realistic metal-free spintronics application.