Origin of the heavy elements in HD 140283: measurement of europium abundance

Context. HD140283 is a nearby (V = 7:7) subgiant metal-poor star, extensively analysed in the literature. Although many spectra have been obtained for this star, none showed a signal-to-noise (S/N) ratio high enough to enable a very accurate derivation of abundances from weak lines. Aims. The detection of europium proves that the neutron-capture elements in this star originate in the r-process, and not in the s-process, as recently claimed in the literature. Methods. Based on the OSMARCS 1D LTE atmospheric model and with a consistent approach based on the spectrum synthesis code Turbospectrum, we measured the europium lines at 4129 Å and 4205 Å, taking into account the hyperfine structure of the transitions. The spectrum, obtained with a long exposure time of seven hours at the Canada-France-Hawaii Telescope (CFHT), has a resolving power of 81 000 and a S/N ratio of 800 at 4100 Å. Results. We were able to determine the abundance A(Eu) =

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Detection of alkali metal ions in DNA crystals using state-of-the-art X-ray diffraction experiments

The observation of light metal ions in nucleic acids crystals is generally a fortuitous event. Sodium ions in particular are notoriously difficult to detect because their X-ray scattering contributions are virtually identical to those of water and Na+…O distances are only slightly shorter than strong hydrogen bonds between well-ordered water molecules. We demonstrate here that replacement of Na+ by K+, Rb+ or Cs+ and precise measurements of anomalous differences in intensities provide a particularly sensitive method for detecting alkali metal ion-binding sites in nucleic acid crystals. Not only can alkali metal ions be readily located in such structures, but the presence of Rb+ or Cs+ also allows structure determination by the single wavelength anomalous diffraction technique. Besides allowing identification of high occupancy binding sites, the combination of high resolution and anomalous diffraction data established here can also pinpoint binding sites that feature only partial occupancy. Conversely, high resolution of the data alone does not necessarily allow differentiation between water and partially ordered metal ions, as demonstrated with the crystal structure of a DNA duplex determined to a resolution of 0.6 Å.

Development of calix[4]arene-functionalized microcantilever array sensing system for the rapid, sensitive and simultaneous detection of metal ions in aqueous solutions

The work described in this thesis was conducted with the aim of: 1) investigating the binding capabilities of calix[4]arene-functionalized microcantilevers towards specific metal ions and 2) developing a new16-microcantilever array sensing system for the rapid, and simultaneous detection of metal ions in fresh water. Part I of this thesis reports on the use of three new bimodal calix[4]arenes (methoxy, ethoxy and crown) as potential host/guest sensing layers for detecting selected ions in dilute aqueous solutions using single microcantilever experimental system. In this work it was shown that modifying the upper rim of the calix[4]arenes with a thioacetate end group allow calix[4]arenes to self-assemble on Au(111) forming complete highly ordered monolayers. It was also found that incubating the microcantilevers coated with 5 nm of Inconel and 40 nm of Au for 1 h in a 1.0 M solution of calix[4]arene produced the highest sensitivity. Methoxy-functionalized microcantilevers showed a definite preference for Ca²⁺ ions over other cationic guests and were able to detect trace concentration as low as 10⁻¹² M in aqueous solutions. Microcantilevers modified with ethoxy calix[4]arene displayed their highest sensitivity towards Sr²⁺ and to a lesser extent Ca²⁺ ions. Crown calix[4]arene-modified microcantilevers were however found to bind selectively towards Cs⁺ ions. In addition, the counter anion was also found to contribute to the deflection. For example methoxy calix[4]arene-modified microcantilever was found to be more sensitive to CaCl₂ over other water-soluble calcium salts such as Ca(NO₃)₂ , CaBr₂ and CaI₂. These findings suggest that the response of calix[4]arene-modified microcantilevers should be attributed to the target ionic species as a whole instead of only considering the specific cation and/or anion. Part II presents the development of a 16-microcantilever sensor setup. The implementation of this system involved the creation of data analysis software that incorporates data from the motorized actuator and a two-axis photosensitive detector to obtain the deflection signal originating from each individual microcantilever in the array. The system was shown to be capable of simultaneous measurements of multiple microcantilevers with different coatings. A functionalization unit was also developed that allows four microcantilevers in the array to be coated with an individual sensing layer one at the time. Because of the variability of the spring constants of different cantilevers within the array, results presented were quoted in units of surface stress unit in order to compare values between the microcantilevers in the array.

A comparative study of alginate beads and an ion-exchange resin for the removal of heavy metals from a metal plating effluent

The capacity of dry protonated calcium alginate beads to sorb metals from an industrial effluent was studied and compared with a commercial ion-exchange resin (Lewatit TP 207). Both sorbents decreased zinc, nickel, iron and calcium concentrations in the effluent, and released sodium during treatment. Alginate beads removed lower amounts of heavy metals than the resin, but exhibited faster uptake kinetics. Zinc desorption from the sorbents was achieved in 30 minutes using 0.1 M HCl or 0.1 M H(2)SO(4). Desorption ratios with these acids varied between 90 and 100% for alginate, and 98 to 100% for the ion-exchange resin. Reusability tests with HCl showed that alginate beads can stand acid desorption and recover binding capacity. Overall, the comparison of dry protonated alginate beads with the resin supports the potential of the biosorbent for the treatment of industrial effluents.

Metal Contaminants in Leachate from Sanitary Landfills

The uncontrolled disposal of solid wastes poses an immediate threat to public health and a long term threat to the environmental well being of future generations. Solid waste is waste resulting from human activities that is solid and unwanted (Peavy et al., 1985). If unmanaged, dumped solid wastes generate liquid and gaseous emissions that are detrimental to the environment. This can lead to a serious form of contamination known as metal contamination, which poses a risk to human health and ecosystems. For example, some heavy metals (cadmium, chromium compounds, and nickel tetracarbonyl) are known to be highly toxic, and are aggressive at elevated concentrations. Iron, copper, and manganese can cause staining, and aluminium causes depositions and discolorations. In addition, calcium and magnesium cause hardness in water causing scale deposition and scum formation. Though not a metal but a metalloid, arsenic is poisonous at relatively high concentrations and when diluted at low concentrations causes skin cancer. Normally, metal contaminants are found in a dissolved form in the liquid percolating through landfills. Because average metal concentrations from full-scale landfills, test cells, and laboratory studies have tended to be generally low, metal contamination originating from landfills is not generally considered a major concern (Kjeldsen et al., 2002; Christensen et al., 1999). However, a number of factors make it necessary to take a closer look at metal contaminants from landfills. One of these factors relates to variability. Landfill leachate can have different qualities depending on the weather and operating conditions. Therefore, at one moment in time, metal contaminant concentrations may be quite low, but at a later time these concentrations could be quite high. Also, these conditions relate to the amount of leachate that is being generated. Another factor is biodiversity. It cannot be assumed that a particular metal contaminant is harmless to flora and fauna (including micro organisms) just because it is harmless to human health. This has significant implications for ecosystems and the environment. Finally, there is the moral factor. Because uncertainty surrounds the potential effects of metal contamination, it is appropriate to take precautions to prevent it from taking place. Consequently, it is necessary to have good scientific knowledge (empirically supported) to adequately understand the extent of the problem and improve the way waste is being disposed of

The Heavy Vehicle Study : a case-control study investigating risk factors for crash in long distance heavy vehicle drivers in Australia

Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.

Modification and validation of a microwave-assisted digestion method for subsequent ICP-MS determination of selected heavy metals in sediment and fish samples in Agusan River, Philippines

This study investigated, validated, and applied the optimum conditions for a modified microwave assisted digestion method for subsequent ICP-MS determination of mercury, cadmium, and lead in two matrices relevant to water quality, that is, sediment and fish. Three different combinations of power, pressure, and time conditions for microwave-assisted digestion were tested, using two certified reference materials representing the two matrices, to determine the optimum set of conditions. Validation of the optimized method indicated better recovery of the studied metals compared to standard methods. The validated method was applied to sediment and fish samples collected from Agusan River and one of its tributaries, located in Eastern Mindanao, Philippines. The metal concentrations in sediment ranged from 2.85 to 341.06 mg/kg for Hg, 0.05 to 44.46 mg/kg for Cd and 2.20 to 1256.16 mg/kg for Pb. The results indicate that the concentrations of these metals in the sediments rapidly decrease with distance downstream from sites of contamination. In the selected fish species, the metals were detected but at levels that are considered safe for human consumption, with concentrations of 2.14 to 6.82 μg/kg for Hg, 0.035 to 0.068 μg/kg for Cd, and 0.019 to 0.529 μg/kg for Pb.

Adsorption of heavy metals by road deposited solids

The research study discussed in the paper investigated the adsorption/desorption behaviour of heavy metals commonly deposited on urban road surfaces, namely, Zn, Cu, Cr and Pb for different particle size ranges of solids. The study outcomes, based on field studies and batch experiments confirmed that road deposited solids particles contain a significantly high amount of vacant charge sites with the potential to adsorb additional heavy metals. Kinetic study and adsorption experiments indicated that Cr is the most preferred metal element to associate with solids due to the relatively high electro negativity and high charge density of trivalent cation (Cr3+). However, the relatively low availability of Cr in the urban road environment could influence this behaviour. Comparing total adsorbed metals present in solids particles, it was found that Zn has the highest capacity for adsorption to solids. Desorption experiments confirmed that a low concentration of Cu, Cr and Pb in solids was present in water-soluble and exchangeable form, whilst a significant fraction of adsorbed Zn has a high likelihood of being released back into solution. Among heavy metals, Zn is considered to be the most commonly available metal among road surface pollutants.

Characterising metal build-up on urban road surfaces

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.

Monitoring android for collaborative anomaly detection : a first architectural draft

Our daily lives become more and more dependent upon smartphones due to their increased capabilities. Smartphones are used in various ways, e.g. for payment systems or assisting the lives of elderly or disabled people. Security threats for these devices become more and more dangerous since there is still a lack of proper security tools for protection. Android emerges as an open smartphone platform which allows modification even on operating system level and where third-party developers first time have the opportunity to develop kernel-based low-level security tools. Android quickly gained its popularity among smartphone developers and even beyond since it bases on Java on top of "open" Linux in comparison to former proprietary platforms which have very restrictive SDKs and corresponding APIs. Symbian OS, holding the greatest market share among all smartphone OSs, was even closing critical APIs to common developers and introduced application certification. This was done since this OS was the main target for smartphone malwares in the past. In fact, more than 290 malwares designed for Symbian OS appeared from July 2004 to July 2008. Android, in turn, promises to be completely open source. Together with the Linux-based smartphone OS OpenMoko, open smartphone platforms may attract malware writers for creating malicious applications endangering the critical smartphone applications and owners privacy. Since signature-based approaches mainly detect known malwares, anomaly-based approaches can be a valuable addition to these systems. They base on mathematical algorithms processing data that describe the state of a certain device. For gaining this data, a monitoring client is needed that has to extract usable information (features) from the monitored system. Our approach follows a dual system for analyzing these features. On the one hand, functionality for on-device light-weight detection is provided. But since most algorithms are resource exhaustive, remote feature analysis is provided on the other hand. Having this dual system enables event-based detection that can react to the current detection need. In our ongoing research we aim to investigates the feasibility of light-weight on-device detection for certain occasions. On other occasions, whenever significant changes are detected on the device, the system can trigger remote detection with heavy-weight algorithms for better detection results. In the absence of the server respectively as a supplementary approach, we also consider a collaborative scenario. Here, mobile devices sharing a common objective are enabled by a collaboration module to share information, such as intrusion detection data and results. This is based on an ad-hoc network mode that can be provided by a WiFi or Bluetooth adapter nearly every smartphone possesses.

Adsorption of heavy metals by road deposited solids

The research study discussed in the paper investigated the adsorption/desorption behaviour of heavy metals commonly deposited on urban road surfaces, namely, Zn, Cu, Cr and Pb for different particle size ranges of solids. The study outcomes, based on field studies and batch experiments confirmed that road deposited solids particles contain a significantly high amount of vacant charge sites with the potential to adsorb additional heavy metals. Kinetic studies and adsorption experiments indicated that Cr is the most preferred metal element to associate with solids due to the relatively high electro negativity and high charge density of trivalent cation (Cr3+). However, the relatively low availability of Cr in the urban road environment could influence this behaviour. Comparing total adsorbed metals present in solids particles, it was found that Zn has the highest capacity for adsorption to solids. Desorption experiments confirmed that a low concentration of Cu, Cr and Pb in solids was present in water-soluble and exchangeable form, whilst a significant fraction of adsorbed Zn has a high likelihood of being released back into solution. Among heavy metals, Zn is considered to be the most commonly available metal among road surface pollutants.

Reply to comment on “Characterising metal build-up on urban road surfaces” by Egodawatta et al. (2013)

In the recent manuscript published by Egodawatta et al. (2013), the authors investigated the build-up process of heavy metals (HMs) associated with road-deposited sediment (RDS) on residential road surfaces, and presented empirical models for the prediction of both the surface loads and build-up rates of HMs on these surfaces...

Fault detection of slow speed rolling element bearing with noise removal techniques

Rolling Element Bearings (REBs) are vital components in rotating machineries for providing rotating motion. In slow speed rotating machines, bearings are normally subjected to heavy static loads and a catastrophic failure can cause enormous disruption to production and human safety. Due to its low operating speed the impact energy generated by the rotating elements on the defective components is not sufficient to produce a detectable vibration response. This is further aggravated by the inability of general measuring instruments to detect and process the weak signals at the initiation of the defect accurately. Furthermore, the weak signals are often corrupted by background noise. This is a serious problem faced by maintenance engineers today and the inability to detect an incipient failure of the machine can significantly increases the risk of functional failure and costly downtime. This paper presents the application of noise removal techniques for enhancing the detection capability for slow speed REB condition monitoring. Blind deconvolution (BD) and adaptive line enhancer (ALE) are compared to evaluate their performance in enhancing the source signal with consequential removal of background noise. In the experimental study, incipient defects were seeded on a number of roller bearings and the signals were acquired using acoustic emission (AE) sensor. Kurtosis and modified peak ratio (mPR) were used to determine the detectability of signal corrupted by noise.