248 resultados para Emission permits auctionsj double auctions.
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The thermal decomposition of halloysite-potassium acetate intercalation compound was investigated by thermogravimetric analysis and infrared emission spectroscopy. The X-ray diffraction patterns indicated that intercalation of potassium acetate into halloysite caused an increase of the basal spacing from 1.00 to 1.41 nm. The thermogravimetry results show that the mass losses of intercalation the compound occur in main three main steps, which correspond to (a) the loss of adsorbed water (b) the loss of coordination water and (c) the loss of potassium acetate and dehydroxylation. The temperature of dehydroxylation and dehydration of halloysite is decreased about 100 °C. The infrared emission spectra clearly show the decomposition and dehydroxylation of the halloysite intercalation compound when the temperature is raised. The dehydration of the intercalation compound is followed by the loss of intensity of the stretching vibration bands at region 3600-3200 cm-1. Dehydroxylation is followed by the decrease in intensity in the bands between 3695 and 3620 cm-1. Dehydration was completed by 300 °C and partial dehydroxylation by 350 °C. The inner hydroxyl group remained until around 500 °C.
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Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.
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A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.
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Acoustic emission (AE) technique is one of the popular diagnostic techniques used for structural health monitoring of mechanical, aerospace and civil structures. But several challenges still exist in successful application of AE technique. This paper explores various tools for analysis of recorded AE data to address two primary challenges: discriminating spurious signals from genuine signals and devising ways to quantify damage levels.
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Managing the sustainability of urban infrastructure requires regular health monitoring of key infrastructure such as bridges. The process of structural health monitoring involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors, and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures, and acoustic emission is one technique that is finding an increasing use in the monitoring of civil infrastructures such as bridges. Acoustic emission technique is based on the recording of stress waves generated by rapid release of energy inside a material, followed by analysis of recorded signals to locate and identify the source of emission and assess its severity. This chapter first provides a brief background of the acoustic emission technique and the process of source localization. Results from laboratory experiments conducted to explore several aspects of the source localization process are also presented. The findings from the study can be expected to enhance knowledge of the acoustic emission process, and to aid the development of effective bridge structure diagnostics systems.
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This paper presents techniques which can be viewed as pre-processing step towards diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time-frequency analysis, selection of optimum frequency band. Some results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals are also outlined. The results on separation of RMS signals show this technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events.
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Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.
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Bridges are an important part of a nation’s infrastructure and reliable monitoring methods are necessary to ensure their safety and efficiency. Most bridges in use today were built decades ago and are now subjected to changes in load patterns that can cause localized distress, which can result in bridge failure if not corrected. Early detection of damage helps in prolonging lives of bridges and preventing catastrophic failures. This paper briefly reviews the various technologies currently used in health monitoring of bridge structures and in particular discusses the application and challenges of acoustic emission (AE) technology. Some of the results from laboratory experiments on a bridge model are also presented. The main objectives of these experiments are source localisation and assessment. The findings of the study can be expected to enhance the knowledge of acoustic emission process and thereby aid in the development of an effective bridge structure diagnostics system.
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Comorbid depression and anxiety in late life present challenges for geriatric mental health care providers. These challenges include identifying the often complex diagnostic presentations both clinically and in a research context. This potent comorbidity can be conceived as double jeopardy in older adults, further diminishing their quality of life. Geriatric health care providers need to understand psychiatric comorbidity of this type for accurate diagnosis and early referral to specialists, and to coordinate interdisciplinary care. Researchers in the field also need to recognize potential multiple impacts of comorbidities with respect to assessment and treatment domains. This article describes the prevalence of late-life depression and anxiety disorders and reviews studies on this comorbidity in older adults. Risk factors and protective factors for anxiety and depression in later life are reviewed, and information is provided about comparative symptoms, the selection of assessment tools, and challenges to the provision of interdisciplinary, evidence-based care.
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Cubic indium hydroxide nanomaterials were obtained by a low temperature soft-chemical method without any surfactants. The transition of nano-cubic indium hydroxide to cubic indium oxide during dehydroxylation has been studied by infrared emission spectroscopy. The spectra are related to the structure of the materials and the changes in the structure upon thermal treatment. The infrared absorption spectrum of In(OH)3 is characterised by an intense OH deformation band at 1150 cm-1 and two O-H stretching bands at 3107 and 3221 cm-1. In the infrared emission spectra, the hydroxyl-stretching and hydroxyl-bending bands diminish dramatically upon heating, and no intensity remains after 200 °C. However, new low intensity bands are found in the OH deformation region at 915 cm-1 and in OH stretching region at 3437 cm-1. These bands are attributed to the vibrations of newly formed InOH bonds because of the release and transfer of protons during calcination of the nanomaterial. The use of infrared emission spectroscopy enables the low-temperature phase transition brought about through dehydration of In(OH)3 nanocubes to be studied.
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We have used a scanning tunneling microscope to manipulate heteroleptic phthalocyaninato, naphthalocyaninato, porphyrinato double-decker molecules at the liquid/solid interface between 1-phenyloctane solvent and graphite. We employed nano-grafting of phthalocyanines with eight octyl chains to place these molecules into a matrix of heteroleptic double-decker molecules; the overlayer structure is epitaxial on graphite. We have also used nano-grafting to place double-decker molecules in matrices of single-layer phthalocyanines with octyl chains. Rectangular scans with a scanning tunneling microscope at low bias voltage resulted in the removal of the adsorbed doubledecker molecular layer and substituted the double-decker molecules with bilayer-stacked phthalocyanines from phenyloctane solution. Single heteroleptic double-decker molecules with lutetium sandwiched between naphthalocyanine and octaethylporphyrin were decomposed with voltage pulses from the probe tip; the top octaethylporphyrin ligand was removed and the bottom naphthalocyanine ligand remained on the surface. A domain of decomposed molecules was formed within the double-decker molecular domain, and the boundary of the decomposed molecular domain self-cured to become rectangular. We demonstrated a molecular “sliding block puzzle” with cascades of double-decker molecules on the graphite surface.
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The mineral nesquehonite Mg(OH)(HCO3)•2H2O has been analysed by a combination of infrared (IR) and infrared emission spectroscopy (IES). Both techniques show OH vibrations, both stretching and deformation modes. IES proves the OH units are stable up to 450°C. The strong IR band at 934 cm-1 is evidence for MgOH deformation modes supporting the concept of HCO3- units in the molecular structure. Infrared bands at 1027, 1052 and 1098 cm-1 are attributed to the symmetric stretching modes of HCO3- and CO32- units. Infrared bands at 1419, 1439, 1511, and 1528 cm-1 are assigned to the antisymmetric stretching modes of CO32- and HCO3- units. IES supported by thermoanalytical results defines the thermal stability of nesquehonite IES defines the changes in the molecular structure of nesquehonite with temperature. The results of IR and IES supports the concept that the formula of nesquehonite is better defined as Mg(OH)(HCO3)•2H2O.
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In a randomized, double-blind study, 202 healthy adults were randomized to receive a live, attenuated Japanese encephalitis chimeric virus vaccine (JE-CV) and placebo 28 days apart in a cross-over design. A subgroup of 98 volunteers received a JE-CV booster at month 6. Safety, immunogenicity, and persistence of antibodies to month 60 were evaluated. There were no unexpected adverse events (AEs) and the incidence of AEs between JE-CV and placebo were similar. There were three serious adverse events (SAE) and no deaths. A moderately severe case of acute viral illness commencing 39 days after placebo administration was the only SAE considered possibly related to immunization. 99% of vaccine recipients achieved a seroprotective antibody titer ≥ 10 to JE-CV 28 days following the single dose of JE-CV, and 97% were seroprotected at month 6. Kaplan Meier analysis showed that after a single dose of JE-CV, 87% of the participants who were seroprotected at month 6 were still protected at month 60. This rate was 96% among those who received a booster immunization at month 6. 95% of subjects developed a neutralizing titer ≥ 10 against at least three of the four strains of a panel of wild-type Japanese encephalitis virus (JEV) strains on day 28 after immunization. At month 60, that proportion was 65% for participants who received a single dose of JE-CV and 75% for the booster group. These results suggest that JE-CV is safe, well tolerated and that a single dose provides long-lasting immunity to wild-type strains
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A randomized, double-blind, study was conducted to evaluate the safety, tolerability and immunogenicity of a live attenuated Japanese encephalitis chimeric virus vaccine (JE-CV) co-administered with live attenuated yellow fever (YF) vaccine (YF-17D strain; Stamaril(®), Sanofi Pasteur) or administered successively. Participants (n = 108) were randomized to receive: YF followed by JE-CV 30 days later, JE followed by YF 30 days later, or the co-administration of JE and YF followed or preceded by placebo 30 days later or earlier. Placebo was used in a double-dummy fashion to ensure masking. Neutralizing antibody titers against JE-CV, YF-17D and selected wild-type JE virus strains was determined using a 50% serum-dilution plaque reduction neutralization test. Seroconversion was defined as the appearance of a neutralizing antibody titer above the assay cut-off post-immunization when not present pre-injection at day 0, or a least a four-fold rise in neutralizing antibody titer measured before the pre-injection day 0 and later post vaccination samples. There were no serious adverse events. Most adverse events (AEs) after JE vaccination were mild to moderate in intensity, and similar to those reported following YF vaccination. Seroconversion to JE-CV was 100% and 91% in the JE/YF and YF/JE sequential vaccination groups, respectively, compared with 96% in the co-administration group. All participants seroconverted to YF vaccine and retained neutralizing titers above the assay cut-off at month six. Neutralizing antibodies against JE vaccine were detected in 82-100% of participants at month six. These results suggest that both vaccines may be successfully co-administered simultaneously or 30 days apart.
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Damage to genetic material represents a persistent and ubiquitous threat to genomic stability. Once DNA damage is detected, a multifaceted signaling network is activated that halts the cell cycle, initiates repair, and in some instances induces apoptotic cell death. In this article, we will review DNA damage surveillance networks, which maintain the stability of our genome, and discuss the efforts underway to identify chemotherapeutic compounds targeting the core components of DNA double-strand breaks (DSB) response pathway. The majority of tumor cells have defects in maintaining genomic stability owing to the loss of an appropriate response to DNA damage. New anticancer agents are exploiting this vulnerability of cancer cells to enhance therapeutic indexes, with limited normal tissue toxicity. Recently inhibitors of the checkpoint kinases Chk1 and Chk2 have been shown to sensitize tumor cells to DNA damaging agents. In addition, the treatment of BRCA1- or BRCA2-deficient tumor cells with poly(ADP-ribose) polymerase (PARP) inhibitors also leads to specific tumor killing. Due to the numerous roles of p53 in genomic stability and its defects in many human cancers, therapeutic agents that restore p53 activity in tumors are the subject of multiple clinical trials. In this article we highlight the proteins mentioned above and catalog several additional players in the DNA damage response pathway, including ATM, DNA-PK, and the MRN complex, which might be amenable to pharmacological interventions and lead to new approaches to sensitize cancer cells to radio- and chemotherapy. The challenge is how to identify those patients most receptive to these treatments.