Infrared study of the adsorption of formic acid on silica-supported copper and oxidised copper catalysts

Infrared spectra are reported of formic acid adsorbed at 300 K on a reduced copper catalyst (Cu/SiO2) and a copper surface which had been oxidised by exposure to nitrous oxide. Formic acid was weakly adsorbed on the silica support. Ligation of formic acid to the copper surface occurred only on the reduced catalyst. Dissociative adsorption resulted in the formation of unidentate formate on the oxidised catalyst. The presence of reduced copper metal instigated a rapid reorientation to a bidentate formate species.

Infrared study of CO adsorption on reduced and oxidised silica-supported copper catalysts

FTIR spectra are reported of CO adsorbed on silica-supported copper catalysts prepared from copper(II) acetate monohydrate. Fully oxidised catalyst gave bands due to CO on CuO, isolated Cu2+ cations on silica and anion vacancy sites in CuO. The highly dispersed CuO aggregated on reduction to metal particles which gave bands due to adsorbed CO characteristic of both low-index exposed planes and stepped sites on high-index planes. Partial surface oxidation with N2O or H2O generated Cu+ adsorption sites which were slowly reduced to Cu° by CO at 300 K. Surface carbonate initially formed from CO was also slowly depleted with time with the generation of CO2. The results are consistent with adsorbed carbonate being an intermediate in the water-gas shift reaction of H2O and CO to H2 and CO2.

Infrared study of the adsorption of methanol on oxidised and reduced Cu/SiO2 catalysts

Infrared spectra are reported of methanol adsorbed at 295 K on reduced Cu/SiO2 and on Cu/SiO2 which had been preoxidised by exposure to excess nitrous oxide. Methanol was chemisorbed on reduced Cu/SiO2 to give methoxy species on both silica and copper, gave a trace of formate on copper via reaction with residual surface oxygen, and was weakly adsorbed at SiOH sites on the silica support. Heating the adsorbed species at 393 K led to the loss of methoxy groups on copper and the concomitant formation of a bidentate surface formate. Heating reduced Cu/SiO2 in methanol at 538 K initially gave both gaseous and adsorbed (on Cu) methyl formate which subsequently decomposed to CO and hydrogen. The reactions of methanol with oxidised Cu/SiO2 were similar to those for the reduced catalyst although surface oxygen promoted the formation of surface methoxy groups on copper. Subsequent heating at 393 K led first to unidentate formate before the appearance of bidentate formate.

Evidence for the adsorption of molecules at special sites located at copper/zinc oxide interfaces. Part 2. -- A fourier-transform infrared spectroscopy study of methanol adsorption on reduced and oxidised Cu/ZnO/SiO2 catalysts

FTIR spectra are reported of methanol adsorbed at 295 K on ZnO/SiO 2, on reduced Cu/ZnO/SiO2 and on Cu/ZnO/SiO2 which had been preoxidised by exposure to nitrous oxide. Methanol on ZnO/SiO2 gave methoxy species on ZnO and SiO, in addition to both strongly and weakly physisorbed methanol on SiO2. The corresponding adsorption of methanol on reduced Cu/ZnO/SiO2 also gave methoxy species on Cu and a small amount of bridging formate. Reaction of methanol with a reoxidised Cu/ZnO/SiO2 catalyst resulted in an enhanced quantity of methoxy species on Cu. Heating adsorbed species on Cu/ZnO/SiO2 at 393 K led to the loss of methoxy groups on Cu and the concomitant formation of formate species on both ZnO and Cu. The comparable reaction on a reoxidised Cu/ZnO/SiO2 catalyst gave an increased amount of formate species on ZnO and this correlated with an increased quantity of methoxy groups lost from Cu. An explanation is given in terms of adsorption of formate and formaldehyde species at special sites located at the copper/zinc oxide interface.

Evidence for the adsorption of molecules at special sites located at copper/zinc oxide interfaces: Part 1. -- A Fourier-transform infrared study of formic acid and formaldehyde adsorption on reduced and oxidised Cu/ZnO/SiO2 catalysts

Fourier-transform infrared (FTIR) spectra are reported of formic acid and formaldehyde on ZnO/SiO2, reduced Cu/ZnO/SiO2 and reoxidised Cu/ZnO/SiO2 catalyst. Formic acid adsorption on ZnO/SiO2 produced mainly bidentate zinc formate species with a lesser quantity of unidentate zinc formate. Formic acid on reduced Cu/ZnO/SiO2 catalyst resulted not only in the formation of bridging copper formate structures but also in an enhanced amount of formate relative to that for ZnO/SiO2 catalyst. Formic acid on reoxidised Cu/ZnO/SiO2 gave unidentate formate species on copper in addition to zinc formate moieties. The interaction of formaldehyde with ZnO/SiO2 catalyst resulted in the formation of zinc formate species. The same reaction on reduced Cu/ZnO/SiO2 catalyst gave bridging formate on copper and a remarkable increase in the quantity of formate species associated with the zinc oxide. Adsorption of formaldehyde on a reoxidised Cu/ZnO/SiO2 catalyst produced bridging copper formate and again an apparent increase in the concentration of zinc formate species. An explanation in terms of the adsorption of molecules at special sites located at the interface between copper and zinc oxide is given.

Evidence for the adsorption of molecules at special sites located at copper/zinc oxide interfaces. Part 3. -- Fourier-transform infrared study of methyl formate adsorption on reduced and oxidised Cu/ZnO/SiO2 catalysts

FTIR spectra are reported of methyl formate adsorbed at 295 K on ZnO/SiO2, reduced Cu/ZnO/SiO2 and on Cu/ZnO/SiO2 which had been preoxidised by exposure to nitrous oxide. Methyl formate on ZnO/SiO2 gave adsorbed zinc formate species and strongly physisorbed molecular methanol on silica. The comparable reaction of methyl formate with reduced Cu/ZnO/SiO2 catalyst produced bridging formate species on copper and a diminished quantity of zinc formate relative to that formed on ZnO/SiO2 catalyst. This effect is explained in terms of site blockage on the ZnO surface by small copper clusters. Addition of methyl formate to a reoxidised Cu/ZnO/SiO2 catalyst produced a considerably greater amount of formate species on zinc oxide and methoxy groups on copper were detected. The increase in concentration of zinc formate species was rationalised in terms of rearrangement of unidentate copper formate species to become bonded to copper and zinc oxide sites located at the interface between these two components.

Spectroscopic studies of the adsorption and reactions of chlorofluorocarbons (CFC-11 and CFC-12) and hydrochlorofluorocarbon (HCFC-22) on oxide surfaces

Raman and Fourier transform infrared (FT-IR) spectroscopy have been applied to a systematic investigation of the adsorption and decomposition of dichlorodifluoromethane (CCl2F2, CFC-12), fluorotrichloromethane (CCl3F, CFC-11), chlorodifluoromethane (CHClF2, HCFC-22) and molecular chlorine on oxide surfaces. Additionally, the effects of heating and ultraviolet photolysis of the CFC and HCFCs adsorbed on the oxide surfaces have been investigated. Spectral features for these species indicated a small wavenumber shift (1-6 cm-1) associated with the adsorbed phase. Some evidence, specifically the appearance of the Raman band at 507 cm-1, is presented to show that chlorine decomposition species are associated with these oxide surfaces. It was concluded that the new spectral feature (at ca. 507 cm-1) related with the decomposition of the CFC and HCFC molecules was an important indicator of the extent to which the reaction between the adsorbed CFC and HCFC and oxide surface has taken place. The extent of CFC-surface interaction has been quantified in terms of a maximum (Raman) frequency shift parameter (AM). Wavenumber shifts suggest both cation-adsorbate and non-specific adsorption interactions are occurring in the internal channels of the zeolites. Slow decomposition of the adsorbed CFCs under ultraviolet-visible photolysis (at ? > 300 nm) and/or thermal treatment was observed spectroscopically. Using FT-IR spectroscopy, the formation of gas-phase products (CO, CO2, HCl) both onyn photolysis and heating was evident. Results of these measurements are compared with the observed atmospheric reactivity of these compounds.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Random Breath Testing in Australia: Is there an Optimum Level of Intensity?

Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.

Harmonic quality of multilevel cascade inverters with random carrier phase pulse width modulation

The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.

Are more city dwellers caught drink driving than country folk? An analysis by random breath testing apprehension rates

Background Random Breath Testing (RBT) remains a central enforcement strategy to deter and apprehend drink drivers in Queensland (Australia). Despite this, there is little published research regarding the exact drink driving apprehension rates across the state as measured through RBT activities. Aims The aim of the current study was to examine the prevalence of apprehending drink drivers in urban versus rural areas. Methods The Queensland Police Service provided data relating to the number of RBT conducted and apprehensions for the period 1 January 2000 to 31 December 2011. Results In the period, 35,082,386 random breath tests (both mobile and stationary) were conducted in Queensland which resulted in 248,173 individuals being apprehended for drink driving offences. Overall drink driving apprehension rates appear to have decreased across time. Close examination of the data revealed that the highest proportion of drink driving apprehensions (when compared with RBT testing rates) was in the Northern and Far Northern regions of Queensland (e.g., rural areas). In contrast, the lowest proportions were observed within the two Brisbane metropolitan regions (e.g., urban areas). However, differences in enforcement styles across the urban and rural regions need to be considered. Discussion and conclusions The research presentation will further outline the major findings of the study in regards to maximising the efficiency of RBT operations both within urban and rural areas of Queensland, Australia.

Identify disorders in health records using Conditional Random Fields and Metamap: AEHRC at ShARe/CLEF 2013 eHealth Evaluation Lab Task 1

The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).

Role of particle size and composition in metal adsorption by solids deposited on urban road surfaces

Despite common knowledge that the metal content adsorbed by fine particles is relatively higher compared to coarser particles, the reasons for this phenomenon has gained little research attention. The research study discussed in the paper investigated the variations in metal content for different particle sizes of solids associated with pollutant build-up on urban road surfaces. Data analysis confirmed that parameters favourable for metal adsorption to solids such as specific surface area, organic carbon content, effective cation exchange capacity and clay forming minerals content decrease with the increase in particle size. Furthermore, the mineralogical composition of solids was found to be the governing factor influencing the specific surface area and effective cation exchange capacity. There is high quartz content in particles >150µm compared to particles <150µm. As particle size reduces below 150µm, the clay forming minerals content increases, providing favourable physical and chemical properties that influence adsorption.

Sequential decision fusion of multibiometrics applied to text-dependent speaker verification for controlled errors

Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.