148 resultados para Effective notch stress method


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With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

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For certain continuum problems, it is desirable and beneficial to combine two different methods together in order to exploit their advantages while evading their disadvantages. In this paper, a bridging transition algorithm is developed for the combination of the meshfree method (MM) with the finite element method (FEM). In this coupled method, the meshfree method is used in the sub-domain where the MM is required to obtain high accuracy, and the finite element method is employed in other sub-domains where FEM is required to improve the computational efficiency. The MM domain and the FEM domain are connected by a transition (bridging) region. A modified variational formulation and the Lagrange multiplier method are used to ensure the compatibility of displacements and their gradients. To improve the computational efficiency and reduce the meshing cost in the transition region, regularly distributed transition particles, which are independent of either the meshfree nodes or the FE nodes, can be inserted into the transition region. The newly developed coupled method is applied to the stress analysis of 2D solids and structures in order to investigate its’ performance and study parameters. Numerical results show that the present coupled method is convergent, accurate and stable. The coupled method has a promising potential for practical applications, because it can take advantages of both the meshfree method and FEM when overcome their shortcomings.

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The process of structural health monitoring (SHM) 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 (AE) is one technique that is finding an increasing use. Acoustic emission waves are the stress waves generated by the mechanical deformation of materials. AE waves produced inside a structure can be recorded by means of sensors attached on the surface. Analysis of these recorded signals can locate and assess the extent of damage. This paper describes preliminary studies on the application of AE technique for health monitoring of bridge structures. Crack initiation or structural damage will result in wave propagation in solid and this can take place in various forms. Propagation of these waves is likely to be affected by the dimensions, surface properties and shape of the specimen. This, in turn, will affect source localization. Various laboratory test results will be presented on source localization, using pencil lead break tests. The results from the tests can be expected to aid in enhancement of knowledge of acoustic emission process and development of effective bridge structure diagnostics system.

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Recognizing the need to offer alternative methods of brief interventions, this study developed correspondence treatments for low-dependent problem drinkers and evaluated their impact. One hundred and twenty-one problem drinkers were recruited by media advertisements and were randomly allocated to a full cognitive behavioural treatment programme (CBT) or to a minimal intervention condition (MI) that gave information regarding alcohol misuse and instructions to record drinking. As predicted, CBT was more effective than MI in reducing alcohol consumption over the 4-month controlled trial period. CBT produced a 50% fall in consumption, bringing the average intake of subjects within recommended maximum levels. Treatment gains at 6 months were well maintained to 12 months. High levels of consumer satisfaction, a high representation of women and a substantial participation from isolated rural areas attested to the feasibility of the correspondence programme as an alternative treatment. However, some drinking occasions still involved high intake for a significant subgroup of subjects, and this issue will be addressed in future programmes. The results supported the use of correspondence delivery as a means of promoting early engagement and equity of access between city and country areas.

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Bananas are susceptible to a diverse range of biotic and abiotic stresses, many of which cause serious production constraints worldwide. One of the most destructive banana diseases is Fusarium wilt caused by the soil-borne fungus, Fusarium oxysporum f. sp. cubense (Foc). No effective control strategy currently exists for this disease which threatens global banana production. Although disease resistance exists in some wild bananas, attempts to introduce resistance into commercially acceptable bananas by conventional breeding have been hampered by low fertility, long generation times and association of poor agronomical traits with resistance genes. With the advent of reliable banana transformation protocols, molecular breeding is now regarded as a viable alternative strategy to generate disease-resistant banana plants. Recently, a novel strategy involving the expression of anti-apoptosis genes in plants was shown to result in resistance against several necrotrophic fungi. Further, the transgenic plants showed increased resistance to a range of abiotic stresses. In this thesis, the use of anti-apoptosis genes to generate transgenic banana plants with resistance to Fusarium wilt was investigated. Since water stress is an important abiotic constraint to banana production, the resistance of the transgenic plants to water stress was also examined. Embryogenic cell suspensions (ECS) of two commercially important banana cultivars, Grand Naine (GN) and Lady Finger (LF), were transformed using Agrobacterium with the anti-apoptosis genes, Bcl-xL, Bcl-xL G138A, Ced-9 and Bcl- 2 3’ UTR. An interesting, and potentially important, outcome was that the use of anti-apoptosis genes resulted in up to a 50-fold increase in Agrobacterium-mediated transformation efficiency of both LF and GN cells over vector controls. Regenerated plants were subjected to a complete molecular characterisation in order to detect the presence of the transgene (PCR), transcript (RT-PCR) and gene product (Western blot) and to determine the gene copy number (Southern blot). A total of 36 independently-transformed GN lines (8 x Bcl-xL, 5 x Bcl-xL G138A, 15 x Ced-9 and 8 x Bcl-2 3’ UTR) and 41 independently-transformed LF lines (8 x Bcl-xL, 7 x BclxL G138A, 13 x Ced-9 and 13 x Bcl-2 3’ UTR) were identified. The 41 transgenic LF lines were multiplied and clones from each line were acclimatised and grown under glasshouse conditions for 8 weeks to allow monitoring for phenotypic abnormalities. Plants derived from 3 x Bcl-xL, 2 x Ced-9 and 5 x Bcl-2 3’ UTR lines displayed a variety of aberrant phenotypes. However, all but one of these abnormalities were off-types commonly observed in tissue-cultured, non-transgenic banana plants and were therefore unlikely to be transgene-related. Prior to determining the resistance of the transgenic plants to Foc race 1, the apoptotic effects of the fungus on both wild-type and Bcl-2 3’ UTR-transgenic LF banana cells were investigated using rapid in vitro root assays. The results from these assays showed that apoptotic-like cell death was elicited in wild-type banana root cells as early as 6 hours post-exposure to fungal spores. In contrast, these effects were attenuated in the root cells of Bcl-2 3’ UTR-transgenic lines that were exposed to fungal spores. Thirty eight of the 41 transgenic LF lines were subsequently assessed for resistance to Foc race 1 in small-plant glasshouse bioassays. To overcome inconsistencies in rating the internal (vascular discolouration) disease symptoms, a MatLab-based computer program was developed to accurately and reliably assess the level of vascular discolouration in banana corms. Of the transgenic LF banana lines challenged with Foc race 1, 2 x Bcl-xL, 3 x Ced-9, 2 x Bcl-2 3’ UTR and 1 x Bcl-xL G138A-transgenic line were found to show significantly less external and internal symptoms than wild-type LF banana plants used as susceptible controls at 12 weeks post-inoculation. Of these lines, Bcl-2 3’ UTR-transgenic line #6 appeared most resistant, displaying very mild symptoms similar to the wild-type Cavendish banana plants that were included as resistant controls. This line remained resistant for up to 23 weeks post-inoculation. Since anti-apoptosis genes have been shown to confer resistance to various abiotic stresses in other crops, the ability of these genes to confer resistance against water stress in banana was also investigated. Clonal plants derived from each of the 38 transgenic LF banana plants were subjected to water stress for a total of 32 days. Several different lines of transgenic plants transformed with either Bcl-xL, Bcl-xL G138A, Ced-9 or Bcl-2 3’ UTR showed a delay in visual water stress symptoms compared with the wild-type control plants. These plants all began producing new growth from the pseudostem following daily rewatering for one month. In an attempt to determine whether the protective effect of anti-apoptosis genes in transgenic banana plants was linked with reactive oxygen species (ROS)-associated programmed cell death (PCD), the effect of the chloroplast-targeting, ROS-inducing herbicide, Paraquat, on wild-type and transgenic LF was investigated. When leaf discs from wild-type LF banana plants were exposed to 10 ìM Paraquat, complete decolourisation occurred after 48 hours which was confirmed to be associated with cell death and ROS production by trypan blue and 3,3-diaminobenzidine (DAB) staining, respectively. When leaf discs from the transgenic lines were exposed to Paraquat, those derived from some lines showed a delay in decolourisation, suggesting only a weak protective effect from the transgenes. Finally, the protective effect of anti-apoptosis genes against juglone, a ROS-inducing phytotoxin produced by the causal agent of black Sigatoka, Mycosphaerella fijiensis, was investigated. When leaf discs from wild-type LF banana plants were exposed to 25 ppm juglone, complete decolourisation occurred after 48 hours which was again confirmed to be associated with cell death and ROS production by trypan blue and DAB staining, respectively. Further, TdT-mediated dUTP nick-end labelling (TUNEL) assays on these discs suggested that the cell death was apoptotic. When leaf discs from the transgenic lines were exposed to juglone, discs from some lines showed a clear delay in decolourisation, suggesting a protective effect. Whether these plants are resistant to black Sigatoka is unknown and will require future glasshouse and field trials. The work presented in this thesis provides the first report of the use of anti-apoptosis genes as a strategy to confer resistance to Fusarium wilt and water stress in a nongraminaceous monocot, banana. Such a strategy may be exploited to generate resistance to necrotrophic pathogens and abiotic stresses in other economically important crop plants.

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A significant number of children suffer long term psychological disturbance following exposure to a natural disaster. Evidence suggests that a dose-response relationship exists, so that children and adolescents who experience the most intense or extensive exposure to the risk factors for PTSD are likely to develop the most serious and persistent symptoms. Risk factors include gender, age, personality, extent of exposure to the natural disaster, amount of damage to property and infrastructure, witnessing injury or death of others or perceiving a threat to their own life. Knowing these factors enables various strategies to be put in place to decrease the risk of psychological disturbance following the aftermath of traumatic events. Re-establishing a sense of safety, security and normality is important in the aftermath of a natural disaster, and promoting social connectedness, positive family functioning, and effective coping mechanisms can make children more resilient in the face of catastrophic events. This paper examines the risk and protective factors associated with the development of post traumatic stress disorder (PTSD), and considers how schools can use this knowledge to contribute to the recovery effort, and reduce the prevalence of PTSD amongst pupils in the wake of a natural disaster.

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Masks are widely used in different industries, for example, traditional metal industry, hospitals or semiconductor industry. Quality is a critical issue in mask industry as it is related to public health and safety. Traditional quality practices for manufacturing process have some limitations in implementing them in mask industries. This paper aims to investigate the suitability of Six Sigma quality control method for the manufacturing process in the mask industry to provide high quality products, enhancing the process capacity, reducing the defects and the returned goods arising in a selected mask manufacturing company. This paper suggests that modifications necessary in Six Sigma method for effective implementation in mask industry.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

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Proper application of sunscreen is essential as an effective public health strategy for skin cancer prevention. Insufficient application is common among sunbathers, results in decreased sun protection and may therefore lead to increased UV damage of the skin. However, no objective measure of sunscreen application thickness (SAT) is currently available for field-based use. We present a method to detect SAT on human skin for determining the amount of sunscreen applied and thus enabling comparisons to manufacturer recommendations. Using a skin swabbing method and subsequent spectrophotometric analysis, we were able to determine SAT on human skin. A swabbing method was used to derive SAT on skin (in mg sunscreen per cm2 of skin area) through the concentration–absorption relationship of sunscreen determined in laboratory experiments. Analysis differentiated SATs between 0.25 and 4 mg cm−2 and showed a small but significant decrease in concentration over time postapplication. A field study was performed, in which the heterogeneity of sunscreen application could be investigated. The proposed method is a low cost, noninvasive method for the determination of SAT on skin and it can be used as a valid tool in field- and population-based studies.

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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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Aim. This paper is a report of a review conducted to identify (a) best practice in information transfer from the emergency department for multi-trauma patients; (b) conduits and barriers to information transfer in trauma care and related settings; and (c) interventions that have an impact on information communication at handover and beyond. Background. Information transfer is integral to effective trauma care, and communication breakdown results in important challenges to this. However, evidence of adequacy of structures and processes to ensure transfer of patient information through the acute phase of trauma care is limited. Data sources. Papers were sourced from a search of 12 online databases and scanning references from relevant papers for 1990–2009. Review methods. The review was conducted according to the University of York’s Centre for Reviews and Dissemination guidelines. Studies were included if they concerned issues that influenced information transfer for patients in healthcare settings. Results. Forty-five research papers, four literature reviews and one policy statement were found to be relevant to parts of the topic, but not all of it. The main issues emerging concerned the impact of communication breakdown in some form, and included communication issues within trauma team processes, lack of structure and clarity during handovers including missing, irrelevant and inaccurate information, distractions and poorly documented care. Conclusion. Many factors influence information transfer but are poorly identified in relation to trauma care. The measurement of information transfer, which is integral to patient handover, has not been the focus of research to date. Nonetheless, documented patient information is considered evidence of care and a resource that affects continuing care.

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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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The detection and potential treatment of oxidative stress in biological systems has been explored using isoindoline-based nitroxide radicals. A novel tetraethyl-fluorescein nitroxide was synthesised for its use as a profluorescent probe for redox processes in biological systems. This tetraethyl system, as well as a tetramethyl-fluorescein nitroxide, were shown to be sensitive and selective probes for superoxide in vitro. The redox environment of cellular systems was also explored using the tetramethylfluorescein species based on its reduction to the hydroxylamine. Flow cytometry was employed to assess the extent of nitroxide reduction, reflecting the overall cellular redox environment. Treatment of normal fibroblasts with rotenone and 2-deoxyglucose resulted in an oxidising cellular environment as shown by the lack of reduction of the fluorescein-nitroxide system. Assessment of the tetraethyl-fluorescein nitroxide system in the same way demonstrated its enhanced resistance to reduction and offers the potential to detect and image biologically relevant reactive oxygen species directly. Importantly, these profluorescent nitroxide compounds were shown to be more effective than the more widely used and commercially available probes for reactive oxygen species such as 2’,7’-dichlorodihydrofluorescein diacetate. Fluorescence imaging of the tetramethyl-fluorescein nitroxide and a number of other rhodamine-nitroxide derivatives was undertaken, revealing the differential cellular localisation of these systems and thus their potential for the detection of redox changes in specific cellular compartments. As well as developing novel methods for the detection of oxidative stress, a number of novel isoindoline nitroxides were synthesised for their potential application as small-molecule antioxidants. These compounds incorporated known pharmacophores into the isoindoline-nitroxide structure in an attempt to increase their efficacy in biological systems. A primary and a secondary amine nitroxide were synthesised which incorporated the phenethylamine backbone of the sympathomimetic amine class of drugs. Initial assessment of the novel primary amine derivative indicated a protective effect comparable to that of 5-carboxy-1,1,3,3- tetramethylisoindolin-2-yloxyl. Methoxy-substituted nitroxides were also synthesised as potential antioxidants for their structural similarity to some amphetamine type stimulants. A copper-catalysed methodology provided access to both the mono- and di-substituted methoxy-nitroxides. Deprotection of the ethers in these compounds using boron tribromide successfully produced a phenolnitroxide, however the catechol moiety in the disubstituted derivative appeared to undergo reaction with the nitroxide to produce quinone-like degradation products. A novel fluoran-nitroxide was also synthesised from the methoxy-substituted nitroxide, providing a pH-sensitive spin probe. An amino-acid precursor containing a nitroxide moiety was also synthesised for its application as a dual-action antioxidant. N-Acetyl protection of the nitroxide radical was necessary prior to the Erlenmeyer reaction with N-acetyl glycine. Hydrolysis and reduction of the azlactone intermediate produced a novel amino acid precursor with significant potential as an effective antioxidant.

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The Airy stress function, although frequently employed in classical linear elasticity, does not receive similar usage for granular media problems. For plane strain quasi-static deformations of a cohesionless Coulomb–Mohr granular solid, a single nonlinear partial differential equation is formulated for the Airy stress function by combining the equilibrium equations with the yield condition. This has certain advantages from the usual approach, in which two stress invariants and a stress angle are introduced, and a system of two partial differential equations is needed to describe the flow. In the present study, the symmetry analysis of differential equations is utilised for our single partial differential equation, and by computing an optimal system of one-dimensional Lie algebras, a complete set of group-invariant solutions is derived. By this it is meant that any group-invariant solution of the governing partial differential equation (provided it can be derived via the classical symmetries method) may be obtained as a member of this set by a suitable group transformation. For general values of the parameters (angle of internal friction and gravity g) it is found there are three distinct classes of solutions which correspond to granular flows considered previously in the literature. For the two limiting cases of high angle of internal friction and zero gravity, the governing partial differential equation admit larger families of Lie point symmetries, and from these symmetries, further solutions are derived, many of which are new. Furthermore, the majority of these solutions are exact, which is rare for granular flow, especially in the case of gravity driven flows.

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Previous research has shown the association between stress and crash involvement. The impact of stress on road safety may also be mediated by behaviours including cognitive lapses, errors, and intentional traffic violations. This study aimed to provide a further understanding of the impact that stress from different sources may have upon driving behaviour and road safety. It is asserted that both stress extraneous to the driving environment and stress directly elicited by driving must be considered part of a dynamic system that may have a negative impact on driving behaviours. Two hundred and forty-seven public sector employees from Queensland, Australia, completed self-report measures examining demographics, subjective work-related stress, daily hassles, and aspects of general mental health. Additionally, the Driver Behaviour Questionnaire (DBQ) and the Driver Stress Inventory (DSI) were administered. All participants drove for work purposes regularly, however the study did not specifically focus on full-time professional drivers. Confirmatory factor analysis of the predictor variables revealed three factors: DSI negative affect; DSI risk taking; and extraneous influences (daily hassles, work-related stress, and general mental health). Moderate intercorrelations were found between each of these factors confirming the ‘spillover’ effect. That is, driver stress is reciprocally related to stress in other domains including work and domestic life. Structural equation modelling (SEM) showed that the DSI negative affect factor influenced both lapses and errors, whereas the DSI risk-taking factor was the strongest influence on violations. The SEMs also confirmed that daily hassles extraneous to the driving environment may influence DBQ lapses and violations independently. Accordingly, interventions may be developed to increase driver awareness of the dangers of excessive emotional responses to both driving events and daily hassles (e.g. driving fast to ‘blow off steam’ after an argument). They may also train more effective strategies for self-regulation of emotion and coping when encountering stressful situations on the road.