Multiple analysis of three common genetic alterations associated with thrombophilia

We have previously reported the use of a novel mini-sequencing protocol for detection of the factor V Leiden variant, the first nucleotide change (FNC) technology. This technology is based on a single nucleotide extension of a primer, which is hybridized immediately adjacent to the site of mutation. The extended nucleotide that carries a reporter molecule (fluorescein) has the power to discriminate the genotype at the site of mutation. More recently, the prothrombin 20210 and thermolabile methylene tetrahydrofolate reductase (MTHFR) 677 variants have been identified as possible risk factors associated with thrombophilia. This study describes the use of the FNC technology in a combined assay to detect factor V, prothrombin and MTHFR variants in a population of Australian blood donors, and describes the objective numerical methodology used to determine genotype cut-off values for each genetic variation. Using FNC to test 500 normal blood donors, the incidence of Factor V Leiden was 3.6% (all heterozygous), that of prothrombin 20210 was 2.8% (all heterozygous) and that of MTHFR was 10% (homozygous). The combined FNC technology offers a simple, rapid, automatable DNA-based test for the detection of these three important mutations that are associated with familial thrombophilia. (C) 2000 Lippincott Williams and Wilkins.

Protection of distributed generation interfaced networks

With the rapid increase in electrical energy demand, power generation in the form of distributed generation is becoming more important. However, the connections of distributed generators (DGs) to a distribution network or a microgrid can create several protection issues. The protection of these networks using protective devices based only on current is a challenging task due to the change in fault current levels and fault current direction. The isolation of a faulted segment from such networks will be difficult if converter interfaced DGs are connected as these DGs limit their output currents during the fault. Furthermore, if DG sources are intermittent, the current sensing protective relays are difficult to set since fault current changes with time depending on the availability of DG sources. The system restoration after a fault occurs is also a challenging protection issue in a converter interfaced DG connected distribution network or a microgrid. Usually, all the DGs will be disconnected immediately after a fault in the network. The safety of personnel and equipment of the distribution network, reclosing with DGs and arc extinction are the major reasons for these DG disconnections. In this thesis, an inverse time admittance (ITA) relay is proposed to protect a distribution network or a microgrid which has several converter interfaced DG connections. The ITA relay is capable of detecting faults and isolating a faulted segment from the network, allowing unfaulted segments to operate either in grid connected or islanded mode operations. The relay does not make the tripping decision based on only the fault current. It also uses the voltage at the relay location. Therefore, the ITA relay can be used effectively in a DG connected network in which fault current level is low or fault current level changes with time. Different case studies are considered to evaluate the performance of the ITA relays in comparison to some of the existing protection schemes. The relay performance is evaluated in different types of distribution networks: radial, the IEEE 34 node test feeder and a mesh network. The results are validated through PSCAD simulations and MATLAB calculations. Several experimental tests are carried out to validate the numerical results in a laboratory test feeder by implementing the ITA relay in LabVIEW. Furthermore, a novel control strategy based on fold back current control is proposed for a converter interfaced DG to overcome the problems associated with the system restoration. The control strategy enables the self extinction of arc if the fault is a temporary arc fault. This also helps in self system restoration if DG capacity is sufficient to supply the load. The coordination with reclosers without disconnecting the DGs from the network is discussed. This results in increased reliability in the network by reduction of customer outages.

Generation of profluorescent isoindoline nitroxides using click chemistry

Novel profluorescent nitroxides bearing a triazole linker between the coumarin fluorophore and an isoindoline nitroxide were prepared in good yields using the coppercatalyzed azide�alkyne 1,3-dipolar cycloaddition reaction (CuAAC). Nitroxides containing 7-hydroxy and 7-diethylamino substitution on their coumarin rings displayed significant fluorescence suppression, and upon reaction with methyl radicals, normal fluorescence emission was returned. The fluorescence emission for the 7-hydroxycoumarin nitroxide and its diamagnetic analogue was found to be strongly influenced by pH with maximal fluorescence emission achieved in basic solution. Solvent polarity was also shown to affect fluorescence emission. The significant difference in fluorescence output between the nitroxides and their corresponding diamagnetic analogues makes these compounds ideal tools for monitoring processes involving free-radical species.

A unifying view of multiple kernel learning

Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion’s dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments.

A unifying view of multiple kernel learning

Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying general optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion's dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments.

The psychosocial factors influencing aggressive driving behaviour

Many drivers in highly motorised countries believe that aggressive driving is increasing. While the prevalence of the behaviour is difficult to reliably identify, the consequences of on-road aggression can be severe, with extreme cases resulting in property damage, injury and even death. This research program was undertaken to explore the nature of aggressive driving from within the framework of relevant psychological theory in order to enhance our understanding of the behaviour and to inform the development of relevant interventions. To guide the research a provisional ‘working’ definition of aggressive driving was proposed encapsulating the recurrent characteristics of the behaviour cited in the literature. The definition was: “aggressive driving is any on-road behaviour adopted by a driver that is intended to cause physical or psychological harm to another road user and is associated with feelings of frustration, anger or threat”. Two main theoretical perspectives informed the program of research. The first was Shinar’s (1998) frustration-aggression model, which identifies both the person-related and situational characteristics that contribute to aggressive driving, as well as proposing that aggressive behaviours can serve either an ‘instrumental’ or ‘hostile’ function. The second main perspective was Anderson and Bushman’s (2002) General Aggression Model. In contrast to Shinar’s model, the General Aggression Model reflects a broader perspective on human aggression that facilitates a more comprehensive examination of the emotional and cognitive aspects of aggressive behaviour. Study One (n = 48) examined aggressive driving behaviour from the perspective of young drivers as an at-risk group and involved conducting six focus groups, with eight participants in each. Qualitative analyses identified multiple situational and person-related factors that contribute to on-road aggression. Consistent with human aggression theory, examination of self-reported experiences of aggressive driving identified key psychological elements and processes that are experienced during on-road aggression. Participants cited several emotions experienced during an on-road incident: annoyance, frustration, anger, threat and excitement. Findings also suggest that off-road generated stress may transfer to the on-road environment, at times having severe consequences including crash involvement. Young drivers also appeared quick to experience negative attributions about the other driver, some having additional thoughts of taking action. Additionally, the results showed little difference between males and females in the severity of behavioural responses they were prepared to adopt, although females appeared more likely to displace their negative emotions. Following the self-reported on-road incident, evidence was also found of a post-event influence, with females being more likely to experience ongoing emotional effects after the event. This finding was evidenced by ruminating thoughts or distraction from tasks. However, the impact of such a post-event influence on later behaviours or interpersonal interactions appears to be minimal. Study Two involved the quantitative analysis of n = 926 surveys completed by a wide age range of drivers from across Queensland. The study aimed to explore the relationships between the theoretical components of aggressive driving that were identified in the literature review, and refined based on the findings of Study One. Regression analyses were used to examine participant emotional, cognitive and behavioural responses to two differing on-road scenarios whilst exploring the proposed theoretical framework. A number of socio-demographic, state and trait person-related variables such as age, pre-study emotions, trait aggression and problem-solving style were found to predict the likelihood of a negative emotional response such as frustration, anger, perceived threat, negative attributions and the likelihood of adopting either an instrumental or hostile behaviour in response to Scenarios One and Two. Complex relationships were found to exist between the variables, however, they were interpretable based on the literature review findings. Factor analysis revealed evidence supporting Shinar’s (1998) dichotomous description of on-road aggressive behaviours as being instrumental or hostile. The second stage of Study Two used logistic regression to examine the factors that predicted the potentially hostile aggressive drivers (n = 88) within the sample. These drivers were those who indicated a preparedness to engage in direct acts of interpersonal aggression on the road. Young, male drivers 17–24 years of age were more likely to be classified as potentially hostile aggressive drivers. Young drivers (17–24 years) also scored significantly higher than other drivers on all subscales of the Aggression Questionnaire (Buss & Perry, 1992) and on the ‘negative problem orientation’ and ‘impulsive careless style’ subscales of the Social Problem Solving Inventory – Revised (D’Zurilla, Nezu & Maydeu-Olivares, 2002). The potentially hostile aggressive drivers were also significantly more likely to engage in speeding and drink/drug driving behaviour. With regard to the emotional, cognitive and behavioural variables examined, the potentially hostile aggressive driver group also scored significantly higher than the ‘other driver’ group on most variables examined in the proposed theoretical framework. The variables contained in the framework of aggressive driving reliably distinguished potentially hostile aggressive drivers from other drivers (Nagalkerke R2 = .39). Study Three used a case study approach to conduct an in-depth examination of the psychosocial characteristics of n = 10 (9 males and 1 female) self-confessed hostile aggressive drivers. The self-confessed hostile aggressive drivers were aged 24–55 years of age. A large proportion of these drivers reported a Year 10 education or better and average–above average incomes. As a group, the drivers reported committing a number of speeding and unlicensed driving offences in the past three years and extensive histories of violations outside of this period. Considerable evidence was also found of exposure to a range of developmental risk factors for aggression that may have contributed to the driver’s on-road expression of aggression. These drivers scored significantly higher on the Aggression Questionnaire subscales and Social Problem Solving Inventory Revised subscales, ‘negative problem orientation’ and ‘impulsive/careless style’, than the general sample of drivers included in Study Two. The hostile aggressive driver also scored significantly higher on the Barrett Impulsivity Scale – 11 (Patton, Stanford & Barratt, 1995) measure of impulsivity than a male ‘inmate’, or female ‘general psychiatric’ comparison group. Using the Carlson Psychological Survey (Carlson, 1982), the self-confessed hostile aggressive drivers scored equal or higher scores than the comparison group of incarcerated individuals on the subscale measures of chemical abuse, thought disturbance, anti-social tendencies and self-depreciation. Using the Carlson Psychological Survey personality profiles, seven participants were profiled ‘markedly anti-social’, two were profiled ‘negative-explosive’ and one was profiled as ‘self-centred’. Qualitative analysis of the ten case study self-reports of on-road hostile aggression revealed a similar range of on-road situational factors to those identified in the literature review and Study One. Six of the case studies reported off-road generated stress that they believed contributed to the episodes of aggressive driving they recalled. Intense ‘anger’ or ‘rage’ were most frequently used to describe the emotions experienced in response to the perceived provocation. Less frequently ‘excitement’ and ‘fear’ were cited as relevant emotions. Notably, five of the case studies experienced difficulty articulating their emotions, suggesting emotional difficulties. Consistent with Study Two, these drivers reported negative attributions and most had thoughts of aggressive actions they would like to take. Similarly, these drivers adopted both instrumental and hostile aggressive behaviours during the self-reported incident. Nine participants showed little or no remorse for their behaviour and these drivers also appeared to exhibit low levels of personal insight. Interestingly, few incidents were brought to the attention of the authorities. Further, examination of the person-related characteristics of these drivers indicated that they may be more likely to have come from difficult or dysfunctional backgrounds and to have a history of anti-social behaviours on and off the road. The research program has several key theoretical implications. While many of the findings supported Shinar’s (1998) frustration-aggression model, two key areas of difference emerged. Firstly, aggressive driving behaviour does not always appear to be frustration driven, but can also be driven by feelings of excitation (consistent with the tenets of the General Aggression Model). Secondly, while the findings supported a distinction being made between instrumental and hostile aggressive behaviours, the characteristics of these two types of behaviours require more examination. For example, Shinar (1998) proposes that a driver will adopt an instrumental aggressive behaviour when their progress is impeded if it allows them to achieve their immediate goals (e.g. reaching their destination as quickly as possible); whereas they will engage in hostile aggressive behaviour if their path to their goal is blocked. However, the current results question this assertion, since many of the hostile aggressive drivers studied appeared prepared to engage in hostile acts irrespective of whether their goal was blocked or not. In fact, their behaviour appeared to be characterised by a preparedness to abandon their immediate goals (even if for a short period of time) in order to express their aggression. The use of the General Aggression Model enabled an examination of the three components of the ‘present internal state’ comprising emotions, cognitions and arousal and how these influence the likelihood of a person responding aggressively to an on-road situation. This provided a detailed insight into both the cognitive and emotional aspects of aggressive driving that have important implications for the design of relevant countermeasures. For example, the findings highlighted the potential value of utilising Cognitive Behavioural Therapy with aggressive drivers, particularly the more hostile offenders. Similarly, educational efforts need to be mindful of the way that person-related factors appear to influence one’s perception of another driver’s behaviour as aggressive or benign. Those drivers with a predisposition for aggression were more likely to perceive aggression or ‘wrong doing’ in an ambiguous on-road situation and respond with instrumental and/or hostile behaviour, highlighting the importance of perceptual processes in aggressive driving behaviour.

Projecting future heat-related mortality under climate change scenarios : A systematic review

Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality. Objectives: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. Data sources and extraction: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English up to 2010. Data synthesis: The review included 14 studies that fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding of the historical temperature-mortality relationships, and consideration of the future changes in climate, population and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socio-economic development, adaptation strategies, land-use patterns, air pollution and mortality displacement. Conclusions: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality.