379 resultados para MULTIPLE-TRAIT
Resumo:
It has been 21 years since the decision in Rogers v Whitaker and the legal principles concerning informed consent and liability for negligence are still strongly grounded in this landmark High Court decision. This paper considers more recent developments in the law concerning the failure to disclose inherent risks in medical procedures, focusing on the decision in Wallace v Kam [2013] HCA 19. In this case, the appellant underwent a surgical procedure that carried a number of risks. The surgery itself was not performed in a sub-standard way, but the surgeon failed to disclose two risks to the patient, a failure that constituted a breach of the surgeon’s duty of care in negligence. One of the undisclosed risks was considered to be less serious than the other, and this lesser risk eventuated causing injury to the appellant. The more serious risk did not eventuate, but the appellant argued that if the more serious risk had been disclosed, he would have avoided his injuries completely because he would have refused to undergo the procedure. Liability was disputed by the surgeon, with particular reference to causation principles. The High Court of Australia held that the appellant should not be compensated for harm that resulted from a risk he would have been willing to run. We examine the policy reasons underpinning the law of negligence in this specific context and consider some of the issues raised by this unusual case. We question whether some of the judicial reasoning adopted in this case, represents a significant shift in traditional causation principles.
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Voltage rise is the main issue which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. In addition, voltage drop at peak load period is a significant power quality concern. This paper proposes a new robust voltage support strategy based on distributed coordination of multiple distribution static synchronous compensators (DSTATCOMs). The study focuses on LV networks with PV as the RE source for customers. The proposed approach applied to a typical LV network and its advantages are shown comparing with other voltage control strategies.
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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.
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This paper presents a method to enable a mobile robot working in non-stationary environments to plan its path and localize within multiple map hypotheses simultaneously. The maps are generated using a long-term and short-term memory mechanism that ensures only persistent configurations in the environment are selected to create the maps. In order to evaluate the proposed method, experimentation is conducted in an office environment. Compared to navigation systems that use only one map, our system produces superior path planning and navigation in a non-stationary environment where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners.
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The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.
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Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.
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Food neophobia is a highly heritable trait characterized by the rejection of foods that are novel or unknown and potentially limits dietary variety, with lower intake and preference particularly for fruits and vegetables. Understanding non-genetic (environmental) factors that may influence the expression of food neophobia is essential to improving children’s consumption of fruits and vegetables and encouraging the adoption of healthier diets. The aim of this study was to examine whether maternal infant feeding beliefs (at four months) were associated with the expression of food neophobia in toddlers and whether controlling feeding practices mediated this relationship. Participants were 244 first-time mothers (M = 30.4, SD = 5.1 years) allocated to the control group of the NOURISH randomized controlled trial. The relationships between infant feeding beliefs (Infant Feeding Questionnaire) at four months and controlling child feeding practices (Child Feeding Questionnaire) and food neophobia (Child Food Neophobia Scale) at 24 months were tested using correlational and multiple linear regression models (adjusted for significant covariates). Higher maternal Concern about infant under-eating and becoming underweight at four months was associated with higher child food neophobia at two years. Similarly, lower Awareness of infant hunger and satiety cues was associated with higher child food neophobia. Both associations were significantly mediated by mothers’ use of Pressure to eat. Intervening early to promote positive feeding practices to mothers may help reduce the use of controlling practices as children develop. Further research that can further elucidate the bi-directional nature of the mother-child feeding relationship is still required.
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This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.
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NLS is a stream cipher which was submitted to the eSTREAM project. A linear distinguishing attack against NLS was presented by Cho and Pieprzyk, which was called Crossword Puzzle (CP) attack. NLSv2 is a tweak version of NLS which aims mainly at avoiding the CP attack. In this paper, a new distinguishing attack against NLSv2 is presented. The attack exploits high correlation amongst neighboring bits of the cipher. The paper first shows that the modular addition preserves pairwise correlations as demonstrated by existence of linear approximations with large biases. Next, it shows how to combine these results with the existence of high correlation between bits 29 and 30 of the S-box to obtain a distinguisher whose bias is around 2^−37. Consequently, we claim that NLSv2 is distinguishable from a random cipher after observing around 2^74 keystream words.
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The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.
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The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.
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This study investigated bullying amongst siblings in both traditional and cyber forms, and the associations of gender, grade, peer bullying perpetration, trait anger and moral disengagement. The participants were 455 children in grades 5 to 12 (262 girls and 177 boys with 16 unknown gender) who had a sibling. As the number of siblings who only bullied by technology was low, these associations were not able to be calculated. However, the findings showed that the percentage of sibling traditional bullying perpetration (31.6%) was higher than peer bullying perpetration (9.8%). Sibling bullies reported engaging in complex behaviours of perpetration and victimisation in both the physical and in cyber settings, although the number was small. Gender, trait anger, moral disengagement and bullying peers at school (but not grade) were all significantly associated with sibling traditional bullying perpetration. The implications of the findings are discussed for bullying intervention and prevention programs to understand childhood bullying in diverse contexts.
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This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.
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Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.
Resumo:
The world of classical ballet exerts considerable physical and psychological stress upon those who participate, and yet the process of coping with such stressors is not well understood. Relationships between coping strategies and competitive trait anxiety were investigated among 104 classical dancers (81 females and 23 males) from three professional ballet companies, two private dance schools, and two full-time, university dance courses in Australia. Coping strategies were assessed using the Modified COPE scale (MCOPE: Crocker & Graham, 1995), a 48-item measure of 12 dimensions of coping. Competitive trait anxiety was assessed using the Sport Anxiety Scale (SAS: Smith, Smoll, & Schutz, 1990), a 21-item measure of three anxiety dimensions. Trait anxiety scores, in particular for Somatic Anxiety and Worry, predicted seven of the 12 coping strategies (Suppression of Competing Activities: R2 = 27.1%; Venting of Emotions: R2 = 23.2%; Active Coping: R2 = 14.3%; Denial: R2 = 17.7%; Self-Blame: R2 = 35.7%; Effort: R2 = 16.6%; Wishful Thinking: R2 = 42.3%). High trait anxious dancers reported more frequent use of all categories of coping strategies, some of which are considered to be maladaptive. No effects of gender or status (professional versus students) were identified. Results emphasize the need for the effectiveness of specific coping strategies to be considered during the process of preparing young classical dancers for a career in professional ballet.