201 resultados para anthropogenic disturbance


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During post-disaster recovery, an infrastructure system may be subject to a number of disturbances originating from several other interdependent infrastructures. These disturbances might result in a series of system failures, thereby having immediate impact on societal living conditions. The inability to detect signs of disturbance from one infrastructure during recovery might cause significant disruptive effects on other infrastructure via the interconnection that exist among them. In such circumstances, it clearly appears that critical infrastructures' interdependencies affect the recovery of each individual infrastructure, as well as those of other interdependent infrastructure systems. This is why infrastructure resilience needs to be improved in function of those interdependencies, particularly during the recovery period to avoid the occurrence of a ‘disaster of disaster’ scenario. Viewed from this perspective, resilience is achieved through an inter-organisational collaboration between the different organisations involved in the reconstruction of interdependent infrastructure systems. This paper suggests that to some extent, the existing degree of interconnectedness between these infrastructure systems can also be found in their resilience ability during post-disaster recovery. For instance, without a resilient energy system, a large-scale power outage could affect simultaneously all the interdependent infrastructures after a disaster. Thus, breaking down the silos of resilience would be the first step in minimizing the risks of disaster failures from one infrastructure to cascade or escalate to other interconnected systems.

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INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.

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In this paper we report the findings from an evaluation of the introduction of sensory modulation (SM) in an acute mental health inpatient unit. It was expected that SM could be used to help settle patients experiencing high levels of disturbance and that as a result, there would be less need for use of more restrictive seclusion practices. The evaluation took place in a hospital in south-east Queensland, Australia. SM was introduced in one acute unit while the other served as a control. The evaluation comprised two studies. In the first study we aimed to determine whether SM reduced the level of disturbance among patients given the opportunity to use it. In the second study we aimed to find out whether the introduction of SM reduced the frequency and duration of seclusion. In study 1, we found that most patients reported marked reduction in disturbance after using SM and there was a very large effect size for the group as a whole. In study 2, we found that frequency of seclusion dropped dramatically in the unit that introduced SM but rose slightly in the unit that did not have access to SM. The change in seclusion rate was highly significant (χ2 = 49.1, df = 1, p < 0.001). Results are discussed, having reference to the limitations inherent in a naturalistic study.

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If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro-ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro-ecosystem. None of these agro-ecosystem models handles all land sector GHG fluxes, and considerable model-based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy-driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro-ecosystem models for use in GHG mitigation policy are proposed.

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Change point estimation is recognized as an essential tool of root cause analyses within quality control programs as it enables clinical experts to search for potential causes of change in hospital outcomes more effectively. In this paper, we consider estimation of the time when a linear trend disturbance has occurred in survival time following an in-control clinical intervention in the presence of variable patient mix. To model the process and change point, a linear trend in the survival time of patients who underwent cardiac surgery is formulated using hierarchical models in a Bayesian framework. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. We use Markov Chain Monte Carlo to obtain posterior distributions of the change point parameters including the location and the slope size of the trend and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time cumulative sum control chart (CUSUM) control charts for different trend scenarios. In comparison with the alternatives, step change point model and built-in CUSUM estimator, more accurate and precise estimates are obtained by the proposed Bayesian estimator over linear trends. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

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Background This study investigated the prevalence and socio-cultural correlates of postnatal mood disturbance amongst women 18–45 years old in Central Vietnam. Son preference and traditional confinement practices were explored as well as factors such as poverty, parity, family and intimate partner relationships and infant health. Methods A cross-sectional study was conducted in twelve randomly selected Commune Health Centres from urban and rural districts of Thua Thien Hue Province, Vietnam. Mother-infant dyads one to six months postpartum were invited to participate. Questionnaires from 431 mothers (urban n = 216; rural n = 215) assessed demographic and family characteristics, traditional confinement practices, son preference, infant health and social capital. The Edinburgh Postnatal Depression Scale (EPDS) and WHO5 Wellbeing Index indicated depressive symptoms and emotional wellbeing. Data were analysed using general linear models. Results Using an EPDS cut-off of 12/13, 18.1 % (n = 78, 95 % CI 14.6 - 22.1) of women had depressive symptoms (20.4 % urban; 15.8 % rural). Contrary to predictions, infant gender and traditional confinement were unrelated to depressive symptoms. Poverty, food insecurity, being frightened of family members, and intimate partner violence increased both depressive symptoms and lowered wellbeing. The first model accounted for 30.2 % of the variance in EPDS score and found being frightened of one’s husband, husband’s unemployment, breastfeeding difficulties, infant diarrhoea, and cognitive social capital were associated with higher EPDS scores. The second model had accounted for 22 % of the variance in WHO5 score. Living in Hue city, low education, poor maternal competence and a negative family response to the baby lowered maternal wellbeing. Conclusions Traditional confinement practices and son preference were not linked to depressive symptoms among mothers, but were correlates of family relationships and wellbeing. Poverty, food insecurity, violence, infant ill health, and discordant intimate and family relationships were linked with depressive symptoms in Central Vietnam.

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Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis. © 2011 Macmillan Publishers Limited. All rights reserved.

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Objective: Sleep disturbance in gastro-oesophageal reflux disease (GORD) in infants and young children has not been systematically studied nor has this manifestation been compared with population norms. Methods: Sleep patterns of 102 infants and children aged 1 to 36 months with and without GORD, defined by pH monitoring, were analysed using the same questionnaire as in recent studies of normal sleep behaviour in this age range. Main outcome measures included time taken to settle at night, the number of night time wakenings requiring parental intervention, day time sleep patterns and parents problems with their childs' sleep behaviour. Results: Compared with the population norms (n=3102), those with GORD (n=76) had greater prevalence of night time waking >3/night (50% vs 13% aged 3-12 months; 60% vs 10% aged 12-24 months, P<0.001), requirement of parental intervention (82% vs 55% aged 3-12 months, P < 0.05; 92% vs 55% aged 12-24 months, P < 0.001), significantly delayed onset of sleeping through the night, and greater prevalence of daytime sleep beyond 24 months. Similar but less striking differences were seen comparing those with (n = 76) and without GORD (n = 26). Conclusions: Sleep interruption occurs more frequently in infants and children with GORD than population norms. Objective evaluation of infants and children with sleep disturbance after the age of 3 months may avoid unnecessary over or under diagnosis of GORD. Systematic investigation of the contribution of GORD to sleep disturbance in infants and young children is warranted

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Background: The use of large-volume electrolyte balanced solutions as preparation for colonoscopy often results in poor patient compliance and acceptance. The tolerance, safety, and efficacy of high-versus low volume colon-cleansing methods as preparation for colonoscopy in children were compared by randomized operator-blinded trial. Methods: Twenty-nine children ages 3.6-14.6 years had either high-volume nasogastric balanced polyethylene glycol electrolyte lavage (20 ml/kg/h) until the effluent was clear (n = 15), or two oral doses of sodium phosphate solution (22.5-45 ml) separated by oral fluid intake (n = 14). Results: Both preparations were equally effective. The low-volume preparation was better tolerated and caused less discomfort that the high-volume preparation, judging by serial nurse observations. The incidence of abdominal symptoms, diarrhea, sleep disturbance, and vomiting was not significantly different between the two groups. Both groups had a small reduction in mean hematocrit and serum calcium levels. The sodium phosphate preparation caused increases in mean serum sodium concentrations from 140 to 145 mmol/L and serum phosphate concentrations from 1.41 to 2.53 mmol/L. Ten hours after the commencement of the preanesthetic fast, these concentrations had returned to normal. Conclusions: There are advantages in terms of tolerance, discomfort, and case of administration with acceptable colonic cleansing with the use of the less-invasive oral sodium phosphate low-volume colon-cleansing preparation in children. Safe use requires ensuring an adequate oral fluid intake during the preparation time and avoidance of use in patients with renal insufficiency.

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This paper presents a motion control system for guidance of an underactuated Unmanned Underwater Vehicle (UUV) on a helical trajectory. The control strategy is developed using Port-Hamiltonian theory and interconnection and damping assignment passivity-based control. Using energy routing, the trajectory of a virtual fully actuated plant is guided onto a vector field. A tracking controller is then used that commands the underactuated plant to follow the velocity of the virtual plant. An integral control is inserted between the two control layers, which adds robustness and disturbance rejection to the design.

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Road deposited dust is a complex mixture of pollutants derived from a wide range of sources. Accurate identification of these sources is seminal for effective source-oriented control measures. A range of techniques such as enrichment factor analysis (EF), principal component analysis (PCA) and hierarchical cluster analysis (HCA) are available for identifying sources of complex mixtures. However, they have multiple deficiencies when applied individually. This study presents an approach for the effective utilisation of EF, PCA and HCA for source identification, so that their specific deficiencies on an individual basis are eliminated. EF analysis confirmed the non-soil origin of metals such as Na, Cu, Cd, Zn, Sn, K, Ca, Sb, Ba, Ti, Ni and Mo providing guidance in the identification of anthropogenic sources. PCA and HCA identified four sources, with soil and asphalt wear in combination being the most prominent sources. Other sources were tyre wear, brake wear and sea salt.

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PURPOSE: Female athletes, in response to intensive training, competition stress and a lean, athletic physique, are at increased risk of altered hypothalamic-pituitary ovarian (HPO) axis function associated with menstrual cycle disturbance and reduced secretion of the ovarian hormones estrogen and progesterone. Because there is evidence suggesting possible detrimental effects on skeletal health associated with deficiencies in these hormones, a suitable means to asses ovarian hormone concentrations in at risk athletes is needed. The aim of this study was to evaluate a simple, economical means to monitor the ovarian hormone production in athletes, in the setting of intensive training. METHODS: Subjects comprised 14 adolescent rowers, 12 lightweight rowers, and two groups of 10 matched control subjects. Ovarian function was monitored during the competition season by estimation of urinary excretion of estrone glucuronide (E1G) and pregnanediol glucuronide (PdG), enabling the menstrual cycles to be classified as ovulatory or anovulatory. RESULTS: Results indicated 35% and 75% of schoolgirl and lightweight rowers had anovulatory menstrual cycles, respectively. These findings were highlighted by significantly lower excretion of E1G and PdG during phases of intensive training in both the lightweight and schoolgirl rowers, compared with the control subjects. CONCLUSION: It was concluded that the urinary E1G and PdG assays were an effective means to assess the influence of intense training on ovarian hormone concentrations in at risk athletes. It is recommended that this technique be applied more widely as a means of early detection of athletes with low estrogen and progesterone levels, in an attempt to avoid detrimental influences on skeletal health.

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Public apathy on the issue of Anthropogenic Climate Change (ACC) is widespread, with more than half of surveyed Australians and Britons in denial of the phenomenon. While much is known about media influences and strategies such as message framing, there is little in the way of research on the impact of designed visual communication. This study builds knowledge and challenges assumptions by employing a relational approach between ACC visual communications, the professionals producing them, and the members of society that these communications are attempting to influence, contributing knowledge to the fields of graphic design, science communication and social science.

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Electromechanical wave propagation characterizes the first-swing dynamic response in a spatially delayed manner. This paper investigates the characteristics of this phenomenon in two-dimensional and one-dimensional power systems. In 2-D systems, the wave front expands as a ripple in a pond. In 1-D systems, the wave front is more concentrated, retains most of its magnitude, and travels like a pulse on a string. This large wave front is more impactful upon any weak link and easily causes transient instability in 1-D systems. The initial disturbance injects both high and low frequency components, but the lumped nature of realistic systems only permits the lower frequency components to propagate through. The kinetic energy split at a junction is equal to the generator inertia ratio in each branch in an idealized continuum system. This prediction is approximately valid in a realistic power system. These insights can enhance understanding and control of the traveling waves.

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Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.