966 resultados para severity scale
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This paper overviews the development of a vision-based AUV along with a set of complementary operational strategies to allow reliable autonomous data collection in relatively shallow water and coral reef environments. The development of the AUV, called Starbug, encountered many challenges in terms of vehicle design, navigation and control. Some of these challenges are discussed with focus on operational strategies for estimating and reducing the total navigation error when using lower-resolution sensing modalities. Results are presented from recent field trials which illustrate the ability of the vehicle and associated operational strategies to enable rapid collection of visual data sets suitable for marine research applications.
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The mean shift tracker has achieved great success in visual object tracking due to its efficiency being nonparametric. However, it is still difficult for the tracker to handle scale changes of the object. In this paper, we associate a scale adaptive approach with the mean shift tracker. Firstly, the target in the current frame is located by the mean shift tracker. Then, a feature point matching procedure is employed to get the matched pairs of the feature point between target regions in the current frame and the previous frame. We employ FAST-9 corner detector and HOG descriptor for the feature matching. Finally, with the acquired matched pairs of the feature point, the affine transformation between target regions in the two frames is solved to obtain the current scale of the target. Experimental results show that the proposed tracker gives satisfying results when the scale of the target changes, with a good performance of efficiency.
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Background: Successful management of atopic dermatitis poses a significant and ongoing challenge to parents of affected children. Despite frequent reports of child behaviour problems and parenting difficulties, there is a paucity of literature examining relationships between child behaviour and parents' confidence and competence with treatment. Objectives: To examine relationships between child, parent, and family variables, parents' self-efficacy for managing atopic dermatitis, self-reported performance of management tasks, observed competence with providing treatment, and atopic dermatitis severity. Design: Cross-sectional study design. Participants A sample of 64 parent-child dyads was recruited from the dermatology clinic of a paediatric tertiary referral hospital in Brisbane, Australia. Methods: Parents completed self-report questionnaires examining child behaviour, parents' adjustment, parenting conflict, parents' relationship satisfaction, and parents' self-efficacy and self-reported performance of key management tasks. Severity of atopic dermatitis was assessed using the Scoring Atopic Dermatitis index. A routine home treatment session was observed, and parents' competence in carrying out the child's treatment assessed. Results: Pearson's and Spearman's correlations identified significant relationships (p< .05) between parents' self-efficacy and disease severity, child behaviour difficulties, parent depression and stress, parenting conflict, and relationship satisfaction. There were also significant relationships between each of these variables and parents' self-reported performance of management tasks. More profound child behaviour difficulties were associated with more severe atopic dermatitis and greater parent stress. Using multiple linear regressions, significant proportions of variation in parents' self-efficacy and self-reported task performance were explained by child behaviour difficulties and parents' formal education. Self-efficacy emerged as a likely mediator for relationships between both child behaviour and parents' education, and self-reported task performance. Direct observation of treatment sessions revealed strong relationships between parents' treatment competence and parents' self-efficacy, outcome expectations, and self-reported task performance. Less competent task performance was also associated with greater parent-reported child behaviour difficulties, parent depression and stress, parenting conflict, and relationship dissatisfaction. Conclusion: This study revealed the importance of child behaviour to parents' confidence and practices in the context of atopic dermatitis management. Children with more severe atopic dermatitis are at risk of presenting with challenging behaviour problems and their parents struggle to manage the condition successfully.
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This thesis is a comparative study of the modelling of mechanical behaviours of F-actin cytoskeleton which is an important structural component in living cells. A new granular model was developed for F-actin cytoskeleton based on the concept of multiscale modelling. This framework overcomes difficulties encountered in physical modelling of cytoskeleton in conventional continuum mechanics modelling, and the computational challenges in all-atom molecular dynamics simulation. The thermostat algorithm was further modified to better predict the thermodynamic properties of F-actin cytoskeleton in modelling. This multiscale modelling framework was applied in explaining the physical mechanisms of cytoskeleton responses to external mechanical loads.
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Self-gifting consumer behaviour (SGCB) is on the rise as consumers seek reward and therapeutic benefits from their shopping experiences. SGCB is defined as personally symbolic, self-communication through special indulgences, which tend to be premeditated and highly context bound. Prior research into the measurement of this growing behavioural phenomenon has been fragmented because of differences in conceptualisation. This research builds upon the prior literature and through a series of qualitative and quantitative studies, develops a valid, multidimensional measure of SGCB that will be useful for future quantitative inquiry into self-gifting consumption.
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Despite being used since 1976, Delusions-Symptoms-States-Inventory/states of Anxiety and Depression (DSSI/sAD) has not yet been validated for use among people with diabetes. The aim of this study was to examine the validity of the personal disturbance scale (DSSI/sAD) among women with diabetes using Mater-University of Queensland Study of Pregnancy (MUSP) cohort data. The DSSI subscales were compared against DSM-IV disorders, the Mental Component Score of the Short Form 36 (SF-36 MCS), and Center for Epidemiologic Studies Depression Scale (CES-D). Factor analyses, odds ratios, receiver operating characteristic (ROC) analyses and diagnostic efficiency tests were used to report findings. Exploratory factor analysis and fit indices confirmed the hypothesized two-factor model of DSSI/sAD. We found significant variations in the DSSI/sAD domain scores that could be explained by CES-D (DSSI-Anxiety: 55%, DSSI-Depression: 46%) and SF-36 MCS (DSSI-Anxiety: 66%, DSSI-Depression: 56%). The DSSI subscales predicted DSM-IV diagnosed depression and anxiety disorders. The ROC analyses show that although the DSSI symptoms and DSM-IV disorders were measured concurrently the estimates of concordance remained only moderate. The findings demonstrate that the DSSI/sAD items have similar relationships to one another in both the diabetes and non-diabetes data sets which therefore suggest that they have similar interpretations.
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PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.
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Epigenetic changes correspond to heritable modifications of the chromosome structure, which do not involve alteration of the DNA sequence but do affect gene expression. These mechanisms play an important role in normal cell differentiation, but aberration is associated also with several diseases, including cancer and neural disorders. In consequence, despite intensive studies in recent years, the contribution of modifications remains largely unquantified due to overall system complexity and insufficient data. Computational models can provide powerful auxiliary tools to experimentation, not least as scales from the sub-cellular through cell populations (or to networks of genes) can be spanned. In this paper, the challenges to development, of realistic cross-scale models, are discussed and illustrated with respect to current work.
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There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.
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Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.
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Emotional and role functioning difficulties are associated with chronic alcohol use and liver disease. Little is known about prospective changes in psychological and psychosocial functioning following orthotopic liver transplantation (OLT) amongst patients with alcoholic liver disease (ALD). We aimed to assess the functioning of this patient group post liver transplantation. Comprehensive psychosocial assessment of depression (Beck Depression Inventory [BDI]), anxiety (State-Trait Anxiety Inventory-Form X [STAI]) and psychosocial adjustment (Psychosocial Adjustment to Illness Scale-Self-Report version [PAIS-SR]) was conducted with 42 ALD patients available for pre and post OLT testing. Dependence severity was assessed by the Brief Michigan Alcoholism Screening Test (bMAST). Significant reductions in average anxiety and depression symptoms were observed 12-months post-OLT. Significant improvements in psychosocial adjustment to illness were also reported. Patients with higher levels of alcohol dependence severity pre transplant assessment improved comparably to those with lower levels of dependence. In summary, the study found that OLT contributed to reducing overall levels of mood and anxiety symptoms in ALD patients, approximating general (non-clinical) population norms. Psychosocial adjustment also improved significantly post liver transplantation.
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Purpose This study tested the effectiveness of a pressure ulcer (PU) prevention bundle in reducing the incidence of PUs in critically ill patients in two Saudi intensive care units (ICUs). Design A two-arm cluster randomized experimental control trial. Methods Participants in the intervention group received the PU prevention bundle, while the control group received standard skin care as per the local ICU policies. Data collected included demographic variables (age, diagnosis, comorbidities, admission trajectory, length of stay) and clinical variables (Braden Scale score, severity of organ function score, mechanical ventilation, PU presence, and staging). All patients were followed every two days from admission through to discharge, death, or up to a maximum of 28 days. Data were analyzed with descriptive correlation statistics, Kaplan-Meier survival analysis, and Poisson regression. Findings The total number of participants recruited was 140: 70 control participants (with a total of 728 days of observation) and 70 intervention participants (784 days of observation). PU cumulative incidence was significantly lower in the intervention group (7.14%) compared to the control group (32.86%). Poisson regression revealed the likelihood of PU development was 70% lower in the intervention group. The intervention group had significantly less Stage I (p = 002) and Stage II PU development (p = 026). Conclusions Significant improvements were observed in PU-related outcomes with the implementation of the PU prevention bundle in the ICU; PU incidence, severity, and total number of PUs per patient were reduced. Clinical Relevance Utilizing a bundle approach and standardized nursing language through skin assessment and translation of the knowledge to practice has the potential to impact positively on the quality of care and patient outcome.
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The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.
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Objective: The aim of the present pilot study was to examine the effectiveness of a relaxation massage therapy programme in reducing stress, anxiety and aggression on a young adult psychiatric inpatient unit. Method: This was a prospective, non-randomized intervention study comparing treatment as usual (TAU) with TAU plus massage therapy intervention (MT) over consecutive 7 week blocks (May–August 2006). MT consisted of a 20 min massage therapy session offered daily to patients during their period of hospitalization. The Kennedy Nurses’ Observational Scale for Inpatient Evaluation (NOSIE), the Symptom Checklist-90–Revised (SCL-90-R), the State–Trait Anxiety Inventory (STAI) and stress hormone (saliva cortisol) levels were used to measure patient outcomes at admission and discharge from the unit. The Staff Observation Aggression Scale–Revised (SOAS-R) was used to monitor the frequency and severity of aggressive incidents on the unit. Results: There was a significant reduction in self-reported anxiety (p < 0.001), resting heart rate (p < 0.05) and cortisol levels (p < 0.05) immediately following the initial and final massage therapy sessions. Significant improvements in hostility (p = 0.007) and depression scores (p < 0.001) on the SCL-90-R were observed in both treatment groups. There was no group×time interaction on any of the measures. Poor reliability of staff-reported incidents on the SOAS-R limited the validity of results in this domain. Conclusions: Massage therapy had immediate beneficial effects on anxiety-related measures and may be a useful de-escalating tool for reducing stress and anxiety in acutely hospitalized psychiatric patients. Study limitations preclude any definite conclusions on the effect of massage therapy on aggressive incidents in an acute psychiatric setting. Randomized controlled trials are warranted.
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Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.