823 resultados para Rating-scale


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Objective Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness on driving ability. However, the degree to which drivers appreciate the dangerousness of driving while sleepy is somewhat unclear. This study sought to determine drivers’ on-road experiences of sleepiness, their prior sleep habits, and personal awareness of the signs of sleepiness. Methods Participants were a random selection of 92 drivers travelling on a major highway in the state of Queensland, Australia, who were stopped by police as part of routine drink driving operations. Participants completed a brief questionnaire that included demographic information, sleepy driving experiences (signs of sleepiness and on-road experiences of sleepiness), and prior sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness in the 15 minutes prior to being stopped by police. Results Participants rating of subjective sleepiness were quite low, with 90% reporting being alert to extremely alert on the KSS. Participants were reasonably aware of the signs of sleepiness, with many signs of sleepiness associated with on-road experiences of sleepiness. Additionally, the number of hours spent driving was positively correlated with the drivers’ level of sleep debt. Conclusions The results suggest the participants had moderate experience of driving while sleepy and many were aware of the signs of sleepiness. The relationship between driving long distances and increased sleep debt is a concern for road safety – increased education regarding the dangers of sleepy driving seems warranted.

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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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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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Dehydroepiandrosterone (DHEA) and its sulphate form (DHEA) are neuroactive steroids with antiglucocorticoid properties. An imbalance in the ratio of cortisol to DHEA(S) has been implicated in the pathophysiology of stress-related psychiatric disorders. This study prospectively investigated circulating cortisol, DHEAS and their ratio in first-episode psychosis (FEP) patients compared to healthy controls, and their relationship to perceived stress, psychotic, negative and mood symptoms. METHODS: Blood cortisol and DHEAS levels were obtained in 39 neuroleptic-naïve or minimally-treated FEP patients and 25 controls. Twenty-three patients and 15 controls received repeat assessments after 12 weeks. Perceived stress was assessed using the Perceived Stress Scale and symptoms were assessed in patients using standard rating scales. RESULTS: At baseline, no differences were observed in cortisol, DHEAS or the cortisol/DHEAS ratio between patients and controls. There were also no group differences in the change in these biological variables during the study period. Within FEP patients, decreases in cortisol and the cortisol/DHEAS ratio over time were directly related to the improvement in depression (r = 0.45; p = 0.031, r = 0.52; p = 0.01), negative (r = 0.51; p = 0.006, r = 0.55; p = 0.008) and psychotic symptoms (cortisol only, r = 0.53; p = 0.01). Perceived stress significantly correlated with DHEAS (r = 0.51; p = 0.019) and the cortisol/DHEAS ratio (r = -0.49; p = 0.024) in controls, but not patients, possibly reflecting an impaired hormonal response to stress in FEP patients. CONCLUSIONS: These findings further support the involvement of the stress system in the pathophysiology of psychotic disorders, with implications for treatment strategies that modulate these neurosteroids.

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With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

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Background Depression is a common psychiatric disorder in older people. The study aimed to examine the screening accuracy of the Geriatric Depression Scale (GDS) and the Collateral Source version of the Geriatric Depression Scale (CS-GDS) in the nursing home setting. Methods Eighty-eight residents from 14 nursing homes were assessed for depression using the GDS and the CS-GDS, and validated against clinician diagnosed depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID) for residents without dementia and the Provisional Diagnostic Criteria for Depression in Alzheimer Disease (PDCdAD) for those with dementia. The screening performances of five versions of the GDS (30-, 15-, 10-, 8-, and 4-item) and two versions of the CS-GDS (30- and 15-item) were analyzed using receiver operating characteristic (ROC) curves. Results Among residents without dementia, both the self-rated (AUC = 0.75–0.79) and proxy-rated (AUC = 0.67) GDS variations performed significantly better than chance in screening for depression. However, neither instrument adequately identified depression among residents with dementia (AUC between 0.57 and 0.70). Among the GDS variations, the 4- and 8-item scales had the highest AUC and the optimal cut-offs were >0 and >3, respectively. Conclusions The validity of the GDS in detecting depression requires a certain level of cognitive functioning. While the CS-GDS is designed to remedy this issue by using an informant, it did not have adequate validity in detecting depression among residents with dementia. Further research is needed on informant selection and other factors that can potentially influence the validity of proxy-based measures in the nursing home setting.

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Existing field data for Rangal coals (Late Permian) of the Bowen Basin, Queensland, Australia, are inconsistent with the depositional model generally accepted in the current geological literature to explain coal deposition. Given the apparent unsuitability of the current depositional model to the Bowen Basin coal data, a new depositional model, here named the Cyclic Salinity Model, is proposed and tested in this study.

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On the 18th of July 2013, three hundred local members of Gladstone, Queensland erupted into song and dance performing the fraught history of their community harbourside through tug boat ballets, taiko drumming, German bell ringing and BMX bike riding. Over 17,500 people attended the four performances of Boomtown, a Queensland Music Festival event. This was the largest regional, outdoor community-engaged musical performance staged in Australia. The narrative moved beyond the dominant, pejorative view of Gladstone as an industrial town to include the community members’ sense of purpose and aspirations. It was a celebratory, contentious and ambitious project that sought to disrupt the traditional conventions of performance-making through working in artistically democratic ways. This article explores the potential for Australian Community Engaged Arts (CEA) projects such as Boomtown to democratically engage community members and co-create culturally meaningful work within a community. Research into CEA projects rarely consider how the often delicate conversations between practitioners and the community work. The complex processes of finding and co-writing the narrative, casting, and rehearsing Boomtown are discussed with reference to artistic director/dramaturge Sean Mee’s innovative approaches. Boomtown began with and concluded with community conversations. Skilful negotiation ensured congruence between the townspeople’s stories and the “community story” presented on stage, abrogating potential problems of narrative ownership. To supplement the research, twenty-one personal interviews were undertaken with Gladstone community members invested in the production before, during and after the project: performers, audience members and local professionals. The stories shared and emphasised in the theatricalised story were based on propitious, meaningful, local stories from lived experiences rather than preconceived, trivial or tokenistic matters, and were underpinned by a consensus formed on what was in the best interests of the majority of community members. Boomtown exposed hidden issues in the community and gave voice to thoughts, feelings and concerns which triggered not just engagement, but honest conversation within the community.

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Public buildings and large infrastructure are typically monitored by tens or hundreds of cameras, all capturing different physical spaces and observing different types of interactions and behaviours. However to date, in large part due to limited data availability, crowd monitoring and operational surveillance research has focused on single camera scenarios which are not representative of real-world applications. In this paper we present a new, publicly available database for large scale crowd surveillance. Footage from 12 cameras for a full work day covering the main floor of a busy university campus building, including an internal and external foyer, elevator foyers, and the main external approach are provided; alongside annotation for crowd counting (single or multi-camera) and pedestrian flow analysis for 10 and 6 sites respectively. We describe how this large dataset can be used to perform distributed monitoring of building utilisation, and demonstrate the potential of this dataset to understand and learn the relationship between different areas of a building.

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Outlines some of the potential risks or actual harms that result from large-scale land leases or acquisitions and the relevant human rights and environmental law principles.

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While numerous full scale experimental programs have been conducted around the world over the past 50 years to investigate the behaviour of steel portal frame buildings, none have comprehensively investigated the behaviour of such buildings under wind uplift. Wind uplift loads often govern designs in the Australian environment and this became the subject of a recent research project at Queensland University of Technology (OUT). This paper describes the full scale experiments on a steel portal frame building subject to wind uplift, racking and gravity loads. The portal rafter and column members utilised hollow flange beam (HFB) sections [5-8] though the paper's findings on the theoretical and experimental building responses relate to conventional types of steel portal frame buildings.

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Background Cancer-related fatigue (CRF) is the most common and distressing symptom reported by breast cancer survivors. The primary aim of this study was to translate and evaluate psychometrically for the first time a Spanish version of the Piper Fatigue Scale-Revised (S-PFS-R). Methods One hundred and eleven women with stage I–IIIA breast cancer who had completed their primary cancer therapy in the previous 6 months with the exception of hormone therapy completed the S-PFS-R, the Profile of Mood States (POMS) Fatigue (POMS-F) and Vigor subscales (POMS-V), and bilateral force handgrip testing. Data analysis included test–retest reliability, construct validity, criterion-related validity, and exploratory factor analyses. Results Test–retest reliability was satisfactory (r > 0.86), and all subscales showed moderate to high construct validity estimates [corrected item-subscale correlations (Pearson r = ≥ 0.65)]. The exploratory factor analysis revealed four dimensions with 75.5 % of the common variance explained. The S-PFS-R total score positively correlated with the POMS-F subscale (r = 0.50–0.78) and negatively with the POMS-V subscale (r = −0.13 to −0.44) confirming criterion-related validity. Negative correlations among force handgrip testing, subscales, and total scores were weak (r = −0.26 to −0.29). Conclusions The Spanish version of PFS-R shows satisfactory psychometric properties in a sample of breast cancer survivors. This is the first study to translate the PFS-R into Spanish and further testing is warranted.

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With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.