912 resultados para sleep pattern


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Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

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PURPOSE: This study examined the effects of overnight sleep deprivation on recovery following competitive rugby league matches. METHODS: Eleven male, amateur rugby league players performed two competitive matches, followed by either a normal night's sleep (~8h; CONT) or a sleep deprived night (~0h; SDEP) in a randomised fashion. Testing was conducted the morning of the match, and immediately post-match, 2h post and the next morning (16h post-match). Measures included counter-movement jump (CMJ) distance, knee extensor maximal voluntary contraction (MVC), voluntary activation (VA), venous blood creatine kinase (CK) and C-reactive protein (CRP), perceived muscle soreness and a word-colour recognition cognitive function test. Percent change between post- and 16h post-match was reported to determine the effect of the intervention the next morning. RESULTS: Large effects indicated a greater post- to 16h post-match percentage decline in CMJ distance following SDEP compared to CONT (P=0.10-0.16; d=0.95-1.05). Similarly, the percentage decline in incongruent word-colour reaction times were increased in SDEP trials (P=0.007; d=1.75). Measures of MVC did not differ between conditions (P=0.40-0.75; d=0.13-0.33), though trends for larger percentage decline in VA were detected in SDEP (P=0.19; d=0.84). Further, large effects indicated higher CK and CRP responses 16h post-match during SDEP compared to CONT (P=0.11-0.87; d=0.80-0.88). CONCLUSIONS: Sleep deprivation negatively affected recovery following a rugby league match, specifically impairing CMJ distance and cognitive function. Practitioners should promote adequate post-match sleep patterns or adjust training demands the next day to accommodate the altered physical and cognitive state following sleep deprivation.

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Background: When experiencing sleep problems for the first time, consumers may often approach community pharmacists for advice as they are easily accessible health care professionals in the community. In Australian community pharmacies there are no specific tools available for use by pharmacists to assist with the assessment and handling of consumers with sleep enquiries. Objective: To assess the feasibility of improving the detection of sleep disorders within the community through the pilot of a newly developed Community Pharmacy Sleep Assessment Tool (COP-SAT). Method: The COP-SAT was designed to incorporate elements from a number of existing, standardized, and validated clinical screening measures. The COP-SAT was trialed in four Australian community pharmacies over a 4-week period. Key findings: A total of 241 community pharmacy consumers were assessed using the COP-SAT. A total of 74 (30.7%) were assessed as being at risk of insomnia, 26 (10.7%) were at risk of daytime sleepiness, 19 (7.9%) were at risk of obstructive sleep apnea, and 121 (50.2%) were regular snorers. A total of 116 (48.1%) participants indicated that they consume caffeine before bedtime, of which 55 (47%) had associated symptoms of sleep onset insomnia. Moreover, 85 (35%) consumed alcohol before bedtime, of which 50 (58%) experienced fragmented sleep, 50 (58%) were regular snorers, and nine (10.6%) had apnea symptoms. The COP-SAT was feasible in the community pharmacy setting. The prevalence of sleep disorders in the sampled population was high, but generally consistent with previous studies on the general population. Conclusion: A large proportion of participants reported sleep disorder symptoms, and a link was found between the consumption of alcohol and caffeine substances at bedtime and associated symptoms. While larger studies are needed to assess the clinical properties of the tool, the results of this feasibility study have demonstrated that the COP-SAT may be a practical tool for the identification of patients at risk of developing sleep disorders in the community.

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Book Description: Life is a mix of good and bad happenings and sometimes terrible things happen to people. Trauma is evident across our lifespan; it is part of our lives. Trauma may not exert the same demands on the individual when they get on with their lives or experience other positive aspects of what life has to offer; however, it does not change its form from trauma to growth – it stays there etched into our psyche as trauma. In simple terms, growth occurs alongside the traumatic etchings. This is a book that will provide some answers to psychologists, counselors, social workers and mental health workers about what happens to people who are traumatized and how they ‘get on with their lives’; it also gives some excellent examples of how therapies can assist them in moving forward in life’s journey.

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A big challenge for classification on text is the noisy of text data. It makes classification quality low. Many classification process can be divided into two sequential steps scoring and threshold setting (thresholding). Therefore to deal with noisy data problem, it is important to describe positive feature effectively scoring and to set a suitable threshold. Most existing text classifiers do not concentrate on these two jobs. In this paper, we propose a novel text classifier with pattern-based scoring that describe positive feature effectively, followed by threshold setting. The thresholding is based on score of training set, make it is simple to implement in other scoring methods. Experiment shows that our pattern-based classifier is promising.

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Background: Heart failure is a serious condition estimated to affect 1.5-2.0% of the Australian population with a point prevalence of approximately 1% in people aged 50-59 years, 10% in people aged 65 years or more and over 50% in people aged 85 years or over (National Heart Foundation of Australian and the Cardiac Society of Australia and New Zealand, 2006). Sleep disturbances are a common complaint of persons with heart failure. Disturbances of sleep can worsen heart failure symptoms, impair independence, reduce quality of life and lead to increased health care utilisation in patients with heart failure. Previous studies have identified exercise as a possible treatment for poor sleep in patients without cardiac disease however there is limited evidence of the effect of this form of treatment in heart failure. Aim: The primary objective of this study was to examine the effect of a supervised, hospital-based exercise training programme on subjective sleep quality in heart failure patients. Secondary objectives were to examine the association between changes in sleep quality and changes in depression, exercise performance and body mass index. Methods: The sample for the study was recruited from metropolitan and regional heart failure services across Brisbane, Queensland. Patients with a recent heart failure related hospital admission who met study inclusion criteria were recruited. Participants were screened by specialist heart failure exercise staff at each site to ensure exercise safety prior to study enrolment. Demographic data, medical history, medications, Pittsburgh Sleep Quality Index score, Geriatric Depression Score, exercise performance (six minute walk test), weight and height were collected at Baseline. Pittsburgh Sleep Quality Index score, Geriatric Depression Score, exercise performance and weight were repeated at 3 months. One hundred and six patients admitted to hospital with heart failure were randomly allocated to a 3-month disease-based management programme of education and self-management support including standard exercise advice (Control) or to the same disease management programme as the Control group with the addition of a tailored physical activity program (Intervention). The intervention consisted of 1 hour of aerobic and resistance exercise twice a week. Programs were designed and supervised by an exercise specialist. The main outcome measure was achievement of a clinically significant change (.3 points) in global Pittsburgh Sleep Quality score. Results: Intervention group participants reported significantly greater clinical improvement in global sleep quality than Control (p=0.016). These patients also exhibited significant improvements in component sleep disturbance (p=0.004), component sleep quality (p=0.015) and global sleep quality (p=0.032) after 3 months of supervised exercise intervention. Improvements in sleep quality correlated with improvements in depression (p<0.001) and six minute walk distance (p=0.04). When study results were examined categorically, with subjects classified as either "poor" or "good" sleepers, subjects in the Control group were significantly more likely to report "poor" sleep at 3 months (p=0.039) while Intervention participants were likely to report "good" sleep at this time (p=0.08). Conclusion: Three months of supervised, hospital based, aerobic and resistance exercise training improved subjective sleep quality in patients with heart failure. This is the first randomised controlled trial to examine the role of aerobic and resistance exercise training in the improvement of sleep quality for patients with this disease. While this study establishes exercise as a therapy for poor sleep quality, further research is needed to investigate the effect of exercise training on objective parameters of sleep in this population.

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Research has consistently described that patients after cardiac surgery experience disturbed sleep yet there has been limited investigation into methods to improve this experience. Complementary therapies may be a method of addressing this issue. Aim: To determine if using progressive muscle relaxation improves self-rated sleep quality for patients following cardiac surgery. Methods and Results: Thirty-five participants' quantitative data on sleep quality were obtained via questionnaire during their first post-operative week after cardiac surgery. Qualitative data were obtained through written responses to open-ended questions. No significant differences in sleep quality scores were found between pre and post-intervention of progressive muscle relaxation using the Wilcoxon Signed Ranks Test. However, the qualitative analysis discovered the intervention aided some participants in initiating their sleep by diversion of thought, inducing relaxation or alleviating pain and anxiety. Conclusions: Qualitative findings suggest that progressive muscle relaxation may help patients who have undergone cardiac surgery initiate their sleep.

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The aims of this study were to examine: (1) the association between sociodemographic and lifestyle factors and sleep quality in a population-based cohort of Australian women and (2) possible influence of reproductive status and mental and physical health factors on these associations. Data on 3,655 women (mean age046.6 years, range 34.3–67.4) were obtained from the Mater Hospital University of Queensland Study of Pregnancy for this cross-sectional study. Self-rated sleep quality was assessed using the Pittsburgh Sleep Quality Index. For the purpose of this study, two cutoff points (scores 5 and 10) were used to divide women into three categories: normal (65.2 %), moderately poor (26.4 %), and very poor sleep quality (8.5 %). Other covariates were measured at 21-year follow-up as well. After adjusting for reproductive status, mental and physical health, there were significant associations between moderately poor sleep quality and education and between very poor sleep quality and unemployment, both measures of socioeconomic status. In addition, work-related exertion was associated with increased rates of moderately poor sleep quality, whereas those women undertaking moderate exercise were less likely to experience very poor sleep quality. Independent associations between sociodemographic factors and exercise with moderately poor and very poor sleep quality were identified. These findings demonstrate the dynamic nature of the association between exercise/exertion, socioeconomic status, and sleep quality and highlight the importance of taking these into consideration when dealing with issues of poor sleep quality in women.

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In a classification problem typically we face two challenging issues, the diverse characteristic of negative documents and sometimes a lot of negative documents that are closed to positive documents. Therefore, it is hard for a single classifier to clearly classify incoming documents into classes. This paper proposes a novel gradual problem solving to create a two-stage classifier. The first stage identifies reliable negatives (negative documents with weak positive characteristics). It concentrates on minimizing the number of false negative documents (recall-oriented). We use Rocchio, an existing recall based classifier, for this stage. The second stage is a precision-oriented “fine tuning”, concentrates on minimizing the number of false positive documents by applying pattern (a statistical phrase) mining techniques. In this stage a pattern-based scoring is followed by threshold setting (thresholding). Experiment shows that our statistical phrase based two-stage classifier is promising.

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BACKGROUND & AIMS Metabolomics is comprehensive analysis of low-molecular-weight endogenous metabolites in a biological sample. It could enable mapping of perturbations of early biochemical changes in diseases and hence provide an opportunity to develop predictive biomarkers that could provide valuable insights into the mechanisms of diseases. The aim of this study was to elucidate the changes in endogenous metabolites and to phenotype the metabolic profiling of d-galactosamine (GalN)-inducing acute hepatitis in rats by UPLC-ESI MS. METHODS The systemic biochemical actions of GalN administration (ip, 400 mg/kg) have been investigated in male wistar rats using conventional clinical chemistry, liver histopathology and metabolomic analysis of UPLC- ESI MS of urine. The urine was collected predose (-24 to 0 h) and 0-24, 24-48, 48-72, 72-96 h post-dose. Mass spectrometry of the urine was analysed visually and via conjunction with multivariate data analysis. RESULTS Results demonstrated that there was a time-dependent biochemical effect of GalN dosed on the levels of a range of low-molecular-weight metabolites in urine, which was correlated with developing phase of the GalN-inducing acute hepatitis. Urinary excretion of beta-hydroxybutanoic acid and citric acid was decreased following GalN dosing, whereas that of glycocholic acid, indole-3-acetic acid, sphinganine, n-acetyl-l-phenylalanine, cholic acid and creatinine excretion was increased, which suggests that several key metabolic pathways such as energy metabolism, lipid metabolism and amino acid metabolism were perturbed by GalN. CONCLUSION This metabolomic investigation demonstrates that this robust non-invasive tool offers insight into the metabolic states of diseases.

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Background: Sleep disturbance in midlife women has been studied extensively, although less is known about sleep after menopause. This study examined the relative impact of socio-demographics, modifiable lifestyle factors, and health status on sleep disturbance in post-menopausal women from Queensland, Australia. Methods: The longitudinal Healthy Aging of Women (HOW) study examines health-related quality of life (HRQOL measured by SF-12©), chronic illness, modifiable lifestyle factors such as physical activity, alcohol consumption, smoking, and sleep disturbance (General Sleep Disturbance Scale, GSDS ≥ 43 represent poor sleep) in midlife and older women from low and high socio-economic, rural and urban areas of South-East Queensland, Australia. This paper presents cross-sectional data from the 322 women, aged 60-70 years, participating in the HOW study in 2011. Results: For women in this study, sleep disturbance was relatively common, with 23% (n = 83) reporting poor sleeping (GSDS ≥ 43). Sleep disturbance scores were strongly correlated with being unemployed or on a disability support pension (β = 18.69, P < 0.01), sedentary lifestyle (β = 23.84, P < 0.01), and lower mental (β = -0.60, P <0.01) and physical health-related quality of life scores (β = -0.32, P = 0.01), and these variables explained almost one third of variance in sleep disturbance scores (ηρ² = 29%). Conclusions: Multivariable analysis revealed that sleep disturbance was correlated with physical and mental health-related quality of life, disability, and sedentary lifestyle, but not other lifestyle and socio-demographic characteristics. It may be however, that modifiable lifestyle factors may indirectly impact on sleep by influencing health status.

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A method for prediction of the radiation pattern of N strongly coupled antennas with mismatched sources is presented. The method facilitates fast and accurate design of compact arrays. The prediction is based on the measured N-port S parameters of the coupled antennas and the N active element patterns measured in a 50 ω environment. By introducing equivalent power sources, the radiation pattern with excitation by sources with arbitrary impedances and various decoupling and matching networks (DMN) can be accurately predicted without the need for additional measurements. Two experiments were carried out for verification: pattern prediction for parasitic antennas with different loads and for antennas with DMN. The difference between measured and predicted patterns was within 1 to 2 dB.

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Objectives To examine the effects on monotonous driving of normal sleep versus one night of sleep restriction in continuous positive airway pressure (CPAP) treated obstructive sleep apnoea (OSA) patients compared with age matched healthy controls. Methods Nineteen CPAP treated compliant male OSA patients (OSA-treated patients (OPs)), aged 50–75 years, and 20 healthy age-matched controls underwent both a normal night’s sleep and sleep restriction to 5 h (OPs remained on CPAP) in a counterbalanced design. All participants completed a 2 h afternoon monotonous drive in a realistic car simulator. Driving was monitored for sleepiness-related minor and major lane deviations, with ‘safe’ driving time being total time driven prior to first major lane deviation. EEGs were recorded continuously, and subjective sleepiness ratings were taken at regular intervals throughout the drive. Results After a normal night’s sleep, OPs and controls did not differ in terms of driving performance or in their ability to assess the levels of their own sleepiness, with both groups driving ‘safely’ for approximately 90 min. However, after sleep restriction, OPs had a significantly shorter (65 min) safe driving time and had to apply more compensatory effort to maintain their alertness compared with controls. They also underestimated the enhanced sleepiness. Nevertheless, apart from this caveat, there were generally close associations between subjective sleepiness, likelihood of a major lane deviation and EEG changes indicative of sleepiness. Conclusions With a normal night’s sleep, effectively treated older men with OSA drive as safely as healthy men of the same age. However, after restricted sleep, driving impairment is worse than that of controls. This suggests that, although successful CPAP treatment can alleviate potential detrimental effects of OSA on monotonous driving following normal sleep, these patients remain more vulnerable to sleep restriction.

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Fatigue/sleepiness is recognised as an important contributory factor in fatal and serious injury road traffic incidents (RTIs), however, identifying fatigue/sleepiness as a causal factor remains an uncertain science. Within Australia attending police officers at a RTI report the causal factors; one option is fatigue/sleepiness. In some Australian jurisdictions police incident databases are subject to post hoc analysis using a proxy definition for fatigue/sleepiness. This secondary analysis identifies further RTIs caused by fatigue/sleepiness not initially identified by attending officers. The current study investigates the efficacy of such proxy definitions for attributing fatigue/sleepiness as a RTI causal factor. Over 1600 Australian drivers were surveyed regarding their experience and involvement in fatigue/sleep-related RTIs and near-misses during the past five years. Driving while fatigued/sleepy had been experienced by the majority of participants (66.0% of participants). Fatigue/sleep-related near misses were reported by 19.1% of participants, with 2.4% being involved in a fatigue/sleep-related RTI. Examination of the characteristics for the most recent event (either a near miss or crash) found that the largest proportion of incidents (28.0%) occurred when commuting to or from work, followed by social activities (25.1%), holiday travel (19.8%), or for work purposes (10.1%). The fatigue/sleep related RTI and near-miss experience of a representative sample of Australian drivers does not reflect the proxy definitions used for fatigue/sleepiness identification. In particular those RTIs that occur in urban areas and at slow speeds may not be identified. While important to have a strategy for identifying fatigue/sleepiness related RTIs proxy measures appear best suited to identifying specific subsets of such RTIs.

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Background The pattern of protein intake following exercise may impact whole-body protein turnover and net protein retention. We determined the effects of different protein feeding strategies on protein metabolism in resistance-trained young men. Methods: Participants were randomly assigned to ingest either 80g of whey protein as 8x10g every 1.5h (PULSE; n=8), 4x20g every 3h (intermediate, INT; n=7), or 2x40g every 6h (BOLUS; n=8) after an acute bout of bilateral knee extension exercise (4x10 repetitions at 80% maximal strength). Whole-body protein turnover (Q), synthesis (S), breakdown (B), and net balance (NB) were measured throughout 12h of recovery by a bolus ingestion of [ 15N]glycine with urinary [15N]ammonia enrichment as the collected end-product. Results PULSE Q rates were greater than BOLUS (?19%, P<0.05) with a trend towards being greater than INT (?9%, P=0.08). Rates of S were 32% and 19% greater and rates of B were 51% and 57% greater for PULSE as compared to INT and BOLUS, respectively (P<0.05), with no difference between INT and BOLUS. There were no statistical differences in NB between groups (P=0.23); however, magnitude-based inferential statistics revealed likely small (mean effect90%CI; 0.590.87) and moderate (0.800.91) increases in NB for PULSE and INT compared to BOLUS and possible small increase (0.421.00) for INT vs. PULSE. Conclusion We conclude that the pattern of ingested protein, and not only the total daily amount, can impact whole-body protein metabolism. Individuals aiming to maximize NB would likely benefit from repeated ingestion of moderate amounts of protein (?20g) at regular intervals (?3h) throughout the day.