603 resultados para allelopathic activity


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Based on unique news data relating to gold and crude oil, we investigate how news volume and sentiment, shocks in trading activity, market depth and trader positions unrelated to information flow covary with realized volatility. Positive shocks to the rate of news arrival, and negative shocks to news sentiment exhibit the largest effects. After controlling for the level of news flow and cross-correlations, net trader positions play only a minor role. These findings are at odds with those of [Wang (2002a). The Journal of Futures Markets, 22, 427–450; Wang (2002b). The Financial Review, 37, 295–316], but are consistent with the previous literature which doesn't find a strong link between volatility and trader positions.

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This study examined patients’ preference ratings for receiving support via remote communication to increase their lifestyle physical activity. Methods People with musculoskeletal disorders ( n=221 of 296 eligible) accessing one of three clinics provided preference ratings for “how much” they wanted to receive physical activity support via five potential communication modalities. The five ratings were generated on a horizontal analogue rating scale (0 represented “not at all”; 10 represented “very much”). Results Most (n=155, 70%) desired referral to a physical activity promoting intervention. “Print and post” communications had the highest median preference rating (7/10), followed by email and telephone (both 5/10), text messaging (1/10), and private Internet-based social network messages (0/10). Desire to be referred was associated with higher preference for printed materials (coefficient = 2.739, p<0.001), telephone calls (coefficient = 3.000, p<0.001), and email (coefficient = 2.059, p=0.02). Older age was associated with lower preference for email (coefficient = −0.100, p<0.001), texting (coefficient = −0.096, p<0.001), and social network messages (coefficient = −0.065, p<0.001). Conclusion Patients desiring support to be physically active indicated preferences for interventions with communication via print, email, or telephone calls.

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It has been argued that transition points in life, such as the approach towards, and early years of retirement present key opportunities for interventions to improve the health of the population. Research has also highlighted inequalities in health status in the retired population and in response to interventions which should be addressed. We aimed to conduct a systematic review to synthesise international evidence on the types and effectiveness of interventions to increase physical activity among people around the time of retirement. A systematic review of literature was carried out between February 2014 and April 2015. Searches were not limited by language or location, but were restricted by date to studies published from 1990 onwards. Methods for identification of relevant studies included electronic database searching, reference list checking, and citation searching. Systematic search of the literature identified 104 papers which described study populations as being older adults. However, we found only one paper which specifically referred to their participants as being around the time of retirement. The intervention approaches for older adults encompassed: training of health care professionals; counselling and advice giving; group sessions; individual training sessions; in-home exercise programmes; in-home computer-delivered programmes; in-home telephone support; in-home diet and exercise programmes; and community-wide initiatives. The majority of papers reported some intervention effect, with evidence of positive outcomes for all types of programmes. A wide range of different measures were used to evaluate effectiveness, many were self-reported and few studies included evaluation of sedentary time. While the retirement transition is considered a significant point of life change, little research has been conducted to assess whether physical activity interventions at this time may be effective in promoting or maintaining activity, or reducing health inequalities. We were unable to find any evidence that the transition to retirement period was, or was not a significant point for intervention. Studies in older adults more generally indicated that a range of interventions might be effective for people around retirement age.

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This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

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This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

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Physical activity (PA) is essential for human health and wellbeing across all age, socioeconomic and ethnic groups. Engagement with the natural world is a new defining criterion for enhancing the benefits of PA particularly for children and young people. Interacting with nature benefits children’s social and emotional wellbeing, develops resilience and reduces the risk of obesity and type 2 diabetes across all population groups. Governments around the world are now recognising the importance of children spending more active time outdoors. However, children’s outdoor activities, free play and nature-related exploration are often structured and supervised by adults due to safety concerns and risks. In this context schools become more accessible and safe options for children to engage in PA outdoors with the presence of nature features. Research on school designs involving young children has revealed that children prefer nature-related features in school environments. Affordances in nature may increase children’s interest in physically active behaviours. Given that present school campuses are designed for operational efficiency and economic reasons there is a need to re-design schools responding to the positive role of nature on human health. If schools were re-designed to incorporate diverse natural features children’s PA and consequent health and wellbeing would likely improve markedly.

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In order to understand student engagement in higher education through the use of digital technologies, it is necessary to appreciate the broader use of differing technologies. Forty-eight first-year university students completed an online survey that queried patterns of digital activity across home, school and community contexts and that included rating scale items that measured learning style (i.e., active-reflective, sensing-intuitive, visual-verbal, sequential-global). Results suggest that students vary widely in digital activities and that such variation is related to differences in learning style. For example, active learners were more likely than reflective learners to engage in digital activities in the community and users of some specific application, as opposed to non-users, were more likely to be verbal than visual learners. Implications for instructional applications of digital technology in higher education are presented.

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A number of analogues of diaryl dihydropyrazole-3-carboxamides have been synthesized. Their activities were evaluated for appetite suppression and body weight reduction in animal models. Depending on the chemical modification of the selected dihydropyrazole scaffold, the lead compoundsthe bisulfate salt of (±)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 26 and the bisulfate salt of (−)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 30showed significant body weight reduction in vivo, which is attributed to their CB1 antagonistic activity and exhibited a favorable pharmacokinetic profile. The molecular modeling studies also showed interactions of two isomers of (±)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 9 with CB1 receptor in the homology model similar to those of N-piperidino-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-3-pyrazole-carboxamide (rimonabant) 1 and 4S-(−)-3-(4-chlorophenyl)-N-methyl-N‘-[(4-chlorophenyl)-sulfonyl]-4-phenyl-4,5-dihydro-1H-pyrazole-1-carboxamidine (SLV-319) 2.

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CD1d-restricted natural killer T (NKT) cells expressing invariant Valpha14Jalpha18 T cell receptor alpha-chains are abundant in murine liver and are implicated in the control of malignancy, infection and autoimmunity. Invariant NKT cells have potent anti-metastatic effects in mice and phase I clinical trials involving their homologues in humans are ongoing. However, invariant NKT cells are less abundant in human liver ( approximately 0.5% of hepatic T cells) than in murine liver (up to 50%) and it is not known if other hepatic T cells are CD1-restricted. We have examined expression of CD1a, CD1b, CD1c and CD1d mRNA and protein in human liver and evaluated the reactivity of mononuclear cells (MNC) from histologically normal and tumour-bearing human liver specimens against these CD1 isoforms. Messenger RNA for all CD1 isotypes was detectable in all liver samples. CD1c and CD1d were expressed at the protein level by hepatic MNC. CD1d, only, was detectable at the cell surface, but CD1c and CD1d were found at an intracellular location in significant numbers of liver MNC. CD1b was not expressed by MNC from healthy livers but was detectable within MNC in all tumour samples tested. Hepatic T cells exhibited reactivity against C1R cells expressing transfected CD1c and CD1d, but neither CD1a nor CD1b. These cells secreted interferon-gamma (IFN-gamma) but not interleukin-4 (IL-4) upon stimulation. In contrast, similar numbers of peripheral T cells released 13- and 16-fold less IFN-gamma in response to CD1c and CD1d, respectively. CD1c and CD1d expression and T cell reactivity were not altered in tumour-bearing liver specimens compared to histologically normal livers. These data suggest that, in addition to invariant CD1d-restricted NKT cells, autoreactive T cells that recognise CD1c and CD1d and release inflammatory cytokines are abundant in human liver.

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Many conventional statistical machine learning al- gorithms generalise poorly if distribution bias ex- ists in the datasets. For example, distribution bias arises in the context of domain generalisation, where knowledge acquired from multiple source domains need to be used in a previously unseen target domains. We propose Elliptical Summary Randomisation (ESRand), an efficient domain generalisation approach that comprises of a randomised kernel and elliptical data summarisation. ESRand learns a domain interdependent projection to a la- tent subspace that minimises the existing biases to the data while maintaining the functional relationship between domains. In the latent subspace, ellipsoidal summaries replace the samples to enhance the generalisation by further removing bias and noise in the data. Moreover, the summarisation enables large-scale data processing by significantly reducing the size of the data. Through comprehensive analysis, we show that our subspace-based approach outperforms state-of-the-art results on several activity recognition benchmark datasets, while keeping the computational complexity significantly low.

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Objectives This efficacy study assessed the added impact real time computer prompts had on a participatory approach to reduce occupational sedentary exposure and increase physical activity. Design Quasi-experimental. Methods 57 Australian office workers (mean [SD]; age = 47 [11] years; BMI = 28 [5] kg/m2; 46 men) generated a menu of 20 occupational ‘sit less and move more’ strategies through participatory workshops, and were then tasked with implementing strategies for five months (July–November 2014). During implementation, a sub-sample of workers (n = 24) used a chair sensor/software package (Sitting Pad) that gave real time prompts to interrupt desk sitting. Baseline and intervention sedentary behaviour and physical activity (GENEActiv accelerometer; mean work time percentages), and minutes spent sitting at desks (Sitting Pad; mean total time and longest bout) were compared between non-prompt and prompt workers using a two-way ANOVA. Results Workers spent close to three quarters of their work time sedentary, mostly sitting at desks (mean [SD]; total desk sitting time = 371 [71] min/day; longest bout spent desk sitting = 104 [43] min/day). Intervention effects were four times greater in workers who used real time computer prompts (8% decrease in work time sedentary behaviour and increase in light intensity physical activity; p < 0.01). Respective mean differences between baseline and intervention total time spent sitting at desks, and the longest bout spent desk sitting, were 23 and 32 min/day lower in prompt than in non-prompt workers (p < 0.01). Conclusions In this sample of office workers, real time computer prompts facilitated the impact of a participatory approach on reductions in occupational sedentary exposure, and increases in physical activity.

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Background The most common pathway to development of diabetes foot ulcers is repetitive daily activity stress on the plantar surface of the neuropathic foot. Studies suggest an association between different diabetic foot complications and physical activity. However, to the best of the authors knowledge the steps/day and sleep patterns of people with diabetic foot ulcers has yet to be investigated. This observational study aims to investigate the physical activity and sleep patterns of three groups of adults with type 2 diabetes and different foot complications Methods Participants with type 2 diabetes were recruited into three groups: 1. those with no reported foot complications (DNIL), 2. those with diagnosis of neuropathy (DPN) and 3. those with a neuropathic ulcer (DFU). Exclusion criteria included peripheral arterial disease and mobility aid use. Participants wore a SenseWear Pro 3 Armband continuously for 7 days and completed an Epworth Sleepiness Scale. The Armband is a validated automated measure of activity (walking steps, average Metabolic Equivalent Task (MET), physical activity (>3 METs) duration), energy expenditure(kJ) (total and physical activity (>3 METs)) and sleep (duration). Data on age, sex, BMI, diabetes duration and HbA1c were also collected. Results Sixty-Six (14 DNIL, 22 DPN and 30 DFU's participants were recruited; 71% males, mean age 61(±12) years, diabetes duration 13(±9) years, HbA1c 8.3(±2.8), BMI 32.6(±5.9), average METs 1.2(0.2). Significant differences were reported in mean(SD) steps/day (5,859(±2,381) in DNIL; 5,007(±3,349) in DPN and 3,271(±2,417) in DFU's and daily energy expenditure (10,868(±1,307)kJ in DNIL; 11,060(±1,916)kJ in DPN and 13,006(± 3,559) in DFU's(p <0.05). No significant differences were reported for average METs, physical activity duration or energy expenditure, sleep time or Epworth score (p>0.1). Conclusions Preliminary findings suggest people with diabetes are sedentary. Results indicate that patients with a diabetic foot ulcer work significantly less than those with neuropathy or nil complications and use significantly more energy to do so. Sleep Parameters showed no differences. Recruitment is still on going.

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The current study sought to identify the impact of whether teammates in a cooperative videogame were controlled by other humans (avatars) or by the game (agents). The impact on player experience was explored through both subjective questionnaire measures and brain wave activity measurement (electroencephalography). Play with human teammates was associated with a greater sense of relatedness, but less competence and flow than play with other computer-controlled teammates. In terms of brain activity, play with human teammates was associated with greater activity in the alpha, theta and beta power bands than play with computer-controlled teammates. Overall, the results suggest that play with human teammates involves greater cognitive activity in terms of 'mentalising' than play with computer-controlled teammates. Additionally, the associations between subjective measures of player experience and brain activity are described. Limitations of the current study are identified and key directions for future research are discussed.

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The US Surgeon General's report was a landmark publication in the field of physical activity and health, but was constrained by a lack of evidence relating to women. This report examines the links between physical activity and health in mid-age and older women. It includes four parts (i)recent evidence relating physical activity to the national public health priorities and reproductive health (ii)consideration of the amount of physical activity required to obtain health benefits (iii)new data from the Australian Longitudinal Study on Women's Health on activity patterns, including relationships between changes in physical activity and life events, sociodemographic characteristics and health behaviours in mid-age and older Australian women (iv)new data from the Australian Longitudinal Study on Women's Health on the relationships between physical activity and menopausal symptoms, stiff or painful joints and arthritis, anxiety and depression, memory problems, falls and fractures, general physical and psychological well-being, and healthcare costs in mid-age and older Australian women

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Issue addressed: Previous research has shown that approximately 60% of nurses in Australia are overweight or obese, insufficiently active and have an unhealthy diet. The aim of this study was to gain an understanding of nurses’ determinants contributing to these behaviours. This will inform a needs assessment for a future workplace health promotion program (WHPP) in this group. Methods: Four focus group discussions (n = 17) were conducted with a convenience sample of nurses aged 25–59 years from three hospitals in the Brisbane metropolitan area. Questions addressed barriers and motivation towards diet and physical activity (PA), and suggestions for future WHPP. Data were analysed with Nvivo10 following a thematic analysis with a realistic approach using Self-determination theory as a framework. Results: Work environment was the main barrier for healthy diet behaviours. Long working hours and lack of breaks challenged nurses’ self-control and self-regulation when making dietary choices. Fatigue was the main barrier for PA. However, relaxation, feeling energised before work and better sleep after working night shifts motivated nurses to do PA. Social environment at work seemed to be an effective external motivation to encourage healthy diet and regular PA. Goal-setting, self-monitoring and social support at work were identified as potential WHHP strategies. Conclusion: The workplace and job demands negatively impacts nurses’ lifestyle behaviours. Future interventions should include social support from colleagues, which could motivate nurses to make healthier food choices at work and be more active outside work.