990 resultados para Event Characteristics
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Objective The main aim of the present study was to identify food consumption in Sri Lankan adults based on serving characteristics. Design Cross-sectional study. Fruits, vegetables, starch, meat, pulses, dairy products and added sugars in the diet were assessed with portion sizes estimated using standard methods. Setting Twelve randomly selected clusters from the Sri Lanka Diabetes and Cardiovascular Study. Subjects Six hundred non-institutionalized adults. Results The daily intake of fruit (0·43), vegetable (1·73) and dairy (0·39) portions were well below national recommendations. Only 3·5 % of adults consumed the recommended 5 portions of fruits and vegetables/d; over a third of the population consumed no dairy products and fewer than 1 % of adults consumed 2 portions/d. In contrast, Sri Lankan adults consumed over 14 portions of starch and 3·5 portions of added sugars daily. Almost 70 % of those studied exceeded the upper limit of the recommendations for starch intake. The total daily number of meat and pulse portions was 2·78. Conclusions Dietary guidelines emphasize the importance of a balanced and varied diet; however, a substantial proportion of the Sri Lankan population studied failed to achieve such a recommendation. Nutrition-related diseases in the country may be closely correlated with unhealthy eating habits.
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Building prefabrication is known as Industrialised Building Systems (IBS) in Malaysia. This construction method possesses unique characteristics that are central to sustainable construction. For example, offsite construction enables efficient management of construction wastage by identifying major causes of waste arising during both the design and construction stages. These causes may then be eliminated by the improvement process in IBS component's manufacturing. However, current decisions on using IBS are typically financial driven and hinder the wider ranged adoption. In addition, current IBS misconceptions and the failure of rating schemes in evaluating the sustainability of IBS affect its implementation. A new approach is required to provide better understanding on the sustainability potential of IBS among stakeholders. Such approach should also help project the outcomes of each levels of decision-making to respond to social, economy and environmental challenges. This paper presents interim findings of research aimed at developing a framework for sustainable IBS development and suggests a more holistic approach to achieve sustainability. A framework of embedding sustainability factors is considered in three main phases of IBS construction; 1) Pre-construction, 2) Construction and 3) Post-construction phase. SWOT analysis was used to evaluate the strengths, weaknesses, opportunities and threats involved in the IBS implementations. The action plans are formulated from the analysis of sustainable objectives. This approach will show where and how sustainability should be integrated to improve IBS construction. A mix of quantitative and qualitative methodology was used in this research to explore the potential of IBS in integrating sustainability. The tools used in the study are questionnaires and semi-structured interviews. Outcomes from these tools lead to the identification of viable approaches involving 18 critical factors to improve sustainability in IBS constructions. Finally, guidelines for decision-making are being developed to provide a useful source of information and support to mutual benefit of the stakeholders in integrating sustainability issues and concepts into IBS applications.
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Men aged 50 years or older are at high risk of melanoma, and both incidence and mortality are increasing in this group1. Skin self-examination (SSE) could be one avenue to improve outcomes from melanoma. Several recent intervention trials successfully increased SSE, but resistance to such interventions is less well studied. This posthoc secondary analysis of interventional study data aimed to identify characteristics of older men who did not take up SSE for the early signs of skin cancer, despite exposure to educational materials during a randomized intervention trial
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During a major flood event, the inundation of urban environments leads to some complicated flow motion most often associated with significant sediment fluxes. In the present study, a series of field measurements were conducted in an inundated section of the City of Brisbane (Australia) about the peak of a major flood in January 2011. Some experiments were performed to use ADV backscatter amplitude as a surrogate estimate of the suspended sediment concentration (SSC) during the flood event. The flood water deposit samples were predominantly silty material with a median particle size about 25 μm and they exhibited a non-Newtonian behavior under rheological testing. In the inundated urban environment during the flood, estimates of suspended sediment concentration presented a general trend with increasing SSC for decreasing water depth. The suspended sediment flux data showed some substantial sediment flux amplitudes consistent with the murky appearance of floodwaters. Altogether the results highlighted the large suspended sediment loads and fluctuations in the inundated urban setting associated possibly with a non-Newtonian behavior. During the receding flood, some unusual long-period oscillations were observed (periods about 18 min), although the cause of these oscillations remains unknown. The field deployment was conducted in challenging conditions highlighting a number of practical issues during a natural disaster.
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This article investigates the role of information communication technologies (ICTs) in establishing a well-aligned, authentic learning environment for a diverse cohort of non-cognate and cognate students studying event management in a higher education context. Based on a case study which examined the way ICTs assisted in accommodating diverse learning needs, styles and stages in an event management subject offered in the Creative Industries Faculty at Queensland University of Technology in Brisbane, Australia, the article uses an action research approach to generate grounded, empirical data on the effectiveness of the dynamic, individualised curriculum frameworks that the use of ICTs makes possible. The study provides insights into the way non-cognate and cognate students respond to different learning tools. It finds that whilst non-cognate and cognate students do respond to learning tools differently, due to a differing degree of emphasis on technical, task or theoretical competencies, the use of ICTs allows all students to improve their performance by providing multiple points of entry into the content. In this respect, whilst the article focuses on the way ICTs can be used to develop an authentic, well-aligned curriculum model that meets the needs of event management students in a higher education context, with findings relevant for event educators in Business, Hospitality, Tourism and Creative Industries, the strategies outlined may also be useful for educators in other fields who are faced with similar challenges when designing and developing curriculum for diverse cohorts.
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Performance of a constructed wetland is commonly reported as variable due to the site specific nature of influential factors. This paper discusses outcomes from an in-depth study which characterised treatment performance of a wetland based on the variation in runoff regime. The study included a comprehensive field monitoring of a well established constructed wetland in Gold Coast, Australia. Samples collected at the inlet and outlet was tested for Total Suspended Solids (TSS), Total Nitrogen (TN) and Total Phosphorus (TP). Pollutant concentrations in the outflow were found to be consistent irrespective of the variation in inflow water quality. The analysis revealed two different treatment characteristics for events with different rainfall depths. TSS and TN load reduction is strongly influenced by hydraulic retention time where performance is higher for rainfall events below the design event. For small events, treatment performance is higher at the beginning of the event and gradually decreased during the course of the event. For large events, the treatment performance is comparatively poor at the beginning and improved during the course of the event. The analysis also confirmed the variable treatment trends for different pollutant types.
Performance of elite seated discus throwers in F30s classes : part II: does feet positioning matter?
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Background: Studies on the relationship between performance and design of the throwing frame have been limited. Part I provided only a description of the whole body positioning. Objectives: The specific objectives were (a) to benchmark feet positioning characteristics (i.e. position, spacing and orientation) and (b) to investigate the relationship between performance and these characteristics for male seated discus throwers in F30s classes. Study Design: Descriptive analysis. Methods: A total of 48 attempts performed by 12 stationary discus throwers in F33 and F34 classes during seated discus throwing event of 2002 International Paralympic Committee Athletics World Championships were analysed in this study. Feet positioning was characterised by tridimensional data of the front and back feet position as well as spacing and orientation corresponding to the distance between and the angle made by both feet, respectively. Results: Only 4 of 30 feet positioning characteristics presented a coefficient correlation superior to 0.5, including the feet spacing on mediolateral and anteroposterior axes in F34 class as well as the back foot position and feet spacing on mediolateral axis in F33 class. Conclusions: This study provided key information for a better understanding of the interaction between throwing technique of elite seated throwers and their throwing frame.
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Articular cartilage defects are common after joint injuries. When left untreated, the biomechanical protective function of cartilage is gradually lost, making the joint more susceptible to further damage, causing progressive loss of joint function and eventually osteoarthritis (OA). In the process of translating promising tissue-engineering cartilage repair approaches from bench to bedside, pre-clinical animal models including mice, rabbits, goats, and horses, are widely used. The equine species is becoming an increasingly popular model for the in vivo evaluation of regenerative orthopaedic approaches. As there is also an increasing body of evidence suggesting that successful lasting tissue reconstruction requires an implant that mimics natural tissue organization, it is imperative that depth-dependent characteristics of equine osteochondral tissue are known, to assess to what extent they resemble those in humans. Therefore, osteochondral cores (4-8 mm) were obtained from the medial and lateral femoral condyles of equine and human donors. Cores were processed for histology and for biochemical quantification of DNA, glycosaminoglycan (GAG) and collagen content. Equine and human osteochondral tissues possess similar geometrical (thickness) and organizational (GAG, collagen and DNA distribution with depth) features. These comparable trends further underscore the validity of the equine model for the evaluation of regenerative approaches for articular cartilage.
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Molecular dynamics simulations were carried out on single chain models of linear low-density polyethylene in vacuum to study the effects of branch length, branch content, and branch distribution on the polymer’s crystalline structure at 300 K. The trans/gauche (t/g) ratios of the backbones of the modeled molecules were calculated and utilized to characterize their degree of crystallinity. The results show that the t/g ratio decreases with increasing branch content regardless of branch length and branch distribution, indicating that branch content is the key molecular parameter that controls the degree of crystallinity. Although t/g ratios of the models with the same branch content vary, they are of secondary importance. However, our data suggests that branch distribution (regular or random) has a significant effect on the degree of crystallinity for models containing 10 hexyl branches/1,000 backbone carbons. The fractions of branches that resided in the equilibrium crystalline structures of the models were also calculated. On average, 9.8% and 2.5% of the branches were found in the crystallites of the molecules with ethyl and hexyl branches while C13 NMR experiments showed that the respective probabilities of branch inclusion for ethyl and hexyl branches are 10% and 6% [Hosoda et al., Polymer 1990, 31, 1999–2005]. However, the degree of branch inclusion seems to be insensitive to the branch content and branch distribution.
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Cold-formed steel members are increasingly used as primary structural elements in the building industries around the world due to the availability of thin and high strength steels and advanced cold-forming technologies. Cold-formed lipped channel beams (LCB) are commonly used as flexural members such as floor joists and bearers. However, their shear capacities are determined based on conservative design rules. For the shear design of LCB web panels, their elastic shear buckling strength must be determined accurately including the potential post-buckling strength. Currently the elastic shear buckling coefficients of LCB web panels are determined by assuming conservatively that the web panels are simply supported at the junction between their flange and web elements. Hence finite element analyses were conducted to investigate the elastic shear buckling behavior of LCBs. An improved equation for the higher elastic shear buckling coefficient of LCBs was proposed based on finite element analysis results and included in the ultimate shear capacity equations of the North American cold-formed steel codes. Finite element analyses show that relatively short span LCBs without flange restraints are subjected to a new combined shear and flange distortion action due to the unbalanced shear flow. They also show that significant post-buckling strength is available for LCBs subjected to shear. New equations were also proposed in which post-buckling strength of LCBs was included.
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This paper develops and applies a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage detection in slab-on-girder bridges. The proposed procedure is first validated through experimental testing of a model bridge. Numerically simulated modal data obtained through finite element analyses are then used to evaluate the vibration parameters before and after damage and used as the indices for assessment of the state of structural health. The procedure is illustrated by its application to full scale slab-on-girder bridges under different damage scenarios involving single and multiple damages on the deck and girders.
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Purpose: The recognition of breast cancer as a spectrum tumor in Lynch syndrome remains controversial. The aim of this study was to explore features of breast cancers arising in Lynch syndrome families. Experimental Design: This observational study involved 107 cases of breast cancer identified from the Colorectal Cancer Family Registry (Colon CFR) from 90 families in which (a) both breast and colon cancer co-occurred, (b) families met either modified Amsterdam criteria, or had at least one early-onset (<50 years) colorectal cancer, and (c) breast tissue was available within the biospecimen repository for mismatch repair (MMR) testing. Eligibility criteria for enrollment in the Colon CFR are available online. Breast cancers were reviewed by one pathologist. Tumor sections were stained for MLH1, PMS2, MSH2, and MSH6, and underwent microsatellite instability testing. Results: Breast cancer arose in 35 mutation carriers, and of these, 18 (51%) showed immunohistochemical absence of MMR protein corresponding to the MMR gene mutation segregating the family. MMR-deficient breast cancers were more likely to be poorly differentiated (P = 0.005) with a high mitotic index (P = 0.002), steroid hormone receptor–negative (estrogen receptor, P = 0.031; progesterone receptor, P = 0.022), and to have peritumoral lymphocytes (P = 0.015), confluent necrosis (P = 0.002), and growth in solid sheets (P < 0.001) similar to their colorectal counterparts. No difference in age of onset was noted between the MMR-deficient and MMR-intact groups. Conclusions: MMR deficiency was identified in 51% of breast cancers arising in known mutation carriers. Breast cancer therefore may represent a valid tissue option for the detection of MMR deficiency in which spectrum tumors are lacking
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The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.
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The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.