975 resultados para EVEN-EVEN NYLONS


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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

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For decades the prevailing idea in B2B marketing has been that buyers are motivated by product/service specifications. Sellers are put on approved supplier lists, invited to respond to RFPs, and are selected on the basis of superior products, at the right price, delivered on time. The history of B2B advertising is filled with the advice “provide product specifications” and your advertising will be noticed, lead to sales inquiries, and eventually result in higher sales. Advertising filled with abstractions might work in the B2C market, but the B2B marketplace is about being literal. What we know about advertising — and particularly the message component of advertising — is based on a combination of experience, unproven ideas and a bit of social science. Over the years, advertising guidelines produced by the predecessors of BMA (National Industrial Advertising Association, Association of Industrial Advertising, and the Business/Professional Advertising Association) stressed emphasizing product features and tangible benefits. The major publishers of B2B magazines, e.g., McGraw-Hill, Penton Publishing, et al. had similar recommendations. Also, B2B marketing books recommend advertising that focuses on specific product features (Kotler and Pfoertsch, 2006; Lamons, 2005). In more recent times, abstraction in advertising messages has penetrated the B2B marketplace. Even though such advertising legends as David Ogilvy (1963, 1985) frequently recommended advertising based on hard-core information, we’ve seen the growing use of emotional appeals, including humor, fear, parental affection, etc. Beyond the use of emotion, marketers attempt to build a stronger connection between their brands and buyers through the use of abstraction and symbolism. Below are two examples of B2B advertisements — Figure 1A is high in literalism and Figure 1B is high in symbolism. Which approach — a “left-brain” (literal) or “right brain” (symbolic) is more effective in B2B advertising? Are the advertising message creation guidelines from the history of B2B advertising accurate? Are the foundations of B2B message creation (experience and unproven ideas) sound?

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The availability of new media as a universal communication tool has an impact on the power of the general public to comment on a variety of issues. This paper examines this increase in consumer power with respect to bloggers. The research context is controversial advertising, and specifically Tourism Australia’s “Where the bloody hell are you?” campaign. By utilising Denegri-Knott’s (2006) four on-line power strategies, a content analysis of weblogs reveals that consumers are distributing information, opinion and even banned advertising material, thereby forming power hubs of like-minded people, with the potential to become online pressure groups. The consequences and implications of this augmented power on regulators, advertisers and bloggers are explored. The findings contribute to the understanding of blogs as a new communication platform and bloggers as a new demographic of activists in the process of advertising.

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This paper examines the effects of an eco-driving message on driver distraction. Two in-vehicle distracter tasks were compared with an eco-driving task and a baseline task in an advanced driving simulator. N = 22 subjects were asked to perform an eco-driving, CD changing, and a navigation task while engaged in critical manoeuvres during which they were expected to respond to a peripheral detection task (PDT) with total duration of 3.5 h. The study involved two sessions over two consecutive days. The results show that drivers’ mental workloads are significantly higher during navigation and CD changing tasks in comparison to the two other scenarios. However, eco-driving mental workload is still marginally significant (p ∼ .05) across different manoeuvres. Similarly, event detection tasks show that drivers miss significantly more events in the navigation and CD changing scenarios in comparison to both the baseline and eco-driving scenario. Analysis of the practice effect shows that drivers’ baseline scenario and navigation scenario exhibit significantly less demand on the second day. Drivers also can detect significantly more events on the second day for all scenarios. The authors conclude that even reading a simple message while driving could potentially lead to missing an important event, especially when executing critical manoeuvres. However, there is some evidence of a practice effect which suggests that future research should focus on performance with habitual rather than novel tasks. It is recommended that sending text as an eco-driving message analogous to the study circumstances should not be delivered to drivers on-line when vehicle is in motion.

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Extreme cold and heat waves, characterised by a number of cold or hot days in succession, place a strain on people’s cardiovascular and respiratory systems. The increase in deaths due to these waves may be greater than that predicted by extreme temperatures alone. We examined cold and heat waves in 99 US cities for 14 years (1987–2000) and investigated how the risk of death depended on the temperature threshold used to define a wave, and a wave’s timing, duration and intensity. We defined cold and heat waves using temperatures above and below cold and heat thresholds for two or more days. We tried five cold thresholds using the first to fifth percentiles of temperature, and five heat thresholds using the ninety-fifth to ninety-ninth percentiles. The extra wave effects were estimated using a two-stage model to ensure that their effects were estimated after removing the general effects of temperature. The increases in deaths associated with cold waves were generally small and not statistically significant, and there was even evidence of a decreased risk during the coldest waves. Heat waves generally increased the risk of death, particularly for the hottest heat threshold. Cold waves of a colder intensity or longer duration were not more dangerous. Cold waves earlier in the cool season were more dangerous, as were heat waves earlier in the warm season. In general there was no increased risk of death during cold waves above the known increased risk associated with cold temperatures. Cold or heat waves earlier in the cool or warm season may be more dangerous because of a build up in the susceptible pool or a lack of preparedness for cold or hot temperatures.

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The purpose of this study was to investigate the effect of very small air gaps (less than 1 mm) on the dosimetry of small photon fields used for stereotactic treatments. Measurements were performed with optically stimulated luminescent dosimeters (OSLDs) for 6 MV photons on a Varian 21iX linear accelerator with a Brainlab μMLC attachment for square field sizes down to 6 mm × 6 mm. Monte Carlo simulations were performed using EGSnrc C++ user code cavity. It was found that the Monte Carlo model used in this study accurately simulated the OSLD measurements on the linear accelerator. For the 6 mm field size, the 0.5 mm air gap upstream to the active area of the OSLD caused a 5.3 % dose reduction relative to a Monte Carlo simulation with no air gap. A hypothetical 0.2 mm air gap caused a dose reduction > 2 %, emphasizing the fact that even the tiniest air gaps can cause a large reduction in measured dose. The negligible effect on an 18 mm field size illustrated that the electronic disequilibrium caused by such small air gaps only affects the dosimetry of the very small fields. When performing small field dosimetry, care must be taken to avoid any air gaps, as can be often present when inserting detectors into solid phantoms. It is recommended that very small field dosimetry is performed in liquid water. When using small photon fields, sub-millimetre air gaps can also affect patient dosimetry if they cannot be spatially resolved on a CT scan. However the effect on the patient is debatable as the dose reduction caused by a 1 mm air gap, starting out at 19% in the first 0.1 mm behind the air gap, decreases to < 5 % after just 2 mm, and electronic equilibrium is fully re-established after just 5 mm.

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Dealing with the aggression of other drivers on the road is an important skill given that driving is a common activity for adults in highly motorised countries. Even though incidents of extreme aggression on the road (such as assault) are reportedly rare, milder forms, some of them dangerous (such as tailgating or deliberately following too closely) are apparently common, and may be increasing. At the very least, this is likely to render the driving environment more stressful, and at worst elevates the risk of crashing by increasing both the level of risky driving behaviours and the likelihood of responses that escalate the situation. Thus the need for drivers to manage incidents of conflict is likely to become increasingly important. However, little research examines how drivers manage their own or others’ aggressive driving behaviour. Recently greater attention has been paid to driver cognitions, especially the attributions that drivers make about other drivers, that then might influence their own driving responses, particularly aggressive or risky ones. The study reported below was the first in a larger exploration of aggressive driving that focussed on driver cognitions, emotions and underlying motivations for aggressive behaviours on the road. Qualitative, in-depth interviews of drivers (n = 30, aged 18-49 years) were subjected to thematic analysis to investigate driver experiences with aggressive driving. Two main themes were identified from these accounts: driver management of self; and driver attempts to influence or manage other drivers. This paper describes the subthemes falling under the management of self main theme. These subthemes were labelled ‘being magnanimous’, ‘chilling out’, ‘slowing down’, and ‘apology/acknowledgment’. ‘Being magnanimous’ referred to situations where the respondent perceived him/herself to be a recipient of another’s aggressive driving and made a deliberate choice not to respond. However, a characteristic of this sub-theme was that this choice was underpinned by the adoption of morally superior stance, or sense of magnanimity. ‘Chilling out’ was a more general response to both the milder aggressive behaviours of other drivers and the general frustrations of driving. ‘Slowing down’ referred to reducing one’s speed in response to the perceived aggressive driving, often tailgating, of another. This subtheme appeared to consist of two separate underlying motivations. One of these was a genuine concern for one’s own safety while the other was more aimed at “getting back” at the other driver. ‘Apology’ referred to how drivers modified their more negative reactions and responses when another driver made gestures that acknowledged their having made a mistake, indicated an apology, or acknowledged the recipient driver. These sub-themes are discussed in relation to their implications for understanding aggressive driving and intervening to reduce it.

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We examine the solution of the two-dimensional Cahn-Hilliard-reaction (CHR) equation in the xy plane as a model of Li+ intercalation into LiFePO4 material. We validate our numerical solution against the solution of the depth-averaged equation, which has been used to model intercalation in the limit of highly orthotropic diffusivity and gradient penalty tensors. We then examine the phase-change behaviour in the full CHR system as these parameters become more isotropic, and find that as the Li+ diffusivity is increased in the x direction, phase separation persists at high currents, even in small crystals with averaged coherency strain included. The resulting voltage curves decrease monotonically, which has previously been considered a hallmark of crystals that fill homogeneously.

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Our aim is to develop a set of leading performance indicators to enable managers of large projects to forecast during project execution how various stakeholders will perceive success months or even years into the operation of the output. Large projects have many stakeholders who have different objectives for the project, its output, and the business objectives they will deliver. The output of a large project may have a lifetime that lasts for years, or even decades, and ultimate impacts that go beyond its immediate operation. How different stakeholders perceive success can change with time, and so the project manager needs leading performance indicators that go beyond the traditional triple constraint to forecast how key stakeholders will perceive success months or even years later. In this article, we develop a model for project success that identifies how project stakeholders might perceive success in the months and years following a project. We identify success or failure factors that will facilitate or mitigate against achievement of those success criteria, and a set of potential leading performance indicators that forecast how stakeholders will perceive success during the life of the project's output. We conducted a scale development study with 152 managers of large projects and identified two project success factor scales and seven stakeholder satisfaction scales that can be used by project managers to predict stakeholder satisfaction on projects and so may be used by the managers of large projects for the basis of project control.

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It is well recognised that there are serious correlates for victims of traditional bullying. These have been shown to include increased levels of depression, anxiety and psychosomatic symptoms, in addition to often severe physical harm and even suicide. Bullied students also feel more socially ineffective; have greater interpersonal difficulties, together with higher absenteeism from school and lower academic competence. In the emerging field of cyberbullying many researchers have hypothesised a greater impact and more severe consequences for victims because of the 24/7 nature and the possibility of the wider audience with this form of bullying. However, to date there is scarce empirical evidence to support this. This study sought to compare victims’ perceptions of the harshness and impact of bullying by traditional and cyber means. The major findings showed that although students who had been victimised by traditional bullying reported that they felt their bullying was harsher, crueller and had more impact on their lives than those students who had been cyberbullied, the correlates of their mental health revealed that cyber victims reported significantly more social difficulties, higher anxiety levels and depression than traditional victims. The implications for school counsellors and mental health workers are discussed.

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Dhaka, the capital of Bangladesh, is facing severe traffic congestion. Owing to the flaws in past land use and transport planning decisions, uncontrolled population growth and urbanization, Dhaka’s traffic condition is worsening. Road space is widely regarded in the literature as a utility, so a common view of transport economists is that its usage ought to be charged. Road pricing policy has proven to be effective in managing travel demand, in order to reduce traffic congestion from road networks in a number of cities including London, Stockholm and Singapore. Road pricing as an economic mechanism to manage travel demand can be more effective and user-friendly when revenue is hypothecated into supply alternatives such as improvements to the transit system. This research investigates the feasibility of adopting road pricing in Dhaka with respect to a significant Bus Rapid Transit (BRT) project. Because both are very new concepts for the population of Dhaka, public acceptability would be a principal issue driving their success or failure. This paper explores the travel behaviour of workers in Dhaka and public perception toward Road Pricing with regards to work trips- based on worker’s travel behaviour. A revealed preference and stated preference survey has been conducted on sample of workers in Dhaka. They were asked limited demographic questions, their current travel behaviour and at the end they had been given several hypothetical choices of integrated BRT and road pricing to choose from. Key finding from the survey is the objective of integrated road pricing; subsidies Bus rapid Transit by road pricing to get reduced BRT fare; cannot be achieved in Dhaka. This is because most of the respondent stated that they would choose the cheapest option Walk-BRT-Walk, even though this would be more time consuming and uncomfortable as they have to walk from home to BRT station and also from BRT station to home. Proper economic analysis has to be carried out to find out the appropriate fare of BRT and road charge with some incentive for the low income people.

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The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

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Addictive drugs can activate systems involved in normal reward-related learning, creating long-lasting memories of the drug's reinforcing effects and the environmental cues surrounding the experience. These memories significantly contribute to the maintenance of compulsive drug use as well as cue-induced relapse which can occur even after long periods of abstinence. Synaptic plasticity is thought to be a prominent molecular mechanism underlying drug-induced learning and memories. Ethanol and nicotine are both widely abused drugs that share a common molecular target in the brain, the neuronal nicotinic acetylcholine receptors (nAChRs). The nAChRs are ligand-gated ion channels that are vastly distributed throughout the brain and play a key role in synaptic neurotransmission. In this review, we will delineate the role of nAChRs in the development of ethanol and nicotine addiction. We will characterize both ethanol and nicotine's effects on nAChR-mediated synaptic transmission and plasticity in several key brain areas that are important for addiction. Finally, we will discuss some of the behavioral outcomes of drug-induced synaptic plasticity in animal models. An understanding of the molecular and cellular changes that occur following administration of ethanol and nicotine will lead to better therapeutic strategies.

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Pressure from study has long been identified as a significant contributor to many mental health problems in school children and adolescents. Students are often stressed by heavy workload, high academic expectation and dissatisfaction with their grades. Excessive amount of this special type of stress (academic stress or educational stress) may then lead to severe psychological symptoms, such as depressed mood, anxious feelings and even suicide thoughts and acts when coping recourses are exhausted. Chinese students are believed to have high academic burden and pressure due to high expectations of their parents and fierce competitions with their peers. Knowledge of the nature and health effects of academic stress may be useful to inform quality education and mental health promotions. This review aims to provide a comprehensive analysis of reported literature regarding educational stress and its relationships with mental health problems worldwide and the current research progress in Chinese adolescents, and to provide directions for future research into this topic in Chinese adolescent populations.

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Grandiflora: Recent Paintings by Daniel Mafe The paintings of Grandiflora are improvised around a range of different flower motifs culled from medieval textiles and botanical illustrations. Each of the paintings is constructed upon a ground of flat, palely luminous yellow occasionally supplemented by additional areas of high-keyed pastel. Pink, blue, green and mauve together with the yellow, generate a shimmering and even incandescent glow. The graphic images of the flowers with the flat colour areas are then contrasted and worked over with richly sensual, abstract gestures of paint. Within the work there is a pronounced almost rococo-esque opticality as it operates between these different visual codes of flat colour, recognizable floral forms, and gesture. These codes combine to produce a definite visceral impact on the viewer, a pronounced and tactile sense of the experience and ambiguity inherent in perceiving. This ambiguity is interestingly at odds with the apparently clean and crisp quality each painting demonstrates as an integrated whole. Indeed each piece goes on to reveal, despite the use of overt figurative quotations, a sense of the purely abstract which in its turn concretely establishes the ornamental.