164 resultados para Fast-day sermons.


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In this paper, we derive a new nonlinear two-sided space-fractional diffusion equation with variable coefficients from the fractional Fick’s law. A semi-implicit difference method (SIDM) for this equation is proposed. The stability and convergence of the SIDM are discussed. For the implementation, we develop a fast accurate iterative method for the SIDM by decomposing the dense coefficient matrix into a combination of Toeplitz-like matrices. This fast iterative method significantly reduces the storage requirement of O(n2)O(n2) and computational cost of O(n3)O(n3) down to n and O(nlogn)O(nlogn), where n is the number of grid points. The method retains the same accuracy as the underlying SIDM solved with Gaussian elimination. Finally, some numerical results are shown to verify the accuracy and efficiency of the new method.

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Global climate change will affect all domains of person-environment relations. Tackling climate change will require social change that can be motivated by people’s imaginings of the future of their society where such social change has occurred. We use the “collective futures” framework to examine whether beliefs about the future of society are related to present-day intentions to take climate change action. Participants from two Brazilian samples imagined their society in 2050 where climate change was mitigated and then rated how this future society would differ from Brazilian society today in terms of societal-level dysfunction and development and personal-level traits and values. To the extent that participants believed preventing climate change would result in societal development and more competence traits, they were more willing to engage in environmental citizenship activities. Individual differences in future time perspective also impacted environmental citizenship intention. Societal development and consideration of future consequences seem to be distinct routes by which future thinking influence climate change action.

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Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

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Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

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The purpose of this study was to identify the factors that influence managers to take advantage of coachable moments in day-to-day management. Interviews with ten managers found that time, skills, and relationships were key factors considered by managers, but that these were considered within the context of potential “risk” to the manager. This paper elaborates on these findings and makes recommendations for further research into how managers consciously assess the risks associated with coaching, in order to decide whether to take advantage of an informal coaching opportunity.

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Purpose The purpose of this paper is to explore what the attitudes of small firm owner-managers are to developing the skills of their key resources and then examine how these and other factors affect owner-managers’ preferences for training these employees. Design/methodology/approach This study of training in small road transport firms in West Australia is cast in light of the literature on human resource management in small firms underpinned by insights drawn using the resource based view of the firm. Small firms (less than 20 people) dominate this industry, while the increasing freight task, and extreme distances between West Australian ports, towns and mines highlight this sectors’ importance. Survey results from 39 small road transport firms and interviews with nine owner-managers are analysed. Findings Legislative, regulatory and licensing requirements were shown to be a key determinant of skills development. Employers ensured that basic standards for employee certification and qualification were met, as the penalty for not doing so would be too high. Regulations drove the need for certain types of training – licenses, fatigue management, occupational health and safety, handling dangerous goods, the Maritime Security Identification Card card, forklift license, mine site inductions – while owner-managers knew where to get the training their staff needed. Although regulation appeared most visible in prescribing what happened in relation to training for drivers, the relevance of owner-managers’ attitudes could not be ignored, nor could conditions in the firms external environment as this shaped how these requirements were met. Research limitations/implications The RBV is useful in showing how skill development enabled similarity in skills across firms, while the attitudes owner-managers and economic and social conditions meant what happened in firms around skill development varied. The importance of small firm owner-managers’ attitudes are clearly highlighted and shown to influence organizational decisions and choices around training, but these were not independent of the regulatory framework and the economic and social conditions within which the firm operated. The small firms in this study did engage workers in formal training when necessary but it was put in the context of the idiosyncratic approach of the owner-manager and the day-to-day needs of the firm. “Training” was essentially about ensuring certain types of skills were held by employees and then passing on knowledge to ensure the behavior of employees was consistent with the owner-manager’s vision for the firm in its current environment. Originality/value Ways industry and government can encourage training activity that goes beyond the day-to-day firm needs are suggested.

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Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

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BACKGROUND After general surgery, the lower limb experiences some of the highest complication rates. However, little is known about contributing factors to surgical site failure in the lower limb dermatological surgery population. OBJECTIVE To determine the incidence of lower limb surgical site failure and to explore the predictors that contribute to surgical site failure. METHODS A prospective observational study design was used to collect data from 73 participants, from July 2010, to March 2012. Incidence was determined as a percentage of surgical site failure from the total population. Predictors were determined by the use of a binary logistic regression model. RESULTS The surgical site failure rate was 53.4%. Split-skin grafting had a higher failure rate than primary closures, 66% versus 26.1%. Predictors of lower limb surgical site failure were identified as increasing age (p = .04) and the presence of postoperative hematoma (p = .01), with all patients who developed surgical site infection experiencing surgical site failure (p = .01). CONCLUSION Findings from this study confirmed that the lower limb is at high risk of surgical site failure. Two predictors of surgical site failure from this cohort were determined. However, to understand this phenomenon and make recommendations to assist and reduce surgical site complications, further research in this field is required.

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This special issue of Tobacco Control for World No Tobacco Day is focused on the theme of Price and Trade.

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This week there has been discussions between leaders from the Pacific Rim over the Trans-Pacific Partnership in Bali, Indonesia at APEC...

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The use of organophosphate esters (PFRs) as flame retardants and plasticizers has increased due to the ban of some brominated flame retardants. There is however some concern regarding the toxicity, particularly carcinogenicity and neurotoxicity, of some of the PFRs. In this study we applied wastewater analysis to assess use of PFRs by the Australian population. Influent samples were collected from eleven wastewater treatment plants (STPs) in Australia on Census day and analysed for PFRs using gas chromatography coupled with mass spectrometry (GC-MS). Per capita mass loads of PFRs were calculated using the accurate Census head counts. The results indicate that tris(2-butoxyethyl) phosphate (TBOEP) has the highest per capita input into wastewater followed by tris(2-chloroisopropyl) phosphate (TCIPP), tris(isobutyl) phosphate (TIBP), tris(2-chloroethyl) phosphate (TCEP) and tris(1,3-dichloroisopropyl) phosphate (TDCIPP). Similar PFR profiles were observed across the Australian STPs and a comparison with European and U.S. STPs indicated similar PFR concentrations. We estimate that approximately 2.1 mg person−1 day−1 of PFRs are input into Australian wastewater which equates to 16 tonnes per annum.

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High conductive graphene films can be grown on metal foils by chemical vapor deposition (CVD). We here analyzed the use of ethanol, an economic precursor, which results also safer than commonly-used methane. A comprehensive range of process parameters were explored in order to obtain graphene films with optimal characteristics in view of their use in optoelectronics and photovoltaics. Commercially-available and electro-polished copper foils were used as substrates. By finely tuning the CVD conditions, we obtained few-layer (2-4) graphene films with good conductivity (-500 Ohm/sq) and optical transmittance around 92-94% at 550 nm on unpolished copper foils. The growth on electro-polished copper provides instead predominantly mono-layer films with lower conductivity (>1000 Ohm/sq) and with a transmittance of 97.4% at 550 nm. As for the device properties, graphene with optimal properties as transparent conductive film were produced by CVD on standard copper with specific process conditions.

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Population size is crucial when estimating population-normalized drug consumption (PNDC) from wastewater-based drug epidemiology (WBDE). Three conceptually different population estimates can be used: de jure (common census, residence), de facto (all persons within a sewer catchment), and chemical loads (contributors to the sampled wastewater). De facto and chemical loads will be the same where all households contribute to a central sewer system without wastewater loss. This study explored the feasibility of determining a de facto population and its effect on estimating PNDC in an urban community over an extended period. Drugs and other chemicals were analyzed in 311 daily composite wastewater samples. The daily estimated de facto population (using chemical loads) was on average 32% higher than the de jure population. Consequently, using the latter would systemically overestimate PNDC by 22%. However, the relative day-to-day pattern of drug consumption was similar regardless of the type of normalization as daily illicit drug loads appeared to vary substantially more than the population. Using chemical loads population, we objectively quantified the total methodological uncertainty of PNDC and reduced it by a factor of 2. Our study illustrated the potential benefits of using chemical loads population for obtaining more robust PNDC data in WBDE.

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An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.