160 resultados para SUPPLY CHAINS
Resumo:
Background Regenerative endodontics is an innovative treatment concept aiming to regenerate pulp, dentin and root structures. In the diseased or necrotic tooth, the limitation in vascular supply renders successful tissue regeneration/generation in a whole tooth challenging. The aim of this study is to evaluate the ability of vascularized tissue to develop within a pulpless tooth using tissue engineering techniques. Materials and methods A pulpless tooth chamber, filled with collagen I gel containing isolated rat dental pulp cells (DPC) and angiogenic growth factors, was placed into a hole created in the femoral cortex or into its own tooth socket, respectively. The gross, histological and biochemical characteristics of the de novo tissue were evaluated at 4 and 8weeks post-transplantation. Results Tooth revascularization and tissue generation was observed only in the femur group, confirming the important role of vascular supply in tissue regeneration. The addition of cells and growth factors significantly promoted connective tissue production in the tooth chamber. Conclusion Successful revascularization and tissue regeneration in this model demonstrate the importance of a direct vascular supply and the advantages of a stem cell approach. © 2012 John Wiley & Sons A/S.
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This project was a step forward in developing the scientific basis for a methodology to assess the resilience of water supply systems under the impacts of climate change. The improved measure of resilience developed in this project provides an approach to assess the ability of water supply systems to absorb the pressure due changing climate while sustaining supply, and their speed of recovery in case of failure. The approach developed can be applied to any generic water supply system.
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The endoplasmic reticulum (ER) is the central organelle in the eukaryotic secretory pathway. The ER functions in protein synthesis and maturation and is crucial for proper maintenance of cellular homeostasis and adaptation to adverse environments. Acting as a cellular sentinel, the ER is exquisitely sensitive to changing environments principally via the ER quality control machinery. When perturbed, ER-stress triggers a tightly regulated and highly conserved, signal transduction pathway known as the unfolded protein response (UPR) that prevents the dangerous accumulation of unfolded/misfolded proteins. In situations where excessive UPR activity surpasses threshold levels, cells deteriorate and eventually trigger programmed cell death (PCD) as a way for the organism to cope with dysfunctional or toxic signals. The programmed cell death that results from excessive ER stress in mammalian systems contributes to several important diseases including hypoxia, neurodegeneration, and diabetes. Importantly, hallmark features and markers of cell death that are associated with ER stress in mammals are also found in plants. In particular, there is a common, conserved set of chaperones that modulate ER cell death signaling. Here we review the elements of plant cell death responses to ER stress and note that an increasing number of plant-pathogen interactions are being identified in which the host ER is targeted by plant pathogens to establish compatibility.
Semiparametric estimates of the supply and demand effects of disability on labor force participation
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This paper modifies and uses the semiparametric methods of Ichimura and Lee (1991) on standard cross-section data to decompose the effect of disability on labor force participation into a demand and a supply effect. It shows that straightforward use of Ichimura and Lee leads to meaningless results while imposing monotonicity on the unknown function leads to substantial results. The paper finds that supply effects dominate the demand effects of disability.
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This study determined the current trends in supply, demand, and equilibrium (ie, the level of employment where supply equals demand) in the market for Certified Registered Nurse Anesthetists (CRNAs). It also forecasts future needs for CRNAs given different possible scenarios. The impact of the current availability of CRNAs, projected retirements, and changes in the demand for surgeries are considered in relation to CRNAs needed for the future. The study used data from many sources to estimate models associated with the supply and demand for CRNAs and the relationship to relevant community and policy characteristics such as per capita income of the community and managed care. These models were used to forecast changes in surgeries and in the supply of CRNAs in the future. The supply of CRNAs has increased in recent years, stimulated by shortages of CRNAs and subsequent increases in the number of CRNAs trained. However, the increases have not offset the number of retiring CRNAs to maintain a constant age in the CRNA population. The average age will continue to increase for CRNAs in the near future despite increases in CRNAs trained. The supply of CRNAs in relation to surgeries will increase in the near future.
Resumo:
Tailoring the density of random single-walled carbon nanotube (SWCNT) networks is of paramount importance for various applications, yet it remains a major challenge due to the insufficient catalyst activation in most growth processes. Here we report on a simple and effective method to maximise the number of active catalyst nanoparticles using catalytic chemical vapor deposition (CCVD). By modulating short pulses of acetylene into a methane-based CCVD growth process, the density of SWCNTs is dramatically increased by up to three orders of magnitude without increasing the catalyst density and degrading the nanotube quality. In the framework of a vapor-liquid-solid model, we attribute the enhanced growth to the high dissociation rate of acetylene at high temperatures at the nucleation stage, which can be effective in both supersaturating the larger catalyst nanoparticles and overcoming the nanotube nucleation energy barrier of the smaller catalyst nanoparticles. These results are highly relevant to numerous applications of random SWCNT networks in next-generation energy, sensing and biomedical devices. © 2011 The Royal Society of Chemistry.
Resumo:
This thesis examined the delay causes of Malaysian public sector projects. Using a systematic approach, the researcher identified the main delay factors and categorised them into pathogens. The pathogens were matched with beneficial Supply Chain Management (SCM) tools and developed into a holistic SCM framework to facilitate improvements in Malaysian public sector projects. The researcher concluded that SCM is the potential saviour for the delay dilemma and that it is necessary for the Malaysian government to initiate the revolutionary practice.
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This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.
Resumo:
This research project provides a scientifically robust approach for assessing the resilience of water supply systems, which are critical infrastructure, to impacts of climate change and population growth. An approach for the identification of trigger points that allows timely and appropriate management actions to be taken to avoid catastrophic system failure is an important outcome of this project. In the current absence of a formal method to evaluate the resilience of a water supply system, the approach developed in this study was based on the characterisation of resilience of a water supply system to a range of surrogate measures. Accordingly, a set of indicators are proposed to evaluate system behaviour and logistic regression analysis was used to assess system behaviour under predicted rainfall, storage and demand conditions.
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Energy usage in general, and electricity usage in particular, are major concerns internationally due to the increased cost of providing energy supplies and the environmental impacts of electricity generation using carbon-based fuels. If a "systems" approach is taken to understanding energy issues then both supply and demand need to be considered holistically. This paper examines two research projects in the energy area with IT tools as key deliverables, one examining supply issues and the other studying demand side issues. The supply side project used hard engineering methods to build the models and software, while the demand side project used a social science approach. While the projects are distinct, there was an overlap in personnel. Comparing the knowledge extraction, model building, implementation and interface issues of these two deliverables identifies both interesting contrasts and commonalities.
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“World food security … is at its lowest in half a century,” wrote Julian Cribb FTSE, a wellknown consultant in science communication and founding editor of www.sciencealert. com.au in the lead article in the 2008 ATSE Focus magazine issue entitled “Food for the world: the nation’s challenge”. Food security continues to be a key national and international concern and it is pleasing to see this issue of Focus again exploring aspects of the topic with the aim of continuing to raise awareness of issues and influencing relevant policy decisions. Statistics (or statistical science, more broadly) has been critical to the information and decision-making value chain needed to optimise agriculture and the food supply chain. The key steps are most often addressed by multidisciplinary research groups including statisticians in collaboration with life and physical scientists, agri-industry personnel and other relevant stakeholders.
Enhanced interfacial thermal transport across graphene–polymer interfaces by grafting polymer chains
Resumo:
Thermal transport in graphene-polymer nanocomposite is complicated and has not been well understood. The interfacial thermal transport between graphene nanofiller and polymer matrix is expected to play a key role in controlling the overall thermal performance of graphene-polymer nanocomposite. In this work, we investigated the thermal transport across graphene-polymer interfaces functionalized with end-grafted polymer chains using molecular dynamics simulations. The effects of grafting density, chain length and initial morphology on the interfacial thermal transport were systematically investigated. It was found that end-grafted polymer chains could significantly enhance interfacial thermal transport and the underlying mechanism was considered to be the enhanced vibration coupling between graphene and polymer. In addition, a theoretical model based on effective medium theory was established to predict the thermal conductivity in graphene-polymer nanocomposites.
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In ecosystems driven by water availability, plant community dynamics depend on complex interactions between vegetation, hydrology, and human water resources use. Along ephemeral rivers—where water availability is erratic—vegetation and people are particularly vulnerable to changes in each other's water use. Sensible management requires that water supply be maintained for people, while preserving ecosystem health. Meeting such requirements is challenging because of the unpredictable water availability. We applied information gap decision theory to an ecohydrological system model of the Kuiseb River environment in Namibia. Our aim was to identify the robustness of ecosystem and water management strategies to uncertainties in future flood regimes along ephemeral rivers. We evaluated the trade-offs between alternative performance criteria and their robustness to uncertainty to account for both (i) human demands for water supply and (ii) reducing the risk of species extinction caused by water mining. Increasing uncertainty of flood regime parameters reduced the performance under both objectives. Remarkably, the ecological objective (species coexistence) was more sensitive to uncertainty than the water supply objective. However, within each objective, the relative performance of different management strategies was insensitive to uncertainty. The ‘best’ management strategy was one that is tuned to the competitive species interactions in the Kuiseb environment. It regulates the biomass of the strongest competitor and, thus, at the same time decreases transpiration, thereby increasing groundwater storage and reducing pressure on less dominant species. This robust mutually acceptable strategy enables species persistence without markedly reducing the water supply for humans. This study emphasises the utility of ecohydrological models for resource management of water-controlled ecosystems. Although trade-offs were identified between alternative performance criteria and their robustness to uncertain future flood regimes, management strategies were identified that help to secure an ecologically sustainable water supply.
Resumo:
The monoanionic ligand 1,1,3,3 tetracyano-2 ethoxypropenide (tcnoet) is reported with its Cu(II)–bpy complex of formula [Cu2(µ-tcnoet)2(tcnoet)2(bpy)2]. The structure has been determined using X-ray diffraction and features an alternating chain with bridging tcnoet ligands. One ligand acts as a bidentate, dinucleating ligand with one short Cu–N and one medium Cu–N bond, whereas the other tcnoet is largely monodentate, albeit with a very weak interdimer Cu–N bond. Despite the arrangement in dinuclear units, further arranged into linear chains through the non-bridging tcnoet ligand, the compound shows no significant magnetic exchange, as deduced from magnetic susceptibility down to 4 K. Ligand-field, IR and EPR spectra in the solid state and in frozen solution are reported and are consistent with the overall structure.