593 resultados para Acid distribution
Resumo:
Integration of small-scale electricity generators, known as Distributed Generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of synchronous-type generator has potential to give the DG a better chance in participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimizes interaction with other active devices, such as On-load Tap Changing Transformer (OLTC) and voltage regulator. The technique has been developed based on the concept of control zone, Line Drop Compensation (LDC), as well as the choice of controller's parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.
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The reliable operation of distribution systems is critically dependent on detailed understanding of load impacts on distribution transformer insulation systems. This paper estimates the impact of rooftop photovoltaic (PV) generation on a typical 200-kVA, 22/0.415-kV distribution transformer life under different operating conditions. This transformer supplies a suburban area with a high penetration of roof top photovoltaic systems. The transformer loads and the phase distribution of the PV systems are significantly unbalanced. Oil and hot-spot temperature and remnant life of distribution transformer under different PV and balance scenarios are calculated. It is shown that PV can significantly extend the transformer life.
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Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.
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This is an invited public lecture. The talk will cover how the music industry has changed due to digital technologies. During the talk I will look at how the changing balance between live music, music licensing and recorded music. I will also discuss online music subscription services and whether they might be a future for music distribution in China and elsewhere in the world. It will also look at how music artists and composers are affected by this change.
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Background L-type amino acid transporters (LATs) uptake neutral amino acids including L-leucine into cells, stimulating mammalian target of rapamycin complex 1 signaling and protein synthesis. LAT1 and LAT3 are overexpressed at different stages of prostate cancer, and they are responsible for increasing nutrients and stimulating cell growth. Methods We examined LAT3 protein expression in human prostate cancer tissue microarrays. LAT function was inhibited using a leucine analog (BCH) in androgen-dependent and -independent environments, with gene expression analyzed by microarray. A PC-3 xenograft mouse model was used to study the effects of inhibiting LAT1 and LAT3 expression. Results were analyzed with the Mann-Whitney U or Fisher exact tests. All statistical tests were two-sided. Results LAT3 protein was expressed at all stages of prostate cancer, with a statistically significant decrease in expression after 4–7 months of neoadjuvant hormone therapy (4–7 month mean = 1.571; 95% confidence interval = 1.155 to 1.987 vs 0 month = 2.098; 95% confidence interval = 1.962 to 2.235; P = .0187). Inhibition of LAT function led to activating transcription factor 4–mediated upregulation of amino acid transporters including ASCT1, ASCT2, and 4F2hc, all of which were also regulated via the androgen receptor. LAT inhibition suppressed M-phase cell cycle genes regulated by E2F family transcription factors including critical castration-resistant prostate cancer regulatory genes UBE2C, CDC20, and CDK1. In silico analysis of BCH-downregulated genes showed that 90.9% are statistically significantly upregulated in metastatic castration-resistant prostate cancer. Finally, LAT1 or LAT3 knockdown in xenografts inhibited tumor growth, cell cycle progression, and spontaneous metastasis in vivo. Conclusion Inhibition of LAT transporters may provide a novel therapeutic target in metastatic castration-resistant prostate cancer, via suppression of mammalian target of rapamycin complex 1 activity and M-phase cell cycle genes.
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Background Ghrelin is a 28 amino acid peptide hormone that is expressed in the stomach and a range of peripheral tissues, where it frequently acts as an autocrine/paracrine growth factor. Ghrelin is modified by a unique acylation required for it to activate its cognate receptor, the growth hormone secretagogue receptor (GHSR), which mediates many of the actions of ghrelin. Recently, the enzyme responsible for adding the fatty acid residue (octanoyl/acyl group) to the third amino acid of ghrelin, GOAT (ghrelin O-acyltransferase), was identified. Methods We used cell culture, quantitative real-time reverse transcription (RT)-PCR and immunohistochemistry to demonstrate the expression of GOAT in prostate cancer cell lines and tissues from patients. Real-time RT-PCR was used to demonstrate the expression of prohormone convertase (PC)1/3, PC2 and furin in prostate cancer cell lines. Prostate-derived cell lines were treated with ghrelin and desacyl ghrelin and the effect on GOAT expression was measured using quantitative RT-PCR. Results We have demonstrated that GOAT mRNA and protein are expressed in the normal prostate and human prostate cancer tissue samples. The RWPE-1 and RWPE-2 normal prostate-derived cell lines and the LNCaP, DU145, and PC3 prostate cancer cell lines express GOAT and at least one other enzyme that is necessary to produce mature, acylated ghrelin from proghrelin (PC1/3, PC2 or furin). Finally, ghrelin, but not desacyl ghrelin (unacylated ghrelin), can directly regulate the expression of GOAT in the RWPE-1 normal prostate derived cell line and the PC3 prostate cancer cell line. Ghrelin treatment (100nM) for 6 hours significantly decreased GOAT mRNA expression two-fold (P < 0.05) in the PC3 prostate cancer cell line, however, ghrelin did not regulate GOAT expression in the DU145 and LNCaP prostate cancer cell lines. Conclusions This study demonstrates that GOAT is expressed in prostate cancer specimens and cell lines. Ghrelin regulates GOAT expression, however, this is likely to be cell-type specific. The expression of GOAT in prostate cancer supports the hypothesis that the ghrelin axis has autocrine/paracrine roles. We propose that the RWPE-1 prostate cell line and the PC3 prostate cancer cell line may be useful for investigating GOAT regulation and function.
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The absorptive capacity of organisations is one of the key drivers of innovation performance in any industry. This research seeks to refine our understanding of the relationship between absorptive capacity and innovation performance, with a focus on characterising the absorptive capacity of the different participant groups within the Australian road industry supply chain. One of the largest and most comprehensive surveys ever undertaken of innovation in road construction was completed in 2011 by the Queensland University of Technology (QUT), based on the Australian road industry. The survey of over 200 construction industry participants covered four sectors, comprising suppliers (manufacturers and distributors), consultants (engineering consultants), contractors (head and subcontractors) and clients (state government road agencies). The survey measured the absorptive capacity and innovation activity exhibited by organisations within each of these participant groups, using the perceived importance of addressing innovation obstacles as a proxy for innovation activity. One of the key findings of the survey is about the impact of participant competency on product innovation activity. The survey found that the absorptive capacity of industry participants had a significant and positive relationship with innovation activity. Regarding the distribution of absorptive capacity, the results indicate that suppliers are more likely to have high levels of absorptive capacity than the other participant groups, with 32% of suppliers showing high absorptive capacity, ahead of contractors (18%), consultants (11%), and clients (7%). These results support the findings of previous studies in the literature and suggest the importance of policies to enhance organisational learning, particularly in relation to openness to new product ideas.
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Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.
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Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.
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Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.
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Electric Energy Storage (EES) is considered as one of the promising options for reducing the need for costly upgrades in distribution networks in Queensland (QLD). However, It is expected, the full potential for storage for distribution upgrade deferral cannot be fully realized due to high cost of EES. On the other hand, EES used for distribution deferral application can support a variety of complementary storage applications such as energy price arbitrage, time of use (TOU) energy cost reduction, wholesale electricity market ancillary services, and transmission upgrade deferral. Aggregation of benefits of these complementary storage applications would have the potential for increasing the amount of EES that may be financially attractive to defer distribution network augmentation in QLD. In this context, this paper analyzes distribution upgrade deferral, energy price arbitrage, TOU energy cost reduction, and integrated solar PV-storage benefits of EES devices in QLD.
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Arachidonic acid metabolism through cyclooxygenase (COX), lipoxygenase (LOX) and cytochrome P-450 epoxygenase (EPOX) pathways is responsible for the formation of biologically active eicosanoids, including prostanoids, leukotrienes, hydroxyeicosatetraenoic acid, epoxyeicosatrienoic acid and hydroperoxyeicosatetraenoic acids. Altered eicosanoid expression levels are commonly observed during tumour development and progression of a range of malignancies, including non-small cell lung cancer (NSCLC). Arachidonic acid-derived eicosanoids affect a range of biological phenomena to modulate tumour processes such as cell growth, survival, angiogenesis, cell adhesion, invasion and migration and metastatic potential. Numerous studies have demonstrated that eicosanoids modulate NSCLC development and progression, while targeting these pathways has generally been shown to inhibit tumour growth/progression. Modulation of these arachidonic acid-derived pathways for the prevention and/or treatment of NSCLC has been the subject of significant interest over the past number of years, with a number of clinical trials examining the potential of COX and LOX inhibitors in combination with traditional and novel molecular approaches. However, results from these trials have been largely disappointing. Furthermore, enthusiasm for the use of selective COX-2 inhibitors for cancer prevention/treatment waned, due to their association with adverse cardiovascular events in chemoprevention trials. While COX and LOX targeting may both retain promise for NSCLC prevention and/or treatment, there is an urgent need to understand the downstream signalling mechanisms through which these and other arachidonic acid-derived signalling pathways mediate their effects on tumourigenesis. This will allow for development of safer and potentially more effective strategies for NSCLC prevention and/or treatment. Chemoprevention studies with PGI2 analogues have demonstrated considerable promise, while binding to/signalling through PGE2 receptors have also been the subject of interest for NSCLC treatment. In this chapter, the role of the eicosanoid signalling pathways in non-small cell lung cancer will be discussed. In particular, the effect of the eicosanoids on tumour cell proliferation, their roles in induction of cell death, effects on angiogenesis, migration, invasion and their regulation of the immune response will be assessed, with signal transduction pathways involved in these processes also discussed. Finally, novel approaches targeting these arachidonic acid-derived eicosanoids (using pharmacological or natural agents) for chemoprevention and/or treatment of NSCLC will be outlined. Elucidating the molecular mechanisms underlying the effects of specific or general arachidonic acid pathway modulators may lead to the design of biologically and pharmacologically targeted therapeutic strategies for NSCLC prevention/treatment, which may be used alone or in combination with conventional therapies.
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Genomic instability underlies the transformation of host cells toward malignancy, promotes development of invasion and metastasis and shapes the response of established cancer to treatment. In this review, we discuss recent advances in our understanding of genomic stability in squamous cell carcinoma of the head and neck (HNSCC), with an emphasis on DNA repair pathways. HNSCC is characterized by distinct profiles in genome stability between similarly staged cancers that are reflected in risk, treatment response and outcomes. Defective DNA repair generates chromosomal derangement that can cause subsequent alterations in gene expression, and is a hallmark of progression toward carcinoma. Variable functionality of an increasing spectrum of repair gene polymorphisms is associated with increased cancer risk, while aetiological factors such as human papillomavirus, tobacco and alcohol induce significantly different behaviour in induced malignancy, underpinned by differences in genomic stability. Targeted inhibition of signalling receptors has proven to be a clinically-validated therapy, and protein expression of other DNA repair and signalling molecules associated with cancer behaviour could potentially provide a more refined clinical model for prognosis and treatment prediction. Development and expansion of current genomic stability models is furthering our understanding of HNSCC pathophysiology and uncovering new, promising treatment strategies. © 2013 Glenn Jenkins et al.
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A typology of music distribution models is proposed consisting of the ownership model, the access model, and the context model. These models are not substitutes for each other and may co‐exist serving different market niches. The paper argues that increasingly the economic value created from recorded music is based on con‐text rather than on ownership. During this process, access‐based services temporarily generate economic value, but such services are destined to eventually become commoditised.
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The ability of poly(acrylic acid) (PAA) with different end groups and molar masses prepared by Atom Transfer Radical Polymerization (ATRP) to inhibit the formation of calcium carbonate scale at low and elevated temperatures was investigated. Inhibition of CaCO3 deposition was affected by the hydrophobicity of the end groups of PAA, with the greatest inhibition seen for PAA with hydrophobic end groups of moderate size (6–10 carbons). The morphologies of CaCO3 crystals were significantly distorted in the presence of these PAAs. The smallest morphological change was in the presence of PAA with long hydrophobic end groups (16 carbons) and the relative inhibition observed for all species were in the same order at 30 °C and 100 °C. As well as distorting morphologies, the scale inhibitors appeared to stabilize the less thermodynamically favorable polymorph, vaterite, to a degree proportional to their ability to inhibit precipitation.