896 resultados para Repair Maintenance Alteration and Addition Works
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In the present paper, we announce new draft genomes of four Leptospira interrogans strains named Acegua, RCA, Prea, and Capivara. These strains were isolated in the state of Rio Grande do Sul, Brazil, from cattle, dog, Brazilian guinea pig, and capybara, respectively.
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The protein p53 binding protein one (53BP1) was discovered in a yeast two-hybrid screen that used the DNA binding domain of p53 as bait. Cloning of full-length 53BP1 showed that this protein contains several protein domains which help make up the protein, which include two tandem BRCT domains and a amino-terminal serine/glutamine cluster domain (SCD). These are two protein domains are often seen in factors that are involved in the cellular response to DNA damage and control of cell cycle checkpoints and we hypothesize that 53BP1 is involved in the cellular response to DNA damage. In support of this hypothesis we observe that 53BP1 is phosphorylated and undergoes a dramatic nuclear re-localization in response to DNA damaging agents. 53BP1 also interacts with several factors that are important in the cellular response to DNA damage, such as the BRCA1 tumor suppressor, ATM and Rad3 related (ATR), and the phosphorylated version of the histone variant H2AX. Mice deficient in 53BP1 display increased sensitivity ionizing radiation (IR), a DNA damaging agent that introduces DNA double strand breaks (DSBs). In addition, 53BP1-deficient mice do not properly undergo the process of class switch recombination (CSR). We also observe that when a defect in 53BP1 is combined with a defect in p53; the resulting mice have an increased rate of formation of spontaneous tumors, notably the formation of B and T lineage lymphomas. The T lineage tumors arise by two distinct mechanisms: one driven by defects in cell cycle regulation and a second driven by defects in the ability to repair DNA DSBs. The B lineage tumors arise by the inability to repair DNA damage and over-expression of the oncogene c-myc. ^ With these observations, we conclude that not only does 53BP1 function in the cellular response to DNA damage, but it also works in concert with p53 to suppress tumor formation. ^
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Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.
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Gross value of cons truction work in the repair , maintenance, minor alte ration and addition (RMAA) sector in Hong Kong has expanded dramatically by 58% from 1998 to 2007, accounting for over 53% of the whole construction market in 2007. Unfortunately, the portion of industrial accidents arising from this sector also increased substantially during the same period. It is important to improve the safety performance of the RMAA sector. This paper has set out the objectives to examine safety statistics of RMAA works; to compare them with those of green field projects; and more importantly, to highlight potential hurdles en countered in the process of comparison and finally to provide effective recommendations for overcoming these impediments. To strive for continuous safety improvement of RMAA works, comparable safety statistics should be compiled for this sector.
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Overlay networks have been used for adding and enhancing functionality to the end-users without requiring modifications in the Internet core mechanisms. Overlay networks have been used for a variety of popular applications including routing, file sharing, content distribution, and server deployment. Previous work has focused on devising practical neighbor selection heuristics under the assumption that users conform to a specific wiring protocol. This is not a valid assumption in highly decentralized systems like overlay networks. Overlay users may act selfishly and deviate from the default wiring protocols by utilizing knowledge they have about the network when selecting neighbors to improve the performance they receive from the overlay. This thesis goes against the conventional thinking that overlay users conform to a specific protocol. The contributions of this thesis are threefold. It provides a systematic evaluation of the design space of selfish neighbor selection strategies in real overlays, evaluates the performance of overlay networks that consist of users that select their neighbors selfishly, and examines the implications of selfish neighbor and server selection to overlay protocol design and service provisioning respectively. This thesis develops a game-theoretic framework that provides a unified approach to modeling Selfish Neighbor Selection (SNS) wiring procedures on behalf of selfish users. The model is general, and takes into consideration costs reflecting network latency and user preference profiles, the inherent directionality in overlay maintenance protocols, and connectivity constraints imposed on the system designer. Within this framework the notion of user’s "best response" wiring strategy is formalized as a k-median problem on asymmetric distance and is used to obtain overlay structures in which no node can re-wire to improve the performance it receives from the overlay. Evaluation results presented in this thesis indicate that selfish users can reap substantial performance benefits when connecting to overlay networks composed of non-selfish users. In addition, in overlays that are dominated by selfish users, the resulting stable wirings are optimized to such great extent that even non-selfish newcomers can extract near-optimal performance through naïve wiring strategies. To capitalize on the performance advantages of optimal neighbor selection strategies and the emergent global wirings that result, this thesis presents EGOIST: an SNS-inspired overlay network creation and maintenance routing system. Through an extensive measurement study on the deployed prototype, results presented in this thesis show that EGOIST’s neighbor selection primitives outperform existing heuristics on a variety of performance metrics, including delay, available bandwidth, and node utilization. Moreover, these results demonstrate that EGOIST is competitive with an optimal but unscalable full-mesh approach, remains highly effective under significant churn, is robust to cheating, and incurs minimal overheads. This thesis also studies selfish neighbor selection strategies for swarming applications. The main focus is on n-way broadcast applications where each of n overlay user wants to push its own distinct file to all other destinations as well as download their respective data files. Results presented in this thesis demonstrate that the performance of our swarming protocol for n-way broadcast on top of overlays of selfish users is far superior than the performance on top of existing overlays. In the context of service provisioning, this thesis examines the use of distributed approaches that enable a provider to determine the number and location of servers for optimal delivery of content or services to its selfish end-users. To leverage recent advances in virtualization technologies, this thesis develops and evaluates a distributed protocol to migrate servers based on end-users demand and only on local topological knowledge. Results under a range of network topologies and workloads suggest that the performance of the distributed deployment is comparable to that of the optimal but unscalable centralized deployment.
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This thesis presents the methodology of linking Total Productive Maintenance (TPM) and Quality Function Deployment (QFD). The Synergic power ofTPM and QFD led to the formation of a new maintenance model named Maintenance Quality Function Deployment (MQFD). This model was found so powerful that, it could overcome the drawbacks of TPM, by taking care of customer voices. Those voices of customers are used to develop the house of quality. The outputs of house of quality, which are in the form of technical languages, are submitted to the top management for making strategic decisions. The technical languages, which are concerned with enhancing maintenance quality, are strategically directed by the top management towards their adoption of eight TPM pillars. The TPM characteristics developed through the development of eight pillars are fed into the production system, where their implementation is focused towards increasing the values of the maintenance quality parameters, namely overall equipment efficiency (GEE), mean time between failures (MTBF), mean time to repair (MTIR), performance quality, availability and mean down time (MDT). The outputs from production system are required to be reflected in the form of business values namely improved maintenance quality, increased profit, upgraded core competence, and enhanced goodwill. A unique feature of the MQFD model is that it is not necessary to change or dismantle the existing process ofdeveloping house ofquality and TPM projects, which may already be under practice in the company concerned. Thus, the MQFD model enables the tactical marriage between QFD and TPM.First, the literature was reviewed. The results of this review indicated that no activities had so far been reported on integrating QFD in TPM and vice versa. During the second phase, a survey was conducted in six companies in which TPM had been implemented. The objective of this survey was to locate any traces of QFD implementation in TPM programme being implemented in these companies. This survey results indicated that no effort on integrating QFD in TPM had been made in these companies. After completing these two phases of activities, the MQFD model was designed. The details of this work are presented in this research work. Followed by this, the explorative studies on implementing this MQFD model in real time environments were conducted. In addition to that, an empirical study was carried out to examine the receptivity of MQFD model among the practitioners and multifarious organizational cultures. Finally, a sensitivity analysis was conducted to find the hierarchy of various factors influencing MQFD in a company. Throughout the research work, the theory and practice of MQFD were juxtaposed by presenting and publishing papers among scholarly communities and conducting case studies in real time scenario.
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The cost of a road construction over its service life is a function of the design, quality of construction, maintenance strategies and maintenance operations. Unfortunately, designers often neglect a very important aspect which is the possibility to perform future maintenance activities. The focus is mainly on other aspects such as investment costs, traffic safety, aesthetic appearance, regional development and environmental effects. This licentiate thesis is a part of a Ph.D. project entitled “Road Design for lower maintenance costs” that aims to examine how the life-cycle costs can be optimized by selection of appropriate geometrical designs for the roads and their components. The result is expected to give a basis for a new method used in the road planning and design process using life-cycle cost analysis with particular emphasis on road maintenance. The project started with a review of literature with the intention to study conditions causing increased needs for road maintenance, the efforts made by the road authorities to satisfy those needs and the improvement potential by consideration of maintenance aspects during planning and design. An investigation was carried out to identify the problems which obstruct due consideration of maintenance aspects during the road planning and design process. This investigation focused mainly on the road planning and design process at the Swedish Road Administration. However, the road planning and design process in Denmark, Finland and Norway were also roughly evaluated to gain a broader knowledge about the research subject. The investigation was carried out in two phases: data collection and data analysis. Data was collected by semi-structured interviews with expert actors involved in planning, design and maintenance and by a review of design-related documents. Data analyses were carried out using a method called “Change Analysis”. This investigation revealed a complex combination of problems which result in inadequate consideration of maintenance aspects. Several urgent needs for changes to eliminate these problems were identified. Another study was carried out to develop a model for calculation of the repair costs for damages of different road barrier types and to analyse how factors such as road type, speed limits, barrier types, barrier placement, type of road section, alignment and seasonal effects affect the barrier damages and the associated repair costs. This study was carried out using a method called the “Case Study Research Method”. Data was collected from 1087 barrier repairs in two regional offices of the Swedish Road Administration, the Central Region and the Western Region. A table was established for both regions containing the repair cost per vehicle kilometre for different combinations of barrier types, road types and speed limits. This table can be used by the designers in the calculation of the life-cycle costs for different road barrier types.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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PURPOSE: The mandibular implant overdenture is a popular treatment modality and is well documented in the literature. Follow-up studies with a long observation period are difficult to perform due to the increasing age of patients. The present data summarize a long-term clinical observation of patients with implant overdentures. MATERIALS AND METHODS: Between 1984 and 1997, edentulous patients were consecutively admitted for treatment with an implant overdenture. The dentures were connected to the implants by means of bars or ball anchors. Regular maintenance was provided with at least one or two scheduled visits per year. Recall attendance and reasons for dropout were analyzed based on the specific history of the patient. Denture maintenance service, relining, repair, and fabrication of new dentures were identified, and complications with the retention devices specified separately. RESULTS: In the time period from 1984 to 2008, 147 patients with a total of 314 implants had completed a follow-up period of >10 years. One hundred one patients were still available in 2008, while 46 patients were not reexamined for various reasons. Compliance was high, with a regular recall attendance of >90%. More than 80% of dentures remained in continuous service. Although major prosthetic maintenance was rather low in relation to the long observation period, visits to a dental hygienist and dentist resulted in an annual visit rate of 1.5 and 2.4, respectively. If new dentures became necessary, these were made in student courses, which increased the treatment time and number of appointments needed. Complications with the retention devices consisted mostly of the mounting of new female retainers, the repair of bars, and the changing of ball anchors. The average number of events and the rate of prosthetic service with ball anchors were significantly higher than those with bars. Twenty-two patients changed from ball anchors to bars; 9 patients switched from a clip bar to a rigid U-shaped bar. CONCLUSIONS: This long-term follow-up study demonstrates that implant overdentures are a favorable solution for edentulous patients with regular maintenance. In spite of specific circumstances in an aging population, it is possible to provide long-term care, resulting in a good prognosis and low risk for this treatment modality. For various reasons the dropout rate can be considerable in elderly patients and prosthetic service must be provided regularly.
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To protect motorists and avoid tort liability, highway agencies expend considerable resources to repair damaged longitudinal barriers, such as w-beam guardrails. With limited funding available, though, highway agencies are unable to maintain all field-installed systems in the ideal as-built condition. Instead, these agencies focus on repairing only damage that has a detrimental effect on the safety performance of the barrier. The distinction between minor damage and more severe performance-altering damage, however, is not always clear. This paper presents a critical review of current United States (US) and Canadian criteria on whether to repair damaged longitudinal barrier. Barrier repair policies were obtained via comprehensive literature review and a survey of US and Canadian transportation agencies. In an analysis of the maintenance procedures of 40 US States and 8 Canadian transportation agencies, fewer than one-third of highway agencies were found to have quantitative measures to determine when barrier repair is warranted. In addition, no engineering basis for the current US barrier repair guidelines could be found. These findings underscore the importance of the development of quantitative barrier repair guidelines based on a strong technical foundation.
MED1, a novel human methyl-CpG-binding endonuclease, interacts with DNA mismatch repair protein MLH1
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The DNA mismatch repair (MMR) is a specialized system, highly conserved throughout evolution, involved in the maintenance of genomic integrity. To identify novel human genes that may function in MMR, we employed the yeast interaction trap. Using the MMR protein MLH1 as bait, we cloned MED1. The MED1 protein forms a complex with MLH1, binds to methyl-CpG-containing DNA, has homology to bacterial DNA repair glycosylases/lyases, and displays endonuclease activity. Transfection of a MED1 mutant lacking the methyl-CpG-binding domain (MBD) is associated with microsatellite instability (MSI). These findings suggest that MED1 is a novel human DNA repair protein that may be involved in MMR and, as such, may be a candidate eukaryotic homologue of the bacterial MMR endonuclease, MutH. In addition, these results suggest that cytosine methylation may play a role in human DNA repair.
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On cover: no. 6.
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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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Maintenance is a time consuming and expensive task for any golf course or driving range manager. For a golf course the primary tasks are grass mowing and maintenance (fertilizer and herbicide spreading), while for a driving range mowing, maintenance and ball collection are required. All these tasks require an operator to drive a vehicle along paths which are generally predefined. This paper presents some preliminary in-field tsting results for an automated tractor vehicle performing golf ball collection on an actual driving range, and mowing on difficult unstructured terrain.