919 resultados para Drop on Demand


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VMD and NAMD are two major molecular dynamics simulation software packages, which can work together for mining structural information of bio-molecules. Carrying out such molecular dynamics simulations can help researchers to understand the roles and functions of various bio-molecules in life science research. Recently, clouds have provided HPC clusters on demand that allow users to benefit from their flexibility, elasticity, and lower costs. Although cloud computing promises to provide seamless access to HPC clusters through the abstraction of services, which hide the details of the underlying software and hardware infrastructure, users without in depth computing knowledge are still forced to cope with many low level system and programming details. Therefore, we have designed and developed a software plugin of VMD, which can provide an integrated framework for NAMD to be executed on Amazon EC2. The proposed Amazon EC2 Plugin for VMD frees users from performing many tedious computing tasks such as launching, connecting and terminating Amazon EC2 compute instances; configuring a HPC cluster; and installing middleware and software applications before the system is readily available for any scientific investigation. This allows VMD/NAMD users to spend less time getting applications to work on HPC clusters but more time for bio-research.

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Cloud computing is the most recent realisation of computing as a utility. Recently, fields with substantial computational requirements, e.g., biology, are turning to clouds for cheap, on-demand provisioning of resources. Of interest to this paper is the execution of compute intensive applications on hybrid clouds. If application requirements exceed private cloud resource capacity, clients require scaling down their applications. The outcome of this research is Web technology realising a new form of cloud called HPC Hybrid Deakin (H2D) Cloud -- an experimental hybrid cloud capable of utilising both local and remote computational services for single large embarrassingly parallel applications.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The resistance to photodegradation of poly [(2-methoxy-5-n-hexyloxy)-p-phenylene vinylene] (OC1OC6-PPV) films was significantly enhanced by the use of poly(vinyl alcohol) 99% hydrolyzed as protective coating. The deposition of poly(vinyl alcohol) onto OC1OC6-PPV films did not affect the absorption and the emission spectra of the luminescent polymer. The protected film showed 5% drop on the absorbance at 500nm after 270 hours of light exposure while the unprotected film completely degraded in the same conditions. The conductivity of the protected film remained stable (around 7 × 10-10 S/m) while the value for the unprotected one dropped around two orders of magnitude after 100 hours of light exposure.

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While polymers with different functional groups along the backbone have intensively been investigated, there is still a challenge in orthogonal functionalization of the end groups. Such well-defined systems are interesting for the preparation of multiblock (co) polymers or polymer networks, for bio-conjugation or as model systems for examining the end group separation of isolated polymer chains. rnHere, Reversible Addition Fragmentation Chain Transfer (RAFT) polymerization was employed as method to investigate improved techniques for an a, w end group functionalization. RAFT produces polymers terminated in an R group and a dithioester-Z group, where R and Z stem from a suitable chain transfer agent (CTA). rnFor alpha end group functionalization, a CTA with an activated pentafluorophenyl (PFP) ester R group was designed and used for the polymerization of various methacrylate monomers, N-isopropylacrylamide and styrene yielding polymers with a PFP ester as a end group. This allowed the introduction of inert propyl amides, of light responsive diazo compounds, of the dyes NBD, Texas Red, or Oregon Green, of the hormone thyroxin and allowed the formation of multiblocks or peptide conjugates. rnFor w end group functionalization, problems of other techniques were overcome through an aminolysis of the dithioester in the presence of a functional methane thiosulfonate (MTS), yielding functional disulfides. These disulfides were stable under ambient conditions and could be cleaved on demand. Using MTS chemistry, terminal methyl disulfides (enabling self-assembly on planar gold surfaces and ligand substitution on gold and semiconductor nanoparticles), butynyl disulfide end groups (allowing the “clicking” of the polymers onto azide functionalized surfaces and the selective removal through reduction), the bio-target biotin, and the fluorescent dye Texas Red were introduced into polymers. rnThe alpha PFP amidation could be performed under mild conditions, without substantial loss of DTE. This way, a step-wise synthesis produced polymers with two functional end groups in very high yields. rnAs examples, polymers with an anchor group for both gold nanoparticles (AuNP) and CdSe / ZnS semi-conductor nanoparticles (QD) and with a fluorescent dye end group were synthesized. They allowed a NP decoration and enabled an energy transfer from QD to dye or from dye to AuNP. Water-soluble polymers were prepared with two different bio-target end groups, each capable of selectively recognizing and binding a certain protein. The immobilization of protein-polymer-protein layers on planar gold surfaces was monitored by surface plasmon resonance.Introducing two different fluorescent dye end groups enabled an energy transfer between the end groups of isolated polymer chains and created the possibility to monitor the behavior of single polymer chains during a chain collapse. rnThe versatility of the synthetic technique is very promising for applications beyond this work.

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Nowadays, data handling and data analysis in High Energy Physics requires a vast amount of computational power and storage. In particular, the world-wide LHC Com- puting Grid (LCG), an infrastructure and pool of services developed and deployed by a ample community of physicists and computer scientists, has demonstrated to be a game changer in the efficiency of data analyses during Run-I at the LHC, playing a crucial role in the Higgs boson discovery. Recently, the Cloud computing paradigm is emerging and reaching a considerable adoption level by many different scientific organizations and not only. Cloud allows to access and utilize not-owned large computing resources shared among many scientific communities. Considering the challenging requirements of LHC physics in Run-II and beyond, the LHC computing community is interested in exploring Clouds and see whether they can provide a complementary approach - or even a valid alternative - to the existing technological solutions based on Grid. In the LHC community, several experiments have been adopting Cloud approaches, and in particular the experience of the CMS experiment is of relevance to this thesis. The LHC Run-II has just started, and Cloud-based solutions are already in production for CMS. However, other approaches of Cloud usage are being thought of and are at the prototype level, as the work done in this thesis. This effort is of paramount importance to be able to equip CMS with the capability to elastically and flexibly access and utilize the computing resources needed to face the challenges of Run-III and Run-IV. The main purpose of this thesis is to present forefront Cloud approaches that allow the CMS experiment to extend to on-demand resources dynamically allocated as needed. Moreover, a direct access to Cloud resources is presented as suitable use case to face up with the CMS experiment needs. Chapter 1 presents an overview of High Energy Physics at the LHC and of the CMS experience in Run-I, as well as preparation for Run-II. Chapter 2 describes the current CMS Computing Model, and Chapter 3 provides Cloud approaches pursued and used within the CMS Collaboration. Chapter 4 and Chapter 5 discuss the original and forefront work done in this thesis to develop and test working prototypes of elastic extensions of CMS computing resources on Clouds, and HEP Computing “as a Service”. The impact of such work on a benchmark CMS physics use-cases is also demonstrated.

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Environmental factors can determine which group size will maximize the fitness of group members. This is particularly important in cooperative breeders, where group members often serve different purposes. Experimental studies are yet lacking to check whether ecologically mediated need for help will change the propensity of dominant group members to accept immigrants. Here, we manipulated the perceived risk of predation for dominant breeders of the cooperatively breeding cichlid fish Neolamprologus pulcher to test their response to unrelated and previously unknown immigrants. Potential immigrants were more readily accepted if groups were exposed to fish predators or egg predators than to herbivorous fish or control situations lacking predation risk. Our data are consistent with both risk dilution and helping effects. Egg predators were presented before spawning, which might suggest that the fish adjust acceptance rates also to a potential future threat. Dominant group members of N. pulcher apparently consider both present and future need of help based on ecological demand. This suggests that acceptance of immigrants and, more generally, tolerance of group members on demand could be a widespread response to ecological conditions in cooperatively breeding animals.

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Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

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Available on demand as hard copy or computer file from Cornell University Library.

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Available on demand as hard copy or computer file from Cornell University Library.

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Available on demand as hard copy or computer file from Cornell University Library.