5 resultados para Flexible pavement, Rigid pavement, Vertical alignment, Horizontal alignment, Sight Distance (SD), Stopping Sight Distance (SSD).

em Duke University


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Carbon nanotubes (CNTs) have attracted attention for their remarkable electrical properties and have being explored as one of the best building blocks in nano-electronics. A key challenge to realize such potential is the control of the nanotube growth directions. Even though both vertical growth and controlled horizontal growth of carbon nanotubes have been realized before, the growth of complex nanotube structures with both vertical and horizontal orientation control on the same substrate has never been achieved. Here, we report a method to grow three-dimensional (3D) complex nanotube structures made of vertical nanotube forests and horizontal nanotube arrays on a single substrate and from the same catalyst pattern by an orthogonally directed nanotube growth method using chemical vapor deposition (CVD). More importantly, such a capability represents a major advance in controlled growth of carbon nanotubes. It enables researchers to control the growth directions of nanotubes by simply changing the reaction conditions. The high degree of control represented in these experiments will surely make the fabrication of complex nanotube devices a possibility.

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Testing for two-sample differences is challenging when the differences are local and only involve a small portion of the data. To solve this problem, we apply a multi- resolution scanning framework that performs dependent local tests on subsets of the sample space. We use a nested dyadic partition of the sample space to get a collection of windows and test for sample differences within each window. We put a joint prior on the states of local hypotheses that allows both vertical and horizontal message passing among the partition tree to reflect the spatial dependency features among windows. This information passing framework is critical to detect local sample differences. We use both the loopy belief propagation algorithm and MCMC to get the posterior null probability on each window. These probabilities are then used to report sample differences based on decision procedures. Simulation studies are conducted to illustrate the performance. Multiple testing adjustment and convergence of the algorithms are also discussed.

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The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.

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BACKGROUND: The majority of total ankle arthroplasty (TAA) systems use extramedullary alignment guides for tibial component placement. However, at least 1 system offers intramedullary referencing. In total knee arthroplasty, studies suggest that tibial component placement is more accurate with intramedullary referencing. The purpose of this study was to compare the accuracy of extramedullary referencing with intramedullary referencing for tibial component placement in total ankle arthroplasty. METHODS: The coronal and sagittal tibial component alignment was evaluated on the postoperative weight-bearing anteroposterior (AP) and lateral radiographs of 236 consecutive fixed-bearing TAAs. Radiographs were measured blindly by 2 investigators. The postoperative alignment of the prosthesis was compared with the surgeon's intended alignment in both planes. The accuracy of tibial component alignment was compared between the extramedullary and intramedullary referencing techniques using unpaired t tests. Interrater and intrarater reliabilities were assessed with intraclass correlation coefficients (ICCs). RESULTS: Eighty-three tibial components placed with an extramedullary referencing technique were compared with 153 implants placed with an intramedullary referencing technique. The accuracy of the extramedullary referencing was within a mean of 1.5 ± 1.4 degrees and 4.1 ± 2.9 degrees in the coronal and sagittal planes, respectively. The accuracy of intramedullary referencing was within a mean of 1.4 ± 1.1 degrees and 2.5 ± 1.8 degrees in the coronal and sagittal planes, respectively. There was a significant difference (P < .001) between the 2 techniques with respect to the sagittal plane alignment. Interrater ICCs for coronal and sagittal alignment were high (0.81 and 0.94, respectively). Intrarater ICCs for coronal and sagittal alignment were high for both investigators. CONCLUSIONS: Initial sagittal plane tibial component alignment was notably more accurate when intramedullary referencing was used. Further studies are needed to determine the effect of this difference on clinical outcomes and long-term survivability of the implants. LEVEL OF EVIDENCE: Level III, retrospective comparative study.