840 resultados para Alternative Initiation Codon
Resumo:
Ensemble learning techniques generate multiple classifiers, so called base classifiers, whose combined classification results are used in order to increase the overall classification accuracy. In most ensemble classifiers the base classifiers are based on the Top Down Induction of Decision Trees (TDIDT) approach. However, an alternative approach for the induction of rule based classifiers is the Prism family of algorithms. Prism algorithms produce modular classification rules that do not necessarily fit into a decision tree structure. Prism classification rulesets achieve a comparable and sometimes higher classification accuracy compared with decision tree classifiers, if the data is noisy and large. Yet Prism still suffers from overfitting on noisy and large datasets. In practice ensemble techniques tend to reduce the overfitting, however there exists no ensemble learner for modular classification rule inducers such as the Prism family of algorithms. This article describes the first development of an ensemble learner based on the Prism family of algorithms in order to enhance Prism’s classification accuracy by reducing overfitting.
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Many factors, both mesoscale and larger scale, often come together in order for a particular convective initiation to take place. The authors describe a modeling study of a case from the Convective Storms Initiation Project (CSIP) in which a single thunderstorm formed behind a front in the southern United Kingdom. The key features of the case were a tongue of low-level high θw air associated with a forward-sloping split front (overrunning lower θw air above), a convergence line, and a “lid” of high static stability air, which the shower was initially constrained below but later broke through. In this paper, the authors analyze the initiation of the storm, which can be traced back to a region of high ground (Dartmoor) at around 0700 UTC, in more detail using model sensitivity studies with the Met Office Unified Model (MetUM). It is established that the convergence line was initially caused by roughness effects but had a significant thermal component later. Dartmoor had a key role in the development of the thunderstorm. A period of asymmetric flow over the high ground, with stronger low-level descent in the lee, led to a hole in a layer of low-level clouds downstream. The surface solar heating through this hole, in combination with the tongue of low-level high θw air associated with the front, caused the shower to initiate with sufficient lifting to enable it later to break through the lid.
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Efficient transport of stem/progenitor cells without affecting their survival and function is a key factor in any practical cell-based therapy. However, the current approach using liquid nitrogen for the transfer of stem cells requires a short delivery time window is technically challenging and financially expensive. The present study aims to use semipermeable alginate hydrogels (crosslinked by strontium) to encapsulate, store, and release stem cells, to replace the conventional cryopreservation method for the transport of therapeutic cells within world-wide distribution time frame. Human mesenchymal stem cell (hMSC) and mouse embryonic stem cells (mESCs) were successfully stored inside alginate hydrogels for 5 days under ambient conditions in an air-tight environment (sealed cryovial). Cell viability, of the cells extracted from alginate gel, gave 74% (mESC) and 80% (hMSC) survival rates, which compared favorably to cryopreservation. More importantly, the subsequent proliferation rate and detection of common stem cell markers (both in mRNA and protein level) from hMSCs and mESCs retrieved from alginate hydrogels were also comparable to (if not better than) results gained following cryopreservation. In conclusion, this new and simple application of alginate hydrogel encapsulation may offer a cheap and robust alternative to cryopreservation for the transport and storage of stem cells for both clinical and research purposes.
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Duchenne muscular dystrophy is a fatal muscle-wasting disorder. Lack of dystrophin compromises the integrity of the sarcolemma and results in myofibers that are highly prone to contraction-induced injury. Recombinant adenoassociated virus (rAAV)-mediated dystrophin gene transfer strategies to muscle for the treatment of Duchenne muscular dystrophy (DMD) have been limited by the small cloning capacity of rAAV vectors and high titers necessary to achieve efficient systemic gene transfer. In this study, we assess the impact of codon optimization on microdystrophin (ΔAB/R3-R18/ΔCT) expression and function in the mdx mouse and compare the function of two different configurations of codon-optimized microdystrophin genes (ΔAB/R3-R18/ΔCT and ΔR4-R23/ΔCT) under the control of a muscle-restrictive promoter (Spc5-12). Codon optimization of microdystrophin significantly increases levels of microdystrophin mRNA and protein after intramuscular and systemic administration of plasmid DNA or rAAV2/8. Physiological assessment demonstrates that codon optimization of ΔAB/R3-R18/ΔCT results in significant improvement in specific force, but does not improve resistance to eccentric contractions compared with noncodon-optimized ΔAB/ R3-R18/ΔCT. However, codon-optimized microdystrophin ΔR4-R23/ΔCT completely restored specific force generation and provided substantial protection from contraction-induced injury. These results demonstrate that codon optimization of microdystrophin under the control of a muscle-specific promoter can significantly improve expression levels such that reduced titers of rAAV vectors will be required for efficient systemic administration.
The role of baroclinic waves in the initiation of tropical cyclones across the southern Indian Ocean
Resumo:
Cases where tropical storms are initiated simultaneously along one latitude are investigated. It is argued that such structure arises as part of a baroclinic wave. A case from February 2008 is examined using European Centre for Medium-Range Forecasts (ECMWF) analyses; the birth of three tropical cyclones in the low-level cyclonic regions to the east of upper-level troughs suggests that the wave was instrumental for initiation. Archived satellite imagery and storm warnings reveal that baroclinic waves over the southern Indian Ocean accompany tropical cyclogenesis twice a season on average, mainly in late summer, when breaking Rossby waves on the subtropical westerly jet are closest to the Intertropical Convergence Zone (ITCZ). Copyright © 2012 Royal Meteorological Society
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Despite the characterization of the auroral substorm more than 40 years ago, controversy still surrounds the processes triggering substorm onset initiation. That stretching of the Earth's magnetotail following the addition of new nightside magnetic flux from dayside reconnection powers the substorm is well understood; the trigger for explosive energy release at substorm expansion phase onset is not. Using ground-based data sets with unprecedented combined spatial and temporal coverage, we report the discovery of new localized and contemporaneous magnetic wave and small azimuthal scale auroral signature of substorm onset. These local auroral arc undulations and magnetic field signatures rapidly evolve on second time scales for several minutes in advance of the release of the auroral surge. We also present evidence from a conjugate geosynchronous satellite of the concurrent magnetic onset in space as the onset of magnetic pulsations in the ionosphere, to within technique error. Throughout this time period, the more poleward arcs that correspond to the auroral oval which maps to the central plasma sheet remain undisturbed. There is good evidence that flows from the midtail crossing the plasma sheet can generate north-south auroral structures, yet no such auroral forms are seen in this event. Our observations present a severe challenge to the standard hypothesis that magnetic reconnection in stretched magnetotail fields triggers onset, indicating substorm expansion phase initiation occurs on field lines that are close to the Earth, as bounded by observations at geosynchronous orbit and in the conjugate ionosphere.
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Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.
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We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. Experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, the mathematical model based on the feedback control in the sensory-motor closed loop predicts a discrete mode transition as the gain factors of the proportional control decease. The conditions of the synchronization were shown as a consequence of the coupled dynamics based on the subsequent feedback loop in the sensory-motor system.
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The increasing amount of available expressed gene sequence data makes whole-transcriptome analysis of certain crop species possible. Potato currently has the second largest number of publicly available expressed sequence tag (EST) sequences among the Solanaceae. Most of these ESTs, plus other proprietary sequences, were combined and used to generate a unigene assembly. The set of 246,182 sequences produced 46,345 unigenes, which were used to design a 44K 60-mer oligo array (Potato Oligo Chip Initiative: POCI). In this study, we attempt to identify genes controlling and driving the process of tuber initiation and growth by implementing large-scale transcriptional changes using the newly developed POCI array. Major gene expression profiles could be identified exhibiting differential expression at key developmental stages. These profiles were associated with functional roles in cell division and growth. A subset of genes involved in the regulation of the cell cycle, based on their Gene Ontology classification, exhibit a clear transient upregulation at tuber onset indicating increased cell division during these stages. The POCI array allows the study of potato gene expression on a much broader level than previously possible and will greatly enhance analysis of transcriptional control mechanisms in a wide range of potato research areas. POCI sequence and annotation data are publicly available through the POCI database (http://pgrc.ipk-gatersleben.de/poci).
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In the absence of market frictions, the cost-of-carry model of stock index futures pricing predicts that returns on the underlying stock index and the associated stock index futures contract will be perfectly contemporaneously correlated. Evidence suggests, however, that this prediction is violated with clear evidence that the stock index futures market leads the stock market. It is argued that traditional tests, which assume that the underlying data generating process is constant, might be prone to overstate the lead-lag relationship. Using a new test for lead-lag relationships based on cross correlations and cross bicorrelations it is found that, contrary to results from using the traditional methodology, periods where the futures market leads the cash market are few and far between and when any lead-lag relationship is detected, it does not last long. Overall, the results are consistent with the prediction of the standard cost-of-carry model and market efficiency.
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This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes
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We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.