928 resultados para Normalized Coarse-grained Information Rate (NCIR).


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In this study, we carried out a comparative analysis between two classical methodologies to prospect residue contacts in proteins: the traditional cutoff dependent (CD) approach and cutoff free Delaunay tessellation (DT). In addition, two alternative coarse-grained forms to represent residues were tested: using alpha carbon (CA) and side chain geometric center (GC). A database was built, comprising three top classes: all alpha, all beta, and alpha/beta. We found that the cutoff value? at about 7.0 A emerges as an important distance parameter.? Up to 7.0 A, CD and DT properties are unified, which implies that at this distance all contacts are complete and legitimate (not occluded). We also have shown that DT has an intrinsic missing edges problem when mapping the first layer of neighbors. In proteins, it may produce systematic errors affecting mainly the contact network in beta chains with CA. The almost-Delaunay (AD) approach has been proposed to solve this DT problem. We found that even AD may not be an advantageous solution. As a consequence, in the strict range up ? to 7.0 A, the CD approach revealed to be a simpler, more complete, and reliable technique than DT or AD. Finally, we have shown that coarse-grained residue representations may introduce bias in the analysis of neighbors in cutoffs up to ? 6.8 A, with CA favoring alpha proteins and GC favoring beta proteins. This provides an additional argument pointing to ? the value of 7.0 A as an important lower bound cutoff to be used in contact analysis of proteins.

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In this work we have studied, by means of Molecular Dynamics simulations, the process of denaturation and self-assembly of short oligonucleotides. Supramolecular ordering of DNA short strands is a promising field which is constantly enriched with new findings. Examples are provided by micellar and fibrils formations and due to the selectivity of DNA bindings, "intelligent" devices have been developed to perform simple logic operations. It is worth to notice that computer simulations of these DNA nanosystems would complement experiments with detailed insight into processes involved in self-assembly. In order to obtain an accurate description of the interactions involved in the complex structure of DNA we used oxDNA, a coarse-grained model developed by Ouldridge. We simulated the melting transition of 4, 6, and 8 base pair sequences. Sequence and length dependence were analyzed, specifically we compared thermodynamic parameters DeltaH, DeltaS and the melting temperature with literature results. Moreover, we have attempted to reproduce liquid crystal ordering of the ultrashort sequence GCCG at relatively high saline concentration, until now only experimentally observed in Bellini's works. We found that our simple model successfully reproduces the experimental phase sequence (isotropic, nematic, columnar) at T= 5 °C as a function of oligonucleotide concentration, and we fully characterized the microscopic structure of the three phases.

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This paper proposes a dynamic framework to study the timing of balance of paymentscrises. The model incorporates two main ingredients: (i) investors have private information; (ii)investors interact in a dynamic setting, weighing the high returns on domestic assets against the incentives to pull out before the devaluation. The model shows that the presence of disaggregated information delays the onset of BOP crises, giving rise to discrete devaluations. It also shows that high interest rates can be eective in delaying and possibly avoiding the abandonment of the peg. The optimal policy is to raise interest rates sharply as fundamentals become very weak. However, this policy is time inconsistent, suggesting a role for commitment devices such as currency boards or IMF pressure.

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Localization, which is the ability of a mobile robot to estimate its position within its environment, is a key capability for autonomous operation of any mobile robot. This thesis presents a system for indoor coarse and global localization of a mobile robot based on visual information. The system is based on image matching and uses SIFT features as natural landmarks. Features extracted from training images arestored in a database for use in localization later. During localization an image of the scene is captured using the on-board camera of the robot, features are extracted from the image and the best match is searched from the database. Feature matching is done using the k-d tree algorithm. Experimental results showed that localization accuracy increases with the number of training features used in the training database, while, on the other hand, increasing number of features tended to have a negative impact on the computational time. For some parts of the environment the error rate was relatively high due to a strong correlation of features taken from those places across the environment.

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The effect of the heat flux on the rate of chemical reaction in dilute gases is shown to be important for reactions characterized by high activation energies and in the presence of very large temperature gradients. This effect, obtained from the second-order terms in the distribution function (similar to those obtained in the Burnett approximation to the solution of the Boltzmann equation), is derived on the basis of information theory. It is shown that the analytical results describing the effect are simpler if the kinetic definition for the nonequilibrium temperature is introduced than if the thermodynamic definition is introduced. The numerical results are nearly the same for both definitions

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Glass is a unique material with a long history. Several glass products are used daily in our everyday life, often unnoticed. Glass can be found not only in obvious applications such as tableware, windows, and light bulbs, but also in tennis rackets, windmill turbine blades, optical devices, and medical implants. The glasses used at present as implants are inorganic silica-based melt-derived compositions mainly for hard-tissue repair as bone graft substitute in dentistry and orthopedics. The degree of glass reactivity desired varies according to implantation situation and it is vital that the ion release from any glasses used in medical applications is controlled. Understanding the in vitro dissolution rate of glasses provides a first approximation of their behavior in vivo. Specific studies concerning dissolution properties of bioactive glasses have been relatively scarce and mostly concentrated to static condition studies. The motivation behind this work was to develop a simple and accurate method for quantifying the in vitro dissolution rate of highly different types of glass compositions with interest for future clinical applications. By combining information from various experimental conditions, a better knowledge of glass dissolution and the suitability of different glasses for different medical applications can be obtained. Thus, two traditional and one novel approach were utilized in this thesis to study glass dissolution. The chemical durability of silicate glasses was tested in water and TRIS-buffered solution at static and dynamic conditions. The traditional in vitro testing with a TRISbuffered solution under static conditions works well with bioactive or with readily dissolving glasses, and it is easy to follow the ion dissolution reactions. However, in the buffered solution no marked differences between the more durable glasses were observed. The hydrolytic resistance of the glasses was studied using the standard procedure ISO 719. The relative scale given by the standard failed to provide any relevant information when bioactive glasses were studied. However, the clear differences in the hydrolytic resistance values imply that the method could be used as a rapid test to get an overall idea of the biodegradability of glasses. The standard method combined with the ion concentration and pH measurements gives a better estimate of the hydrolytic resistance because of the high silicon amount released from a glass. A sensitive on-line analysis method utilizing inductively coupled plasma optical emission spectrometer and a flow-through micro-volume pH electrode was developed to study the initial dissolution of biocompatible glasses. This approach was found suitable for compositions within a large range of chemical durability. With this approach, the initial dissolution of all ions could be measured simultaneously and quantitatively, which gave a good overall idea of the initial dissolution rates for the individual ions and the dissolution mechanism. These types of results with glass dissolution were presented for the first time during the course of writing this thesis. Based on the initial dissolution patterns obtained with the novel approach using TRIS, the experimental glasses could be divided into four distinct categories. The initial dissolution patterns of glasses correlated well with the anticipated bioactivity. Moreover, the normalized surface-specific mass loss rates and the different in vivo models and the actual in vivo data correlated well. The results suggest that this type of approach can be used for prescreening the suitability of novel glass compositions for future clinical applications. Furthermore, the results shed light on the possible bioactivity of glasses. An additional goal in this thesis was to gain insight into the phase changes occurring during various heat treatments of glasses with three selected compositions. Engineering-type T-T-T curves for glasses 1-98 and 13-93 were stablished. The information gained is essential in manufacturing amorphous porous implants or for drawing of continuous fibers of the glasses. Although both glasses can be hot worked to amorphous products at carefully controlled conditions, 1-98 showed one magnitude greater nucleation and crystal growth rate than 13-93. Thus, 13-93 is better suited than 1-98 for working processes which require long residence times at high temperatures. It was also shown that amorphous and partially crystalline porous implants can be sintered from bioactive glass S53P4. Surface crystallization of S53P4, forming Na2O∙CaO∙2SiO2, was observed to start at 650°C. The secondary crystals of Na2Ca4(PO4)2SiO4, reported for the first time in this thesis, were detected at higher temperatures, from 850°C to 1000°C. The crystal phases formed affected the dissolution behavior of the implants in simulated body fluid. This study opens up new possibilities for using S53P4 to manufacture various structures, while tailoring their bioactivity by controlling the proportions of the different phases. The results obtained in this thesis give valuable additional information and tools to the state of the art for designing glasses with respect to future clinical applications. With the knowledge gained we can identify different dissolution patters and use this information to improve the tuning of glass compositions. In addition, the novel online analysis approach provides an excellent opportunity to further enhance our knowledge of glass behavior in simulated body conditions.

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This paper presents an adaptive frame length mechanism based on a cross-layer analysis of intrinsic relations between the MAC frame length, bit error rate (BER) of the wireless link and normalized goodput. The proposed mechanism selects the optimal frame length that keeps the service normalized goodput at required levels while satisfying the lowest requirement on the BER, thus increasing the transmission reliability. Numerical results are provided and show that an optimal frame length satisfying the lowest BER requirement does indeed exist. The performance of BER requirement as a function of the MAC frame length is evaluated and compared for transmission scenarios with and without automatic repeat request (ARQ). Furthermore, issues related to the MAC overhead length are also discussed to illuminate the functionality and performance of the proposed mechanism.

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This paper uses appropriately modified information criteria to select models from the GARCH family, which are subsequently used for predicting US dollar exchange rate return volatility. The out of sample forecast accuracy of models chosen in this manner compares favourably on mean absolute error grounds, although less favourably on mean squared error grounds, with those generated by the commonly used GARCH(1, 1) model. An examination of the orders of models selected by the criteria reveals that (1, 1) models are typically selected less than 20% of the time.

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Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.

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Stress corrosion cracking susceptibility was investigated for an ultra-fine grained (UFG) AI-7.5Mg alloy and a conventional 5083 H111 alloy in natural seawater using slow strain rate testing (SSRT) at very slow strain rates between 1E(-5) s(-1), 1E(-6) s(-1) and 1E(-7) s(-1). The UFG Al-7.5Mg alloy was produced by cryomilling, while the 5083 H111 alloy is considered as a wrought manufactured product. The response of tensile properties to strain rate was analyzed and compared. Negative strain rate sensitivity was observed for both materials in terms of the elongation to failure. However, the UFG alloy displayed strain rate sensitivity in relation to strength while the conventional alloy was relatively strain rate insensitive. The mechanical behavior of the conventional 5083 alloy was attributed to dynamic strain aging (DSA) and delayed pit propagation while the performance of the UFG alloy was related to a diffusion-mediated stress relaxation mechanism that successfully delayed crack initiation events, counteracted by exfoliation and pitting which enhanced crack initiation. (C) 2014 Elsevier B.V. All rights reserved.

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OBJECTIVES: To evaluate the relationship between T1 after intravenous contrast administration (T1Gd) and Delta relaxation rate (DeltaR1) = (1/T1(Gd) - 1/T1o) in the delayed Gadolinium-Enhanced MRI of cartilage (dGEMRIC) evaluation of cartilage repair tissue. MATERIALS AND METHODS: Thirty single MR examinations from 30 patients after matrix-associated autologous chondrocyte transplantations of the knee joint with different postoperative intervals were examined using an 8-channel knee-coil at 3T. T1 mapping using a 3D GRE sequence with a 35/10 degrees flip angle excitation pulse combination was performed before and after contrast administration (dGEMRIC technique). T1 postcontrast (T1(Gd)) and the DeltaR1 (relative index of pre- and postcontrast R1 value) were calculated for repair tissue and the weight-bearing normal appearing control cartilage. For evaluation of the different postoperative intervals, MR exams were subdivided into 3 groups (up to 12 months, 12-24 months, more than 24 months). For statistical analysis Spearman correlation coefficients were calculated. RESULTS: The mean value for T1 postcontrast was 427 +/- 159 ms, for DeltaR1 1.85 +/- 1.0; in reference cartilage 636 +/- 181 ms for T1 postcontrast and 0.83 +/- 0.5 for DeltaR1.The correlation coefficients were highly significant between T1 (Gd) and DeltaR1 for repair tissue (0.969) as well as normal reference cartilage (0.928) in total, and for the reparative cartilage in the early, middle postoperative, and late postoperative interval after surgery (R values: -0.986, -0.970, and -0.978, respectively). Using either T1(Gd) or DeltaR1, the 2 metrics resulted in similar conclusions regarding the time course of change of repair tissue and control tissue, namely that highly significant (P > 0.01) differences between cartilage repair tissue and reference cartilage were found for all follow-up groups. Additionally, for both metrics highly significant differences (P < 0.01) between early follow up and the 2 later postoperative groups for cartilage repair tissue were found. No statistical differences were found between the 2 later follow-up groups of reparative cartilage either for T1 (Gd) or DeltaR1. CONCLUSION: The high correlation between T1 (Gd) and DeltaR1 and the comparable conclusions reached utilizing metric implies that T1 mapping before intravenous administration of MR contrast agent is not necessary for the evaluation of repair tissue. This will help to reduce costs, inconvenience for the patients, simplifies the examination procedure, and makes dGEMRIC more attractive for follow-up of patients after cartilage repair surgeries.

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Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

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Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

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To reach the goals established by the Institute of Medicine (IOM) and the Centers for Disease Control's (CDC) STOP TB USA, measures must be taken to curtail a future peak in Tuberculosis (TB) incidence and speed the currently stagnant rate of TB elimination. Both efforts will require, at minimum, the consideration and understanding of the third dimension of TB transmission: the location-based spread of an airborne pathogen among persons known and unknown to each other. This consideration will require an elucidation of the areas within the U.S. that have endemic TB. The Houston Tuberculosis Initiative (HTI) was a population-based active surveillance of confirmed Houston/Harris County TB cases from 1995–2004. Strengths in this dataset include the molecular characterization of laboratory confirmed cases, the collection of geographic locations (including home addresses) frequented by cases, and the HTI time period that parallels a decline in TB incidence in the United States (U.S.). The HTI dataset was used in this secondary data analysis to implement a GIS analysis of TB cases, the locations frequented by cases, and their association with risk factors associated with TB transmission. ^ This study reports, for the first time, the incidence of TB among the homeless in Houston, Texas. The homeless are an at-risk population for TB disease, yet they are also a population whose TB incidence has been unknown and unreported due to their non-enumeration. The first section of this dissertation identifies local areas in Houston with endemic TB disease. Many Houston TB cases who reported living in these endemic areas also share the TB risk factor of current or recent homelessness. Merging the 2004–2005 Houston enumeration of the homeless with historical HTI surveillance data of TB cases in Houston enabled this first-time report of TB risk among the homeless in Houston. The homeless were more likely to be US-born, belong to a genotypic cluster, and belong to a cluster of a larger size. The calculated average incidence among homeless persons was 411/100,000, compared to 9.5/100,000 among housed. These alarming rates are not driven by a co-infection but by social determinants. The unsheltered persons were hospitalized more days and required more follow-up time by staff than those who reported a steady housing situation. The homeless are a specific example of the increased targeting of prevention dollars that could occur if TB rates were reported for specific areas with known health disparities rather than as a generalized rate normalized over a diverse population. ^ It has been estimated that 27% of Houstonians use public transportation. The city layout allows bus routes to run like veins connecting even the most diverse of populations within the metropolitan area. Secondary data analysis of frequent bus use (defined as riding a route weekly) among TB cases was assessed for its relationship with known TB risk factors. The spatial distribution of genotypic clusters associated with bus use was assessed, along with the reported routes and epidemiologic-links among cases belonging to the identified clusters. ^ TB cases who reported frequent bus use were more likely to have demographic and social risk factors associated with poverty, immune suppression and health disparities. An equal proportion of bus riders and non-bus riders were cultured for Mycobacterium tuberculosis, yet 75% of bus riders were genotypically clustered, indicating recent transmission, compared to 56% of non-bus riders (OR=2.4, 95%CI(2.0, 2.8), p<0.001). Bus riders had a mean cluster size of 50.14 vs. 28.9 (p<0.001). Second order spatial analysis of clustered fingerprint 2 (n=122), a Beijing family cluster, revealed geographic clustering among cases based on their report of bus use. Univariate and multivariate analysis of routes reported by cases belonging to these clusters found that 10 of the 14 clusters were associated with use. Individual Metro routes, including one route servicing the local hospitals, were found to be risk factors for belonging to a cluster shown to be endemic in Houston. The routes themselves geographically connect the census tracts previously identified as having endemic TB. 78% (15/23) of Houston Metro routes investigated had one or more print groups reporting frequent use for every HTI study year. We present data on three specific but clonally related print groups and show that bus-use is clustered in time by route and is the only known link between cases in one of the three prints: print 22. (Abstract shortened by UMI.)^

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Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.