251 resultados para pair


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Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of tibia. Selection of the correct nail insertion point is important for axial alignment of bone fragments and to avoid iatrogenic fractures. However, the standard entry point (SEP) may not always optimise the bone-nail fit due to geometric variations of bones. This study aimed to investigate the optimal entry for a given bone-nail pair using the fit quantification software tool previously developed by the authors. The misfit was quantified for 20 bones with two nail designs (ETN and ETN-Proximal Bend) related to the SEP and 5 entry points which were 5 mm and 10 mm away from the SEP. The SEP was the optimal entry point for 50% of the bones used. For the remaining bones, the optimal entry point was located 5 mm away from the SEP, which improved the overall fit by 40% on average. However, entry points 10 mm away from the SEP doubled the misfit. The optimised bone-nail fit can be achieved through the SEP and within the range of a 5 mm radius, except posteriorly. The study results suggest that the optimal entry point should be selected by considering the fit during insertion and not only at the final position.

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Methods are presented for the production, affinity purification and analysis of plasmid DNA (pDNA). Batch fermentation is used for the production of the pDNA, and expanded bed chromatography, via the use of a dual affinity glutathione S-transferase (GST) fusion protein, is used for the capture and purification of the pDNA. The protein is composed of GST, which displays affinity for glutathione immobilized to a solid-phase adsorbent, fused to a zinc finger transcription factor, which displays affinity for a target 9-base pair sequence contained within the target pDNA. A Picogreen™ fluorescence assay and/or anx ethidium bromide agarose gel electrophoresis assay can be used to analyze the eluted pDNA.

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Magnetic resonance is a well-established tool for structural characterisation of porous media. Features of pore-space morphology can be inferred from NMR diffusion-diffraction plots or the time-dependence of the apparent diffusion coefficient. Diffusion NMR signal attenuation can be computed from the restricted diffusion propagator, which describes the distribution of diffusing particles for a given starting position and diffusion time. We present two techniques for efficient evaluation of restricted diffusion propagators for use in NMR porous-media characterisation. The first is the Lattice Path Count (LPC). Its physical essence is that the restricted diffusion propagator connecting points A and B in time t is proportional to the number of distinct length-t paths from A to B. By using a discrete lattice, the number of such paths can be counted exactly. The second technique is the Markov transition matrix (MTM). The matrix represents the probabilities of jumps between every pair of lattice nodes within a single timestep. The propagator for an arbitrary diffusion time can be calculated as the appropriate matrix power. For periodic geometries, the transition matrix needs to be defined only for a single unit cell. This makes MTM ideally suited for periodic systems. Both LPC and MTM are closely related to existing computational techniques: LPC, to combinatorial techniques; and MTM, to the Fokker-Planck master equation. The relationship between LPC, MTM and other computational techniques is briefly discussed in the paper. Both LPC and MTM perform favourably compared to Monte Carlo sampling, yielding highly accurate and almost noiseless restricted diffusion propagators. Initial tests indicate that their computational performance is comparable to that of finite element methods. Both LPC and MTM can be applied to complicated pore-space geometries with no analytic solution. We discuss the new methods in the context of diffusion propagator calculation in porous materials and model biological tissues.

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Through larger-scale molecular dynamics simulations, we investigated the impacts from vacancy-initiated linkages on the thermal conductivity of bilayer graphene sheets (of size L × W = 24.5 nm × 3.7 nm). Three different interlayer linkages, including divacancy bridging, “spiro” interstitial bridging and Frenkel pair defects, are considered. It is found that the presence of interlayer linkages induces a significant degradation in the thermal conductivity of the bilayer graphene sheet. The degradation is strongly dependent on the interlayer linkage type, concentration and location. More importantly, the linkages that contain vacancies lead to more severe suppression of the thermal conductivity, in agreement with theoretical predictions that vacancies induce strong phonon scattering. Our finding provides useful guidelines for the application of multilayer graphene sheets in practical thermal management.

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The NLM stream cipher designed by Hoon Jae Lee, Sang Min Sung, Hyeong Rag Kim is a strengthened version of the LM summation generator that combines linear and non-linear feedback shift registers. In recent works, the NLM cipher has been used for message authentication in lightweight communication over wireless sensor networks and for RFID authentication protocols. The work analyses the security of the NLM stream cipher and the NLM-MAC scheme that is built on the top of the NLM cipher. We first show that the NLM cipher suffers from two major weaknesses that lead to key recovery and forgery attacks. We prove the internal state of the NLM cipher can be recovered with time complexity about nlog7×2, where the total length of internal state is 2⋅n+22⋅n+2 bits. The attack needs about n2n2 key-stream bits. We also show adversary is able to forge any MAC tag very efficiently by having only one pair (MAC tag, ciphertext). The proposed attacks are practical and break the scheme with a negligible error probability.

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This paper addresses the development of trust in the use of Open Data through incorporation of appropriate authentication and integrity parameters for use by end user Open Data application developers in an architecture for trustworthy Open Data Services. The advantages of this architecture scheme is that it is far more scalable, not another certificate-based hierarchy that has problems with certificate revocation management. With the use of a Public File, if the key is compromised: it is a simple matter of the single responsible entity replacing the key pair with a new one and re-performing the data file signing process. Under this proposed architecture, the the Open Data environment does not interfere with the internal security schemes that might be employed by the entity. However, this architecture incorporates, when needed, parameters from the entity, e.g. person who authorized publishing as Open Data, at the time that datasets are created/added.

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The most important aspect of modelling a geological variable, such as metal grade, is the spatial correlation. Spatial correlation describes the relationship between realisations of a geological variable sampled at different locations. Any method for spatially modelling such a variable should be capable of accurately estimating the true spatial correlation. Conventional kriged models are the most commonly used in mining for estimating grade or other variables at unsampled locations, and these models use the variogram or covariance function to model the spatial correlations in the process of estimation. However, this usage assumes the relationships of the observations of the variable of interest at nearby locations are only influenced by the vector distance between the locations. This means that these models assume linear spatial correlation of grade. In reality, the relationship with an observation of grade at a nearby location may be influenced by both distance between the locations and the value of the observations (ie non-linear spatial correlation, such as may exist for variables of interest in geometallurgy). Hence this may lead to inaccurate estimation of the ore reserve if a kriged model is used for estimating grade of unsampled locations when nonlinear spatial correlation is present. Copula-based methods, which are widely used in financial and actuarial modelling to quantify the non-linear dependence structures, may offer a solution. This method was introduced by Bárdossy and Li (2008) to geostatistical modelling to quantify the non-linear spatial dependence structure in a groundwater quality measurement network. Their copula-based spatial modelling is applied in this research paper to estimate the grade of 3D blocks. Furthermore, real-world mining data is used to validate this model. These copula-based grade estimates are compared with the results of conventional ordinary and lognormal kriging to present the reliability of this method.

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The genomics era provides opportunities to assess the genetic overlap across phenotypes at the measured genotype level; however, current approaches require individual-level genome-wide association (GWA) single nucleotide polymorphism (SNP) genotype data in one or both of a pair of GWA samples. To facilitate the discovery of pleiotropic effects and examine genetic overlap across two phenotypes, I have developed a user-friendly web-based application called SECA to perform SNP effect concordance analysis using GWA summary results. The method is validated using publicly available summary data from the Psychiatric Genomics Consortium.

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Cued recall and item recognition are considered the standard episodic memory retrieval tasks. However, only the neural correlates of the latter have been studied in detail with fMRI. Using an event-related fMRI experimental design that permits spoken responses, we tested hypotheses from an auto-associative model of cued recall and item recognition [Chappell, M., & Humphreys, M. S. (1994). An auto-associative neural network for sparse representations: Analysis and application to models of recognition and cued recall. Psychological Review, 101, 103-128]. In brief, the model assumes that cues elicit a network of phonological short term memory (STM) and semantic long term memory (LTM) representations distributed throughout the neocortex as patterns of sparse activations. This information is transferred to the hippocampus which converges upon the item closest to a stored pattern and outputs a response. Word pairs were learned from a study list, with one member of the pair serving as the cue at test. Unstudied words were also intermingled at test in order to provide an analogue of yes/no recognition tasks. Compared to incorrectly rejected studied items (misses) and correctly rejected (CR) unstudied items, correctly recalled items (hits) elicited increased responses in the left hippocampus and neocortical regions including the left inferior prefrontal cortex (LIPC), left mid lateral temporal cortex and inferior parietal cortex, consistent with predictions from the model. This network was very similar to that observed in yes/no recognition studies, supporting proposals that cued recall and item recognition involve common rather than separate mechanisms.

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The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples.

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We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

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The Older Australian Twins Study (OATS) was recently initiated to investigate genetic and environmental factors and their associations and interactions in healthy brain ageing and ageing-related neurocognitive disorders. The study extends the classic MZ-DZ design to include one or two equivalently aged siblings for each twin pair and utilizes the rich resources of the Australian Twin Registry. The study has a number of distinguishing features including comprehensive psychiatric, neuropsychological, cardiovascular, metabolic, and neuroimaging assessments, a longitudinal design and links with a brain donor program. The study measures many behavioral and environmental factors, but in particular lifetime physical and mental activity, physical and psychological trauma, loss of parent early in life, later losses and life events, early-life socioeconomic environment, alcohol and drug use, occupational exposure, and nutrition. It also includes comprehensive cardiovascular assessment, blood biochemistry, genetics and proteomics. The socio-demographic and health data on the first 172 pairs of twins participating in this study are presented. Prevalence of mild cognitive impairment is 12.8% and of dementia 1.5% in the sample. The target sample size is 1000, with at least 400 pairs of twins aged 65-90 years. The cohort will be assessed every two years, with in-depth assessments being repeated. OATS offers an excellent opportunity for collaboration with other similar studies as well as researchers who share the same interests.

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This paper uses a unique data set of trades in a unique pair of securities that enables the precise identification of individual broker activity and the trade direction of that activity. We find direct evidence that the imposition (removal) of short-sale constraints limits (generates) trading activity consistent with brokers exploiting apparent mispricing.

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The oily bittering Acheilognathus koreensis is a freshwater species that is endemic to Korea and is experiencing severe declines in natural populations as a result of habitat fragmentation and water pollution. For the conservation and restoration of this species, it is necessary to assess its genetic diversity at the population level. We developed 13 polymorphic microsatellite loci that were used to analyze the genetic diversity of two populations collected from the Kum River and the Tamjin River in Korea. All loci exhibited Mendelian inheritance patterns when examined in controlled crosses. Both populations revealed high levels of variability, with the number of alleles ranging from 3 to 20 and observed and expected heterozygosities ranging from 0.500 to 0.969 and from 0.529 to 0.938, respectively. None of the loci showed significant deviation from Hardy–Weinberg equilibrium, and one pair of loci showed significant linkage disequilibrium after Bonferroni correction. Pairwise F ST and genetic distance estimation showed significant differences between two populations. These results suggest that the microsatellites developed herein can be used to study the genetic diversity, population structure and conservation measure of A. koreensis.

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Silk fibroin provides a promising biomaterial for ocular tissue reconstruction including the damaged outer blood-retinal barrier of patients afflicted with age-related macular degeneration (AMD). The aim of the present study was to evaluate the function of retinal pigment epithelial (RPE) cells in vitro, when grown on fibroin membranes manufactured to a similar thickness as Bruch’s membrane (3 μm). Confluent cultures of RPE cells (ARPE-19) were established on fibroin membranes and maintained under conditions designed to promote maturation over 4 months. Control cultures were grown on polyester cell culture well inserts (Transwell). Cultures established on either material developed a cobblestoned morphology with partial pigmentation within 12 weeks. Immunocytochemistry at 16 weeks revealed a similar distribution pattern between cultures for F-actin, ZO-1, ezrin, cytokeratin pair 8/18, RPE-65 and Na+/K+-ATPase. Electron microscopy revealed that cultures grown on fibroin displayed a rounder apical surface with a more dense distribution of microvilli. Both cultures avidly ingested fluorescent microspheres coated with vitronectin and bovine serum albumin (BSA), but not controls coated with BSA alone. VEGF and PEDF were detected in the conditioned medium collected from above and below both membrane types. Levels of PEDF were significantly higher than for VEGF on both membranes and a trend was observed towards larger amounts of PEDF in apical compartments. These findings demonstrate that RPE cell functions on fibroin membranes are equivalent to those observed for standard test materials (polyester membranes). As such, these studies support advancement to studies of RPE cell implantation on fibroin membranes in a preclinical model.