Chest size matching in single and double lung transplantation

We applied predicted vital capacity to chest size matching between donor and recipient in lung transplantation to 15 single-lung transplant recipients with pulmonary fibrosis and to 20 double-lung transplant recipients with emphysema or non-emphysema. The predicted vital capacity of the donor was significantly correlated with the predicted vital capacity of the recipient both in double-lung transplantation (r = 0.79, p = 0.001) and single-lung transplantation (r = 0.71, p = 0.003). In double-lung transplantation, the post-transplant vital capacity was correlated with the predicted vital capacity of the recipient (r = 0.74, p = 0.002). Emphysema patients and non-emphysema patients contributed equally to this correlation. In left single lung transplantation, there was a weak correlation between the post-transplant vital capacity and the predicted vital capacity of the donor in the allograft (r = 0.57, p = 0.1095). In right single lung transplantation, the post-transplant vital capacity of the allograft tended to be correlated with the predicted vital capacity of recipient (r = 0.77, p = 0.0735). We concluded that donors were actually selected based on the comparison of predicted vital capacity between donor and recipient. In double-lung transplantation, the post-transplant vital capacity was limited by the recipient's normal thoracic volume and was not influenced by underlying pulmonary disease. In single-lung transplantation with pulmonary fibrosis, the allograft transplanted in the left chest could expand to its own size, and the allograft transplanted in the right chest could expand to the recipient's normal thoracic volume as in double-lung transplantation.

Sharpness Matching in Stereo Images

When stereo images are captured under less than ideal conditions, there may be inconsistencies between the two images in brightness, contrast, blurring, etc. When stereo matching is performed between the images, these variations can greatly reduce the quality of the resulting depth map. In this paper we propose a method for correcting sharpness variations in stereo image pairs which is performed as a pre-processing step to stereo matching. Our method is based on scaling the 2D discrete cosine transform (DCT) coefficients of both images so that the two images have the same amount of energy in each of a set of frequency bands. Experiments show that applying the proposed correction method can greatly improve the disparity map quality when one image in a stereo pair is more blurred than the other.

Explicit context matching in content-based publish/subscribe systems

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without fltering the cost of SIENA-like topology changes.

Applying machine learning to catalogue matching in astrophysics

We present the results of applying automated machine learning techniques to the problem of matching different object catalogues in astrophysics. In this study, we take two partially matched catalogues where one of the two catalogues has a large positional uncertainty. The two catalogues we used here were taken from the H I Parkes All Sky Survey (HIPASS) and SuperCOSMOS optical survey. Previous work had matched 44 per cent (1887 objects) of HIPASS to the SuperCOSMOS catalogue. A supervised learning algorithm was then applied to construct a model of the matched portion of our catalogue. Validation of the model shows that we achieved a good classification performance (99.12 per cent correct). Applying this model to the unmatched portion of the catalogue found 1209 new matches. This increases the catalogue size from 1887 matched objects to 3096. The combination of these procedures yields a catalogue that is 72 per cent matched.

Imitating the neighbours: vocal dialect matching in a mimic-model system

Vocal mimicry provides a unique system for investigating song learning and cultural evolution in birds. Male lyrebirds produce complex vocal displays that include extensive and accurate mimicry of many other bird species. We recorded and analysed the songs of the Albert's lyrebird (Menura alberti) and its most commonly imitated model species, the satin bowerbird (Ptilonorhynchus violaceus), at six sites in southeast Queensland, Australia. We show that each population of lyrebirds faithfully reproduces the song of the local population of bowerbirds. Within a population, lyrebirds show less variation in song structure than the available variation in the songs of the models. These results provide the first quantitative evidence for dialect matching in the songs of two species that have no direct ecological relationship.

Sequences of Maximal Degree Vertices in Graphs

2000 Mathematics Subject Classification: 05C35.

A Study of Some Centrality Measures in Graphs

Centrality is in fact one of the fundamental notions in graph theory which has established its close connection with various other areas like Social networks, Flow networks, Facility location problems etc. Even though a plethora of centrality measures have been introduced from time to time, according to the changing demands, the term is not well defined and we can only give some common qualities that a centrality measure is expected to have. Nodes with high centrality scores are often more likely to be very powerful, indispensable, influential, easy propagators of information, significant in maintaining the cohesion of the group and are easily susceptible to anything that disseminate in the network.

Selection of Matching Variables in Community Health Intervention Trials

In a matched experimental design, the effectiveness of matching in reducing bias and increasing power depends on the strength of the association between the matching variable and the outcome of interest. In particular, in the design of a community health intervention trial, the effectiveness of a matched design, where communities are matched according to some community characteristic, depends on the strength of the correlation between the matching characteristic and the change in the health behavior being measured. We attempt to estimate the correlation between community characteristics and changes in health behaviors in four datasets from community intervention trials and observational studies. Community characteristics that are highly correlated with changes in health behaviors would potentially be effective matching variables in studies of health intervention programs designed to change those behaviors. Among the community characteristics considered, the urban-rural character of the community was the most highly correlated with changes in health behaviors. The correlations between Per Capita Income, Percent Low Income & Percent aged over 65 and changes in health behaviors were marginally statistically significant (p < 0.08).

Preference Structure and Random Paths to Stability in Matching Markets

This paper examines how preference correlation and intercorrelation combine to influence the length of a decentralized matching market's path to stability. In simulated experiments, marriage markets with various preference specifications begin at an arbitrary matching of couples and proceed toward stability via the random mechanism proposed by Roth and Vande Vate (1990). The results of these experiments reveal that fundamental preference characteristics are critical in predicting how long the market will take to reach a stable matching. In particular, intercorrelation and correlation are shown to have an exponential impact on the number of blocking pairs that must be randomly satisfied before stability is attained. The magnitude of the impact is dramatically different, however, depending on whether preferences are positively or negatively intercorrelated.

Topological SLAM using a graph-matching based method on omnidirectional images

Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.

A stable graph-based representation for object recognition through high-order matching

Many Object recognition techniques perform some flavour of point pattern matching between a model and a scene. Such points are usually selected through a feature detection algorithm that is robust to a class of image transformations and a suitable descriptor is computed over them in order to get a reliable matching. Moreover, some approaches take an additional step by casting the correspondence problem into a matching between graphs defined over feature points. The motivation is that the relational model would add more discriminative power, however the overall effectiveness strongly depends on the ability to build a graph that is stable with respect to both changes in the object appearance and spatial distribution of interest points. In fact, widely used graph-based representations, have shown to suffer some limitations, especially with respect to changes in the Euclidean organization of the feature points. In this paper we introduce a technique to build relational structures over corner points that does not depend on the spatial distribution of the features. © 2012 ICPR Org Committee.

Prevalence of cytomegalovirus infection in different patient groups of a urban university in Brazil

This study sought for etndence of previous CMV infection in patients of a general hospital serving the low income population of Rio de Janeiro. An enzyme immunoassay was used to detect anti-CMV antibodies in 713 typical hospital patients classified into eight different groups. Positive tests were found in 87% of pregnant women, 85% of newborns, 61% of pediatric patients, 77% of adolescent patients, 81% of adult patients, 87% of dialysed transplant candidates, 89% of kidney donors, and 92% of patients after transplantation. Depending of the subgroup studied these results carry different meanings and necessitate different clinical approaches. The risk of congenital disease is probably low in view of the reduced number of pregnant women still susceptible to primary infection. The number of primary infections will also be low in transplant recipients. However, those still susceptible will almost certainly acquire the infection from, their donor. Prophylactic CMV matching in kidney transplantation is not a realistic approach due to the low probability of finding pairs of seronegative donors and recipients.