Improvements in the 6-Min Walk Test and Spirometry Following Thoracentesis for Symptomatic Pleural Effusions

Background: Impairment in pulmonary capacity due to pleural effusion compromises daily activity. Removal of fluid improves symptoms, but the impact, especially on exercise capacity, has not been determined. Methods: Twenty-five patients with unilateral pleural effusion documented by chest radiograph were included. The 6-min walk test, Borg modified dyspnea score, FVC, and FEV, were analyzed before and 48 h after the removal of large pleural effusions. Results: The mean fluid removed was 1,564 +/- 695 mL. After the procedure, values of FVC, FEV and 6-min walk distance increased (P<.001), whereas dyspnea decreased (P<.001). Statistical correlations (P<.001) between 6-min walk distance and FVC (r=0.725) and between 6-min walk distance and FEV, (r=0.661) were observed. Correlations also were observed between the deltas (prethoracentesis X postthoracentesis) of the 6-min walk test and the percentage of FVC (r=0.450) and of FEV, (r=0.472) divided by the volume of fluid removed (P<.05). Conclusion: In addition to the improvement in lung function after thoracentesis, the benefits of fluid removal are more evident in situations of exertion, allowing better readaptation of patients to routine activities. CHEST 2011; 139(6):1424-1429

A fuzzy max-flow min-cut theorem

Interval-valued versions of the max-flow min-cut theorem and Karp-Edmonds algorithm are developed and provide robustness estimates for flows in networks in an imprecise or uncertain environment. These results are extended to networks with fuzzy capacities and flows. (C) 2001 Elsevier Science B.V. All rights reserved.

Unified min-max and interlacing theorems for linear operators

There exist striking analogies in the behaviour of eigenvalues of Hermitian compact operators, singular values of compact operators and invariant factors of homomorphisms of modules over principal ideal domains, namely diagonalization theorems, interlacing inequalities and Courant-Fischer type formulae. Carlson and Sa [D. Carlson and E.M. Sa, Generalized minimax and interlacing inequalities, Linear Multilinear Algebra 15 (1984) pp. 77-103.] introduced an abstract structure, the s-space, where they proved unified versions of these theorems in the finite-dimensional case. We show that this unification can be done using modular lattices with Goldie dimension, which have a natural structure of s-space in the finite-dimensional case, and extend the unification to the countable-dimensional case.

Efficient computation of min and max sensor values in multihop networks

Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take individual sensor readings, however, in many cases, it is relevant to compute aggregated quantities of these readings. In fact, the minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. In this context, we propose an algorithm for computing the min or max of sensor readings in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter.

Exploiting a prioritized MAC protocol to efficiently compute min and max in multihop networks

Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take sensor readings but individual sensor readings are not very important. It is important however to compute aggregated quantities of these sensor readings. The minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. We propose an algorithm for computing the min or max of sensor reading in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter.

Desenvolvimento de padrão gravimétrico de medição de caudal de fluidos entre 10 mL/min e 100 nL/min

Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.

TUL:n toiminta ollut korvaamaton rikkaus

Puhe TUL:n VIII liittojuhlassa 10.6.1979