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Abstract Background Reduced gas transfer in patients with pulmonary arterial hypertension (PAH) is traditionally attributed to remodeling and progressive loss of pulmonary arterial vasculature that results in decreased capillary blood volume available for gas exchange. Methods We tested this hypothesis by determination of lung diffusing capacity (DL) and its components, the alveolar capillary membrane diffusing capacity (Dm) and lung capillary blood volume (Vc) in 28 individuals with PAH in comparison to 41 healthy individuals, and in 19 PAH patients over time. Using single breath simultaneous measure of diffusion of carbon monoxide (DLCO) and nitric oxide (DLNO), DL and Dm were respectively determined, and Vc calculated. Dm and Vc were evaluated over time in relation to standard clinical indicators of disease severity, including brain natriuretic peptide (BNP), 6-minute walk distance (6MWD) and right ventricular systolic pressure (RVSP) by echocardiography. Results Both DLCO and DLNO were reduced in PAH as compared to controls and the lower DL in PAH was due to loss of both Dm and Vc (all p CO of PAH patients did not change over time, DLNO decreased by 24 ml/min/mmHg/year (p = 0.01). Consequently, Dm decreased and Vc tended to increase over time, which led to deterioration of the Dm/Vc ratio, a measure of alveolar-capillary membrane functional efficiency without changes in clinical markers. Conclusions The findings indicate that lower than normal gas transfer in PAH is due to loss of both Dm and Vc, but that deterioration of Dm/Vc over time is related to worsening membrane diffusion.

Segmenting precisely affected parts of the lungs from the output of CT (Computed Tomography) is critical in making inquiries on lung malignancy and can offer significant data for clinical conclusions. It plays a major and effective role in researches on lung diseases. The crux of the problem is developing automatic detection of lesion and segments them with perfect accuracy. Heterogeneity of lesion part makes segmentation a very difficult task. In TBGA (Toboggan Based Growing Automatic Segmentation Approach), the lack of degree of recognition results in difficulty in the boundary detection process during segmentation. To overcome the drawbacks, a Regression Neural Networks (RNN) Segmentation approach has been proposed in this paper. The degree of recognition is less in tissues which are associated to the neighboring lesion with pixels having same intensity. RNN provides a greater accuracy of recognition of the adjacent lesions with similar intensity when compared to other methods like Skeleton graph cut and Level set method. Segmentation is done based on the degree of recognition. So the RNN method proposed in this paper concentrates mainly on the precise detection of boundary for juxtapleural and juxtavascular lesions. The accuracy of segmenting lung parenchyma is a challenge in lesion segmentation. In RNN segmentation process, the result of parenchyma forms the basis of extracting lesion. RNN is a Learning Algorithm so the complexity of automatic lesion detection is avoided. RNN uses a trained set of data, so the resulting outcome is accurate. [ABSTRACT FROM AUTHOR]

The paper discusses the tracking of a manoeuvring target using fuzzy information fusion filters (FIFFs), based on bearing only measurements received from multiple sensors. While a number of tracking filters including the Kalman filters have been proposed and demonstrated successfully for tracking, the information filter has been reported to be capable of estimating the state of a target even without an initial estimate. However, the estimate is often seen to diverge after a short period. A FIFF has been shown to track small manoeuvres in target following a constant velocity model but is not effective when the target switches to a coordinated turn model. In this paper, the idea of using the FIFF for tracking manoeuvring target is proposed and demonstrated. The filter uses only the bearing measurements in tracking the target and also for detecting the manoeuvre. Using an adaptive turn rate model, the turning rate of the moving target is estimated from the range rate. Here, the range rate is also computed directly from bearing measurements. The detection of the onset of manoeuvre is on the basis of consistent change in the turning rate of the target. A number of different scenarios involving manoeuvring targets are given to demonstrate the efficacy of this approach. [ABSTRACT FROM AUTHOR]

The letter highlights the importance of modeling the phase noise of an oscillator using the impulse sensitivity function. A Colpitts oscillator in the common collector configuration is analyzed to obtain an expression for its phase noise. The oscillator design is thus optimized for phase noise with respect to process and design parameters. The fabricated voltage-controlled oscillator at an oscillating frequency of 52.8 GHz has a measured phase noise of −98.9° dBc/Hz at 1 MHz offset. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:290-295, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27320 [ABSTRACT FROM AUTHOR]