Meta-analysis of death and myocardial infarction in the DEFINE-FLAIR and iFR-SWEDEHEART trials: a hypothesis generating note of caution

In patients with coronary heart disease, revascularization can improve symptoms and in certain high-risk subgroups may improve prognosis. Coronary angiography provides anatomical information and the physiological significance of a stenosis can be determined using fractional flow reserve (FFR). Decisions on the need for and mode of revascularization can be optimized using FFR, however this involves administering adenosine to induce hyperemia. Generally, this test is well tolerated, but in some healthcare systems adenosine is either not licensed, unavailable, or expensive, limiting the use of FFR-guided management

Resolving depth measurement ambiguity with commercially available range imaging cameras

Time-of-flight range imaging is typically performed with the amplitude modulated continuous wave method. This involves illuminating a scene with amplitude modulated light. Reflected light from the scene is received by the sensor with the range to the scene encoded as a phase delay of the modulation envelope. Due to the cyclic nature of phase, an ambiguity in the measured range occurs every half wavelength in distance, thereby limiting the maximum useable range of the camera. This paper proposes a procedure to resolve depth ambiguity using software post processing. First, the range data is processed to segment the scene into separate objects. The average intensity of each object can then be used to determine which pixels are beyond the non-ambiguous range. The results demonstrate that depth ambiguity can be resolved for various scenes using only the available depth and intensity information. This proposed method reduces the sensitivity to objects with very high and very low reflectance, normally a key problem with basic threshold approaches. This approach is very flexible as it can be used with any range imaging camera. Furthermore, capture time is not extended, keeping the artifacts caused by moving objects at a minimum. This makes it suitable for applications such as robot vision where the camera may be moving during captures. The key limitation of the method is its inability to distinguish between two overlapping objects that are separated by a distance of exactly one non-ambiguous range. Overall the reliability of this method is higher than the basic threshold approach, but not as high as the multiple frequency method of resolving ambiguity

Polarized Diffuse Emission at 2.3 GHz in a High Galactic Latitude Area

Polarized diffuse emission observations at 2.3 GHz in a high Galactic latitude area are presented. The 2\degr X 2\degr field, centred in (\alpha=5^h,\delta=-49\degr), is located in the region observed by the BOOMERanG experiment. Our observations has been carried out with the Parkes Radio telescope and represent the highest frequency detection done to date in low emission areas. Because of a weaker Faraday rotation action, the high frequency allows an estimate of the Galactic synchrotron contamination of the Cosmic Microwave Background Polarization (CMBP) that is more reliable than that done at 1.4 GHz. We find that the angular power spectra of the E- and B-modes have slopes of \beta_E = -1.46 +/- 0.14 and \beta_B = -1.87 +/- 0.22, indicating a flattening with respect to 1.4 GHz. Extrapolated up to 32 GHz, the E-mode spectrum is about 3 orders of magnitude lower than that of the CMBP, allowing a clean detection even at this frequency. The best improvement concerns the B-mode, for which our single-dish observations provide the first estimate of the contamination on angular scales close to the CMBP peak (about 2 degrees). We find that the CMBP B-mode should be stronger than synchrotron contamination at 90 GHz for models with T/S > 0.01. This low level could move down to 60-70 GHz the optimal window for CMBP measures.Comment: 5 pages, 6 figures, accepted for publication in MNRAS Letter

Reprocessing the Hipparcos data for evolved giant stars II. Absolute magnitudes for the R-type carbon stars

The Hipparcos Intermediate Astrometric Data for carbon stars have been reprocessed using an algorithm which provides an objective criterion for rejecting anomalous data points and constrains the parallax to be positive. New parallax solutions have been derived for 317 cool carbon stars, mostly of types R and N. In this paper we discuss the results for the R stars. The most important result is that the early R stars (i.e., R0 - R3) have absolute magnitudes and V-K colors locating them among red clump giants in the Hertzsprung-Russell diagram. Stars with subtypes R4 - R9 tend to be cooler and have similar luminosity to the N-type carbon stars, as confirmed by their position in the (J-H, H-K) color-color diagram. The sample of early R-type stars selected from the Hipparcos Catalogue appears to be approximately complete to magnitude K_0 ~ 7, translating into a completeness distance of 600 pc if all R stars had M_K= -2 (400 pc if M_K= -1). With about 30 early R-type stars in that volume, they comprise about 0.04% (0.14% for M_K= -1) of the red clump stars in the solar neighborhood. Identification with the red clump locates these stars at the helium core burning stage of stellar evolution, while the N stars are on the asymptotic giant branch, where helium shell burning occurs. The present analysis suggests that for a small fraction of the helium core burning stars (far lower than the fraction of helium shell-burning stars), carbon produced in the interior is mixed to the atmosphere in sufficient quantities to form a carbon star.Comment: 11 pages, 6 figures, A&A Latex. To appear in A&

Advantages of 3D time-of-flight range imaging cameras in machine vision applications

Machine vision using image processing of traditional intensity images is in wide spread use. In many situations environmental conditions or object colours or shades cannot be controlled, leading to difficulties in correctly processing the images and requiring complicated processing algorithms. Many of these complications can be avoided by using range image data, instead of intensity data. This is because range image data represents the physical properties of object location and shape, practically independently of object colour or shading. The advantages of range image processing are presented, along with three example applications that show how robust machine vision results can be obtained with relatively simple range image processing in real-time applications