The aim of this meta-analysis was to determine whether pulsatile perfusion during cardiac surgery has a lesser effect on renal dysfunction than nonpulsatile perfusion after cardiac surgery in randomized controlled trials. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were used to identify available articles published before April 25, 2014. Meta-analysis was conducted to determine the effects of pulsatile perfusion on postoperative renal functions, as determined by creatinine clearance (CrCl), serum creatinine (Cr), urinary neutrophil gelatinase-associated lipocalin (NGAL), and the incidences of acute renal insufficiency (ARI) and acute renal failure (ARF). Nine studies involving 674 patients that received pulsatile perfusion and 698 patients that received nonpulsatile perfusion during cardiopulmonary bypass (CPB) were considered in the meta-analysis. Stratified analysis was performed according to effective pulsatility or unclear pulsatility of the pulsatile perfusion method in the presence of heterogeneity. NGAL levels were not significantly different between the pulsatile and nonpulsatile groups. However, patients in the pulsatile group had a significantly higher CrCl and lower Cr levels when the analysis was restricted to studies on effective pulsatile flow (P < 0.00001, respectively). The incidence of ARI was significantly lower in the pulsatile group (P < 0.00001), but incidences of ARF were similar. In conclusion, the meta-analysis suggests that the use of pulsatile flow during CPB results in better postoperative renal function.

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RTI is an image-based rendering method which can represent the appearance of an object under varying illuminations. To create realistic synthetic-images using RTI, it is necessary to take dozens of images on a mounted camera with a calibrated point light source. Conventional RTI methods have proposed complex lighting systems in a hemispherical dome, or manually calibrate light poses using a reflective probe. In most cases, those methods are not suitable for the large-scale object in an outdoor environment because the size of the target object is restricted by the configuration of measurement systems. In this paper, we present a new RTI method which can create photorealistic images of a large scale outdoor scene under arbitrary light directions. Instead of capturing RTI samples at a time for an entire domain, we divide the RTI domain into a set of subsections. RTI samples in each section are acquired using a camera and an uncalibrated light source. After acquiring samples, we estimate svBRDF of measured samples without any prior knowledge of a 3D model, light poses, and surface normals. We also present an approach to merge the partial RTI images into a panoramic image. Experimental results show that our framework can extend the RTI methods applicable to large-scale objects.

With the emergence of smart LEDs, lighting based interior design is becoming popular. However, most of the smart LED-based lighting systems rely on expert-human intervention to create a desired atmosphere. For convenience, commercial lighting systems offer a number of options but their usability is fairly restricted. Therefore, an intuitive interface is required for novice users to generate the desired lighting environment. In this paper, we have developed a software, named MudGet, which automatically extracts the light mood from a digital image and controls the LED lamps to reproduce a desired lighting effect according to the extracted light mood. In our method, the light mood is regarded as a set of the representative colors of the digital image. The representative colors are extracted by utilizing K-means clustering algorithm. The dimming parameters are set for which each of the LED lamps create the lighting environment with the mood extracted by the software. To evaluate the feasibility of mood reproduction qualitatively, the degree of similarity between the light mood in the digital image and the reproduced result using LEDs is evaluated by a user study under a miniaturized experimental set. We observe that users can easily produce a desired atmosphere through the proposed MudGet software. Highlights An image based lighting design interface is proposed. The interface controls customized LED module wirelessly. Desired lighting effect is generated from the color clustering centers of image.