The ability of a camera to record a high dynamic range image, whether by taking one snapshot or a sequence, is limited by the presence of veiling glare - the tendency of bright objects in the scene to reduce the contrast everywhere within the field of view. Veiling glare is a global illumination effect that arises from multiple scattering of light inside the camera's body and lens optics. By measuring separately the direct and indirect components of the intra-camera light transport, one can increase the maximum dynamic range a particular camera is capable of recording. In this paper, we quantify the presence of veiling glare and related optical artifacts for several types of digital cameras, and we describe two methods for removing them: deconvolution by a measured glare spread function, and a novel direct-indirect separation of the lens transport using a structured occlusion mask. In the second method, we selectively block the light that contributes to veiling glare, thereby attaining significantly higher signal-to-noise ratios than with deconvolution. Finally, we demonstrate our separation method for several combinations of cameras and realistic scenes.
Memory latency is an important bottleneck in system performance that cannot be adequately solved by hardware alone. Several promising software techniques have been shown to address this problem successfully in specific situations. However, the generality of these software approaches has been limited because current architectures do not provide a fine-grained, low-overhead mechanism to observe memory behavior directly. To fill this need, we propose a new set of memory operations called informing memory operations, and in particular, we describe the design and functionality of an informing load instruction. This instruction serves as a primitive that allows the software to observe cache misses and to act upon this information inexpensively (i.e. under the miss, when the processor would typically be idle) within the current software context. Informing loads enable new solutions to several important software problems. We demonstrate this through examples that show their usefulness in (i) the collection of fine-grained memory profiles with high precision and low overhead and (ii) the automatic improvement of memory system performance through compiler techniques that take advantage of cache-miss information. Overall, we find that the apparent benefit of an informing load instruction is quite high, while the hardware cost of this functionality is quite modest. In fact, the bulk of the required hardware support is already present in today''s high-performance processors.
MiR classifiers show promising prognostic associations with major cancer outcomes and specific miRs are consistently identified across diverse studies and platforms. These types of classifiers require careful external validation in large groups of cancer patients that have adequate protection from bias. -
The rapidly growing number of molecular epidemiology studies is providing an enormous, often multidimensional, body of evidence on the association of various disease outcomes and biomarkers. The testing and validation of statistical hypotheses in genetic and molecular epidemiology presents a major challenge requiring methodological rigor and analytical power. The non-replication of many genetic and other biomarker association studies suggests that there may be an abundance of spurious findings in the field. This chapter will discuss ways of combining evidence from different sources using meta-analysis methods. Research synthesis not only aims at producing a summary effect estimate for a specific biomarker, but also offers a unique opportunity for a meticulous attempt to critically appraise a research field, identify substantial differences between or within studies, and detect sources of bias. Systematic reviews and meta-analyses in human genome epidemiology are specifically discussed, as they comprise the bulk of the available evidence in molecular epidemiology where these methods have been applied to date. Considered here are issues regarding validity and interpretation in genetic association studies, as well as strategies for developing and integrating evidence through international consortia. Finally, there is a brief look at how combining data through meta-analysis may be applied in other areas of molecular epidemiology.
(18)F-FDG PET has very good discriminating ability in the evaluation of both primary and recurrent soft-tissue lesions. (18)F-FDG PET may be helpful in tumor grading but offers inadequate discrimination between low-grade tumors and benign lesions.
