Figure 1: Comparisons between greedy error minimization (GEM) [Rousselle et al. 2011] and our SURE-based filtering. With SURE, we are able to use kernels (cross bilateral filters in this case) that are more effective than GEM's isotropic Gassians. Thus, our approach better adapts to anisotropic features (such as the motion blur pattern due to the motion of the airplane) and preserves scene details (such as the textures on the floor and curtains). The kernels of both methods are visualized for comparison. AbstractWe apply Stein's Unbiased Risk Estimator (SURE) to adaptive sampling and reconstruction to reduce noise in Monte Carlo rendering. SURE is a general unbiased estimator for mean squared error (MSE) in statistics. With SURE, we are able to estimate error for an arbitrary reconstruction kernel, enabling us to use more effective kernels rather than being restricted to the symmetric ones used in previous work. It also allows us to allocate more samples to areas with higher estimated MSE. Adaptive sampling and reconstruction can therefore be processed within an optimization framework. We also propose an efficient and memory-friendly approach to reduce the impact of noisy geometry features where there is depth of field or motion blur. Experiments show that our method produces images with less noise and crisper details than previous methods.

We demonstrated control and detection of UV-induced 3-aminopropyltriethoxysilane (APTES) polarization using silicon nanowire field-effect transistors made by top-down lithograph technology. The electric dipole moment in APTES films induced by UV-illumination was shown to produce negative effective charges. When individual dipoles were aligned with an externally applied electric field, the collective polarization can prevail over the UV-induced charges in the wires and give rise to an abnormal resistance enhancement in n-type wires. Real-time detection of hybridization of 15-mer poly-T/poly-A DNA molecules was performed, and the amount of hybridization-induced charges in the silicon wire was estimated. Based on these results, detection sensitivity of the wire sensors was discussed.Hetero-interfaces between organic and semiconductor oxides have attracted extensive attentions 1-4 due to the critical role of molecule assembly in the sensing electronics involving hybrid structures. APTES 5 (3-aminopropyltriethoxysilane) and other compounds such as PTS 6 (n-propyltrichlorosilane), OTS 7 (n-octadecyltrichlorosilane), TCTS 8 (n-triacontyltrichlorosilane), OTMS 9 (n-octadecyltrimethoxysilane), and AHT-MS 9 (n-aminoheptadecyltrimethoxysilane) with head-andtail functional groups are widely used interfacing molecules, and assembly of these molecules is essential in surfacemodification technologies. Silanization of oxidized semiconductor surfaces is a commonly employed scheme for functionalization of sensors. The functional groups would then provide binding sites for attachment of probe molecules, such as single-strand DNA (ssDNA), on the semiconductor sensing devices. The nanowire-based sensors have been demonstrated 10-14 as an ultra sensitive detector for probing molecular charges at the wire surface. However, surface modification of the functional groups on the nanowire surface is not a trivial task. Extensive studies in the surfacemodification were reported in the past years, 5-9 but issues concerning monolayer molecule ordering in terms of the electric dipole moment remain unexplored. Taking APTES as an example, in this study, we proposed a simple method to align the molecule dipoles, and the degree of alignment was examined by underneath Si-nanowire (SiNW) field effect transistors. This method provides a sensitive way for structure investigation of few molecules at the nanometer scale, which is otherwise unfeasible by the present-day examination tools. † These authors contributed equally to this work.