Camera spectral sensitivity functions relate scene radiance with captured RGB triplets. They are important for many computer vision tasks that use color information, such as multispectral imaging, color rendering, and color constancy. In this paper, we aim to explore the space of spectral sensitivity functions for digital color cameras. After collecting a database of 28 cameras covering a variety of types, we find this space convex and two-dimensional. Based on this statistical model, we propose two methods to recover camera spectral sensitivities using regular reflective color targets (e.g., color checker) from a single image with and without knowing the illumination. We show the proposed model is more accurate and robust for estimating camera spectral sensitivities than other basis functions. We also show two applications for the recovery of camera spectral sensitivities -simulation of color rendering for cameras and computational color constancy.

Strongyloidiasis is a much-neglected but sometimes fatal soil born helminthiasis. The causing agent, the small intestinal parasitic nematode Strongyloides stercoralis can reproduce sexually through the indirect/heterogonic life cycle, or asexually through the auto-infective or the direct/homogonic life cycles. Usually, among the progeny of the parasitic females both, parthenogenetic parasitic (females only) and sexual free-living (females and males) individuals, are present simultaneously. We isolated S . stercoralis from people living in a village with a high incidence of parasitic helminths, in particular liver flukes ( Clonorchis sinensis ) and hookworms, in the southern Chinese province Guangxi. We determined nuclear and mitochondrial DNA sequences of individual S . stercoralis isolated from this village and from close by hospitals and we compared these S . stercoralis among themselves and with selected published S . stercoralis from other geographic locations. For comparison, we also analyzed the hookworms present in the same location. We found that, compared to earlier studies of S . stercoralis populations in South East Asia, all S . stercoralis sampled in our study area were very closely related, suggesting a recent common source of infection for all patients. In contrast, the hookworms from the same location, while all belonging to the species Necator americanus , showed rather extensive genetic diversity even within host individuals. Different from earlier studies conducted in other geographic locations, almost all S . stercoralis in this study appeared heterozygous for different sequence variants of the 18S rDNA hypervariable regions (HVR) I and IV. In contrast to earlier investigations, except for three males, all S . stercoralis we isolated in this study were infective larvae, suggesting that the sampled population reproduces predominantly, if not exclusively through the clonal life cycles. Consistently, whole genome sequencing of individual worms revealed higher heterozygosity than reported earlier for likely sexual populations of S . stercoralis . Elevated heterozygosity is frequently associated with asexual clonal reproduction.

The interplay of small noncoding RNAs (sRNAs), mRNAs, and proteins has been shown to play crucial roles in almost all cellular processes. As key post-transcriptional regulators of gene expression, the mechanisms and roles of sRNAs in various cellular processes still need to be fully understood. When participating in cellular processes, sRNAs mainly mediate mRNA degradation or translational repression. Here, we show how the dynamics of two minimal architectures is drastically affected by these two mechanisms. A comparison is also given to reveal the implication of the fundamental differences. This study may help us to analyze complex networks assembled by simple modules more easily. A better knowledge of the sRNA-mediated motifs is also of interest for bio-engineering and artificial control.

Cameras face a fundamental trade-off between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video cameras have relatively low spatial resolution. It is hard to overcome this trade-off without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing, and reconstructing the space-time volume to overcome this trade-off. Our approach has two important distinctions compared to previous works: 1) We achieve sparse representation of videos by learning an overcomplete dictionary on video patches, and 2) we adhere to practical hardware constraints on sampling schemes imposed by architectures of current image sensors, which means that our sampling function can be implemented on CMOS image sensors with modified control units in the future. We evaluate components of our approach, sampling function and sparse representation, by comparing them to several existing approaches. We also implement a prototype imaging system with pixel-wise coded exposure control using a liquid crystal on silicon device. System characteristics such as field of view and modulation transfer function are evaluated for our imaging system. Both simulations and experiments on a wide range of scenes show that our method can effectively reconstruct a video from a single coded image while maintaining high spatial resolution.