PartDiff: Image Super-resolution with Partial Diffusion Models

Denoising diffusion probabilistic models (DDPMs) have achieved impressive performance on various image generation tasks, including image super-resolution. By learning to reverse the process of gradually diffusing the data distribution into Gaussian noise, DDPMs generate new data by iteratively denoising from random noise. Despite their impressive performance, diffusion-based generative models suffer from high computational costs due to the large number of denoising steps.In this paper, we first observed that the intermediate latent states gradually converge and become indistinguishable when diffusing a pair of low- and high-resolution images. This observation inspired us to propose the Partial Diffusion Model (PartDiff), which diffuses the image to an intermediate latent state instead of pure random noise, where the intermediate latent state is approximated by the latent of diffusing the low-resolution image. During generation, Partial Diffusion Models start denoising from the intermediate distribution and perform only a part of the denoising steps. Additionally, to mitigate the error caused by the approximation, we introduce "latent alignment", which aligns the latent between low- and high-resolution images during training. Experiments on both magnetic resonance imaging (MRI) and natural images show that, compared to plain diffusion-based super-resolution methods, Partial Diffusion Models significantly reduce the number of denoising steps without sacrificing the quality of generation

Silicon nitride metalenses for unpolarized high-NA visible imaging

As one of nanoscale planar structures, metasurface has shown excellent superiorities on manipulating light intensity, phase and/or polarization with specially designed nanoposts pattern. It allows to miniature a bulky optical lens into the chip-size metalens with wavelength-order thickness, playing an unprecedented role in visible imaging systems (e.g. ultrawide-angle lens and telephoto). However, a CMOS-compatible metalens has yet to be achieved in the visible region due to the limitation on material properties such as transmission and compatibility. Here, we experimentally demonstrate a divergent metalens based on silicon nitride platform with large numerical aperture (NA~0.98) and high transmission (~0.8) for unpolarized visible light, fabricated by a 695-nm-thick hexagonal silicon nitride array with a minimum space of 42 nm between adjacent nanoposts. Nearly diffraction-limit virtual focus spots are achieved within the visible region. Such metalens enables to shrink objects into a micro-scale size field of view as small as a single-mode fiber core. Furthermore, a macroscopic metalens with 1-cm-diameter is also realized including over half billion nanoposts, showing a potential application of wide viewing-angle functionality. Thanks to the high-transmission and CMOS-compatibility of silicon nitride, our findings may open a new door for the miniaturization of optical lenses in the fields of optical fibers, microendoscopes, smart phones, aerial cameras, beam shaping, and other integrated on-chip devices.Comment: 16 pages, 7 figure

CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation

A large portion of volumetric medical data, especially magnetic resonance imaging (MRI) data, is anisotropic, as the through-plane resolution is typically much lower than the in-plane resolution. Both 3D and purely 2D deep learning-based segmentation methods are deficient in dealing with such volumetric data since the performance of 3D methods suffers when confronting anisotropic data, and 2D methods disregard crucial volumetric information. Insufficient work has been done on 2.5D methods, in which 2D convolution is mainly used in concert with volumetric information. These models focus on learning the relationship across slices, but typically have many parameters to train. We offer a Cross-Slice Attention Module (CSAM) with minimal trainable parameters, which captures information across all the slices in the volume by applying semantic, positional, and slice attention on deep feature maps at different scales. Our extensive experiments using different network architectures and tasks demonstrate the usefulness and generalizability of CSAM. Associated code is available at https://github.com/aL3x-O-o-Hung/CSAM

A HIV-1 heterosexual transmission chain in Guangzhou, China: a molecular epidemiological study

<p>Abstract</p> <p>Background</p> <p>We conducted molecular analyses to confirm four clustering HIV-1 infections (Patient A, B, C & D) in Guangzhou, China. These cases were identified by epidemiological investigation and suspected to acquire the infection through a common heterosexual transmission chain.</p> <p>Methods</p> <p><it>Env C2V3V4 </it>region, <it>gag p17/p24 </it>junction and partial <it>pol </it>gene of HIV-1 genome from serum specimens of these infected cases were amplified by reverse transcription polymerase chain reaction (RT-PCR) and nucleotide sequenced.</p> <p>Results</p> <p>Phylogenetic analyses indicated that their viral nucleotide sequences were significantly clustered together (bootstrap value is 99%, 98% and 100% in <it>env</it>, <it>gag </it>and <it>pol </it>tree respectively). Evolutionary distance analysis indicated that their genetic diversities of <it>env</it>, <it>gag </it>and <it>pol </it>genes were significantly lower than non-clustered controls, as measured by unpaired <it>t</it>-test (<it>env </it>gene comparison: <it>p </it>< 0.005; <it>gag </it>gene comparison: <it>p </it>< 0.005; <it>pol </it>gene comparison: <it>p </it>< 0.005).</p> <p>Conclusion</p> <p>Epidemiological results and molecular analyses consistently illustrated these four cases represented a transmission chain which dispersed in the locality through heterosexual contact involving commercial sex worker.</p

A systematic investigation of conceptual color associations

Associations with colours are a rich source of meaning and there has been considerable interest in understanding the capacity of colour to shape our functioning and behaviour as a result of colour associations. However, abstract conceptual colour associations have not been comprehensively investigated and many of the effects of colour on psychological functioning reported in the literature are therefore reliant on ad hoc rationalisations of conceptual associations with colour (e.g. blue – openness) to explain effects. In the present work we conduct a systematic, cross-cultural, mapping of conceptual colour associations using the full set of hues from the World Colour Survey (WCS). In Experiments 1a and 1b we explored the conceptual associations that English monolingual, Chinese bilingual and Chinese monolingual speaking adults have with each of the 11 Basic English Colour Terms (black, white, red, yellow, green, blue, brown, purple, pink, orange, grey). In Experiment 2 we determined which specific physical WCS colours are associated with which concepts in these three language groups. The findings reveal conceptual colour associations that appear to be ‘universal’ across all cultures (e.g. white – purity; blue – water/sky related; green – health; purple – regal; pink – ‘female’ traits) as well as culture specific (e.g. red and orange – enthusiastic in Chinese; red – attraction in English). Importantly, the findings provide a crucial constraint on, and resource for, future work that seeks to understand the effect of colour on cognition and behaviour, enabling stronger a priori predictions about universal as well as culturally relative effects of conceptual colour associations on cognition and behaviour to be systematically tested