Frequency Compensated Diffusion Model for Real-scene Dehazing

Due to distribution shift, deep learning based methods for image dehazing suffer from performance degradation when applied to real-world hazy images. In this paper, we consider a dehazing framework based on conditional diffusion models for improved generalization to real haze. First, we find that optimizing the training objective of diffusion models, i.e., Gaussian noise vectors, is non-trivial. The spectral bias of deep networks hinders the higher frequency modes in Gaussian vectors from being learned and hence impairs the reconstruction of image details. To tackle this issue, we design a network unit, named Frequency Compensation block (FCB), with a bank of filters that jointly emphasize the mid-to-high frequencies of an input signal. We demonstrate that diffusion models with FCB achieve significant gains in both perceptual and distortion metrics. Second, to further boost the generalization performance, we propose a novel data synthesis pipeline, HazeAug, to augment haze in terms of degree and diversity. Within the framework, a solid baseline for blind dehazing is set up where models are trained on synthetic hazy-clean pairs, and directly generalize to real data. Extensive evaluations show that the proposed dehazing diffusion model significantly outperforms state-of-the-art methods on real-world images.Comment: 16 page

Learn Single-horizon Disease Evolution for Predictive Generation of Post-therapeutic Neovascular Age-related Macular Degeneration

Most of the existing disease prediction methods in the field of medical image processing fall into two classes, namely image-to-category predictions and image-to-parameter predictions. Few works have focused on image-to-image predictions. Different from multi-horizon predictions in other fields, ophthalmologists prefer to show more confidence in single-horizon predictions due to the low tolerance of predictive risk. We propose a single-horizon disease evolution network (SHENet) to predictively generate post-therapeutic SD-OCT images by inputting pre-therapeutic SD-OCT images with neovascular age-related macular degeneration (nAMD). In SHENet, a feature encoder converts the input SD-OCT images to deep features, then a graph evolution module predicts the process of disease evolution in high-dimensional latent space and outputs the predicted deep features, and lastly, feature decoder recovers the predicted deep features to SD-OCT images. We further propose an evolution reinforcement module to ensure the effectiveness of disease evolution learning and obtain realistic SD-OCT images by adversarial training. SHENet is validated on 383 SD-OCT cubes of 22 nAMD patients based on three well-designed schemes based on the quantitative and qualitative evaluations. Compared with other generative methods, the generative SD-OCT images of SHENet have the highest image quality. Besides, SHENet achieves the best structure protection and content prediction. Qualitative evaluations also demonstrate that SHENet has a better visual effect than other methods. SHENet can generate post-therapeutic SD-OCT images with both high prediction performance and good image quality, which has great potential to help ophthalmologists forecast the therapeutic effect of nAMD

Investigation of strength and fatigue life of rubber asphalt mixture

Strength and fatigue life are essential parameters of pavement structure design. To accurately determine the pavement structure resistance of rubber asphalt mixture, the strength tests at various temperatures, loading rate, and fatigue tests at different stress levels were conducted in this research. Based on the proposed experiments, the change law of rubber asphalt mixture strength with different temperatures and loading rates was revealed. The phenomenological fatigue equation of rubber asphalt mixture was established. The genetic algorithm optimized backpropagation neural network (GA-BPNN) is highly reliable for optimizing production processes in civil engineering, and it has a remarkable application effect. A GA-BPNN strength and fatigue life prediction model was created in this study. The reliability of the prediction model was verified through experiments. The results showed that the rubber asphalt mixture strength decreases and increases with the increase of temperature and loading rate, respectively. The goodness of fit of the rubber asphalt mixture strength and fatigue life prediction model based on the GA-BPNN could reach 0.989 and 0.998, respectively. The indicators of the fatigue life prediction model are superior to the conventional phenomenological fatigue equation model. The GA-BPNN provides an effective method for predicting the rubber asphalt mixture strength and fatigue life, which significantly improves the accuracy of the resistance design of the rubber asphalt pavement structure

Single-Cell RNA Sequencing of hESC-Derived 3D Retinal Organoids Reveals Novel Genes Regulating RPC Commitment in Early Human Retinogenesis.

The development of the mammalian retina is a complicated process involving the generation of distinct types of neurons from retinal progenitor cells (RPCs) in a spatiotemporal-specific manner. The progression of RPCs during retinogenesis includes RPC proliferation, cell-fate commitment, and specific neuronal differentiation. In this study, by performing single-cell RNA sequencing of cells isolated from human embryonic stem cell (hESC)-derived 3D retinal organoids, we successfully deconstructed the temporal progression of RPCs during early human retinogenesis. We identified two distinctive subtypes of RPCs with unique molecular profiles, namely multipotent RPCs and neurogenic RPCs. We found that genes related to the Notch and Wnt signaling pathways, as well as chromatin remodeling, were dynamically regulated during RPC commitment. Interestingly, our analysis identified that CCND1, a G1-phase cell-cycle regulator, was coexpressed with ASCL1 in a cell-cycle-independent manner. Temporally controlled overexpression of CCND1 in retinal organoids demonstrated a role for CCND1 in promoting early retinal neurogenesis. Together, our results revealed critical pathways and novel genes in early retinogenesis of humans

Mesenchymal Stem Cells: A Double-edged Sword in Regulating Immune Responses

Mesenchymal stem cells (MSCs) have been employed successfully to treat various immune disorders in animal models and clinical settings. Our previous studies have shown that MSCs can become highly immunosuppressive upon stimulation by inflammatory cytokines, an effect exerted through the concerted action of chemokines and nitric oxide (NO). Here, we show that MSCs can also enhance immune responses. This immune-promoting effect occurred when proinflammatory cytokines were inadequate to elicit sufficient NO production. When inducible nitric oxide synthase (iNOS) production was inhibited or genetically ablated, MSCs strongly enhance T-cell proliferation in vitro and the delayed-type hypersensitivity response in vivo. Furthermore, iNOS-/- MSCs significantly inhibited melanoma growth. It is likely that in the absence of NO, chemokines act to promote immune responses. Indeed, in CCR5-/- CXCR3-/- mice, the immune-promoting effect of iNOS-/- MSCs is greatly diminished. Thus, NO acts as a switch in MSC-mediated immunomodulation. More importantly, the dual effect on immune reactions was also observed in human MSCs, in which indoleamine 2,3-dioxygenase (IDO) acts as a switch. This study provides novel information about the pathophysiological roles of MSCs. © 2012 Macmillan Publishers Limited All rights reserved

Correlation of the chemical composition, phase content, structural characteristics and magnetic properties of the Bi-substituted M-type hexaferrites

Bi-substituted M-type hexaferrites, BaFe12-xBixO19 (0.1 ≤ x ≤ 1.2), or Bi-BaM, were produced by the solid-state reactions. The correlation between the phase content, chemical composition, crystal structure features, and peculiarities of the magnetic properties of Bi-BaM was established using XRD (X-ray diffraction), SEM (scanning electron microscopy), and VSM (vibrational sample magnetometry). XRD phase analysis made it possible to establish the limit of substitution of Fe3+ ions by Bi3+ ions. It was shown that at a low substitution level (x ≤ 0.3), no impurity phases were detected, and the samples are characterized by a single-phase state with the space group (SG) P63/mmc. As the degree of substitution (x ≥ 0.6) increases, the formation of impurity phases was observed, which can be explained by the difficulties of ion diffusion in the process of solid-phase synthesis as well as the formation of defects in the magnetoplumbite structure due to the large ionic radius of Bi3+. As impurity phases in the studied compositions (x ≥ 0.6) the following were noted: BiFeO3 (SG: Pnma); BiO2 (SG: Fm-3m); BaBi2O6 (SG: R-3); and Ba0.5Bi1.5O2.16 (SG: Im-3m). The content of the main phase (SG: P63/mmc) decreases from 95.11 to 88.27 vol% with an increase in x from 0.6 to 1.2, respectively. Analysis of SEM images showed the growth of particles up to 10 μm, depending on the concentration of bismuth oxide during hexaferrite synthase. The Bi-BaM magnetic characteristics were examined using VSM in the range of 3 T at 300 K. Due to the magnetic structure's frustration, with increased x a decrease in saturation magnetization (Ms) was found. There were two concentration diapasons with different speeds of Ms decrease. In the first diapason, the main contribution belong to the magnetic structure frustration in the frame of the main phase (P63/mmc) due to the long-range Fe-O-Fe exchange interaction weakening (under Bi substitution). In the second diapason, the main contribution belong to the impurity phase formation and decrease of the main magnetic phase concentration in samples

Single Endemic Genotype of Measles Virus Continuously Circulating in China for at Least 16 Years

The incidence of measles in China from 1991 to 2008 was reviewed, and the nucleotide sequences from 1507 measles viruses (MeV) isolated during 1993 to 2008 were phylogenetically analyzed. The results showed that measles epidemics peaked approximately every 3 to 5 years with the range of measles cases detected between 56,850 and 140,048 per year. The Chinese MeV strains represented three genotypes; 1501 H1, 1 H2 and 5 A. Genotype H1 was the predominant genotype throughout China continuously circulating for at least 16 years. Genotype H1 sequences could be divided into two distinct clusters, H1a and H1b. A 4.2% average nucleotide divergence was found between the H1a and H1b clusters, and the nucleotide sequence and predicted amino acid homologies of H1a viruses were 92.3%–100% and 84.7%–100%, H1b were 97.1%–100% and 95.3%–100%, respectively. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Cluster H1a and H1b viruses were co-circulating during 1993 to 2005, while no H1b viruses were detected after 2005 and the transmission of that cluster has presumably been interrupted. Analysis of the nucleotide and predicted amino acid changes in the N proteins of H1a and H1b viruses showed no evidence of selective pressure. This study investigated the genotype and cluster distribution of MeV in China over a 16-year period to establish a genetic baseline before MeV elimination in Western Pacific Region (WPR). Continuous and extensive MeV surveillance and the ability to quickly identify imported cases of measles will become more critical as measles elimination goals are achieved in China in the near future. This is the first report that a single endemic genotype of measles virus has been found to be continuously circulating in one country for at least 16 years

In Vitro and In Vivo Germ Line Potential of Stem Cells Derived from Newborn Mouse Skin

We previously reported that fetal porcine skin-derived stem cells were capable of differentiation into oocyte-like cells (OLCs). Here we report that newborn mice skin-derived stem cells are also capable of differentiating into early OLCs. Using stem cells from mice that are transgenic for Oct4 germline distal enhancer-GFP, germ cells resulting from their differentiation are expected to be GFP+. After differentiation, some GFP+ OLCs reached 40–45 µM and expressed oocyte markers. Flow cytometric analysis revealed that ∼0.3% of the freshly isolated skin cells were GFP+. The GFP-positive cells increased to ∼7% after differentiation, suggesting that the GFP+ cells could be of in vivo origin, but are more likely induced upon being cultured in vitro. To study the in vivo germ cell potential of skin-derived cells, they were aggregated with newborn ovarian cells, and transplanted under the kidney capsule of ovariectomized mice. GFP+ oocytes were identified within a subpopulation of follicles in the resulting growth. Our finding that early oocytes can be differentiated from mice skin-derived cells in defined medium may offer a new in vitro model to study germ cell formation and oogenesis