Recently, neural style transfer has become a popular task in both academic research and industrial applications. Although the existing methods made great progress in terms of quality and efficiency, ...most of them mainly focus on extracting high-level features. Therefore, it is still challenging to display the hierarchical structure of the content image due to lack of texture information, which causes blurred boundaries and distortion of the stylized image. In this paper, a novel neural image and video style transfer scheme is proposed to suppress distortion and preserve the semantic content of the content image, which is capable of yielding satisfactory stylized images and videos of a variety of scenarios. We first propose to assemble a refine network into an auto-encoder framework to guide style transfer, which can ensure that the stylized image have diverse levels of details. Then, we introduce the global content loss and the local region structure loss to train the model and enhance the robustness of the model. In addition, in order to produce a high-quality stylized video, our method not only preserves the image structure, but also introduces a temporal consistency loss and a cycle-temporal loss to avoid temporal incoherence and motion blur as far as possible. Our approach is also friendly for photographic and exposed image and video style transfer. Both quantitative and qualitative evaluation demonstrated the effectiveness of our method.
How fibroblast growth factor 23 works SHIGUANG LIU; QUARLES, L. Darryl
Journal of the American Society of Nephrology,
06/2007, Volume:
18, Issue:
6
Journal Article
Peer reviewed
Open access
There is a discontinuum of hereditary and acquired disorders of phosphate homeostasis that are caused by either high or low circulating levels of the novel phosphaturic hormone fibroblastic growth ...factor 23 (FGF23). Disorders that are caused by high circulating levels of FGF23 are characterized by hypophosphatemia, decreased production of 1,25-dihydroxyvitamin D, and rickets/osteomalacia. On the other end of the spectrum are disorders that are caused by low circulating levels of FGF23, which are characterized by hyperphosphatemia, elevated production of 1,25-dihydroxyvitamin D, soft tissue calcifications, and hyperostosis. Knowledge of the genetic basis of these hereditary disorders of phosphate homeostasis and studies of their mouse homologues have uncovered a bone-kidney axis and new systems biology that govern bone mineralization, vitamin D metabolism, parathyroid gland function, and renal phosphate handling. Further understanding of this primary phosphate homeostatic pathway has the potential to have a significant impact on the diagnosis and treatment of disorders of bone and mineral metabolism.
•An emotional image color transfer framework based on deep learning is proposed.•Both global emotion classification information and local semantic information are considered.•Our method solves the ...unnatural color problem in traditional methods.•Our method is easy to implement without any user interaction.
Different colors in images convey different emotions, e.g., artists often use different color combinations to convey different emotions in their creation. Traditional image color emotion transfer methods do not take the semantic information of images into account, which may lead to unnatural transfer results. To this end, this paper proposes a new emotional image color transfer framework by exploiting deep learning which can process images in an end-to-end fashion. Our network contains four main components, namely a low level feature network, an emotion classification network, a fusion network and a colorization network. The low level feature network extracts the semantic information which is designed to prevent the anti-natural phenomenon. The emotion classification network is used to constrain the color to make the enhancement results meet user's emotion. Then, the final deep learning framework combine the emotion classification network and the low level feature network by a fusion network. Finally, we use the colorization network to get the enhanced images. Various experiment results and comparisons validate our method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Time-varying effects simulation plays a critical role in computer graphics. Fruit diseases are typical time-varying phenomena. Due to the biological complexity, the existing methods fail to represent ...the biodiversity and biological law of symptoms. To this end, this paper proposes a biology-aware, physically-based framework that respects biological knowledge for realistic simulation of fruit mildew diseases. The simulated symptoms include skin discoloration, fungus growth, and volume shrinkage. Specifically, we take advantage of both the zero-order kinetic model and reaction–diffusion model to represent the complex fruit skin discoloration related to skin biological characteristics. To reproduce 3D mildew growth, we employ the Poisson-disk sampling technique and propose a template model instancing method. One can flexibly change hyphal template models to characterize the fungal biological diversity. To model the fruit’s biological structure, we fill the fruit mesh interior with particles in a biologically-based arrangement. Based on this structure, we propose a turgor pressure and a Lennard-Jones force-based adaptive mass–spring system to simulate the fruit shrinkage in a biological manner. Experiments verified that the proposed framework can effectively simulate mildew diseases, including gray mold, powdery mildew, and downy mildew. Our results are visually compelling and close to the ground truth. Both quantitative and qualitative experiments validated the proposed method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Imbalanced datasets commonly exist in real world and greatly challenge the performances of deep neural models. The authors discover that the traditional balance strategies in the existing imbalanced ...learning methods emphasize/suppress the importance of minority/majority class in a fixed way. Even the minority class is fully represented, the minority/majority class is still emphasized/suppressed, eventually leading to sub‐optimal models. The authors argue that the importance of minority/majority class should be emphasized/suppressed in a dynamic manner. They propose to dynamically balance class losses (DBCL), which first suppresses the importance of majority class, and then gradually restores the importance of majority class. By adding the idea of DBCL into three state‐of‐the‐art cost‐sensitive loss functions, the authors propose three novel loss functions: dynamic constrained‐focal‐loss (DCFL), dynamic balance‐cross‐entropy based on the effective number of samples (DBENS) and dynamic balance‐cross‐entropy based on class frequencies (DBCEF). They apply DCFL, DBENS and DBCEF to the imbalanced learning in salient‐instance segmentation. The results show that their methods significantly improve the classification abilities of models.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Image decolorization known as the process to transform a color image to a grayscale one is widely used in single-channel image processing, black and white printing, etc. It is a dimension reduction ...process which inevitably suffers from information loss. The general goal of image decolorization is to preserve the color contrast of the color image. Traditional image decolorization methods are generally divided into local methods and global methods. However, local methods are not accurate enough to process local pixel blocks which may tend to cause local artifacts. While global methods cannot deal well in local color blocks, which are usually time-consuming, too. Therefore, this paper presents a way to combine the local semantic features and the global features. The traditional image decolorization method uses the low-level features of an image. Instead, in this paper, the convolution neural network is used to learn the global features and local semantic features of an image which can better preserve the contrast in both local color blocks and adjacent pixels of the color image. Finally, the global features and the local semantic features are combined to decolorize the image. Experiments indicate that our method outperforms the state of the arts in terms of contrast preservation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
A typical rainfall scenario contains tens of thousands of dynamic sound sources. A characteristic of the large-scale scene is the strong randomness in raindrop distribution, which makes it ...notoriously expensive to synthesize such sounds with purely physical methods. Moreover, the raindrops hitting different surfaces (liquid or various solids) can emit distinct sounds, for which prior methods with unified impact sound models are ill-suited.
In this paper, we present a physically-based statistical simulation method to synthesize realistic rain sound, which respects surface materials. We first model the raindrop sound with two mechanisms, namely the initial impact and the subsequent pulsation of entrained bubbles. Then we generate material sound textures (MSTs) based on a specially designed signal decomposition and reconstruction model. This allows us to distinguish liquid surface with bubble sound and different solid surfaces with MSTs. Furthermore, we build a basic rain sound (BR-sound) bank with the proposed raindrop sound clustering method based on a statistical model, and design a sound source activator for simulating spatial propagation in an efficient manner. This novel method drastically decreases the computational cost while producing convincing sound results. Various experiments demonstrate the effectiveness of our sound simulation model.
Star polymers with poly(ethylene glycol) (PEG) arms and a degradable cationic core were synthesized by the atom transfer radical copolymerization (ATRP) of poly(ethylene glycol) methyl ether ...methacrylate macromonomer (PEGMA), 2-(dimethylamino)ethyl methacrylate (DMAEMA), and a disulfide dimethacrylate (cross-linker, SS) via an “arm-first” approach. The star polymers had a diameter ∼15 nm and were degraded under redox conditions by glutathione treatment into individual polymeric chains due to cleavage of the disulfide cross-linker, as confirmed by dynamic light scattering. The star polymers were cultured with mouse calvarial preosteoblast-like cells, embryonic day 1, subclone 4 (MC3T3-E1.4) to determine biocompatibility. Data suggest star polymers were biocompatible, with ≥80% cell viability after 48 h of incubation even at high concentration (800 μg/mL). Zeta potential values varied with N/P ratio confirming complexation with siRNA. Successful cellular uptake of the star polymers in MC3T3-E1.4 cells was observed by confocal microscopy and flow cytometry after 24 h of incubation.
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IJS, KILJ, NUK, PNG, UL, UM
Low-grade glioma (LGG) is a heterogeneous tumor that might develop into high-grade malignant glioma, which markedly reduces patient survival time. Endocytosis is a cellular process responsible for ...the internalization of cell surface proteins or external materials into the cytosol. Dysregulated endocytic pathways have been linked to all steps of oncogenesis, from initial transformation to late invasion and metastasis. However, endocytosis-related gene (ERG) signatures have not been used to study the correlations between endocytosis and prognosis in cancer. Therefore, it is essential to develop a prognostic model for LGG based on the expression profiles of ERGs.
The Cancer Genome Atlas and the Genotype-Tissue Expression database were used to identify differentially expressed ERGs in LGG patients. Gene ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene set enrichment analysis methodologies were adopted for functional analysis. A protein-protein interaction (PPI) network was constructed and hub genes were identified based on the Search Tool for the Retrieval of Interacting Proteins database. Univariate and multivariate Cox regression analyses were used to develop an ERG signature to predict the overall survival (OS) of LGG patients. Finally, the association between the ERG signature and gene mutation status was further analyzed.
Sixty-two ERGs showed distinct mRNA expression patterns between normal brain tissues and LGG tissues. Functional analysis indicated that these ERGs were strikingly enriched in endosomal trafficking pathways. The PPI network indicated that EGFR was the most central protein. We then built a 29-gene signature, dividing patients into high-risk and low-risk groups with significantly different OS times. The prognostic performance of the 29-gene signature was validated in another LGG cohort. Additionally, we found that the mutation scores calculated based on the
,
,
, and
mutation status were significantly correlated with the endocytosis-related prognostic signature. Finally, a clinical nomogram with a concordance index of 0.881 predicted the survival probability of LGG patients by integrating clinicopathologic features and ERG signatures.
Our ERG-based prediction models could serve as an independent prognostic tool to accurately predict the outcomes of LGG.
The regulation of the phosphaturic factor fibroblast growth factor 23 (FGF23) is not well understood. It was found that administration of 1,25-dihydroxyvitamin D(3) (1,25OH(2)D(3)) to mice rapidly ...increased serum FGF23 concentrations from a basal level of 90.6 +/- 8.1 to 213.8 +/- 14.6 pg/ml at 8 h (mean +/- SEM; P < 0.01) and resulted in a four-fold increase in FGF23 transcripts in bone, the predominate site of FGF23 expression. In the Hyp-mouse homologue of X-linked hypophosphatemic rickets, administration of 1,25(OH)(2)D(3) further increased circulating FGF23 levels. In Gcm2 null mice, low 1,25(OH)(2)D(3) levels were associated with a three-fold reduction in FGF23 levels that were increased by administration of 1,25(OH)(2)D(3). In osteoblast cell cultures, 1,25(OH)(2)D(3) but not calcium, phosphate, or parathyroid hormone stimulated FGF23 mRNA levels and resulted in a dose-dependent increase in FGF23 promoter activity. Overexpression of a dominant negative vitamin D receptor inhibited 1,25(OH)(2)D(3) stimulation of FGF23 promoter activity, and mutagenesis of the FGF23 promoter identified a vitamin D-responsive element (-1180 GGAACTcagTAACCT -1156) that is responsible for the vitamin D effects. These data suggest that 1,25(OH)(2)D(3) is an important regulator of FGF23 production by osteoblasts in bone. The physiologic role of FGF23 may be to act as a counterregulatory phosphaturic hormone to maintain phosphate homeostasis in response to vitamin D.
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