Fuzzy aesthetic semantics description and extraction for art image retrieval

AbstractMore and more digitized art images are accumulated and expanded in our daily life and techniques are needed to be established on how to organize and retrieve them. Though content-based image retrieval (CBIR) made great progress, current low-level visual information based retrieval technology in CBIR does not allow users to search images by high-level semantics for art image retrieval. We propose a fuzzy approach to describe and to extract the fuzzy aesthetic semantic feature of art images. Aiming to deal with the subjectivity and vagueness of human aesthetic perception, we utilize the linguistic variable to describe the image aesthetic semantics, so it becomes possible to depict images in linguistic expression such as ‘very action’. Furthermore, we apply neural network approach to model the process of human aesthetic perception and to extract the fuzzy aesthetic semantic feature vector. The art image retrieval system based on fuzzy aesthetic semantic feature makes users more naturally search desired images by linguistic expression. We report extensive empirical studies based on a 5000-image set, and experimental results demonstrate that the proposed approach achieves excellent performance in terms of retrieval accuracy

Prognostic value of growth differentiation factor-15 in Chinese patients with heart failure: A prospective observational study

  Background: Growth differentiation factor-15 (GDF-15), a biomarker associated with remodeling, oxidative stress and inflammation, has been used to stratify heart failure (HF) patients. However, its prognostic value in Chinese HF patients is still unknown. Methods: GDF-15 levels were examined on admission in 272 consecutive HF patients in Beijing Hospital (a Chinese tertiary medical center) by a commercial enzyme-linked immunosorbent assay. We recorded the incidence of all-cause mortality and/or readmission for HF during a median follow-up period of 558 days. Patients were stratified according to the tertiles of GDF-15. Results: Fifty-three (19.5%) patients died and 103 (37.9%) patients had major adverse cardiac events (MACE) which included the composite outcome of all-cause mortality or readmission for HF at the end of follow-up. Kaplan-Meier survival curves showed that the third tertile of GDF-15 was associated with increased rate of all-cause mortality (compared with the first and second tertiles, log rank p = 0.001 and 0.001, respectively) or MACE (compared with the first and second tertiles, log rank p = 0.002 and p < 0.001, respectively). In addition, multivariate Cox regression model showed that the highest tertile of GDF-15 was independently associated with increased risk of all-cause death (hazard ratio = 5.95, 95% confidence interval 1.88–18.78, p = 0.002) compared with the lowest tertile after adjustment for related clinical variables such as age, renal function or N-terminal pro-B-type natriuretic peptide.  Conclusions: Plasma GDF-15 is an independent predictor of all-cause mortality in Chinese patients with HF. It may potentially be used to stratify and prognosticate HF patients

VEGF Is Involved in the Increase of Dermal Microvascular Permeability Induced by Tryptase

Tryptases are predominantly mast cell-specific serine proteases with pleiotropic biological activities and play a critical role in skin allergic reactions, which are manifested with rapid edema and increases of vascular permeability. The exact mechanisms of mast cell tryptase promoting vascular permeability, however, are unclear and, therefore, we investigated the effect and mechanism of tryptase or human mast cells (HMC-1) supernatant on the permeability of human dermal microvascular endothelial cells (HDMECs). Both tryptase and HMC-1 supernatant increased permeability of HDMECs significantly, which was resisted by tryptase inhibitor APC366 and partially reversed by anti-VEGF antibody and SU5614 (catalytic inhibitor of VEGFR). Furthermore, addition of tryptase to HDMECs caused a significant increase of mRNA and protein levels of VEGF and its receptors (Flt-1 and Flk-1) by Real-time RT-PCR and Western blot, respectively. These results strongly suggest an important role of VEGF on the permeability enhancement induced by tryptase, which may lead to novel means of controlling allergic reaction in skin

DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction

Self-supervised depth learning from monocular images normally relies on the 2D pixel-wise photometric relation between temporally adjacent image frames. However, they neither fully exploit the 3D point-wise geometric correspondences, nor effectively tackle the ambiguities in the photometric warping caused by occlusions or illumination inconsistency. To address these problems, this work proposes Density Volume Construction Network (DevNet), a novel self-supervised monocular depth learning framework, that can consider 3D spatial information, and exploit stronger geometric constraints among adjacent camera frustums. Instead of directly regressing the pixel value from a single image, our DevNet divides the camera frustum into multiple parallel planes and predicts the pointwise occlusion probability density on each plane. The final depth map is generated by integrating the density along corresponding rays. During the training process, novel regularization strategies and loss functions are introduced to mitigate photometric ambiguities and overfitting. Without obviously enlarging model parameters size or running time, DevNet outperforms several representative baselines on both the KITTI-2015 outdoor dataset and NYU-V2 indoor dataset. In particular, the root-mean-square-deviation is reduced by around 4% with DevNet on both KITTI-2015 and NYU-V2 in the task of depth estimation. Code is available at https://github.com/gitkaichenzhou/DevNet.Comment: Accepted by European Conference on Computer Vision 2022 (ECCV2022

Effect of the combination of cognitive behavioral therapy and oral paroxetine hydrochloride in patients with post-stroke depression

Purpose: To determine the effects of combined use of cognitive behavioral therapy (CBT) and paroxetine hydrochloride tablets in patients with post-stroke depression (PSD), and its effect on scores on Hamilton Rating Scale for Depression (HAMD) and Stroke Specific Quality of Life Scale (SS-QOL). Methods: Clinical data for 96 patients with PSD who were treated in Dongying Traditional Chinese Hospital, Dongying City, China from June 2018 to June 2019 were retrospectively analyzed. Patients who met the inclusion criteria were divided into treatment group (TG, n = 48) and reference group (RG, n = 48) based on odd and even hospitalization numbers. Both groups received conventional treatment, but RG patients were in addition given clopidogrel, while TG received CBT in combination with paroxetine hydrochloride tablets. Clinical indices were evaluated in both groups before and after treatment. Moreover, therapeutic effects in the two different treatment methods on PSD, as well as on Hamilton Rating Scale for Depression (HAMD) and Stroke Specific Quality of Life Scale (SS-QOL) scores were analyzed. Results: After treatment, TG had lower HAMD score (p < 0.001), lower scores on modified Rankin scale, and few incidences of adverse reactions at 3, 7, 15 and 30 days of treatment (p < 0.05), but higher total clinical effectiveness and mean SS-QOL score (p < 0.05), when compared with RG. Conclusion: Combined use of CBT and oral paroxetine hydrochloride tablets may be a promising strategy for treating depression and enhancing the quality of life of PSD patients, as it greatly improves neurological deficit and prognosis. However, further clinical trials should be carried out prior to introducing it in clinical practice