349 research outputs found
Segmentation of Fuzzy and Touching Cells Based on Modified Minimum Spanning Tree and Concave Point Detection
In order to segment fuzzy and touching cell images accurately, an improved algorithm is proposed based on minimum spanning tree (MST) and concave point detection. First, the cell images are smoothed and enhanced by a Gaussian filter. Then, the improved minimum spanning tree algorithm is used to segment the cell images. The MST algorithm is modified from three aspects, namely, weight function of edges, difference function of internal and inter region, and threshold function and parameter k. Furthermore, the problem of cell touching is solved by means of concave point detection. According to the rugged topography of touching cells, the concave points are found from the concave regions in the touching cell images, which are used to find the separation points quickly and accurately. Experimental results indicate that the new algorithm is ideal and effective
PEA265: Perceptual Assessment of Video Compression Artifacts
The most widely used video encoders share a common hybrid coding framework
that includes block-based motion estimation/compensation and block-based
transform coding. Despite their high coding efficiency, the encoded videos
often exhibit visually annoying artifacts, denoted as Perceivable Encoding
Artifacts (PEAs), which significantly degrade the visual Qualityof- Experience
(QoE) of end users. To monitor and improve visual QoE, it is crucial to develop
subjective and objective measures that can identify and quantify various types
of PEAs. In this work, we make the first attempt to build a large-scale
subjectlabelled database composed of H.265/HEVC compressed videos containing
various PEAs. The database, namely the PEA265 database, includes 4 types of
spatial PEAs (i.e. blurring, blocking, ringing and color bleeding) and 2 types
of temporal PEAs (i.e. flickering and floating). Each containing at least
60,000 image or video patches with positive and negative labels. To objectively
identify these PEAs, we train Convolutional Neural Networks (CNNs) using the
PEA265 database. It appears that state-of-theart ResNeXt is capable of
identifying each type of PEAs with high accuracy. Furthermore, we define PEA
pattern and PEA intensity measures to quantify PEA levels of compressed video
sequence. We believe that the PEA265 database and our findings will benefit the
future development of video quality assessment methods and perceptually
motivated video encoders.Comment: 10 pages,15 figures,4 table
Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment
Compressed videos often exhibit visually annoying artifacts, known as
Perceivable Encoding Artifacts (PEAs), which dramatically degrade video visual
quality. Subjective and objective measures capable of identifying and
quantifying various types of PEAs are critical in improving visual quality. In
this paper, we investigate the influence of four spatial PEAs (i.e. blurring,
blocking, bleeding, and ringing) and two temporal PEAs (i.e. flickering and
floating) on video quality. For spatial artifacts, we propose a visual saliency
model with a low computational cost and higher consistency with human visual
perception. In terms of temporal artifacts, self-attention based TimeSFormer is
improved to detect temporal artifacts. Based on the six types of PEAs, a
quality metric called Saliency-Aware Spatio-Temporal Artifacts Measurement
(SSTAM) is proposed. Experimental results demonstrate that the proposed method
outperforms state-of-the-art metrics. We believe that SSTAM will be beneficial
for optimizing video coding techniques
Geometry-based spherical JND modeling for 360 display
360 videos have received widespread attention due to its realistic
and immersive experiences for users. To date, how to accurately model the user
perceptions on 360 display is still a challenging issue. In this paper,
we exploit the visual characteristics of 360 projection and display and
extend the popular just noticeable difference (JND) model to spherical JND
(SJND). First, we propose a quantitative 2D-JND model by jointly considering
spatial contrast sensitivity, luminance adaptation and texture masking effect.
In particular, our model introduces an entropy-based region classification and
utilizes different parameters for different types of regions for better
modeling performance. Second, we extend our 2D-JND model to SJND by jointly
exploiting latitude projection and field of view during 360 display.
With this operation, SJND reflects both the characteristics of human vision
system and the 360 display. Third, our SJND model is more consistent
with user perceptions during subjective test and also shows more tolerance in
distortions with fewer bit rates during 360 video compression. To
further examine the effectiveness of our SJND model, we embed it in Versatile
Video Coding (VVC) compression. Compared with the state-of-the-arts, our
SJND-VVC framework significantly reduced the bit rate with negligible loss in
visual quality
A potential three-gene-based diagnostic signature for idiopathic pulmonary fibrosis
Background: Idiopathic pulmonary fibrosis (IPF) is a life-threatening disease whose etiology remains unknown. This study aims to explore diagnostic biomarkers and pathways involved in IPF using bioinformatics analysis.Methods: IPF-related gene expression datasets were retrieved and downloaded from the NCBI Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened, and weighted correlation network analysis (WGCNA) was performed to identify key module and genes. Functional enrichment analysis was performed on genes in the clinically significant module. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were run to screen candidate biomarkers. The expression and diagnostic value of the biomarkers in IPF were further validated in external test datasets (GSE110147).Results: 292 samples and 1,163 DEGs were screened to construct WGCNA. In WGCNA, the blue module was identified as the key module, and 59 genes in this module correlated highly with IPF. Functional enrichment analysis of blue module genes revealed the importance of extracellular matrix-associated pathways in IPF. IL13RA2, CDH3, and COMP were identified as diagnostic markers of IPF via LASSO and SVM-RFE. These genes showed good diagnostic value for IPF and were significantly upregulated in IPF.Conclusion: This study indicates that IL13RA2, CDH3, and COMP could serve as diagnostic signature for IPF and might offer new insights in the underlying diagnosis of IPF
Preventive Effects of a Chinese Herbal Formula, Shengjiang Xiexin Decoction, on Irinotecan-Induced Delayed-Onset Diarrhea in Rats
Irinotecan is a well-known chemotherapy drug for the treatment of various cancers. However, delayed-onset diarrhea is a common adverse reaction, limiting the application of the drug. The study presented was designed to evaluate the preventive effects of Shengjiang Xiexin decoction (SXD) on irinotecan-induced diarrhea and to explore the possible mechanisms of this action. We established a diarrhea rat model. The condition of the rats was observed. The proliferation and apoptosis of intestinal cells were measured using immunohistochemical assays and a caspase-3 activity assay, respectively. The expression of Lgr5 and CD44 staining were used to observe intestinal stem cells (ISCs). In addition, the activity of β-glucuronidase in the rats’ feces was measured. Our results showed that the number of proliferating intestinal cells in the SXD groups was obviously higher, while the activity of caspase-3 was lower. The expression of Lgr5 and the integrated option density (IOD) of CD44 stain were increased significantly by SXD. Additionally, SXD decreased the activity of β-glucuronidase after irinotecan administration. In conclusion, SXD exhibited preventive effects on irinotecan-induced diarrhea, and this action was associated with an inhibitory effect on intestinal apoptosis and β-glucuronidase and a promotive effect on intestinal cell proliferation due to increased maintenance of ISCs
High-Speed X-Ray Transmission and Numerical Study of Melt Flows inside the Molten Pool during Laser Welding of Aluminum Alloy
By using the X-ray transmission imaging system, melt flows inside a molten pool were studied during laser welding of aluminum alloy at different welding speeds. Then, the correlation between temperature gradients along the direction of weld penetration and melt flows in the rear part of a molten pool was analyzed by using a three-dimensional numerical method. And the presented model was verified by experimental results. The corresponding investigation was carried out to further study the correlation between temperature gradient and melt flow behavior of the molten pool in the plate heated by preheating temperature. The results indicated that, in the rear part of the molten pool, the maximum flow velocity was located at the bottom of the molten pool. The melt metal in the rear molten pool caused by different welding speeds had significantly different flow trends. As the welding speed increased, the absorbed intensity on the keyhole front wall also increased as well as the recoil pressure that could maintain the keyhole opened. Consequently, the increase of the welding speed was more beneficial to improving the stability of the molten pool
Mineralogical characterization of manganese oxide minerals of the Devonian Xialei manganese deposit
The Guangxi Zhuang Autonomous Region is an important manganese ore district in Southwest China, with manganese ore resource reserves accounting for 23% of the total manganese ore resource reserves in China. The Xialei manganese deposit (Daxin County, Guangxi) is the first super-large manganese deposit discovered in China. The Mn oxide in the supergene oxidation zone of the Xialei deposit was characterized using scanning electron microscopy (SEM), energy spectrometer (EDS), transmission electron microscopy (TEM, HRTEM), and X-ray diffraction analysis (XRD). The Mn oxides have a gray-black/steel-gray color, a semi-metallic-earthy luster, and appear as oolitic, pisolitic, banded, massive, and cellular textures. Scanning electron microscopy images show that the manganese oxide minerals are present as fine-spherical particles with an earthy surface. TEM and HRTEM indicate the presence of oriented bundled and staggered nanorods, and nanopores between the crystals. The Mn oxide ore can be classified into two textural types: (1) oolitic and pisolitic (often with annuli) Mn oxide, and (2) massive Mn oxide. Pyrolusite, cryptomelane, and hollandite are the main Mn oxide minerals. The potassium contents of cryptomelane and pyrolusite are discussed. The unit cell parameters of pyrolusite are refined
- …