Perceptual Quality-of-Experience of Stereoscopic 3D Images and Videos

With the fast development of 3D acquisition, communication, processing and display technologies, automatic quality assessment of 3D images and videos has become ever important. Nevertheless, recent progress on 3D image quality assessment (IQA) and video quality assessment (VQA) remains limited. The purpose of this research is to investigate various aspects of human visual quality-of-experience (QoE) when viewing stereoscopic 3D images/videos and to develop objective quality assessment models that automatically predict visual QoE of 3D images/videos. Firstly, we create a new subjective 3D-IQA database that has two features that are lacking in the literature, i.e., the inclusion of both 2D and 3D images, and the inclusion of mixed distortion types. We observe strong distortion type dependent bias when using the direct average of 2D image quality to predict 3D image quality. We propose a binocular rivalry inspired multi-scale model to predict the quality of stereoscopic images and the results show that the proposed model eliminates the prediction bias, leading to significantly improved quality predictions. Second, we carry out two subjective studies on depth perception of stereoscopic 3D images. The first one follows a traditional framework where subjects are asked to rate depth quality directly on distorted stereopairs. The second one uses a novel approach, where the stimuli are synthesized independent of the background image content and the subjects are asked to identify depth changes and label the polarities of depth. Our analysis shows that the second approach is much more effective at singling out the contributions of stereo cues in depth perception. We initialize the notion of depth perception difficulty index (DPDI) and propose a novel computational model for DPDI prediction. The results show that the proposed model leads to highly promising DPDI prediction performance. Thirdly, we carry out subjective 3D-VQA experiments on two databases that contain various asymmetrically compressed stereoscopic 3D videos. We then compare different mixed-distortions asymmetric stereoscopic video coding schemes with symmetric coding methods and verify their potential coding gains. We propose a model to account for the prediction bias from using direct averaging of 2D video quality to predict 3D video quality. The results show that the proposed model leads to significantly improved quality predictions and can help us predict the coding gain of mixed-distortions asymmetric video compression. Fourthly, we investigate the problem of objective quality assessment of Multi-view-plus-depth (MVD) images, with a main focus on the pre- depth-image-based-rendering (pre-DIBR) case. We find that existing IQA methods are difficult to be employed as a guiding criterion in the optimization of MVD video coding and transmission systems when applied post-DIBR. We propose a novel pre-DIBR method based on information content weighting of both texture and depth images, which demonstrates competitive performance against state-of-the-art IQA models applied post-DIBR

Stereoscopic image quality assessment by deep convolutional neural network

The final publication is available at Elsevier via https://doi.org/10.1016/j.jvcir.2018.12.006. © 2018 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this paper, we propose a no-reference (NR) quality assessment method for stereoscopic images by deep convolutional neural network (DCNN). Inspired by the internal generative mechanism (IGM) in the human brain, which shows that the brain first analyzes the perceptual information and then extract effective visual information. Meanwhile, in order to simulate the inner interaction process in the human visual system (HVS) when perceiving the visual quality of stereoscopic images, we construct a two-channel DCNN to evaluate the visual quality of stereoscopic images. First, we design a Siamese Network to extract high-level semantic features of left- and right-view images for simulating the process of information extraction in the brain. Second, to imitate the information interaction process in the HVS, we combine the high-level features of left- and right-view images by convolutional operations. Finally, the information after interactive processing is used to estimate the visual quality of stereoscopic image. Experimental results show that the proposed method can estimate the visual quality of stereoscopic images accurately, which also demonstrate the effectiveness of the proposed two-channel convolutional neural network in simulating the perception mechanism in the HVS.This work was supported in part by the Natural Science Foundation of China under Grant 61822109 and 61571212, Fok Ying Tung Education Foundation under Grant 161061 and by the Natural Science Foundation of Jiangxi under Grant 20181BBH80002

Thirty-six months recurrence after acute ischemic stroke among patients with comorbid type 2 diabetes: A nested case-control study

Background: Stroke patients have to face a high risk of recurrence, especially for those with comorbid T2DM, which usually lead to much more serious neurologic damage and an increased likelihood of death. This study aimed to explore determinants of stroke relapse among patients with comorbid T2DM. Materials and methods: We conducted this case-control study nested a prospective cohort of ischemic stroke (IS) with comorbid T2DM. During 36-month follow-up, the second stroke occurred in 84 diabetic IS patients who were allocated into the case group, while 613 patients without recurrence were the controls. We collected the demographic data, behaviors and habits, therapies, and family history at baseline, and measured the variables during follow-up. LASSO and Logistic regression analyses were carried out to develop a prediction model of stroke recurrence. The receiver operator characteristic (ROC) curve was employed to evaluate the performance of the prediction model. Results: Compared to participants without recurrence, the higher levels of pulse rate (78.29 ± 12.79 vs. 74.88 ± 10.93) and hypertension (72.6 vs. 61.2 %) were recorded at baseline. Moreover, a lower level of physical activity (77.4 vs. 90.4 %), as well as a higher proportion of hypoglycemic therapy (36.9 vs. 23.3 %) was also observed during 36-month follow-up. Multivariate logistic regression revealed that higher pulse rate at admission (OR = 1.027, 95 % CI = 1.005 – 1.049), lacking physical activity (OR = 2.838, 9 5 % CI = 1.418 – 5.620) and not receiving hypoglycemic therapy (OR = 1.697, 95 % CI = 1.013 – 2.843) during follow-up increased the risk of stroke recurrence. We developed a prediction model using baseline pulse rate, hypoglycemic therapy, and physical activity, which produced an area under ROC curve (AUC) of 0.689. Conclusion: Physical activity and hypoglycemic therapy play a protective role for IS patients with comorbid diabetes. In addition to targeted therapeutics, the improvement of daily-life habit contributes to slowing the progress of the IS

Empirical model for fitting the viscosity of lithium bromide solution with CuO nanoparticles and E414

To research viscosity fitting model of stable nano-lithium bromide solution (nano-LiBr), the stability of the nano-LiBr and the dynamic viscosity of LiBr were measued by Ultraviolet-visible spectroscopy (UV-vis) and rotational viscometer respectively. Two LiBr with different additives were measured, i.e., LiBr with dispersant (E414) and LiBr with dispersant + copper oxide nanoparticles (CuO). The ranges of measuring temperature were from 25°C–60°C, the concentrations of LiBr were from 50%–59%, the volume fractions of the dispersants were from 0%–4%, and the fractions of nanoparticle volume were from 0%–0.05%. Results indicated that the nano-LiBr with E414 had good stability. The viscosity of the LiBr decreased when temperature increased, and increased when LiBr concentration and dispersant amount were increased. It is also found that the viscosity was directly proportional to the volume fraction of the nanoparticles. This study also showed that the higher the concentration of the base fluid was, the more significant increase of the viscosity was. An empirical viscosity model of stable nano-LiBr with a maximum error of 13% was developed

Single Nucleotide Polymorphism WRN Leu1074Phe Is Associated with Prostate Cancer Susceptibility in Chinese Subjects

Deficiencies in the human DNA repair gene WRN are the cause of Werner syndrome, a rare autosomal recessive disorder characterized by premature aging and a predisposition to cancer. This study evaluated the association of WRN Leu1074Phe (rs1801195), a common missense single nucleotide polymorphism in WRN, with prostate cancer susceptibility in Chinese subjects. One hundred and forty-seven prostate cancer patients and 111 male cancer-free control subjects from 3 university hospitals in China were included. Blood samples were obtained from each subject, and the single nucleotide polymorphism WRN Leu1074Phe was genotyped by using a Snapshot assay. The results showed that WRN Leu1074Phe was associated with the risk of prostate cancer in Chinese men and that the TG/GG genotype displayed a decreased prevalence of prostate cancer compared with the TT genotype (OR＝0.58, 95%CI:0.35-0.97, p＝0.039). Through stratified analysis, more significant associations were revealed for the TG/GG genotype in the subgroup with diagnosis age <_ 72 yr (OR＝0.27, 95%CI:0.12-0.61, p＝0.002) and in patients with localized diseases (OR＝0.36, 95%CI:0.19-0.70, p＝0.003). However, no statistically significant difference was found in the subgroup with age ＞72 yr or in patients with advanced diseases. We concluded that the genetic variant Leu1074Phe in the DNA repair gene WRN might play a role in the risk of prostate cancer in Chinese subjects

Optoelectronic crystal of artificial atoms in strain-textured molybdenum disulphide

The isolation of the two-dimensional semiconductor molybdenum disulphide introduced a new optically active material possessing a band gap that can be facilely tuned via elastic strain. As an atomically thin membrane with exceptional strength, monolayer molybdenum disulphide subjected to biaxial strain can embed wide band gap variations overlapping the visible light spectrum, with calculations showing the modified electronic potential emanating from point-induced tensile strain perturbations mimics the Coulomb potential in a mesoscopic atom. Here we realize and confirm this ‘artificial atom’ concept via capillary-pressure-induced nanoindentation of monolayer molybdenum disulphide from a tailored nanopattern, and demonstrate that a synthetic superlattice of these building blocks forms an optoelectronic crystal capable of broadband light absorption and efficient funnelling of photogenerated excitons to points of maximum strain at the artificial-atom nuclei. Such two-dimensional semiconductors with spatially textured band gaps represent a new class of materials, which may find applications in next-generation optoelectronics or photovoltaics

Stromal protein CCN family contributes to the poor prognosis in lower-grade gioma by modulating immunity, matrix, stemness, and metabolism

Background: The CCN family of stromal proteins is involved in the regulation of many important biological functions. However, the role of dysregulated CCN proteins in lower-grade glioma (LGG) remain less understand.Methods: The clinical significance of the CCN proteins was explored based on RNA-seq profiles from multiple cohorts. A CCNScore was constructed using LASSO regression analysis. The PanCanAtlas data and MEXPRESS database were employed to elucidate molecular underpinnings.Results: The expression of CCN4 was associated with poor prognosis in LGG. The CCNScore (CCN1 = 0.06, CCN4 = 0.86) showed implication in prognosis prediction, subtype assessment and therapy selection. The gene mutation pattern of the high-CCNScore group was similar with glioblastoma, including EGFR, PTEN, and NF1 mutation frequently. Besides, the high-CCNScore group was comprised of samples mainly classic-like and mesenchymal-like, had lower methylation levels, higher stemness, higher inflammation, higher levels of extracellular matrix remodel and dysfunction of metabolic pathways. On the other hand, the low-CCNScore group consisted mainly of IDH-mutation LGG, and was characterized by TP53, CIC, and ATRX gene mutations, hyper-methylation status, lower stemness, lower proliferation, immune quietness and low extracellular matrix stiffness.Conclusion: In summary, these results outlined the role of CCN family in LGG and provided a potential and promising therapeutic target