Bridge the Gap Between VQA and Human Behavior on Omnidirectional Video: A Large-Scale Dataset and a Deep Learning Model

Omnidirectional video enables spherical stimuli with the $360 \times 180^ \circ$ viewing range. Meanwhile, only the viewport region of omnidirectional video can be seen by the observer through head movement (HM), and an even smaller region within the viewport can be clearly perceived through eye movement (EM). Thus, the subjective quality of omnidirectional video may be correlated with HM and EM of human behavior. To fill in the gap between subjective quality and human behavior, this paper proposes a large-scale visual quality assessment (VQA) dataset of omnidirectional video, called VQA-OV, which collects 60 reference sequences and 540 impaired sequences. Our VQA-OV dataset provides not only the subjective quality scores of sequences but also the HM and EM data of subjects. By mining our dataset, we find that the subjective quality of omnidirectional video is indeed related to HM and EM. Hence, we develop a deep learning model, which embeds HM and EM, for objective VQA on omnidirectional video. Experimental results show that our model significantly improves the state-of-the-art performance of VQA on omnidirectional video.Comment: Accepted by ACM MM 201

One-for-All: Towards Universal Domain Translation with a Single StyleGAN

In this paper, we propose a novel translation model, UniTranslator, for transforming representations between visually distinct domains under conditions of limited training data and significant visual differences. The main idea behind our approach is leveraging the domain-neutral capabilities of CLIP as a bridging mechanism, while utilizing a separate module to extract abstract, domain-agnostic semantics from the embeddings of both the source and target realms. Fusing these abstract semantics with target-specific semantics results in a transformed embedding within the CLIP space. To bridge the gap between the disparate worlds of CLIP and StyleGAN, we introduce a new non-linear mapper, the CLIP2P mapper. Utilizing CLIP embeddings, this module is tailored to approximate the latent distribution in the P space, effectively acting as a connector between these two spaces. The proposed UniTranslator is versatile and capable of performing various tasks, including style mixing, stylization, and translations, even in visually challenging scenarios across different visual domains. Notably, UniTranslator generates high-quality translations that showcase domain relevance, diversity, and improved image quality. UniTranslator surpasses the performance of existing general-purpose models and performs well against specialized models in representative tasks. The source code and trained models will be released to the public

Effect of childhood maltreatment on cognitive function and its relationship with personality development and social coping style in major depression disorder patients: A latent class model and network analysis

Study objectivesThe study aimed to (1) analyze the interrelationships among different types of childhood adversity, diverse personality dimensions, and individual coping style integratively among major depressive disorder (MDD) patients and healthy participants using a network approach; (2) explore the latent class of child maltreatment (CM) and its relationship with cognitive function.MethodsData were collected from the Objective Diagnostic Markers and Personalized Intervention in MDD Patients (ODMPIM) study, including 1,629 Chinese participants. Using the Childhood Trauma Questionnaire to assess CM, the Simplified Coping Style Questionnaire to measure individual coping style, Eysenck Personality Questionnaire Revised-Short Form for personality characters, and a series of neurocognitive tests, including seven tests with 18 subtests for cognitive assessments. We used the “Network Module” in Jeffreys’s Amazing Statistics Program (JASP) and R package for network analysis. A latent class analysis was performed with SAS9.4.ResultsChild maltreatment was more common in MDD patients than in healthy controls, except for emotional abuse. Network analysis showed that emotional abuse, emotional neglect, physical abuse, and physical neglect formed quadrangle connections. Personality dimensions were associated with physical neglect and emotional abuse. All types of CM (excluding sex abuse) showed an association with coping style. Emotional neglect showed the highest centrality measures. Physical neglect had a high level of closeness. To a concerning strength, emotional and physical neglect showed the highest levels. The structure of the networks is variant between groups (M = 0.28, P = 0.04). Latent class analysis (LCA) revealed that three classes provided the best fit statistics. Neglect and abuse classes tended to perform more poorly on the five cognitive domains.ConclusionThis study provided insights on multi-type of CM. Neglect played an important role in different routes through the relation between CM with personality traits and social coping style. However, neglect has often been ignored in previous studies and should receive more public attention

Carbon neutral hydrogen storage and release cycles based on dual-functional roles of formamides

Abstract The development of alternative clean energy carriers is a key challenge for our society. Carbon-based hydrogen storage materials are well-suited to undergo reversible (de)hydrogenation reactions and the development of catalysts for the individual process steps is crucial. In the current state, noble metal-based catalysts still dominate this field. Here, a system for partially reversible and carbon-neutral hydrogen storage and release is reported. It is based on the dual-functional roles of formamides and uses a small molecule Fe-pincer complex as the catalyst, showing good stability and reusability with high productivity. Starting from formamides, quantitative production of CO-free hydrogen is achieved at high selectivity ( > 99.9%). This system works at modest temperatures of 90 °C, which can be easily supplied by the waste heat from e.g., proton-exchange membrane fuel cells. Employing such system, we achieve >70% H2 evolution efficiency and >99% H2 selectivity in 10 charge-discharge cycles, avoiding undesired carbon emission between cycles

NL3DLogTNN: An Effective Hyperspectral Image Denoising Method Combined Non-Local Self-Similarity and Low-Fibered- Rank Regularization

Hyperspectral image denoising is an important research topic in the field of remote sensing image processing. Recently, methods based on non-local low-rank tensor approximation have gained widespread attention towing to their ability to fully exploit non-local self-similarity. However, existing non-local low-rank tensor approximation methods fall short in capturing the correlations between various modes in hyperspectral images, thus failing to achieve the optimal approximation. To solve this issue, a novel three-directional log-based tensor nuclear norm (3DLogTNN)–based non-local hyperspectral image denoising model NL3DLogTNN is proposed. The correlation between the various modes of the model was obtained by performing TNN decomposition in three directions on the extracted non-local comparable blocks, better capturing the global low-rank property of the image. To effectively solve the proposed NL3DLogTNN model, we developed an approximate alternating direction method of multipliers (ADMM)-based methodology and offered a thorough numerical convergence proof. Extensive experiments are conducted on hyperspectral image datasets with simulated noise and real-world noise, which demonstrated that the proposed NL3DLogTNN model outperforms state-of-the-art methods in terms of quantitative and visual performance evaluation

Hygrothermal ageing performance of high temperature vulcanised silicone rubber and its degradation mechanism

Abstract High temperature vulcanised silicone rubber (SR) has excellent hydrophobicity and thus is widely applied both in indoor and outdoor insulation. According to the analysis of different experimental ageing tests and field investigation of SR, temperature and humidity are considered to be the fundamental factors during degradation. Hygrothermal ageing was proposed in this study to simulate the chalking state of the SR, finally leading to the irreversible degradation far below the thermal decomposition temperature. The variation of morphology, hardness and polydimethylsiloxane (PDMS) content was quantified during the yearlong hygrothermal ageing test. It is implied that the gradual process of whitening and hardening are accompanied by the decline of the PDMS content. Finally, ageing delamination in SR and its degradation mechanism were proposed

A flexible Hf0.5Zr0.5O2 thin film with highly robust ferroelectricity

Flexible hafnia-based ferroelectric memories are arousing much interest with the ever-growing demands for nonvolatile data storage in wearable electronic devices. Here, high-quality flexible Hf0.5Zr0.5O2 membranes with robust ferroelectricity were fabricated on inorganic pliable mica substrates via an atomic layer deposition technique. The flexible Hf0.5Zr0.5O2 thin membranes with a thickness of ∼8 nm exhibit a high remanent polarization of ∼16 μC/cm2, which possess very robust polarization switching endurance (>1010 cycles, two orders of magnitude better than reported flexible HfO2-based films) and superior retention ability (expected >10 years). In particular, stable ferroelectric polarization as well as excellent endurance and retention performance show negligible degradations under 6 mm radius bending conditions or after 104 bending cycles with a 6 mm bending radius. These results mark a crucial step in the development of flexible hafnium oxide-based ferroelectric memories for wearable electronic devices

Plasma exosomes lncRNA-miRNA-mRNA network construction and its diagnostic efficacy identification in first-episode schizophrenia

Abstract Background The exosomal lncRNA-miRNA-mRNA networks in first episode schizophrenia (FOS) have not reported yet. This study examined the lncRNA, miRNA and mRNA expression level in exosome derived from first episode schizophrenia (FOS) patients, and explored the the potential of exosomes as biomarkers for schizophrenia. Methods We recruited 10 FOS patients and healthy controls (HCs) respectively, examined the lncRNA, miRNA and mRNA expression level of plasma exosome by high throughput sequencing, constructed lncRNA-miRNA-mRNA network, and performed correlation analysis, GO and KEGG pathway analysis, PPI network construction and ROC analysis. Results There were 746 differently expressed lncRNA, 22 differently expressed miRNA, and 2637 differently expressed mRNA in plasma exosome in FOS compared with HCs. Then we constructed ceRNA network consisting of 8 down-regulated lncRNA, 7 up-regulated miRNA and 65 down-regulated mRNA, and 1 up-regulated lncRNA, 1 down-regulated miRNA and 4 up-regulated mRNA. The expression level of 1 lncRNA and 7 mRNA in exosomal network were correlated with PANSS score. GO and KEGG pathway analysis showed that 4 up-regulated mRNAs were enriched in neuropsychiatric system function. Down-regulated mRNA EZH2 and SIRT1 were identified as hub gene. Finally, we detected the ROC curve of ENSG00000251562, miR-26a-5p, EZH2, miR-22-3p, SIRT1, ENSG00000251562—miR-26a-5p—EZH2, ENSG00000251562—miR-22-3p—SIRT1, and found that the AUC of ceRNA network was higher than lncRNA, miRNA and mRNA alone. Conclusion We constructed the lncRNA-miRNA-mRNA network in exosome derived from FOS plasma, and found that lncRNA-miRNA-mRNA network has potential as biomarkers for FOS

Multiselective gridization achieved by electrophilic C-X activation of dual halogen bonding cooperation

Organic science & technology (OST) become the frontier horizon after nanotechnology, information technology as well as biotechnology toward the era of consciousness. Organic nanogridarenes (ONGAs) are becoming robust nanoscaffolds for next-generation multifunctional/intelligent semiconductors with tunable cross-scale features. However, the prerequisite of trans-dimensional & intelligent design is to clarify the gridization rules for the discovery of the powerful molecular gridization protocols. Here, we report an efficient and multiselective Csp2-Csp3 gridization based on dual halogen bonding (X···π and X···S, X = Br, I) self-activated electrophilic substitution of halogenated electron-rich molecular blocks under supersonic conditions. Windmill-type nanogrids of cyclopenta[1,2-b:5,4-b\u27]dithiophene (WG4) were obtained with the maximum path selectivity (96%), nanogrid-size selectivity (67%), site-selectivity (>99%) and moderate diastereoselectivity (WG4-1-6:WG4-2-6:WG4-3-6:WG4-4-6 =1:3.3:5.3:0), superior to the previous Friedel-Crafts gridization. Mechanistic studies have revealed the roles of XBs where the X···S bonding accelerates dehalogenation after electrophilic attack, and the X···π bonding leads to the multiselectivity of WG4. Impressively, C2-symmetric WG4-1-6 (21×21×15 Å) crystallizes into a Fd3̄c space group as the 16th pure organic molecules in CCDC library and hierarchically self-assemble into a complex 3D porous superstructure