22 research outputs found
Super-Resolution and Scalable Video Coding
Bits on the wire not only impact video quality delivered to customers but also drive the costs of video streaming services. This project aims at building state-of-the-art deep-learning-based video super-resolution (VSR) algorithms while addressing the compression artifact, and then integrate the VSR into the Scalable Extension of High Efficiency Video Coding (SHVC) by replacing the inter-layer upscaler with the VSR upscaler, and benchmark the codec performance. The discrete cosine transform upsampling filter in SHVC is applied to the base layer reconstructed video, there-fore the reference video for the enhancement layer has scaling artifacts and compression artifacts. The VSR model used to perform upsampling can provide a higher quality reference for the EL.
However, the traditional VSR model can’t be directly used on the SHVC as the low-resolution video used as input for the VSR upscaler is pristine but in SHVC the LR input to the upscaler is compressed by the base layer codec. High-frequency details are lost during the compression and artifacts are introduced by the block-based hybrid video coding framework. Therefore the video super-resolution models need to be modified as the compression process added artifacts to the input. In this work deartifact network (DANet) was introduced to perform the artifacts reduction and super-resolution at the same time. DANet is based on FRVSR which estimates the optical flow between frames and uses motion compensation to align local frames for the super-resolution.
Our DANet performs 0.28dB and 0.81 VMAF better than the FRVSR on the PRIME7 test set with CRF23 LRC video as input.
After integrating DANet to the SHVC codec, on the PRIMT7 test set, using PSNR as the metric, this VSR-integrated scalable video coding framework achieved -5.62% BD-rate reduction at the same video quality and 0.17 dB BD-PSNR quality improvement at the same bitrates compared with the original SHVC. Using VMAF as the metric, our VSR-SHVC achieved -10.01% BD-rate reduction and 0.79 BD-VMAF quality improvement
HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videos
We conducted a large-scale study of human perceptual quality judgments of
High Dynamic Range (HDR) and Standard Dynamic Range (SDR) videos subjected to
scaling and compression levels and viewed on three different display devices.
HDR videos are able to present wider color gamuts, better contrasts, and
brighter whites and darker blacks than SDR videos. While conventional
expectations are that HDR quality is better than SDR quality, we have found
subject preference of HDR versus SDR depends heavily on the display device, as
well as on resolution scaling and bitrate. To study this question, we collected
more than 23,000 quality ratings from 67 volunteers who watched 356 videos on
OLED, QLED, and LCD televisions. Since it is of interest to be able to measure
the quality of videos under these scenarios, e.g. to inform decisions regarding
scaling, compression, and SDR vs HDR, we tested several well-known
full-reference and no-reference video quality models on the new database.
Towards advancing progress on this problem, we also developed a novel
no-reference model called HDRPatchMAX, that uses both classical and bit-depth
sensitive distortion statistics more accurately than existing metrics
The MAP Kinase SsKpp2 Is Required for Mating/Filamentation in Sporisorium scitamineum
In the phytopathogenic fungus Sporisorium scitamineum, sexual mating between two compatible haploid cells and the subsequent formation of dikaryotic hyphae is essential for infection. This process was shown to be commonly regulated by a mitogen-activated protein kinase (MAPK) and a cAMP/PKA signaling pathway in the corn smut fungus Ustilago maydis but remains largely unknown in S. scitamineum. In this study, we identified a conserved putative MAP kinase Kpp2 in S. scitamineum and named it as SsKpp2. The sskpp2Δ mutant displayed significant reduction in mating/filamentation, which could be partially restored by addition of cAMP or tryptophol, a quorum-sensing molecule identified in budding yeast. Transcriptional profiling showed that genes governing S. scitamineum mating or tryptophol biosynthesis were significantly differentially regulated in the sskpp2Δ mutant compared to the WT, under mating condition. Our results demonstrate that the MAP kinase SsKpp2 is required for S. scitamineum mating/filamentation likely through regulating the conserved pheromone signal transduction pathway and tryptophol production
Novel anion exchange membranes based on polymerizable imidazolium salt for alkaline fuel cell applications
A new polymerizable imidazolium salt monomer, 1-(4-vinylbenzyl)-3-methyl-imidazolium chloride ([VBMI]Cl), has been readily synthesized by reaction of 4-vinylbenzyl chloride with 1-methylimidazole. Novel anion exchange membranes (AEMs) based on the copolymers of [VBMI]Cl and styrene have been prepared and characterized. Excellent thermostability of the membranes is observed through the thermo-gravimetric analysis (TGA) curves. Water uptake and ion exchange capacity (IEC) of the OH(-) form AEMs range from 26.1% to 61.9% and from 0.95 to 1.45 mmol g(-1), respectively. This type of AEM displays significant ionic conductivities over the order of 10(-2) S cm(-1) in deionized water at room temperature, and the membranes are stable in 10 mol L(-1) NaOH solution at 60 degrees C for 120 h. For the H(2)/air single fuel cell at 30 degrees C with this novel AEM, the peak power density of 33 mW cm(-2) is obtained at a current density of 59 mA cm(-2).High-Tech Research and Development Program of China[2008AA05Z107]; National Nature Science Foundation of China[20876129
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities
Multi-modal Large Language Models (MLLMs) have shown impressive abilities in
generating reasonable responses with respect to multi-modal contents. However,
there is still a wide gap between the performance of recent MLLM-based
applications and the expectation of the broad public, even though the most
powerful OpenAI's GPT-4 and Google's Gemini have been deployed. This paper
strives to enhance understanding of the gap through the lens of a qualitative
study on the generalizability, trustworthiness, and causal reasoning
capabilities of recent proprietary and open-source MLLMs across four
modalities: ie, text, code, image, and video, ultimately aiming to improve the
transparency of MLLMs. We believe these properties are several representative
factors that define the reliability of MLLMs, in supporting various downstream
applications. To be specific, we evaluate the closed-source GPT-4 and Gemini
and 6 open-source LLMs and MLLMs. Overall we evaluate 230 manually designed
cases, where the qualitative results are then summarized into 12 scores (ie, 4
modalities times 3 properties). In total, we uncover 14 empirical findings that
are useful to understand the capabilities and limitations of both proprietary
and open-source MLLMs, towards more reliable downstream multi-modal
applications
Turtle interacts with borderless in regulating glial extension and axon ensheathment
Abstract Proper recognition between axons and glial processes is required for the establishment of axon ensheathment in the developing nervous system. Recent studies have begun to reveal molecular events underlying developmental control of axon-glia recognition. In our previous work, we showed that the transmembrane protein Borderless (Bdl) is specifically expressed in wrapping glia (WG), and is required for the extension of glial processes and the ensheathment of photoreceptor axons in the developing Drosophila visual system. The exact mechanism by which Bdl mediates axon-glia recognition, however, remains unknown. Here, we present evidence showing that Bdl interacts with the Ig transmembrane protein Turtle (Tutl). Tutl is specifically expressed in photoreceptor axons. Loss of tutl in photoreceptors, like loss of bdl in WG, disrupts glial extension and axon ensheatment. Epistasis analysis shows that Tutl interacts genetically with Bdl. Tutl interacts with Bdl in trans in cultured cells. We propose that Tutl interacts with Bdl in mediating axon-glia recognition for WG extension and axon ensheathment
Comparison of machine learning models and CEUS LI-RADS in differentiation of hepatic carcinoma and liver metastases in patients at risk of both hepatitis and extrahepatic malignancy
Abstract Background CEUS LI-RADS (Contrast Enhanced Ultrasound Liver Imaging Reporting and Data System) has good diagnostic efficacy for differentiating hepatic carcinoma (HCC) from solid malignant tumors. However, it can be problematic in patients with both chronic hepatitis B and extrahepatic primary malignancy. We explored the diagnostic performance of LI-RADS criteria and CEUS-based machine learning (ML) models in such patients. Methods Consecutive patients with hepatitis and HCC or liver metastasis (LM) who were included in a multicenter liver cancer database between July 2017 and January 2022 were enrolled in this study. LI-RADS and enhancement features were assessed in a training cohort, and ML models were constructed using gradient boosting, random forest, and generalized linear models. The diagnostic performance of the ML models was compared with LI-RADS in a validation cohort of patients with both chronic hepatitis and extrahepatic malignancy. Results The mild washout time was adjusted to 54 s from 60 s, increasing accuracy from 76.8 to 79.4%. Through feature screening, washout type II, rim enhancement and unclear border were identified as the top three predictor variables. Using LI-RADS to differentiate HCC from LM, the sensitivity, specificity, and AUC were 68.2%, 88.6%, and 0.784, respectively. In comparison, the random forest and generalized linear model both showed significantly higher sensitivity and accuracy than LI-RADS (0.83 vs. 0.784; all P < 0.001). Conclusions Compared with LI-RADS, the random forest and generalized linear model had higher accuracy for differentiating HCC from LM in patients with chronic hepatitis B and extrahepatic malignancy
Flow Characteristics and Heat-Transfer Enhancement of Air Agitation in Ice Storage Air Conditioning Systems
A large number of bubbles generated by the air agitation device in an external melting ice storage system can cause the disturbance of the ice–water mixture, which can enhance the heat transfer and contribute to the reduction in energy consumption. The structural design and optimization of the air agitation device in an external melting ice storage system is the key issue for energy savings. In this study, the influence of different orifice spacings and diameters on the distribution of the gas–liquid flow field, gas holdup, heat-transfer coefficient, and power consumption in the ice storage tank was investigated by numerical simulation. The simulated results showed that the heat-transfer coefficient of the ice–water mixture with air bubbles should be 3–5 times higher than the natural convection when the air superficial velocity is 0.03 m/s. The gas holdup was mainly affected by the orifice spacing, and the maximum varied from 5.0% to 8.2%. When the orifice spacing was less than 150 mm, the gas holdup changed a little in the horizontal direction, and the uniformity became worse when the orifice spacing was larger than 180 mm. An orifice diameter larger than 3 mm can improve the heat transfer and cause less air-compressing energy consumption, which decreased by approximately 1.62%
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Improving Quantitative Power in Digital PCR through Digital High-Resolution Melting.
Applying digital PCR (dPCR) technology to challenging clinical and industrial detection tasks has become more prevalent because of its capability for absolute quantification and rare target detection. However, practices learned from quantitative PCR (qPCR) that promote assay robustness and wide-ranging utility are not readily applied in dPCR. These include internal amplification controls to account for false-negative reactions and amplicon high-resolution melt (HRM) analysis to distinguish true positives from false positives. Incorporation of internal amplification controls in dPCR is challenging because of the limited fluorescence channels available on most machines, and the application of HRM analysis is hindered by the separation of heating and imaging functions on most dPCR systems. We use a custom digital HRM platform to assess the utility of HRM-based approaches for mitigation of false positives and false negatives in dPCR. We show that detection of an exogenous internal control using dHRM analysis reduces the inclusion of false-negative partitions, changing the calculated DNA concentration up to 52%. The integration of dHRM analysis enables classification of partitions that would otherwise be considered ambiguous "rain," which accounts for up to ∼3% and ∼10% of partitions in intercalating dye and hydrolysis probe dPCR, respectively. We focused on developing an internal control method that would be compatible with broad-based microbial detection in dPCR-dHRM. Our approach can be applied to a number of DNA detection methods including microbial profiling and may advance the utility of dPCR in clinical applications where accurate quantification is imperative