Versatile Video Coding (VVC) was finalized in July 2020 as the most recent international video coding standard. It was developed by the Joint Video Experts Team (JVET) of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) to serve an ever-growing need for improved video compression as well as to support a wider variety of today's media content and emerging applications. This paper provides an overview of the novel technical features for new applications and the core compression technologies for achieving significant bit rate reductions in the neighborhood of 50% over its predecessor for equal video quality, the High Efficiency Video Coding (HEVC) standard, and 75% over the currently most-used format, the Advanced Video Coding (AVC) standard. It is explained how these new features in VVC provide greater versatility for applications. Highlighted applications include video with resolutions beyond standard-and high-definition, video with high dynamic range and wide color gamut, adaptive streaming with resolution changes, computer-generated and screen-captured video, ultralow-delay streaming, 360° immersive video, and multilayer coding e.g., for scalability. Furthermore, early implementations are presented to show that the new VVC standard is implementable and ready for real-world deployment.

This paper provides an overview of SHVC, the scalable extensions of the High Efficiency Video Coding (HEVC) standard, published in the second version of HEVC. In addition to the temporal scalability already provided by the first version of HEVC, SHVC further provides spatial, SNR, bit depth, and color gamut scalability functionalities, as well as combinations of any of these. The SHVC architecture design enables SHVC implementations to be built using multiple repurposed single-layer HEVC codec cores, with the addition of inter-layer reference picture processing modules. The general multi-layer high-level syntax design common to all multi-layer HEVC extensions, including SHVC, MV-HEVC, and 3D-HEVC, is described. The inter-layer reference picture processing modules, including texture and motion resampling and color mapping, are also described. Performance comparisons are provided of SHVC versus simulcast HEVC and versus the Scalable Video Coding (SVC) extension to H.264/AVC. Index Terms-SHVC, HEVC, JCT-VC, JCT-3V, MPEG, scalable video coding, SVC, video standards, VCEG, video compression.Y. Ye is with InterDigital Communications LLC,

Mobile devices, increasingly equipped with high capability processors and connected with fast wireless networks, have become a major consumer of multi-media content. Limited battery life on mobile devices makes power saving a critical factor in delivering a good user experience. This paper proposes a power aware streaming system that combines the emerging High Efficiency Video Coding (HEVC) standard and the Dynamic Adaptive Streaming over HTTP (DASH) standard. The proposed system uses power aware HEVC encoding technologies and client side power adaptation logic to adaptively control power consumption on the client device. The proposed power aware HEVC streaming system can improve quality of experience by setting full-length video playback as client' s objective. Demonstration of the proposed power aware HEVC system is available on the ASUS Transformer Xfinity (TF700T) tablet using an ARM processor. Index Terms-HEVC, DASH, battery life, power saving, video streaming, video coding the information about the video being rendered, such as the decoding complexity level of the video segment, the current power dissipation rate, and remaining playback time. In the prototype implementation, instead of MP4 encapsulation, raw HEVC elementary bitstreams are used at the server side. 3. POWER A WARE ENCODING Compared to H.264/AVC, HEVC uses larger video blocks. The size of the largest video blocks, also called the coding tree blocks (CTB), is signaled in the Sequence Parameter Set (SPS). Each CTB is quadtree partitioned into coding units (CU) with variable sizes. Each CU consists of prediction units (PU) and transfonn units (TU). Complexity analyses of HEVC decoder implementations have been made available in [3] [5] ; it is reported that, in the random access encoding configuration with hierarchical B prediction [13] , typically motion compensation (MC), deblocking, and entropy decoding take about 50%, 20%, and 20% of the overall decoding time, respectively. Profiling of our HEVC decoder implementation on ARM showed similar results. Based on this observation, the power aware HEVC encoder in the proposed system considers motion compensation and deblocking when generating bitstreams with different complexity levels. In HEVC, I-D interpolation filters are applied when fractional motion vectors are used (up to 114-pel precision); the interpolation filters are 7-and 8-tap for luma and 4-tap for chroma. Depending on the fractional positions of the motion vectors, the memory size fetched for MC, number of filters applied, as well as the filter symmetry can be

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BackgroundBrick tea type fluorosis is a public health concern in the north-west area of China. The association between SNPs of genes influencing bone mass and fluorosis has attracted attention, but the association of SNPs with the risk of brick-tea type of fluorosis has not been reported.ObjectiveTo investigate the modifying roles of GSTP1 rs1695 polymorphisms on this association.MethodsA cross-sectional study was conducted. Brick-tea water was tested by the standard of GB1996-2005 (China). Urinary fluoride was tested by the standard of WS/T 89-2006 (China). Skeletal fluorosis was diagnosed by X-ray, the part we scheduled was forearm, shank, and pelvic, then diagnosed the skeletal fluorosis by the standard of WS/192-2008 (China). Gene polymorphism was tested by Sequenom MassARRAY system.ResultThe prevalence rate in different ethnical participants was different: Tibetan individuals had the highest prevalence rate of skeletal fluorosis. There were significant differences in genotype frequencies of GSTP1 Rs1695 among different ethnical participants (p<0.001): Tibetan, Mongolian and Han subjects with homozygous wild type (GSTP1-AA) genotype were numerically higher than Kazakh and Russian subjects (p<0.001). Compared to Tibetan participants who carried homozygous A allele of GSTP1 Rs1695, Tibetan participants who carried G allele had a significantly decreased risk of skeletal fluorosis (OR = 0.558 [95% CI, 0.326-0.955]). For Kazakh participants, a decreased risk of skeletal fluorosis among carriers of the G allele was limited to non high-loaded fluoride status (OR = 0. 166 [95% CI, 0.035–0.780] vs. OR = 1.478 [95% CI, 0.866–2.552] in participants with high-loaded fluoride status). Neither SNP-IF nor SNP-age for GSTP1 Rs1695 was observed.ConclusionThe prevalence rate of the brick tea type fluorosis might have ethnic difference. For Tibetan individuals, who had the highest prevalence rate, G allele of GSTP1 Rs1695 might be a protective factor for brick tea type skeletal fluorosis.