Recent years have witnessed tremendous growth of video streaming applications. To describe users' expectations videos, QoE was proposed, which is critical for content providers. Current delivery systems optimize with ABR algorithms. However, usually designed an abstract "average user" without considering that varies users. In this paper, to investigate the difference in user preferences, we conduct a study 90 subjects and find average can not represent all This observation inspires us...

Previous studies have demonstrated that individuals showed higher risk preference in the afternoon than morning. However, few aimed to explore alteration of feedback learning effect during risky decision making, which is one important psychological processes real behaviors. Moreover, cognitive function altered at off-peak time due impaired inhibitory control. The present study investigate time-of-day on making and control whether causes differences across day.We adopted a within-participants...

The objective of this study was to explore the effect dam body conformations on birth traits including stillbirth, dystocia, gestation length and weight Chinese Holstein calves provide a reference for improving cow reproductive performance. We collected phenotype data 20 conformation cows analyzed impact trait linear scores calf weight. feet angle, set rear legs, fore udder attachment height dairy significantly affected risk stillbirth. dystocia decreases with increase in stature pin width....

With the rapid development of various multimedia applications, research on image compression technology has become particularly important. Learning-based methods have developed rapidly and achieved excellent rate-distortion performance. Most existing researches focused designing a better entropy model to facilitate probability estimation without attaching importance how extract features from images more effectively. However, information extracted by networks is often not realistic complete...

This paper presents a learned low bitrate video compression framework that consists of pre-processing, and post-processing. In pre-processing stage, the source videos are optionally reduced to low-resolution or low-frame-rate ones better meet with limited band-width. inter-frame prediction is performed by deformable convolution (DCN). The predicted frame then used as temporal conditions compress current frame. post-processing decoded fed into Space-Time Super-Resolution module, in which...

Benefiting from flexible network designs and end-to-end joint optimization approach, learned image compression (LIC) has demonstrated excellent coding performance in recent years. However, existing models suffer serious multi-generation loss, which always occurs during editing transcoding. During the process of repeatedly encoding decoding, quality will rapidly degrade, resulting various types distortion, significantly limits practical application LIC. In this paper, a thorough analysis is...

Multiplexed analysis of feature biomarkers enhances the accuracy molecular diagnostic results. Molecular computing systems exhibited potentials for intelligent multiplexed biomarkers. However, chemical reaction networks current suffer from use large number oligonucleotides and limited encoding capability. Here, we developed a platform termed as Digital DNA Strand Displacement (DDSD), utilizing features polymerase-mediated strand extension displacement to achieve robust linear weight well...

Abstract Marigold, as an important traditional Chinese medicine with the functions of clearing heat and detoxification, protecting liver, beautifying face well promoting health eyes, etc. Its demand is increasing day by day, mechanized harvesting has become inevitable trend in industrialization marigold harvesting. Therefore, this study tries to collect a new dataset south Xinjiang, China, which for production focusing on improving YOLOv7 model lightweighting, proposing set detection models...

We present a bionic dissipation system featuring adjustable fuel flux by dynamic DNA nanotechnology allowing for controllable transient states.

This paper presents a learned video compression method in response to track of the 6th Challenge on Learned Image Compression (CLIC), at DCC 2024.Specifically, we propose unified contextual framework (UCVC) for joint P-frame and B-frame coding. Each non-intra frame refers two neighboring decoded frames, which can be either both from past compression, or one future compression. In training stage, model parameters are jointly optimized with P-frames B-frames. Benefiting designs, support coding...

This paper presents a learned video compression method in response to track of the 6th Challenge on Learned Image Compression (CLIC), at DCC 2024. Specifically, we propose unified contextual framework (UCVC) for joint Pframe and B-frame coding. Each non-intra frame refers two neighboring decoded frames, which can be either both from past P-frame compression, or one future compression. In training stage, model parameters are jointly optimized with P-frames B-frames. Benefiting designs,...

The objective of this study was to explore the relationship between calf birth traits and their susceptibility diseases before reaching adulthood. A total 5253 Chinese Holstein calves were examined, including gestation length (GL), weight at (CW), calving ease score (CES), which ranges from 1 (easy) 5 (very difficult). Furthermore, monthly medical records scrutinized for pneumonia diarrhea in these calves. assessed five aspects disease manifestation calves: age first onset, frequency...

Currently, convolution neural network is widely applied in image compression frameworks. However, classical can only capture local information because of the heavy restriction fixed-shape receptive field. In this paper, we propose a novel network, which introduces graph block (GCB) to enhance capability extracting encoder. GCB, and residual are utilized acquire global features at same time. Furthermore, an effective dequantization strategy developed so that decoder learn better parameters...

Abstract Background: Tillage practices and residue management are highly important agricultural practices. However, very few studies have examined the influence of tillage on both bacterial fungal communities network patterns in consecutive years. Results: We effects different practices, including no tillage, rotary deep soil co-occurrence networks following removal retention 2017 2018. This study showed that were unaffected by 2017, but they significantly influenced In addition, operational...