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Article ; Online: Fumos: Neural Compression and Progressive Refinement for Continuous Point Cloud Video Streaming.

Liang, Zhicheng / Liu, Junhua / Dasari, Mallesham / Wang, Fangxin

IEEE transactions on visualization and computer graphics

2024 Volume 30, Issue 5, Page(s) 2849–2859

Abstract: Point cloud video (PCV) offers watching experiences in photorealistic 3D scenes with six-degree-of-freedom (6-DoF), enabling a variety of VR and AR applications. The user's Field of View (FoV) is more fickle with 6-DoF movement than 3-DoF movement in 360- ...

Abstract	Point cloud video (PCV) offers watching experiences in photorealistic 3D scenes with six-degree-of-freedom (6-DoF), enabling a variety of VR and AR applications. The user's Field of View (FoV) is more fickle with 6-DoF movement than 3-DoF movement in 360-degree video. PCV streaming is extremely bandwidth-intensive. However, current streaming systems require hundreds of Mbps bandwidth, exceeding the bandwidth capabilities of commodity devices. To save bandwidth, FoV-adaptive streaming predicts a user's FoV and only downloads point cloud data falling in the predicted FoV. But it is difficult to accurately predict the user's FoV even 2-3 seconds before playback due to 6-DoF. Misprediction of FoV or network bandwidth dips results in frequent stalls. To avoid rebuffering, existing systems would cause incomplete FoV and degraded experience, deteriorating the user's quality of experience (QoE). In this paper, we describe Fumos, a novel system that preserves interactive experience by avoiding playback stalls while maintaining high perceptual quality and high compression rate. We find a research gap in inter-frame redundant utilization and progressive mechaism. Fumos has three crucial designs, including (1) Neural compression framework with inter-frame coding, namely N-PCC, which achieves both bandwidth efficiency and high fidelity. (2) Progressive refinement streaming framework that enables continuous playback by incrementally upgrading a fetched portion to a higher quality (3) System-level adaptation that employs Lyapunov optimization to jointly optimize the long-term user QoE. Experimental results demonstrate that Fumos significantly outperforms Draco, achieving an average decoding rate acceleration of over 260×. Moreover, the proposed compression framework N-PCC attains remarkable BD-Rate gains, averaging 91.7% and 51.7% against the state-of-the-art point cloud compression methods G-PCC and V-PCC, respectively.
Language	English
Publishing date	2024-04-19
Publishing country	United States
Document type	Journal Article
ISSN	1941-0506
ISSN (online)	1941-0506
DOI	10.1109/TVCG.2024.3372096
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: LMaaS

Wu, Panlong / Liu, Qi / Dong, Yanjie / Wang, Fangxin

Exploring Pricing Strategy of Large Model as a Service for Communication

2024

Abstract: The next generation of communication is envisioned to be intelligent communication, that can replace traditional symbolic communication, where highly condensed semantic information considering both source and channel will be extracted and transmitted ... ...

Abstract	The next generation of communication is envisioned to be intelligent communication, that can replace traditional symbolic communication, where highly condensed semantic information considering both source and channel will be extracted and transmitted with high efficiency. The recent popular large models such as GPT4 and the boosting learning techniques lay a solid foundation for the intelligent communication, and prompt the practical deployment of it in the near future. Given the characteristics of "training once and widely use" of those multimodal large language models, we argue that a pay-as-you-go service mode will be suitable in this context, referred to as Large Model as a Service (LMaaS). However, the trading and pricing problem is quite complex with heterogeneous and dynamic customer environments, making the pricing optimization problem challenging in seeking on-hand solutions. In this paper, we aim to fill this gap and formulate the LMaaS market trading as a Stackelberg game with two steps. In the first step, we optimize the seller's pricing decision and propose an Iterative Model Pricing (IMP) algorithm that optimizes the prices of large models iteratively by reasoning customers' future rental decisions, which is able to achieve a near-optimal pricing solution. In the second step, we optimize customers' selection decisions by designing a robust selecting and renting (RSR) algorithm, which is guaranteed to be optimal with rigorous theoretical proof. Extensive experiments confirm the effectiveness and robustness of our algorithms.
Keywords	Computer Science - Networking and Internet Architecture ; Computer Science - Computer Science and Game Theory ; Computer Science - Machine Learning
Subject code	303
Publishing date	2024-01-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Current Status of Antisense Gene Therapies for Bacteria-caused Diseases Challenges and Opportunities.

Li, Jiawei / Liang, Xuejun / Wang, Fangxin / Wang, Juping / Ding, Feng

Current pharmaceutical design

2023 Volume 29, Issue 4, Page(s) 272–282

Abstract: Bacteria-caused diseases continue to pose a serious threat to human health. The current situation of overused antibiotics against those diseases further spurs and exacerbates the ever-increasing drug resistance problems, which really leaves us very few ... ...

Abstract	Bacteria-caused diseases continue to pose a serious threat to human health. The current situation of overused antibiotics against those diseases further spurs and exacerbates the ever-increasing drug resistance problems, which really leaves us very few options to combat those nasty bugs. Gene therapies based on the antisense oligonucleotide, though developed more than 40 years ago, did not reform the current treatments as originally expected. Along with the advances of new delivery technologies, this old field thrives again. In addition, newly evolving gene-editing tools based on the CRISPR-Cas system shed new light on this old field, bringing a breeze of hope to gene therapies for bacteria-caused diseases. As a fast-growing field, we strive to summarize in this review the recent progress in using gene therapies in those areas, analyze the potential challenges or problems from using antisense or gene-editing tools for targeting bacterial diseases and seek to explore any potential solutions to the current dilemmas. As a short review, we will focus our discussion mainly on antisense oligonucleotide-based gene therapies while briefly touching on the CRISPR-Cas based ones as the latter is just beginning to get more attention for application in the prokaryotic kingdom.
MeSH term(s)	Humans ; Gene Editing ; CRISPR-Cas Systems/genetics ; Genetic Therapy ; Bacteria ; Bacterial Infections/genetics
Language	English
Publishing date	2023-01-19
Publishing country	United Arab Emirates
Document type	Review ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1304236-1
ISSN	1873-4286 ; 1381-6128
ISSN (online)	1873-4286
ISSN	1381-6128
DOI	10.2174/1381612829666230118152428
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Book ; Online: MANSY

Wu, Duo / Wu, Panlong / Zhang, Miao / Wang, Fangxin

Generalizing Neural Adaptive Immersive Video Streaming With Ensemble and Representation Learning

2023

Abstract: The popularity of immersive videos has prompted extensive research into neural adaptive tile-based streaming to optimize video transmission over networks with limited bandwidth. However, the diversity of users' viewing patterns and Quality of Experience ( ...

Abstract	The popularity of immersive videos has prompted extensive research into neural adaptive tile-based streaming to optimize video transmission over networks with limited bandwidth. However, the diversity of users' viewing patterns and Quality of Experience (QoE) preferences has not been fully addressed yet by existing neural adaptive approaches for viewport prediction and bitrate selection. Their performance can significantly deteriorate when users' actual viewing patterns and QoE preferences differ considerably from those observed during the training phase, resulting in poor generalization. In this paper, we propose MANSY, a novel streaming system that embraces user diversity to improve generalization. Specifically, to accommodate users' diverse viewing patterns, we design a Transformer-based viewport prediction model with an efficient multi-viewport trajectory input output architecture based on implicit ensemble learning. Besides, we for the first time combine the advanced representation learning and deep reinforcement learning to train the bitrate selection model to maximize diverse QoE objectives, enabling the model to generalize across users with diverse preferences. Extensive experiments demonstrate that MANSY outperforms state-of-the-art approaches in viewport prediction accuracy and QoE improvement on both trained and unseen viewing patterns and QoE preferences, achieving better generalization. Comment: This work has been submitted to the IEEE Transactions on Mobile Computing for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Keywords	Computer Science - Networking and Internet Architecture
Subject code	006
Publishing date	2023-11-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients

Wu, Chenrui / Li, Zexi / Wang, Fangxin / Wu, Chao

2023

Abstract: Federated learning (FL) is a distributed framework for collaboratively training with privacy guarantees. In real-world scenarios, clients may have Non-IID data (local class imbalance) with poor annotation quality (label noise). The co-existence of label ... ...

Abstract	Federated learning (FL) is a distributed framework for collaboratively training with privacy guarantees. In real-world scenarios, clients may have Non-IID data (local class imbalance) with poor annotation quality (label noise). The co-existence of label noise and class imbalance in FL's small local datasets renders conventional FL methods and noisy-label learning methods both ineffective. To address the challenges, we propose FedCNI without using an additional clean proxy dataset. It includes a noise-resilient local solver and a robust global aggregator. For the local solver, we design a more robust prototypical noise detector to distinguish noisy samples. Further to reduce the negative impact brought by the noisy samples, we devise a curriculum pseudo labeling method and a denoise Mixup training strategy. For the global aggregator, we propose a switching re-weighted aggregation method tailored to different learning periods. Extensive experiments demonstrate our method can substantially outperform state-of-the-art solutions in mix-heterogeneous FL environments. Comment: Accepted by IEEE ICME 2023
Keywords	Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2023-04-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Neodontobutis lani, a new sleeper fish of the family Odontobutidae (Teleostei: Gobiiformes) from Guangxi, southern China.

Zhou, Mingwei / He, Anyou / Wang, Fangxin / Li, Yusen / Li, Chenhong

Zootaxa

2022 Volume 5134, Issue 1, Page(s) 113–124

Abstract: A new species, Neodontobutis lani (Odontobutidae) is described from the Zuojiang River, a tributary of the Xijiang River of the Pearl River basin, at Longzhou Town, Guangxi Zhuang Autonomous Region, Southern China. This species can be distinguished from ... ...

Abstract	A new species, Neodontobutis lani (Odontobutidae) is described from the Zuojiang River, a tributary of the Xijiang River of the Pearl River basin, at Longzhou Town, Guangxi Zhuang Autonomous Region, Southern China. This species can be distinguished from other Neodontobutis species by following characters: anterior head flat, with interorbital width / eye diameter = 1.41.9 (vs. less than 1.4); several rows (vs. single row) of transforming ctenii on posterior edges of body scales; sensory papilla on lower jaw arranged in two oblong clusters (vs. two single lines). It can be distinguished from Odontobutis species by: separated right and left gill membrane (vs. joined); barbel-like projection present on sensory papillae. Molecular phylogenetic analysis of 2,076 nuclear coding loci indicates that N. lani is a sister species of N. hainanensis, the only Neodontobutis species that has been described from China.
MeSH term(s)	Animals ; Cell Nucleus ; China ; Perciformes ; Phylogeny ; Rivers
Language	English
Publishing date	2022-05-09
Publishing country	New Zealand
Document type	Journal Article
ISSN	1175-5334
ISSN (online)	1175-5334
DOI	10.11646/zootaxa.5134.1.5
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Article ; Online: Total Synthesis of Quebrachamine and Kopsiyunnanine D.

Liu, Hui / Yuan, Wei / Ran, Meng-Yan / Wei, Gang / Zhao, Yi / Liao, Zhi-Qiang / Liang, Hong / Chen, Zhen-Feng / Wang, Fang-Xin

The Journal of organic chemistry

2024 Volume 89, Issue 8, Page(s) 5905–5910

Abstract: The total syntheses of (±)-quebrachamine and (±)-kopsiyunnanine D are reported. Key transformations include an intermolecular Horner-Wadsworth-Emmons olefination to merge the two fragments convergently and an intramolecular Mitsunobu reaction to ... ...

Abstract	The total syntheses of (±)-quebrachamine and (±)-kopsiyunnanine D are reported. Key transformations include an intermolecular Horner-Wadsworth-Emmons olefination to merge the two fragments convergently and an intramolecular Mitsunobu reaction to introduce the synthetically challenging nine-membered azonane ring efficiently.
Language	English
Publishing date	2024-04-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	123490-0
ISSN	1520-6904 ; 0022-3263
ISSN (online)	1520-6904
ISSN	0022-3263
DOI	10.1021/acs.joc.4c00363
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Zs.A 4473: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

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Article ; Online: Triterpenoids from the Leaves of

Huang, Lan / Wang, Ziqi / Wang, Fangxin / Wang, Song / Wang, Dezhi / Gao, Meihua / Li, Hua / Song, Min / Zhang, Xiaoqi

Molecules (Basel, Switzerland)

2024 Volume 29, Issue 7

Abstract: ... Six new ... ...

Abstract	Six new 2
MeSH term(s)	Diospyros ; Molecular Docking Simulation ; Plant Leaves ; Hydroxy Acids ; Triterpenes/pharmacology
Chemical Substances	Hydroxy Acids ; Triterpenes
Language	English
Publishing date	2024-04-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules29071640
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.MO 81: Show issues

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Book ; Online: FSVVD

Hu, Kaiyuan / Jin, Yili / Yang, Haowen / Liu, Junhua / Wang, Fangxin

A Dataset of Full Scene Volumetric Video

2023

Abstract: Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space. Volumetric videos, as an emerging representative 3D video paradigm that empowers extended reality, stand out to ... ...

Abstract	Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space. Volumetric videos, as an emerging representative 3D video paradigm that empowers extended reality, stand out to provide unprecedented immersive and interactive video watching experience. Despite the tremendous potential, the research towards 3D volumetric video is still in its infancy, relying on sufficient and complete datasets for further exploration. However, existing related volumetric video datasets mostly only include a single object, lacking details about the scene and the interaction between them. In this paper, we focus on the current most widely used data format, point cloud, and for the first time release a full-scene volumetric video dataset that includes multiple people and their daily activities interacting with the external environments. Comprehensive dataset description and analysis are conducted, with potential usage of this dataset. The dataset and additional tools can be accessed via the following website: https://cuhksz-inml.github.io/full_scene_volumetric_video_dataset/. Comment: Accepted by MMSys'23 Open Dataset and Software Track. The dataset and additional tools can be accessed via https://cuhksz-inml.github.io/full_scene_volumetric_video_dataset/
Keywords	Computer Science - Multimedia ; Computer Science - Computer Vision and Pattern Recognition ; Electrical Engineering and Systems Science - Image and Video Processing
Subject code	004
Publishing date	2023-03-06
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Where Are You Looking?

Jin, Yili / Liu, Junhua / Wang, Fangxin / Cui, Shuguang

A Large-Scale Dataset of Head and Gaze Behavior for 360-Degree Videos and a Pilot Study

2022

Abstract: 360{\deg} videos in recent years have experienced booming development. Compared to traditional videos, 360{\deg} videos are featured with uncertain user behaviors, bringing opportunities as well as challenges. Datasets are necessary for researchers and ... ...

Abstract	360{\deg} videos in recent years have experienced booming development. Compared to traditional videos, 360{\deg} videos are featured with uncertain user behaviors, bringing opportunities as well as challenges. Datasets are necessary for researchers and developers to explore new ideas and conduct reproducible analyses for fair comparisons among different solutions. However, existing related datasets mostly focused on users' field of view (FoV), ignoring the more important eye gaze information, not to mention the integrated extraction and analysis of both FoV and eye gaze. Besides, users' behavior patterns are highly related to videos, yet most existing datasets only contained videos with subjective and qualitative classification from video genres, which lack quantitative analysis and fail to characterize the intrinsic properties of a video scene. To this end, we first propose a quantitative taxonomy for 360{\deg} videos that contains three objective technical metrics. Based on this taxonomy, we collect a dataset containing users' head and gaze behaviors simultaneously, which outperforms existing datasets with rich dimensions, large scale, strong diversity, and high frequency. Then we conduct a pilot study on user's behaviors and get some interesting findings such as user's head direction will follow his/her gaze direction with the most possible time interval. A case of application in tile-based 360{\deg} video streaming based on our dataset is later conducted, demonstrating a great performance improvement of existing works by leveraging our provided gaze information. Our dataset is available at https://cuhksz-inml.github.io/head_gaze_dataset/ Comment: Accepted by ACM MM 2022. Dataset is available at https://cuhksz-inml.github.io/head_gaze_dataset
Keywords	Computer Science - Multimedia
Subject code	004
Publishing date	2022-08-08
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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