Bone loss recovery in mice following microgravity with concurrent bone-compartment-specific osteocyte characteristics

Space missions provide the opportunity to investigate the influence of gravity on the dynamic remodelling processes in bone. Mice were examined following space flight and subsequent recovery to determine the effects on bone compartment-specific microstructure and composition. The resulting bone loss following microgravity recovered only in trabecular bone, while in cortical bone the tissue mineral density was restored after only one week on Earth. Detection of TRAP-positive bone surface cells in the trabecular compartment indicated increased resorption following space flight. In cortical bone, a persistent reduced viability of osteocytes suggested an impaired sensitivity to mechanical stresses. A compartment-dependent structural recovery from microgravity-induced bone loss was shown, with a direct osteocytic contribution to persistent low bone volume in the cortical region even after a recovery period. Trabecular recovery was not accompanied by changes in osteocyte characteristics. These post-space-flight findings will contribute to the understanding of compositional changes that compromise bone quality caused by unloading, immobilisation, or disuse.

IRTS: An Intelligent and Reliable Transmission Scheme for Screen Updates Delivery in DaaS

Desktop-as-a-service (DaaS) has been recognized as an elastic and economical solution that enables users to access personal desktops from anywhere at any time. During the interaction process of DaaS, users rely on screen updates to perceive execution results remotely, and thus the reliability and timeliness of screen updates transmission have a great influence on users’ quality of experience (QoE). However, the efficient transmission of screen updates in DaaS is facing severe challenges: most transmission schemes applied in DaaS determine sending strategies in terms of pre-set rules, lacking the intelligence to utilize bandwidth rationally and fit new network scenarios. Meanwhile, they tend to focus on reliability or timeliness and perform unsatisfactorily in ensuring reliability and timeliness simultaneously, leading to lower transmission efficiency of screen updates and users’ QoE when network conditions turn unfavorable. In this article, an intelligent and reliable end-to-end transmission scheme (IRTS) is proposed to cope with the preceding issues. IRTS draws support from reinforcement learning by adopting SARSA, an online learning method based on the temporal difference update rule, to grasp the optimal mapping between network states and sending actions, which extricates IRTS from the reliance on pre-set rules and augments its adaptability to different network conditions. Moreover, IRTS guarantees reliability and timeliness via an adaptive loss recovery method, which intends to recover lost screen updates data automatically with fountain code while controlling the number of redundant packets generated. Extensive performance evaluations are conducted, and numerical results show that IRTS outperforms the reference schemes in display quality, end-to-end delay/delay jitter, and fairness when transferring screen updates under various network conditions, proving that IRTS can enhance the transmission efficiency of screen updates and users’ QoE in DaaS.

The Performance and Future of QUIC Protocol in the Modern Internet

Quick UDP Internet Connections (QUIC) protocol is a potential replacement for the TCP protocol to transport HTTP encrypted traffic. It is based on UDP and offers flexibility, speed, and low latency. The performance of QUIC is related to the everyday web browsing experience. QUIC is famous for its Forward Error Correction (Luyi, Jinyi, & Xiaohua, 2012) and congestion control (Hari, Hariharan, & Srinivasan, 1999) algorithm that improves user browsing delay by reducing the time spent on loss recovery (Jörg, Ernst, & Don, 1998). This paper will compare QUIC with other protocols such as HTTP/2 over TCP, WebSocket, and TCP fast open in terms of latency reduction and loss recovery to determine the role of each protocol in the modern internet. Furthermore, this paper will propose potential further improvements to the QUIC protocol by studying other protocols.

Reliable Multicast Based on Congestion-Aware Cache in ICN

Reliable multicast distribution is essential for some applications such as Internet of Things (IoT) alarm information and important file distribution. Traditional IP reliable multicast usually relies on multicast source retransmission for recovery losses, causing huge recovery delay and redundancy. Moreover, feedback implosion tends to occur towards multicast source as the number of receivers grows. Information-Centric Networking (ICN) is an emerging network architecture that is efficient in content distribution by supporting multicast and in-network caching. Although ubiquitous in-network caching provides nearby retransmission, the design of cache strategy greatly affects the performance of loss recovery. Therefore, how to recover losses efficiently and quickly is an urgent problem to be solved in ICN reliable multicast. In this paper, we first propose an overview architecture of ICN-based reliable multicast and formulate a problem using recovery delay as the optimization target. Based on the architecture, we present a Congestion-Aware Probabilistic Cache (CAPC) strategy to reduce recovery delay by caching recently transmitted chunks during multicast transmission. Then, we propose NACK feedback aggregation and recovery isolation scheme to decrease recovery overhead. Finally, experimental results show that our proposal can achieve fully reliable multicast and outperforms other approaches in recovery delay, cache hit ratio, transmission completion time, and overhead.