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- Pierantozzi, E., et al.
(författare)
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Impaired Intracellular Ca2+ Dynamics, M-Band and Sarcomere Fragility in Skeletal Muscles of Obscurin KO Mice
- 2022
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Ingår i: International Journal of Molecular Sciences. - : MDPI AG. - 1661-6596 .- 1422-0067. ; 23:3
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Tidskriftsartikel (refereegranskat)abstract
- Obscurin is a giant sarcomeric protein expressed in striated muscles known to establish several interactions with other proteins of the sarcomere, but also with proteins of the sarcoplasmic reticulum and costameres. Here, we report experiments aiming to better understand the contribution of obscurin to skeletal muscle fibers, starting with a detailed characterization of the diaphragm muscle function, which we previously reported to be the most affected muscle in obscurin (Obscn) KO mice. Twitch and tetanus tension were not significantly different in the diaphragm of WT and Obscn KO mice, while the time to peak (TTP) and half relaxation time (HRT) were prolonged. Differences in force-frequency and force-velocity relationships and an enhanced fatigability are observed in an Obscn KO diaphragm with respect to WT controls. Voltage clamp experiments show that a sarcoplasmic reticulum’s Ca2+ release and SERCA reuptake rates were decreased in muscle fibers from Obscn KO mice, suggesting that an impairment in intracellular Ca2+ dynamics could explain the observed differences in the TTP and HRT in the diaphragm. In partial contrast with previous observations, Obscn KO mice show a normal exercise tolerance, but fiber damage, the altered sarcomere ultrastructure and M-band disarray are still observed after intense exercise. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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- Braga Jr, Iran Mesquita, et al.
(författare)
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Joint Resource Allocation and Transceiver Design for Sum-Rate Maximization Under Latency Constraints in Multicell MU-MIMO Systems
- 2021
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Ingår i: IEEE Transactions on Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0090-6778 .- 1558-0857. ; 69:7, s. 1-1
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Tidskriftsartikel (refereegranskat)abstract
- Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model. Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the widespread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model.
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- Braga Jr, Iran M., et al.
(författare)
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User Scheduling Based on Multi-Agent Deep Q-Learning for Robust Beamforming in Multicell MISO Systems
- 2020
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Ingår i: IEEE Communications Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1089-7798 .- 1558-2558. ; 24:12, s. 2809-2813
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Tidskriftsartikel (refereegranskat)abstract
- Maximizing the rate in multiple input single output (MISO) systems using distributed algorithms is an important task that typically incurs high computational cost. In this work, we propose two deep Q-learning-based user scheduling schemes to solve the beamforming problem of sum-rate maximization with per base station power constraints in multicell MISO scenarios. The two key features of the proposed algorithms are that they are executed in a distributed fashion and are robust with respect to channel state information (CSI) errors. Simulation results show that in the presence of CSI errors the proposed schemes outperform state-of-the-art algorithms both in terms of average spectral efficiency and execution time.
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- Saraiva, J. V., et al.
(författare)
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Energy Efficiency Maximization Under Minimum Rate Constraints in Multi-Cell MIMO Systems with Finite Buffers
- 2021
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 5:1, s. 174-189
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Tidskriftsartikel (refereegranskat)abstract
- Having recognized the dramatic increase in the number of mobile devices and infrastructure nodes, standards organizations and regulatory bodies have adopted energy efficiency (EE) as a key performance metric for fifth-generation networks. Recent works on multiple input multiple output (MIMO) systems have suggested that it is important to use finite-buffer models, because they may lead to better transceiver designs and more accurate performance analyses than full-buffer traffic models. Therefore, this paper addresses the MIMO transceiver design problem for EE maximization in the downlink of finite-buffer multicell systems. Unlike previous works, our problem formulation takes into account per-user minimum rate requirements. We arrive at a nonconvex fractional optimization problem, which is hard to tackle. By exploiting the properties of fractional programming, and using Dinkelbach’s method, the resulting fractional form optimization problem is transformed to an equivalent optimization problem in subtractive form. Next, the nonconvexity of this problem is handled using successive convex approximation, leading to iterative centralized and decentralized resource allocation solutions. Finally, considering a realistic channel model with space, frequency and time correlations, numerical results confirm the effectiveness of the proposed algorithms and indicate significant performance gains in terms of achieved EE over existing solutions for full and finite-buffer models. IEEE
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