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Carma3 is an intracellular scaffolding protein that can form complex with Bcl10 and Malt1 to mediate G protein–coupled receptor– or growth factor receptor–induced NF-κB activation. However, the in vivo function of Carma3 has remained elusive. Here, by establishing a Con A–induced autoimmune hepatitis model, we show that liver injury is exacerbated in Carma3−/− mice. Surprisingly, we find that the Carma3 expression level is higher in liver sinusoidal endothelial cells (LSECs) than in hepatocytes in the liver. In Carma3−/− mice, Con A treatment induces more LSEC damage, accompanied by severer coagulation. In vitro we find that Carma3 localizes at mitochondria and Con A treatment can trigger more mitochondrial damage and cell death in Carma3-deficient LSECs. Taken together, our data uncover an unrecognized role of Carma3 in maintaining LSEC integrity, and these results may extend novel strategies to prevent liver injury from toxic insults.

The spectrum efficiency is a greatly important issue when we establish connection requests in elastic optical data center networks (EODCNs). In this paper, we address the spectrum efficiency problems of the shared-path protection with spectrum-sharing-maximized approaches for the optical network survivability. Two integer linear program (ILP) models, i.e., flow-based and path-based ILP models, named FB-ILP and PB-ILP, are developed to minimize the frequency slots occupied with the spectrum-sharing-maximized protection, and two heuristic approaches with the spectrum-sharing-maximized protection (HA-SSMP) and with the general spectrum-sharing protection (HA-GSSP) are also proposed to improve spectrum efficiency in EODCNs. For comparison, we introduce a heuristic approach with the existing shared-path protection (HA-ESPP) in EODCNs. On one hand, simulation results show that FB-ILP can minimize the number of frequency slots occupied, but leads to higher average number of hops and longer running time compared to PB-ILP, HA-SSMP, HA-GSSP, and HA-ESPP in static traffic scenario in EODCNs. On the other hand, the simulation results of our proposed HA-SSMP are very close to the solutions of FB-ILP. In dynamical traffic scenario, simulation results show that HA-SSMP significantly improves the spectrum efficiency and effectively suppresses the blocking probability, but leads to higher average number of hops compared to HA-GSSP and HA-ESPP in EODCNs.

Filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) is a promising candidate for 5G mobile fronthaul system. Due to the inherent imaginary interference of FBMC/OQAM signals, an accurate channel estimation is particularly indispensable. In this paper, an efficient method is proposed based on complex-valued neural networks (CVNN) for an accurate channel estimation of FBMC/OQAM signals with low computational complexity and pilot overhead. Here, the channel frequency response (CFR) is first calculated for training the CVNN. Next, the CFR estimated from the extracted pilots is exploited as the input of the trained CVNN to yield the CFR of data symbols. We experimentally demonstrate a 12.5-GBd intensity modulation direct detection (IM/DD) FBMC/OQAM transmission system over 30-km and 50-km standard single mode fibers (SSMF). The experimental results show that the proposed method achieves 3-dB and 1-dB receiver sensitivity improvement at the bit error ratio (BER) of 3.810-3 with only 5% pilot overhead respectively, compared to the conventional least square (LS) and linear minimum mean error (LMMSE) methods. When the pilot overhead decreases from 10% to 1%, its BER performance is always better than LS and LMMSE. For the computational complexity, its complexity is the same order of magnitude as LS and lower than LMMSE. On the other hand, the CVNN requires less hidden neurons to keep the similar BER performance as real-valued neural networks (RVNN). Meanwhile, it has excellent resilience to fiber chromatic dispersion over 30-km and 50-km SSMF.

Multi-carrier optical communication schemes are attractive for high-speed mobile fronthaul networks, edge cloud computing and passive optical networks. Compared with conventional orthogonal frequency-division multiplexing (OFDM), universal filter multi-carrier (UFMC) can shape the spectrum of the transmitted signal by introducing universal filter banks. Meanwhile, probabilistic shaping (PS) can make full use of achieved signal-to-noise ratio (SNR) to adaptively adjust the entropy loading according to the measured SNR of each subchannel. However, the significant amount of required distribution matcher (DM) is challenging in the practical implementation. In this work, we experimentally demonstrated 12.5-GBd and 25-GBd PS-UFMC transmissions with approximate 10-GHz bandwidth-limited system over 30-km standard single mode fiber. Due to the sharp cutoff frequency-response of filters, the effect of the frequency decaying in the 25-GBd OFDM system has been eliminated in the UFMC system. Consequently, each subband has similar SNR and therefore the number of required DMs is reduced. Moreover, considering the receiver complexity constraints, the improved bit error ratio performance was achieved by optimizing the allocation of data subbands to mitigate inter symbol interference caused by the dispersion of transmitted fiber.

Optical signal-to-noise ratio (OSNR) is an important parameter in coherent optical communication systems to monitor the quality of the received signal and the transmission-link fault. The OSNR monitoring technique based on the moments of the received signals is simply and blind, where no extra training sequence is required. The moments-based method works well with QPSK signals with constant modulus constellations but has degraded performance for 16-QAM and 64-QAM signals with multilevel constellations. Instead of calculating higher-order moments, we proposed an accurate second- and fourth-order moments-based OSNR monitoring scheme, where the clock recovery of the M-QAM signal is first implemented and then the inner amplitude level is extracted to estimate the OSNR values. The proposed method has been verified and evaluated in QPSK, 16-QAM and 64-QAM simulations and experiments.

Adaptive orthogonal frequency division multiplexing (OFDM) systems are promising for high-bit-rate short-reach communication by optimizing the allocation of modulation format and power to each subcarrier. Because adaptive OFDM systems involve multiple modulation formats, automatic modulation format identification (AMFI) is significant for subsequent signal processing and symbol decision of OFDM receivers. In this work, we proposed and experimentally demonstrated a blind modulation format identification technique based on constellation diagrams achieved from channel estimation of OFDM system. In the proposed AMFI scheme, the identification feature is the number of signals’ constellation clusters. First, we use the peak-density clustering algorithm to track the centers of signals’ constellation clusters by plotting the density–distance graph, where the clusters’ centers have much larger density and distance values than that of the other clusters’ points. Then, we use the K nearest neighbor regression algorithm to automatically calculate the number of signals’ constellation clusters. Finally, we evaluated and measured the identification accuracies of QPSK, 8-QAM, 8-PSK, 16-QAM, 64-QAM and 128 QAM signals in simulation and experiment.

The effects of hydraulic fractures with complex boundaries on the well performance of a shale gas well, considering a more realistic corner point geological model, have rarely been studied previously. In this study, the nonintrusive embedded discrete fracture model (EDFM) method was employed to investigate the effects of different boundary shapes of hydraulic fracture, coupling a network of sophisticated natural fractures discrete fracture network (DFN) on well performance. First, by implementing the powerful EDFM technology, concepts of two categories (rectangle and diamond) of hydraulic fracture with different boundaries were designed. Next, the geometric equations defining vertices of multiple rectangular- or diamond-shaped hydraulic fractures in arbitrary coordinate systems were derived. Subsequently, the horizontal well with multistaged hydraulic fractures and sophistically oriented 3D natural fractures was inputted into the reservoir model to perform history matching. After history matching, the results were further analyzed to compare the production forecast from the two categories. The results show that 20-year cumulative gas productions for rectangle- and diamond-shaped fractures are approximately 1.237×108 m3 and 1.486×108 m3, respectively. In other words, the diamond category can produce 20.1% more gas than the rectangle category. For cumulative water production, the diamond category produces 3.8×104 m3, as against the 3.0×104 m3 produced by the rectangle category (or 26.7% more). This implies that the diamond-shaped fractures have the potential to reach the far field region of the reservoir away from the wellbore. This means that more intersections with natural fractures DFN can be achieved, and more drainage area is unlocked. The visualization of pressure distributions and drainage volume was easily shown, and these results further confirm that the extent of fluid drainage by the diamond fracture is larger compared to that by the rectangular fracture given the same total surface area.

In order to realize the green computing of the edge-cloud fiber-wireless networks, the cooperation between the edge servers and the cloud servers is particularly important to reduce the network energy consumption. Therefore, this paper proposes an energy-efficient workload allocation (EEWA) scheme to improve the energy efficiency by using the architecture of edge-cloud fiber-wireless networks. The feasibility of the proposed EEWA scheme was verified on our SDN testbed. We also do the simulation to obtain the optimal results for a given set of task requests. Simulation results show that our proposed EEWA scheme greatly reduces the blocking probability and the average energy consumption of task requests in edge-cloud fiber-wireless networks.

In this Letter, we propose a flexible bandwidth compression scheme for visible light communication (VLC) systems employing multi-band carrierless amplitude and phase (CAP) modulation. The scheme combines a narrow filtering for every subband at the transmitter and an N-symbol look-up-table (LUT) based maximum likelihood sequence estimation (MLSE) at the receiver. The N-symbol LUT is generated by recording pattern-dependent distortions induced by inter-symbol-interference (ISI), inter-band-interference (IBI), and the other channel effects upon the transmitted signal. The idea is experimentally demonstrated on a 1 m free space optical transmission platform. The results show that the proposed scheme can improve the subband overlap tolerance up to 42% in subband overlapping scenarios, that is, 3 bit/s/Hz, which is the highest spectral efficiency (SE) among the experimented schemes.

Pro-angiogenic factors are key regulators of angiogenesis. Here we report that highly migratory cells patrol the area of capillary formation in chick embryo chorioallantoic membrane. These cells deposit migrasomes on their migration tracks, creating migrasome-enriched areas. Single-cell sequencing identified these cells as monocytes. Depletion of monocytes impairs capillary formation. Quantitative mass spectrometry analysis reveals that monocyte migrasomes are enriched with pro-angiogenic factors. Purified migrasomes promote capillary formation and monocyte recruitment in vivo, and endothelial cell tube formation and monocyte chemotaxis in vitro. Knockdown or knockout of TSPAN4 reduces migrasome formation and impairs capillary formation and monocyte recruitment. Mechanistically, monocytes promote angiogenesis via VEGFA and CXCL12 in migrasomes. In summary, monocytes deposit migrasomes enriched in pro-angiogenic factors to promote angiogenesis.

IM/DD probabilistically-shaped multicarrier communication is attractive for optical interconnects due to low cost and power consumption, enhanced resilience to noise and flexibility of entropy allocation. In this work, we present its principles and key features.

With the rapid development of Internet of Things (IoT), 5G, and cloud computing, a large number of emerging applications has emerged, such as mobile payment and self-driving cars. Collaborative cloud-edge computing networks (CCECNs) is an effective way to alleviate the limitation of computing capacity by offloading complex tasks from IoT. Thus, this paper mainly proposes selective offloading network resource optimization approaches to address the offloading network resource problems for user requests in CCECNs. Simulation results show that proposed approaches can optimize network resource allocation and can reduce end-to-end (E2E) latency and blocking probability.

With the rapid development of cloud computing, video, smart home, and Internet of things (IoT), the bandwidth requirements for communications networks are also greatly increasing. The internet is facing new demands and challenges. Space Division Multiplexing (SDM) is an approach to increase the channel bandwidth capacity to explore potential spectrum resources in the spatial dimension with a multi-core fiber (MCF). Thus, this paper mainly proposes a spectrum-efficiency VON mapping approach with the inter-core crosstalk to reduce the spectrum occupancy and the inter-core crosstalk values in Space Division Multiplexing Elastic Optical Data Center Networks (SDM-EODCNs). Simulation results show that the proposed VON approach can efficiently reduce the spectrum occupancy rate and average inter-core crosstalk.

We propose a new method to discriminate and identify the modulation format of signals based on an unsupervised neural network named convolutional Gaussian-Bernoulli restricted Boltzmann machine (CGBRBM). Tests are performed to demonstrate how the proposed method works and to evaluate the discrimination/identification accuracy for different input combinations. Signals of five modulation formats are used to test the CGBRBM-based algorithm including QPSK, 8QAM, 16QAM, 32QAM, and 64QAM. The results indicate the performance of the proposed method when dealing with various application scenarios and reveal the relation between discrimination accuracy and identification accuracy.

We experimentally demonstrated a scheme to improve the security of one-dimensional chaotic encryption based on quantum noise stream cipher. The experimental results verified its feasibility in the OFDM-PON over 30-km single mode fiber transmission.

We proposed a novel rotation-decision blind phase search algorithm for carrier phase recovery of M-QAM signals. For the scenarios of severe phase noise, the proposed method can achieve 10% BER improvement with the fast convergence.