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Satellite communications plays an important role in future Internet of Things (IoT) networks, and mega satellite constellations can further provide global coverage and high-quality services for IoT communications. In the mega constellation, large-scale satellites are launched to enhance the capacity. However, the dense distribution of satellites brings intra-constellation interference, limiting the performance. In order to evaluate the restriction of interference caused by system parameters such as the scale of constellation or the frequency reuse factor, we investigate uplink intra-constellation interference and performance of the mega satellite constellation. First, a multi-beam polar constellation with uplink spatial frequency reuse is assumed. Then, the interference model is constructed considering the antenna gain of interfering user terminals and multi-beam satellites, where the details of satellite-fixed frequency reuse scheme and coordinates of co-frequency cells are provided. To evaluate the performance, expressions of outage probability, ergodic capacity and sum ergodic capacity are driven. The analytical results disclose the impact of system design on the performance, and the accuracy of analysis results is obtained through extensive simulation evaluation. Results show that sum ergodic capacity achieves highest in the case of full frequency reuse for frequency limited constellation system, and it gets a linear growth at first but then keeps flat with a trend of fluctuating downward as scale increases, therefore, the impact of the scale should be considered when constructing mega constellations.

A novel rapid code acquisition scheme is proposed for low spreading factor satellite communication systems relying on message passing algorithms (MPA), where the acquisition of pseudonoise (PN) codes is converted to a sequence estimation problem. Due to the presence of data transitions in low spreading factor systems, conventional acquisition methods based on correlation would show poor capture performance. To overcome the impact of data transitions, this letter proposes a joint data chip and PN sequence estimation technique with the aid of factor graph and belief propagation (BP) algorithm. Meanwhile, in view of the short-term invariance of data chips, this letter models data chips as Markov chains to improve prior knowledge. Simulation results demonstrate that the proposed algorithm can save the mean acquisition time (MAT) about three orders of magnitude and improve the acquisition performance by 2 dB at 99% detection probability compared with serial search.

A novel low-complexity multiuser detection scheme is proposed for the asynchronous non-orthogonal multiple access (NOMA). Directly applying the conventional symbol-synchronous detection techniques for the asynchronous NOMA would result in high complexity. For low-complexity, we divide one frame with a large number of symbols into several small blocks. Furthermore, for real-time and low-delay processing under the scenario with a large number of users, each block is independently processed in a parallel way by an approximate message passing-based algorithm. Furthermore, a jointly detection technique is proposed to address the large detection error in the boundary of the blocks, which is induced by the non-interaction between neighbor blocks. Simulation results demonstrate that the proposed detection scheme can achieve near optimal performance with a much lower complexity.

In helicopter satellite communication systems, the received signal is blocked by the helicopter rotor blades during propagation, incurring the unstableness of traditional methods of channel estimation due to unknown channel state. To this end, a joint occlusion detection and phase estimation algorithm is proposed by factor graph in this paper. For occlusion detection to acquire channel state, the occlusion channel model is established relying on a Markov chain with a priori blocking ratio, in which the probability distribution of the channel state is calculated by the proposed message-passing algorithm. To obtain the occlusion position and update the blocking ratio, a cross-correlation method is designed. Furthermore, a joint block detection and phase estimation algorithm is developed based on the proposed occlusion detection algorithm to realize phase estimation by iterative receiver, where occlusion detection, phase estimation, and decoding are performed in turn for one turbo iteration and the result of decoding is then sent back to the occlusion detection step for the next iteration. Simulation results show that the proposed algorithm is adaptive to the dynamical change in the blocking ratio and can achieve bit error rate performance that is close to the performance bounds based on perfect channel state.

Alternative polyadenylation (APA) enhances gene regulatory potential by increasing the diversity of mRNA transcripts. 3' UTR shortening through APA correlates with enhanced cellular proliferation and is a widespread phenomenon in tumor cells. Here, we show that the ubiquitously expressed transcription factor Sp1 binds RNA in vivo and is a common repressor of distal poly(A) site usage. RNA sequencing identified 2,344 genes (36% of the total mapped mRNA transcripts) with lengthened 3' UTRs upon Sp1 depletion. Sp1 preferentially binds the 3' UTRs of such lengthened transcripts and inhibits cleavage at distal sites by interacting with the subunits of the core cleavage and polyadenylation (CPA) machinery. The 3' UTR lengths of Sp1 target genes in breast cancer patient RNA-seq data correlate with Sp1 expression levels, implicating Sp1-mediated APA regulation in modulating tumorigenic properties. Taken together, our findings provide insights into the mechanism for dynamic APA regulation by unraveling a previously unknown function of the DNA-binding transcription factor Sp1.

This paper proposes a distributed power control scheme based on the constrained model predictive control (MPC) for the underlay cognitive satellite terrestrial networks (CSTNs), where the primary satellite communication network coexists with the secondary terrestrial mobile network. We model this power control problem as a closed-loop dynamic control system with the inner loop and outer loop. On the basis of combining target power control (TPC) algorithm in the inner loop and tracking of flexible target signal to interference plus noise ratio (SINR) in the outer loop, we develop a corresponding state space expression of the problem where the fluctuation of each channel power gain is formulated as the exogenous disturbance input so that we do not need the accurate instantaneous channel state information (CSI). Then we design a SINR regulator in the outer loop, which is a constrained model predicted controller with rolling optimal operation subject to the interference temperature constraint obtained by calculating a linear matrix inequality. Finally, we obtain our constrained model predictive power control algorithm. In contrast to the previous static power control schemes based on the optimization theory that highly depend on the known instantaneous CSI and large signalling exchanges, the proposed scheme only needs locally measured information and outdate feedbacks. The performance of the proposed algorithm is shown to be effective through computer simulations.

In the multi-antenna satellite communication system, beamforming and artificial noise are usually adopted to enhance physical layer security. However, due to the long distance between the satellite and the terrestrial terminal, the coverage of the main lobe in the satellite downlink is so large that the eavesdropper can get into the coverage easily despite of using spot beams. When the eavesdropper is close to the legitimate user, the difference between the main channel and the wiretap channel is small, which makes the secrecy capacity decrease rapidly. This paper proposes a novel scheme to solve this problem by using two different beams which work on different frequencies to transmit the same signal to the legitimate user. This dual-beam dual- frequency scheme can enlarge the difference between the desired channel and the wiretap channel. Then, if we add some artificial noise set the proper beamforming vectors, the secrecy capacity will remain high when the eavesdropper is in the small zone near the legitimate user. In order to derive the artificial noise and the beamforming vectors, we transform the problem into a semidefinite problem and use CVX tools to solve the problem. Simulation results prove that this scheme can achieve high secrecy capacity even when the eavesdropper is very close to the legitimate user.

Random access is a key technology in satellite communication, as a large number of machine- type communication (MTC) terminals accessing the satellite makes it difficult to guarantee the access quality. Irregular repetition slotted ALOHA (IRSA) is one random access protocol relying on transmitting irregular number of replicas in multiple time slots, achieving a peak throughput at 0.8 in practical implementations. However, the probability of sending a certain number of replicas stays the same when given degree distribution, without considering the effects of different loads, which means there are extra useless packets sent and brings power waste in IRSA. Therefore, enhanced irregular repetition slotted ALOHA (EIRSA) based on tracking degree distribution control (TDDC) algorithm is proposed in this paper with adaptive degree distribution adjustment scheme to reduce the number of replicas while maintaining the same access performance with adaptation. Simulation results show that proposed protocol can achieve higher performance at the same power level and it is adaptive to load change.

Due to limited volume, weight and power consumption, micro-satellite has to reduce data transmission and storage capacity by image compression when performs earth observation missions. However, the quality of images may be unsatisfied. This paper considers the problem of recovering sparse signals by exploiting their unknown sparsity pattern. To model structured sparsity, the prior correlation of the support is encoded by imposing a transformed Gaussian process on the spike and slab probabilities. Then, an efficient approximate message-passing algorithm with structured spike and slab prior is derived for posterior inference, which, combined with a fast direct method, reduces the computational complexity significantly. Further, a unified scheme is developed to learn the hyperparameters using expectation maximization (EM) and Bethe free energy optimization. Simulation results on both synthetic and real data demonstrate the superiority of the proposed algorithm.

Long-term exposure to high levels of arsenic (As) will result in damage to organs. Compared with free arsenic, protein-bound arsenic are more difficult to be excreted from the bodies due to their complexation with biological macromolecules. We developed a method of size exclusion chromatography (SEC) and ion exchange chromatography (IEC) combined with inductively coupled plasma-mass spectrometry (ICP-MS) and multiple reaction monitoring (MRM) mode, which was used to determine bound-arsenic species. DMAV was identified as bound arsenic species in rat livers after As4S4 overexposure. Subsequent proteomics analysis showed the potential binding partners included hemoglobin, glutathione S-transferases, superoxide dismutase [Cu-Zn] & [Mn], thiosulfate sulfurtransferase, and metallothionein-2. The method developed here was sensitive, repeatable, and conducive to arsenic analysis, especially for toxicity evaluation of arsenic-containing substances in vivo.

The P-element-induced wimpy testis (PIWI)-interacting RNA (piRNA) pathway plays a central role in transposon silencing and genome protection in the animal germline. A family of Tudor domain proteins regulates the piRNA pathway through direct Tudor domain-PIWI interactions. Tudor domains are known to fulfill this function by binding to methylated PIWI proteins in an arginine methylation-dependent manner. Here, we report a mechanism of methylation-independent Tudor domain-PIWI interaction. Unlike most other Tudor domains, the extended Tudor domain of mammalian Tudor domain-containing protein 2 (TDRD2) preferentially recognizes an unmethylated arginine-rich sequence from PIWI-like protein 1 (PIWIL1). Structural studies reveal an unexpected Tudor domain-binding mode for the PIWIL1 sequence in which the interface of Tudor and staphylococcal nuclease domains is primarily responsible for PIWIL1 peptide recognition. Mutations disrupting the TDRD2-PIWIL1 interaction compromise piRNA maturation via 3'-end trimming in vitro. Our work presented here reveals the molecular divergence of the interactions between different Tudor domain proteins and PIWI proteins.

In this paper, we address the design of message-passing receiver for massive multiple-input multiple-output orthogonal frequency division multiplex (MIMO-OFDM) systems. With the aid of the central limit argument and Taylor-series approximation, a computationally efficient receiver that performs joint channel estimation and decoding is devised by the framework of expectation propagation. In particular, the local belief defined at the channel transition function is expanded up to the second order with Wirtinger calculus, to transform the messages sent by the channel transition function to a tractable form. As a result, the channel impulse response between each pair of antennas is estimated by Gaussian message passing. In addition, a variational expectation-maximization-based method is derived to learn the channel power-delay profiles. The proposed scheme is assessed in 3D massive MIMO-OFDM systems with spatially correlated channels, and the empirical results corroborate its superiority in terms of performance and complexity.

The carboxy-terminal domain (CTD) of the RNA polymerase II (RNAPII) subunit POLR2A is a platform for modifications specifying the recruitment of factors that regulate transcription, mRNA processing, and chromatin remodelling. We previously found that symmetrical dimethylation (me2s) of a CTD Arginine residue (R1810 in human) causes recruitment of the Tudor domain of SMN, which interacts with Senataxin. SMN is mutated in spinal muscular atrophy (SMA), and Senataxin is sometimes mutated in Amyotrophic Lateral Sclerosis (ALS). R1810me2s and SMN, like Senataxin, are important for resolving R-loops (DNA:RNA hybrids) at transcription terminators. FUS and TDP-43 (TARDBP) are DNA/RNA binding proteins that are sometimes mutated in ALS and FTD (Frontotemporal dementia). Here we show that TDP-43 and, to some extent, FUS are recruited by the R1810me2s-SMN pathway. Defects in FUS and TDP-43 recruitment influence RNAPII termination and R-loop accumulation, leading to elevated DNA damage at terminators that may contribute to neurodegenerative disorders like ALS and FTD.

Recently, the random access (RA) protocols are widely used in modern wireless communication systems. However, message collisions in RA usually cause low channel efficiency and high time delay. In this paper, a novel RA scheme named multi-power contention resolution diversity slotted aloha (MP-CRDSA) is proposed. In MP-CRDSA, the RA packets are transmitted in random power levels and multiple slots. In the receiver, the collisions are solved by iterative successive interference cancellation (SIC). Theoretical analysis and numerical results show that the proposed RA scheme performs high throughput, low packet loss ratio and low time delay, outperforming the ordinary RA scheme.

Grant-free non-orthogonal multiple access (NOMA) is highly expected to support massive connectivity and reduce the transmission latency for future wireless communications. In this paper, we present a joint active user and data detection with no priori knowledge of the active users relying on expectation propagation (EP) and Gaussian approximation (GA) algorithm. To detect the user activity, a structured spike and slab prior is introduced to present the sparsity of transmission signal. Further, the parameters unknown are learned via expectation maximization (EM), which improves the performance of active user detection. Specifically, the active user detection problem in NOMA is firstly formulated under EM framework by parameter learning, and then the transmission data can be detected accurately by message-passing algorithms (MPA). Simulation experiments demonstrate the superiority of our proposed EP-GA-EM algorithm both in the performance of reconstruction and the bit error rate (BER).

To address the challenging problem of downlink channel estimation with low pilot overhead in massive multiple-input multiple-output (MIMO) systems, an empirical Bayesian block expectation propagation (EP) algorithm is proposed. Specifically, a block Bernoulli–Gaussian prior channel model is proposed to fit the underlying block sparsity, and a block EP algorithm is derived to estimate the channels more accurately by clustering all the channel taps that pertain to the same delay, while the model parameters are learned by minimizing the Bethe free energy. Simulation results show that the proposed algorithm achieves considerable reduction of pilot overhead in a massive MIMO system with tens of antennas, while maintaining superior channel estimation performance.

Our analysis examines the conservation of multiprotein complexes among metazoa through use of high resolution biochemical fractionation and precision mass spectrometry applied to soluble cell extracts from 5 representative model organisms Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Strongylocentrotus purpuratus, and Homo sapiens. The interaction network obtained from the data was validated globally in 4 distant species (Xenopus laevis, Nematostella vectensis, Dictyostelium discoideum, Saccharomyces cerevisiae) and locally by targeted affinity-purification experiments. Here we provide details of our massive set of supporting biochemical fractionation data available via ProteomeXchange (http://www.ebi.ac.uk/pride/archive/projects/PXD002319-http://www.ebi.ac.uk/pride/archive/projects/PXD002328), PPIs via BioGRID (185267); and interaction network projections via (http://metazoa.med.utoronto.ca) made fully accessible to allow further exploration. The datasets here are related to the research article on metazoan macromolecular complexes in Nature [1]. Keywords: Proteomics, Metazoa, Protein complexes, Biochemical, Fractionation

The carboxy-terminal domain (CTD) of the RNA polymerase II (RNAP II) subunit POLR2A is a platform for modifications specifying the recruitment of factors that regulate transcription, mRNA processing, and chromatin remodelling. Here we show that a CTD arginine residue (R1810 in human) that is conserved across vertebrates is symmetrically dimethylated (me2s). This R1810me2s modification requires protein arginine methyltransferase 5 (PRMT5) and recruits the Tudor domain of the survival of motor neuron (SMN, also known as GEMIN1) protein, which is mutated in spinal muscular atrophy. SMN interacts with senataxin, which is sometimes mutated in ataxia oculomotor apraxia type 2 and amyotrophic lateral sclerosis. Because POLR2A R1810me2s and SMN, like senataxin, are required for resolving RNA-DNA hybrids created by RNA polymerase II that form R-loops in transcription termination regions, we propose that R1810me2s, SMN, and senataxin are components of an R-loop resolution pathway. Defects in this pathway can influence transcription termination and may contribute to neurodegenerative disorders.