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In this paper, we present a new scenario of direction of arrival (DOA) estimation using massive multiple-input multiple-output (MIMO) receive array with low-resolution analog-to-digital convertors (ADCs), which can strike a good balance between performance and circuit cost. Based on the linear additive quantization noise model (AQNM), the effect of low-resolution ADCs on the methods, such as Root-MUSIC method, is analyzed. Also, the closed-form expression of Cramer-Rao lower bound (CRLB) is derived to evaluate the performance loss caused by the low-resolution ADCs. The simulation results show that the Root-MUSIC methods can achieve the corresponding CRLB. Furthermore, 2-3 bits are acceptable for most applications if the 1dB performance loss.

Proactive edge association is capable of improving wireless connectivity at the cost of increased handover (HO) frequency and energy consumption, while relying on a large amount of private information sharing required for decision making. In order to improve the connectivity-cost trade-off without privacy leakage, we investigate the privacy-preserving joint edge association and power allocation (JEAPA) problem in the face of the environmental uncertainty and the infeasibility of individual learning. Upon modelling the problem by a decentralized partially observable Markov Decision Process (Dec-POMDP), it is solved by federated multi-agent reinforcement learning (FMARL) through only sharing encrypted training data for federatively learning the policy sought. Our simulation results show that the proposed solution strikes a compelling trade-off, while preserving a higher privacy level than the state-of-the-art solutions., 6 pages, 4 figures, IEEE Trans. on Veh. Technol

Online teaching transition during COVID-19 school lockdown elicited challenges for teachers and schools across the globe. The existing literature on the impact of COVID-19 in the education sector is predominantly descriptive and focused on the difficulties faced by teachers during the process of transferring into online teaching, mainly in the higher education sector. This study adopted a mixed-method design to examine online teaching self-efficacy (TSE) during COVID-19, its associated factors and moderators. A sample of 351 Chinese school teachers retrospectively reported their online TSE at the beginning and end of COVID-19 school lockdown, out of which six were followed up for an in-depth interview. TSE for online instruction did not significantly increase (β = .014, p > 0.05) whereas that for technology application increased significantly (β = .231, p

In this paper, we investigate the approximations of stochastic \begin{document}$ p $\end{document} -Laplacian equation with additive white noise by a family of piecewise deterministic partial differential equations driven by a stationary stochastic process. We firstly obtain the tempered pullback attractors for the random \begin{document}$ p $\end{document} -Laplacian equation with a general diffusion. We secondly prove the convergence of solutions and the upper semi-continuity of pullback attractors of the Wong-Zakai approximation equations in a Hilbert space for the additive case. Thirdly, by a truncation technique, the uniform compactness of pullback attractor with respect to the quantity of approximations is derived in the space of \begin{document}$ q $\end{document} -times integrable functions, where the upper semi-continuity of the attractors of the approximation equations is well established.

Background and aims: Hepatitis B virus (HBV)-related cirrhosis is associated with decreased bone mineral density (BMD); however, the mechanism is yet unknown. To assess the incidence of osteoporosis in patients with HBV-associated cirrhosis and relevant mechanisms. Methods: A total of 80 hospitalized patients with HBV-associated cirrhosis and 80 healthy controls were enrolled. The levels of serum osteocalcin, total procollagen type 1 amino-terminal propeptide, β-C-terminal telopeptide of type I collagen (β-CTX), and 25-hydroxy vitamin D3 (25(OH)D3) was evaluated in the cirrhosis group. Results: The BMDs of the lumbar spine (P

The routing and wavelength assignment problem arises from the investigation of optimal wavelength allocation in an optical network that employs Wavelength Division Multiplexing (WDM). Consider an optical network that is represented by a connected, simple graph G . An all-to-all routing R in G is a set of paths connecting all pairs of vertices of G . The undirected optical index of G is the minimum integer k to guarantee the existence of a mapping ϕ : R → { 1 , 2 , … , k } , such that ϕ ( P ) ≠ ϕ ( P ′ ) if P and P ′ have common edge(s), over all possible routings R . A natural lower bound of the undirected optical index of G is the (undirected) edge-forwarding index, which is defined to be the minimum of the maximum edge-load over all possible all-to-all routings. In this paper, we first derive the exact value of the optical index of the complete m -ary trees, and then investigate the gap between undirected optical and edge-forwarding indices.

Introduction: An outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei Province, China. This study aimed to analyze the clinical and epidemiologic characteristics of patients with COVID-19 to better differentiate the suspected patients in Beijing, China. Methodology: This was a retrospective, single-center study. Clinical and epidemiologic data were collected from suspected patients with COVID-19 admitted to Beijing Ditan Hospital from January 29 to February 21, 2020. Results: One hundred and six patients (60 males and 46 females, median age 36 years) were enrolled. Thirty-six patients were ultimately laboratory confirmed. Fifty-three were excluded from the diagnosis of COVID-19. The remaining 17 patients were highly suspected, although their nucleic acid tests were repeatedly negative. The confirmed patients and highly suspected patients had a significantly higher proportion of epidemiologic history than the excluded patients (P < 0.001). There was no significant difference in clinical symptoms or the underlying diseases among the three groups. The confirmed patients had a higher frequency of lymphopenia and eosinopenia than the highly suspected and excluded patients. Chest computed tomography scans showed bilateral lung involvement, and ground-glass opacity was more likely observed in the confirmed patients. Conclusion: The clinical features of the confirmed patients with COVID-19 were insufficient for early diagnosis of COVID-19. The epidemiologic history was of great significance in the early diagnosis of COVID-19. More sensitive diagnostic methods are needed to aid the differential diagnosis of suspected patients with COVID-19.

COVID-19 (coronavirus disease 2019) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and discovered in 2019. The clinical manifestations include fever, coughing, difficulty in breathing and even death from multiple organ failure. Nucleic acid test is the golden standard method for confirmation of infection. According to the Chinese ‘Seventh Edition of the COVID-19 Diagnosis and Treatment Protocol’, suspected patients with negative nucleic acid tests from two consecutive airway specimens can be excluded from diagnosis and released from quarantine. The current report describes a suspected COVID-19 case that had a history of close contact with a COVID-19 patient. The diagnosis was confirmed after the SARS-CoV-2 nucleic acid was detected after four sputum sample tests (sampling interval of at least 24 h).

The collision channel without feedback (CCw/oFB) introduced by Massey and Mathys, depicts a scenario where multiple users share a communication channel but have arbitrary time offsets, and can never learn these time offsets due to the lack of feedback. This paper considers an extension of the CCw/oFB, which allows the receiver to use successive interference cancellation (SIC) to cancel the interference caused by those collided packets whose contents have been known by the receiver. We derive the zero-packet-loss throughput regions of this model for both the unsynchronized and slot-synchronized cases. Given an arbitrary number of users and a packet alphabet of arbitrary size, it is shown that these two regions coincide, and the outer boundary of this common region is the set of all points with only nonnegative components that add up to one. It is further shown that all points on this outer boundary with only rational components can be achieved without packet loss in the slot-synchronized case. The constructive proofs are based on a joint design of protocol sequences, identification/location algorithm and erasure correcting codes. These findings indicate that the negative impact of the lack of time synchronization on the throughput performance can be removed by the help of SIC.

Intelligent reflecting surface (IRS) is envisioned to be widely applied in future wireless networks. In this paper, we investigate a multi-user communication system assisted by cooperative IRS devices with the capability of energy harvesting. Aiming to maximize the long-term average achievable system rate, an optimization problem is formulated by jointly designing the transmit beamforming at the base station (BS) and discrete phase shift beamforming at the IRSs, with the constraints on transmit power, user data rate requirement and IRS energy buffer size. Considering time-varying channels and stochastic arrivals of energy harvested by the IRSs, we first formulate the problem as a Markov decision process (MDP) and then develop a novel multi-agent Q-mix (MAQ) framework with two layers to decouple the optimization parameters. The higher layer is for optimizing phase shift resolutions, and the lower one is for phase shift beamforming and power allocation. Since the phase shift optimization is an integer programming problem with a large-scale action space, we improve MAQ by incorporating the Wolpertinger method, namely, MAQ-WP algorithm to achieve a sub-optimality with reduced dimensions of action space. In addition, as MAQ-WP is still of high complexity to achieve good performance, we propose a policy gradient-based MAQ algorithm, namely, MAQ-PG, by mapping the discrete phase shift actions into a continuous space at the cost of a slight performance loss. Simulation results demonstrate that the proposed MAQ-WP and MAQ-PG algorithms can converge faster and achieve data rate improvements of 10.7% and 8.8% over the conventional multi-agent DDPG, respectively., Comment: 14 pages, 11 figures

We propose a germanium (Ge) photonic crystal thin slab to achieve perfect absorption efficiency in telecom band. The maximum absorption is increased 14-fold compared to a planar cell with the same thickness at normal incidence. The absorption enhancement is attributed to the critical coupling with guided resonances by introducing an airhole photonic crystal on the thin slab. This novel design constitutes an important step towards high responsivity and high-speed photodetection with strong energy harvesting.

Near-infrared perfect wave harvesting of graphene is theoretically and numerically obtained in a hybrid dielectric configuration without assistance of a reflecting mirror. The absorption is increased 43-fold compared to a suspended graphene layer at normal incidence. The mechanism of perfect absorption is based on critical coupling with a guided resonance introduced by a silicon bar array and Fabry–Perot (FP) effect of a silicon oxide layer. This lossless design is expected to find applications to allow the active area with effective generation and fast transport of photocarriers, paving a new way for on-chip small-footprint ultrahigh responsivity and ultrahigh-speed photodetection in silicon photonics.

Loquat fruit are susceptible to chilling injuries induced by postharvest storage at low temperature. The major symptoms are increased lignin content and flesh firmness, which cause a leathery texture. Pretreatment with methyl jasmonate (MeJA) can alleviate this low-temperature-induced lignification, but the mechanism is not understood. In this study, we characterized a novel class III peroxidase, EjPRX12, and studied its relationship to lignification. Transcript levels of EjPRX12 were attenuated following MeJA pretreatment, consistent with the reduced lignin content in fruit. In vitro enzyme activity assay indicated that EjPRX12 polymerized sinapyl alcohol, and overexpression of EjPRX12 in Arabidopsis promoted lignin accumulation, indicating that it plays a functional role in lignin polymerization. We also identified an HD-ZIP transcription factor, EjHB1, repressed by MeJA pretreatment, which directly bound to and significantly activated the EjPRX12 promoter. Overexpression of EjHB1 in Arabidopsis promoted lignin accumulation with induced expression of lignin-related genes, especially AtPRX64. Furthermore, a JAZ-interacting repressor, EjbHLH14, was characterized, and it is proposed that MeJA pretreatment caused EjbHLH14 to be released to repress the expression of EjHB1. These results identified a novel regulatory pathway involving EjbHLH14-EjHB1-EjPRX12 and revealed the molecular mechanism whereby MeJA alleviated lignification of loquat fruit at low temperature.

For emergencies, the reliability of information can not be guaranteed. At the same time, due to the lack of information and knowledge, neither the criteria itself nor the credibility can be given a precise evaluation by decision-makers(DMs). Therefore, we combine intuitionistic fuzzy set and Z-number to get a new class of fuzzy set, complete Z-intuitionistic fuzzy set(CZIFS), and its degenerate form, A-type Z-intuitionistic fuzzy set(AZIFS) and B-type Z-intuitionistic fuzzy set(BZIFS). CZIFS can serve as a reliable tool to depict the hesitant degree both on the ambiguity and reliability of uncertain information. In addition, we introduce the score and accuracy functions and distance measure of complete Z-intuitionistic fuzzy number(CZIFN), with which we have considered both reliability information and DMs' preference on it. Then, we improve traditional MULTIMOORA by developing reference point(RP) model to consider both the risk and profile of alternatives and integrating analytic hierarchy process(AHP) in the process of ranking aggregation method to take into account the preference of DMs on three subordinate rankings. Besides, to solve multicriteria group decision making(MCGDM) problem, we develop improved MULTIMOORA method to the environment of CZIFN. Finally, to illustrate the proposed method, we give a numerical example, solving site selecting of Fangcang shelter hospital for COVID-19.

In this paper, a new concept, the fuzzy rate of an operator in linear spaces is proposed for the very first time. Some properties and basic principles of it are studied. Fuzzy rate of an operator B which is specific in a plane is discussed. As its application, a new fixed point existence theorem is proved.

Small World Effect (or Six Degrees of Separation theory) has generated significant influence in the world. Many researchers and institutes have done lots of work on the study of it. We model Small World Effect by random process and Graph, calculate the probability that any two people i and j in the world can contact each other after n steps (forwarding messages by intermediaries) based on different R (average number of acquaintances everyone has in the world).When R=50 or 80, if n≥5, the probability is 0.848 and the search is very likely to happen. When R=150, n=4, this probability is 0.99994, that is, after 4 steps, any two people in the world will establish connection almost surely. In the sense of Dunbar's number (R=150), six degrees of separation becomes four degrees of separation. We propose the concepts of (directed) Random Fuzzy Graph for the very first time which can describe the fact of recognition among people best, because the relation among persons is random and fuzzy.

With the development of federated learning (FL), mobile devices (MDs) are able to train their local models with private data and sends them to a central server for aggregation, thereby preventing sensitive raw data leakage. In this paper, we aim to improve the training performance of FL systems in the context of wireless channels and stochastic energy arrivals of MDs. To this purpose, we dynamically optimize MDs' transmission power and training task scheduling. We first model this dynamic programming problem as a constrained Markov decision process (CMDP). Due to high dimensions rooted from our CMDP problem, we propose online stochastic learning methods to simplify the CMDP and design online algorithms to obtain an efficient policy for all MDs. Since there are long-term constraints in our CMDP, we utilize Lagrange multipliers approach to tackle this issue. Furthermore, we prove the convergence of the proposed online stochastic learning algorithm. Numerical results indicate that the proposed algorithms can achieve better performance than the benchmark algorithms.

This paper considers a multiple-access system with multiple-packet reception (MPR) capability $\gamma $ , i.e., a packet can be successfully received as long as it overlaps with $\gamma -1$ or fewer other packets at any instant during its lifetime. To efficiently utilize the MPR capability, this paper generalizes $p$ -persistent carrier-sense multiple access (CSMA) to consider that a user with carrier sensing capability $c$ adopts the transmission probability $p_{n}$ if this user has sensed $n$ ongoing transmissions for $n=0,1,\ldots ,c-1$ . This paper aims to model the characteristics of such CSMA and to design transmission probabilities for achieving maximum saturation throughput. To this end, we first formulate such CSMA as a parameterized Markov decision process (MDP) and use the long-run average performance to evaluate the saturation throughput. Second, by observing that the exact values of optimal transmission probabilities are in general infeasible to find, we modify this MDP to establish an upper bound on the maximum throughput, and modify this MDP again to propose a heuristic design with near-optimal performance. Simulations with respect to a wide range of configurations are provided to validate our study. The throughput performance under more general models and the robustness of our design are also investigated.

This paper considers random access in a communication channel, which is shared by $N$ active users with saturated traffic. Following a slotted ALOHA-type protocol, each active user attempts to transmit in every slot with a common probability. It is assumed that the channel has the multiple-packet reception capability to enable the correct reception of up to $M$ ( $1 \leq M ) time-overlapping transmissions. To support mission- and time-critical applications that require reliable delivery within a strict delivery deadline $D$ (in units of slot), the aim of this paper is to achieve the maximum deadline-constrained reliability. First, we prove the uniqueness of the optimal transmission probability for any $1\leq M and any $D\geq 1$ . Second, we show it can be computed by a fixed-point iteration for all the cases. Third, for real-life scenarios where $N$ may be unknown and changing, we develop a distributed algorithm for $M>1$ , which allows each active user to dynamically tune its transmission probability based on a method for estimating $N$ . Simulation results verify our analysis and show that the proposed tuning algorithm is effective with near-optimal performance. In addition, as a special case (i.e., $D=1$ ) of our study, the issue of saturation throughput maximization is completely addressed for the first time.

In secure spatial modulation systems, an active antenna-group (AAG) selection of maximizing the average secrecy rate (SR) is proposed to avoid the disadvantage that conventional AAG selection scheme of minimizing bit error ratio at desired receiver may lead to a substantial SR loss. However, due to the limited active antenna pattern and finite-alphabet inputs, it is very hard for us to optimize the SR without closed-form expression. To address the two issues, first, by exploiting the relationship between minimum mean-square error and mutual information, the expression of SR in the low signal-to-noise ratio (SNR) region is derived. Using the expression, the problem of maximizing SR (Max-SR), called Max-SR I, is converted to integer programming problem. In the high SNR region, we derive an asymptotical lower bound for SR, and find the fact that the Max-SR can be reduced to maximizing the difference of Bob’s minimum Euclidean distance and Eve’s one, called Max-SR II. Through this conclusion, we can find the relationship between SR and bit-error rate. Furthermore, Max-SR III is proposed to overcome the disadvantage of the SR performance loss for the above two asymptotical algorithms in the moderate SNR region, where an approximate expression is exploited as the efficient metric to design AAG. Numerical results show that the SR performance of the proposed Max-SR III is close to that of optimal exhaustive search method, and the Max-SR I and Max-SR II can achieve acceptable SR performance with extremely low complexity.

Medium-scale or large-scale receive antenna array with digital beamforming can be employed at receiver to make a significant interference reduction but leads to expensive cost and high complexity of the RF-chain circuit. To deal with this issue, classic analog-and-digital beamforming (ADB) structure was proposed in the literature for greatly reducing the number of RF-chains. Based on the ADB structure, in this paper, we propose a robust hybrid ADB scheme to resist directions of arrival (DOAs) estimation errors. The key idea of our scheme is to employ null space projection (NSP) in the analog beamforming domain and diagonal loading (DL) method in digital beamforming domain. The simulation results show that the proposed scheme performs more robustly, and moreover, it has a significant improvement on the receive signal-to-interference-plus-noise ratio compared to NSP ADB scheme and DL method.

Millimeter wave (mmWave) communication has been regarded as one of the most promising technologies for the future generation wireless networks because of its advantages of providing a ultra-wide new spectrum and ultra-high data transmission rate. To reduce the power consumption and circuit cost for mmWave systems, hybrid digital and analog (HDA) architecture is preferred in such a scenario. In this paper, an artificial noise (AN) aided secure HDA beamforming scheme is proposed for mmWave multiple input single output (MISO) system with low resolution digital-to-analog converters (DACs) and finite-quantized phase shifters on radio frequency. The additive quantization noise model for AN aided HDA system is established to make an analysis of the secrecy performance of such systems. With the partial channel knowledge of eavesdropper available, an approximate expression of secrecy rate (SR) is derived. Then using this approximation formula, we propose a two-layer alternatively iterative structure (TLAIS) for optimizing digital precoder (DP) of confidential message (CM), digital AN projection matrix (DANPM) and analog precoder (AP). The inner-layer iteration loop is to design the DP of CMs and DANPM alternatively given a fixed matrix of AP. The outer-layer iteration loop is between digital baseband part and analog part, where the former refers to DP and DANPM, and the latter is AP. Then for a given digital part, we propose a gradient ascent algorithm to find the AP vector. Given a matrix of AP, we make use of general power iteration (GPI) method to compute DP and DANPM. This process is repeated until the terminal condition is reached. Simulation results show that the proposed TLAIS can achieve a better SR performance than existing methods, especially in the high signal-to-noise ratio region.

We demonstrate twist-controlled resonant tunneling in a monolayer graphene (MLG)/hexagonal boron nitride ( h-BN)/ABA-stacked trilayer graphene (TLG) van der Waals (vdW) junction, in which MLG and TLG flakes are aligned with a small twist angle θ of ∼1.05° between their crystallographic orientations through a thin h-BN barrier. Owing to the small interlayer twist, resonant tunneling attributed to the conservation of momentum and energy was observed between the single linear band of MLG and multiple subbands of TLG. We show that different subbands of TLG—bilayer-graphene-like subbands and a MLG-like subband—exhibit distinctly different resonant tunneling behaviors. Therefore, we demonstrate subband-resolved resonant tunneling. This technique provides a method to determine band parameters (Slonczewski–Weiss–McClure parameters) and probes the band dispersion of different two-dimensional materials by utilizing a MLG electrode.

Conflict-avoiding codes (CACs) were introduced by Levenshtein as a single-channel transmission scheme for a multiple-access collision channel without feedback. When the number of simultaneously active source nodes is less than or equal to the weight of a CAC, it is able to provide a hard guarantee that each active source node transmits at least one packet successfully within a fixed time duration, no matter what the relative time offsets between the source nodes are. In this paper, we extend CACs to multichannel CACs for providing such a hard guarantee over multiple orthogonal channels. Upper bounds on the number of codewords for multichannel CACs of weights three and four are derived, and constructions that are optimal with respect to these bounds are presented., 12 pages. Accepted for publication in IEEE Transaction on Information Theory

Background In December 2019, the outbreak of 2019 novel coronavirus disease (COVID-19) began in Wuhan, Hubei Province, China. The disease has rapidly spread from Wuhan to other provinces and other countries. Clinical and epidemiological knowledge is limited. We aimed to describe the clinical and epidemiological characteristics of a family cluster of COVID-19 in Beijing.Methods We reported a family cluster of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases in Beijing, China. We obtained and analyzed clinical and epidemiologic data from these patients. Throat swab samples were tested for SARS-CoV-2 using real-time reverse transcriptase-polymerase chain reaction assays.Results This family comprised three laboratory confirmed cases with clinical symptoms. All three patients had close contact with a relative from Wuhan, Hubei Province. Chest computerized tomography revealed ground-glass opacities and consolidation. Patient 1 was finally intubated and mechanical ventilated. Patient 2 received high-flow oxygen therapy. The clinical condition of Patient 3 has resolved.Conclusion SARS-CoV-2 infections tend to clusters. Advanced age and comorbidities are associated with adverse outcomes. Physicians should be aware of contact history so that infected patients can be identified promptly and further spreading prevented.

In this paper, we consider a multiuser uplink status update system, where a monitor aims to timely collect randomly generated status updates from multiple end nodes through a shared wireless channel. We adopt the recently proposed metric, termed age of information (AoI), to quantify the information timeliness and freshness. Due to the random generation of the status updates at the end node side, the monitor only grasps a partial knowledge of the status update arrivals. Under such a practical scenario, we aim to address a fundamental multiuser scheduling problem: how to schedule the end nodes to minimize the network-wide AoI? To solve this problem, we formulate it as a partially observable Markov decision process (POMDP), and develop a dynamic programming (DP) algorithm to obtain the optimal scheduling policy. By noting that the optimal policy is computationally prohibitive, we further design a low-complexity myopic policy that only minimizes the one-step expected reward. Simulation results show that the performance of the myopic policy can approach that of the optimal policy, and is better than that of the baseline policy.