Search

A method of steel structure surface crack identification based on artificial intelligence technology is proposed to solve the problem that steel cracks can not be detected and forewarned in time when they appear in the railway industrial environment. The appearance of steel cracks greatly weakens the stability of steel structures, and will seriously endanger the safety of the railway industry if it is not detected and repaired in time. However, the common steel crack detection methods cannot achieve real-time monitoring of steel structures. In order to monitor the surface of steel structure in real-time and explore the recognition effect and model the advantages of common classification neural network models for surface cracks of railway industrial steel, this study evaluates the network model with multiple indicators and parameters under two experimental conditions. In this study, the steel surface cracks in the railway industrial environment are taken as samples, and the steel cracks are identified through the neural network model. For large-volume datasets, the recognition accuracy of the three network models has reached 97%, of which the YOLOv5 model has the best comprehensive recognition ability, and the C-Alex model has the best performance and convergence speed in small-volume datasets. This study explores the application prospects of models under different scenarios, proving that the three models can effectively detect steel surface cracks in real-time, and at the same time, it will pave the way for the development and application of artificial intelligence multi-model fusion technology in the field of the railway industry.

In this article, the problem of joint transceiver design for network-assisted full-duplex (NAFD) systems under cell-free massive multiple-input multiple-output (MIMO) network with simultaneous wireless information and power transfer is investigated. The uplink users’ transmit power, the uplink and downlink beamforming vectors, the fronthaul compression ratio, and the power-splitting ratio are jointly optimized to minimize the total transmission power under the constraints of signal-to-noise ratio, quality of service (QoS), energy harvesting, fronthaul capacity and transmit power of users, and remote antenna units. Applying the block-coordinate-descent method and the successive convex approximation, an algorithm is proposed to handle the nonconvex optimization problem. Finally, the simulation results validate the effectiveness of the proposed algorithm and show that NAFD systems can achieve lower transmission power than cloud radio access network co-frequency co-time full-duplex systems.

Electronic skins are artificial skin-type multifunctional sensors, which hold great potentials in intelligent robotics, limb prostheses and human health monitoring. However, it is a great challenge to independently and accurately read various physical signals without power supplies. Here, a self-powered flexible temperature-pressure bimodal sensor based on high-performance thermoelectric films and porous microconed conductive elastic materials is presented. Through introducing flexible heat-sink design and harvesting body heat energy, the thin-film thermoelectric device could not only precisely sense temperature signal but also drive the pressure sensor for detecting external tactile stimulus. The integration of Bi-Te based thermoelectric film with high stability in wide temperature range enables the sensor to sense the ambient temperature with high resolution (

Channel covariance matrix, or large-scale channel state information, is usually assumed to be perfectly known, which is not practical due to the quickly changing environment. This letter proposes a highly accurate channel covariance matrix estimation method based on fingerprint-based localization. In initial pilot assignment stage, we eliminate the impact of inference and noise by introducing random phase shift to estimate channel covariance matrices, which are regarded as fingerprints for estimating locations. Users are clustered based on locations and pilots are reassigned accordingly to improve estimation accuracy. Simulation results show that the proposed method achieves higher covariance matrix estimation accuracy.

OBJECTIVE To evaluate the effects of cryopreservation in post-thaw umbilical cord blood units for the survivability of Gram-positive bacteria strains. BACKGROUND Microbial screening is required for all cord blood units (CBUs). Four gram-positive contaminants were documented to survive cryopreservation poorly and isolation of other contaminants were reported. METHODS Forty-eight contaminated CBUs detected with either Staphylococcus epidermidis, Corynebacterium species, Peptostreptococcus or Streptococcus species before cryopreservation were used in this study. CBUs were processed, DMSO-infused and microbial screened before cryopreservation. Post-thaw microbial screening was achieved using 1 and 10 ml inoculants in BACTEC culture bottles. Positive bottles were subjected for microbial identification and results were compared with those from pre-freeze. RESULTS A higher rate of microbial contamination was found using the 10 ml inoculant. Screening of 11 CBUs did not detect any contaminants while 30 CBUs screened detected more than one unknown contaminants and majority of contaminants were identified to be gram-negative species. CONCLUSION A higher inoculation volume used at post-thaw for microbial screening improves contamination detection but leads to the loss of precious cord blood. Some contaminants did not survive cryopreservation or were not identified due to their low microbial levels. Contrasting contaminants found at post-thaw suggest the improvements made in detection and identification of contaminants over the years.

In this paper, we investigate the problem of sum rate maximization by guaranteeing the quality of service (QoS) of both uplink and downlink in cell-free with network-assisted full Duplexing (NAFD), where the users operate in half-duplex mode and access points (APs) operate in either full-duplex mode or half-duplex mode. In the considered network, the central processor unit (CPU) sends the compressed beamformed signals to the transmit-APs (T-APs) over the downlink fronthaul, and the T-APs forward the signals to downlink users. At the same time, the receive-APs (R-APs) compress the signals transmitted by uplink users and forward them to the CPU via uplink fronthaul. We aim to maximize the spectral efficiency and the number of users that should be admitted by the network, where users’ requirements of both downlink and uplink signal-to-interference-plus-noise (SINR) constraints, fronthaul capacity constraints, energy harvesting constraints and simultaneous wireless information and power transfer (SWIPT) ratio design are considered. A successive convex approximation-based algorithm is proposed to solve the highly coupled problem, which is guaranteed to converge to the Karush-Kuhn-Tucker (KKT) conditions. We conduct a comprehensive comparison between the NAFD scheme and the traditional co-frequency co-time full duplex (CCFD) scheme and time division duplex (TDD) scheme and offer some valuable opinions about the system design.

In the micro electro mechanical system (MEMS) area, micro metal devices fabricating by the electroplating process were used widely in biology, medicine and optics field. However, due to the oxide layer of the metal substrate surface, the electroplating layer suffers from the poor adhesion. In order to reduce the oxide layer of the metal substrate surface, effects of the ultrasonic assisted electrochemical potential activation method have been investigated originally. The electrochemical test was processed by an electrochemical station. The oxide content of the substrate surface was measured by the X‐ray photoelectron spectroscopy (XPS) method. The experimental results show that, comparing with the ultrasound free one, the ultrasonic assisted electrochemical potential activation method can improve the hydrogen evolution reaction and reduce the metal ion nucleation rate. Then the Cu substrate surface oxide content has been restored. Results of this paper can provide a new ultrasonic electrochemical potential activation method to activate the oxide layer of the substrate surface, as well as to improve the adhesion.

In this letter, we are committed to obtaining load-balanced user association and optimal beamforming in an energy-saving downlink distributed Millimeter-Wave (mmWave) network, with per-user quality of service (QoS) requirements, user association constraints and remote radio unit (RRU) transmission power limits. A mixed discrete nonlinear programming (MINLP) problem is formulated, which is NP-hard. The traditional sparse beamforming method (SBM) can jointly optimize the user association and the beamforming vector by inducing the beamformer sparsity via the reweighted $\ell _{1}$ norm technique. However, such existing scheme may cause unbalanced load of RRU, thus degrading the mmWave network performance. For better load-balanced user association, we introduce the Fuzzy inference System (FIS) to pursue further advancement of SBM. In addition, the good scalability of FIS framework can help itself to be extended to more indicators in the next generation of communication systems. Simulation results show that the improved algorithm can obtain a load-balanced user association, meanwhile the transmit power consumption of mmWave networks can be significantly reduced.

Network-assisted full-duplex enable simultaneous uplink (UL) and downlink (DL) communications by allocating remote antenna units (RAUs) to perform either UL reception of DL transmission at each time slot, which improve the spectral efficiency (SE) of cell-free massive multiple-input multiple-output (MIMO) systems. However, previous studies mainly focus on analyzing the system performance under given duplex mode of RAUs. In this letter, we propose to dynamically optimize the duplex mode of RAUs to further improve the SE. An algorithm based on parallel successive convex approximation is proposed to solve the non-convex duplex mode optimization problem. To reduce algorithm complexity and achieve higher SE, a reinforcement learning algorithm based on enhanced Q-learning is also proposed. Simulation results show that the proposed algorithms improve the SE of cell-free massive MIMO systems greatly with lower complexity.

Multiple remote antenna units (RAUs) cooperate to serve a certain user in cell-free distributed massive multiple-input multiple-output (MIMO) systems. Due to the different distances between each RAU and the user, asynchronous reception effects will occur. This paper studies the impacts of asynchronous reception effects on cell-free distributed massive MIMO systems. We first derive the minimum-mean-square error (MMSE) channel estimation under the asynchronous reception effects. Given the estimated channel state information, we derive the closed-form expressions of the user achievable rates with maximum ratio transmission (MRT) and regularized zero-forcing (RZF) precoders, which are further used to analyze the impacts of asynchronous reception effects. The accuracy of the closed-form expressions are verified. Simulation results demonstrate that asynchronous reception effects cause a non-negligible drop on the system spectral efficiency. Moreover, the performance degradation is proportional to the subcarrier sequence number and even more serious with the increasing of signal-to-noise ratio (SNR) or the number of antennas per RAU.

As an emerging donor, China’s growing role in the international development arena has provoked much debate. This paper explores the effects of China’s aid on its Outward Foreign Direct Investment (OFDI) to the recipient countries with great prevalence of informal economy, which is often neglected in recent research. Using a dataset of 51 countries receiving China’s aid during 2003–2014, we find that aid from China promotes China’s OFDI flows to the recipient countries. Moreover, the existence of the informal economy of recipient countries accelerates their inflows of FDI from China, while undermines the facilitating effects of China’s aid on its OFDI to the recipient countries. In addition, the undermining effects of informal economy are found only for African countries, rather than Asian countries. However, a sharp contrast is found from the case of the US. Therefore, our findings suggest that informal economy should be under serious consideration in the research.

Background: Inflammatory myofibroblastic tumor (IMT) is a distinctive tumor composed of spindle cells accompanied by mixed inflammatory cells, and immunohistochemical positivity for ALK (anaplastic lymphoma kinase protein) can be detected in half of IMTs. The diagnosis of ALK-negative IMT could be a challenge. Recently, the fusions of some kinase genes, such as RET, NTRK1, ROS1, etc., are revealed in ALK-negative IMT. Case presentation: A 19-year-old woman presented with swelling of the left upper arm. Magnetic resonance imaging (MRI) scan revealed a tumor in the left postbrachium extended to the left axillary, serratus anterior muscle, and latissimus dorsi muscle. Histopathologically, the irregular-circumscribed tumor was composed of dense spindle-shaped cells with eosinophilic abundant cytoplasm and hyalinized mesenchyme in an inflammatory background. Immunohistochemically (IHC), tumor cells were positive for SMA, MDM2, and p16; the cells were negative for desmin, MyoD1, Myogenin, pan-cytokeratin, S100, SOX10, HMB45, Malen-A, CD34, CD31, CD99, and ALK. By RNA-based NGS, a novel fusion between TPD52L2 3’ end of exon 1-4 and ROS1 5’ end of exon 36-43 was revealed. ROS1 IHC staining was negative. The final diagnosis of IMT with TPD52L2-ROS1fusion was made.Subsequently, the patient experienced a good clinical response to Crizotinib, and clinical follow-up showed stable disease after 9 months. Conclusion: This report expands the spectrum of ROS1 gene rearrangements in the IMT and highlights the importance of molecular analysis of IMT for getting a diagnostic clue and determining potential therapeutic strategies.