Showing papers by "Harbin Engineering University published in 2020"

The Effects of Social Support on Sleep Quality of Medical Staff Treating Patients with Coronavirus Disease 2019 (COVID-19) in January and February 2020 in China.

Abstract: BACKGROUND Coronavirus disease 2019 (COVID-19), formerly known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 2019 novel coronavirus (2019-nCoV), was first identified in December 2019 in Wuhan City, China. Structural equation modeling (SEM) is a multivariate analysis method to determine the structural relationship between measured variables. This observational study aimed to use SEM to determine the effects of social support on sleep quality and function of medical staff who treated patients with COVID-19 in January and February 2020 in Wuhan, China. MATERIAL AND METHODS A one-month cross-sectional observational study included 180 medical staff who treated patients with COVID-19 infection. Levels of anxiety, self-efficacy, stress, sleep quality, and social support were measured using the and the Self-Rating Anxiety Scale (SAS), the General Self-Efficacy Scale (GSES), the Stanford Acute Stress Reaction (SASR) questionnaire, the Pittsburgh Sleep Quality Index (PSQI), and the Social Support Rate Scale (SSRS), respectively. Pearson's correlation analysis and SEM identified the interactions between these factors. RESULTS Levels of social support for medical staff were significantly associated with self-efficacy and sleep quality and negatively associated with the degree of anxiety and stress. Levels of anxiety were significantly associated with the levels of stress, which negatively impacted self-efficacy and sleep quality. Anxiety, stress, and self-efficacy were mediating variables associated with social support and sleep quality. CONCLUSIONS SEM showed that medical staff in China who were treating patients with COVID-19 infection during January and February 2020 had levels of anxiety, stress, and self-efficacy that were dependent on sleep quality and social support.

Social Capital and Sleep Quality in Individuals Who Self-Isolated for 14 Days During the Coronavirus Disease 2019 (COVID-19) Outbreak in January 2020 in China.

Abstract: BACKGROUND From the end of December 2019, coronavirus disease 2019 (COVID-19) began to spread in central China. Social capital is a measure of social trust, belonging, and participation. This study aimed to investigate the effects of social capital on sleep quality and the mechanisms involved in people who self-isolated at home for 14 days in January 2020 during the COVID-19 epidemic in central China. MATERIAL AND METHODS Individuals (n=170) who self-isolated at home for 14 days in central China, completed self-reported questionnaires on the third day of isolation. Individual social capital was assessed using the Personal Social Capital Scale 16 (PSCI-16) questionnaire. Anxiety was assessed using the Self-Rating Anxiety Scale (SAS) questionnaire, stress was assessed using the Stanford Acute Stress Reaction (SASR) questionnaire, and sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Path analysis was performed to evaluate the relationships between a dependent variable (social capital) and two or more independent variables, using Pearson's correlation analysis and structural equation modeling (SEM). RESULTS Low levels of social capital were associated with increased levels of anxiety and stress, but increased levels of social capital were positively associated with increased quality of sleep. Anxiety was associated with stress and reduced sleep quality, and the combination of anxiety and stress reduced the positive effects of social capital on sleep quality. CONCLUSIONS During a period of individual self-isolation during the COVID-19 virus epidemic in central China, increased social capital improved sleep quality by reducing anxiety and stress.

GSH-Depleted Nanozymes with Hyperthermia-Enhanced Dual Enzyme-Mimic Activities for Tumor Nanocatalytic Therapy

Abstract: Nanocatalytic therapy, using artificial nanoscale enzyme mimics (nanozymes), is an emerging technology for therapeutic treatment of various malignant tumors. However, the relatively deficient catalytic activity of nanozymes in the tumor microenvironment (TME) restrains their biomedical applications. Here, a versatile and bacteria-like PEG/Ce-Bi@DMSN nanozyme is developed by coating uniform Bi2 S3 nanorods (NRs) with dendritic mesoporous silica (Bi2 S3 @DMSN) and then decorating ultrasmall ceria nanozymes into the large mesopores of Bi2 S3 @DMSN. The nanozymes exhibit dual enzyme-mimic catalytic activities (peroxidase-mimic and catalase-mimic) under acidic conditions that can regulate the TME, that is, simultaneously elevate oxidative stress and relieve hypoxia. In addition, the nanozymes can effectively consume the overexpressed glutathione (GSH) through redox reaction. Photothermal therapy (PTT) is introduced to synergistically improve the dual enzyme-mimicking catalytic activities and depletion of the overexpressed GSH in the tumors by photonic hyperthermia. This is achieved by taking advantage of the desirable light absorbance in the second near-infrared (NIR-II) window of the PEG/Ce-Bi@DMSN nanozymes. Subsequently the reactive oxygen species (ROS)-mediated therapeutic efficiency is significantly improved. Therefore, this study provides a proof of concept of hyperthermia-augmented multi-enzymatic activities of nanozymes for tumor ablation.

In Situ Reconstruction of a Hierarchical Sn-Cu/SnOx Core/Shell Catalyst for High-Performance CO2 Electroreduction.

Abstract: The electrochemical CO2 reduction reaction (CO2 RR) to give C1 (formate and CO) products is one of the most techno-economically achievable strategies for alleviating CO2 emissions. Now, it is demonstrated that the SnOx shell in Sn2.7 Cu catalyst with a hierarchical Sn-Cu core can be reconstructed in situ under cathodic potentials of CO2 RR. The resulting Sn2.7 Cu catalyst achieves a high current density of 406.7±14.4 mA cm-2 with C1 Faradaic efficiency of 98.0±0.9 % at -0.70 V vs. RHE, and remains stable at 243.1±19.2 mA cm-2 with a C1 Faradaic efficiency of 99.0±0.5 % for 40 h at -0.55 V vs. RHE. DFT calculations indicate that the reconstructed Sn/SnOx interface facilitates formic acid production by optimizing binding of the reaction intermediate HCOO* while promotes Faradaic efficiency of C1 products by suppressing the competitive hydrogen evolution reaction, resulting in high Faradaic efficiency, current density, and stability of CO2 RR at low overpotentials.

Dual-Band Metasurface-Based Decoupling Method for Two Closely Packed Dual-Band Antennas

Abstract: In this communication, a metasurface-based decoupling method (MDM) is proposed to reduce the mutual couplings at two independent bands of two coupled multiple-input-multiple-output (MIMO) antennas. The metasurface superstrate is composed of pairs of non-uniform cut wires with two different lengths. It is compact in size and effective in decoupling two nearby dual-band patch antennas that are strongly coupled in the H-plane with the edge-to-edge spacing of only 0.008 wavelength at low-frequency band (LB). The antenna is fabricated and measured and the results show that the isolation between two dual-band antennas can be improved to more than 25 dB at both 2.5–2.7 GHz and 3.4–3.6 GHz bands, while their reflection coefficients remain to be below −10 dB after the metasurface superstrate is introduced. Moreover, the total efficiency is improved by about 15% in the low band and the envelope correlation coefficient (ECC) between the two antennas is reduced from 0.46 to 0.08 at 2.6 GHz and 0.08 to 0.01 at 3.5 GHz. The proposed method can find plenty of applications in dual-band MIMO and 5G communication systems.

All-in-One Theranostic Nanomedicine with Ultrabright Second Near-Infrared Emission for Tumor-Modulated Bioimaging and Chemodynamic/Photodynamic Therapy

Abstract: Reactive oxygen species (ROS)-based therapeutic modalities including chemodynamic therapy (CDT) and photodynamic therapy (PDT) hold great promise for conquering malignant tumors. However, these two methods tend to be restricted by the overexpressed glutathione (GSH) and hypoxia in the tumor microenvironment (TME). Here, we develop biodegradable copper/manganese silicate nanosphere (CMSN)-coated lanthanide-doped nanoparticles (LDNPs) for trimodal imaging-guided CDT/PDT synergistic therapy. The tridoped Yb3+/Er3+/Tm3+ in the ultrasmall core and the optimal Yb3+/Ce3+ doping in the shell enable the ultrabright dual-mode upconversion (UC) and downconversion (DC) emissions of LDNPs under near-infrared (NIR) laser excitation. The luminescence in the second near-infrared (NIR-II, 1000-1700 nm) window offers deep-tissue penetration, high spatial resolution, and reduced autofluorescence when used for optical imaging. Significantly, the CMSNs are capable of relieving the hypoxic TME through decomposing H2O2 to produce O2, which can react with the sample to generate 1O2 upon excitation of UC photons (PDT). The GSH-triggered degradation of CMSNs results in the release of Fenton-like Mn2+ and Cu+ ions for •OH generation (CDT); simultaneously, the released Mn2+ ions couple with NIR-II luminescence imaging, computed tomography (CT) imaging, and magnetic resonance (MR) imaging of LDNPs, performing a TME-amplified trimodal effect. In such a nanomedicine, the TME modulation, bimetallic silicate photosensitizer, Fenton-like nanocatalyst, and NIR-II/MR/CT contrast agent were achieved "one for all", thereby realizing highly efficient tumor theranostics.

Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries.

Abstract: The stability of food supply chains is crucial to the food security of people around the world. Since the beginning of 2020, this stability has been undergoing one of the most vigorous pressure tests ever due to the COVID-19 outbreak. From a mere health issue, the pandemic has turned into an economic threat to food security globally in the forms of lockdowns, economic decline, food trade restrictions, and rising food inflation. It is safe to assume that the novel health crisis has badly struck the least developed and developing economies, where people are particularly vulnerable to hunger and malnutrition. However, due to the recency of the COVID-19 problem, the impacts of macroeconomic fluctuations on food insecurity have remained scantily explored. In this study, the authors attempted to bridge this gap by revealing interactions between the food security status of people and the dynamics of COVID-19 cases, food trade, food inflation, and currency volatilities. The study was performed in the cases of 45 developing economies distributed to three groups by the level of income. The consecutive application of the autoregressive distributed lag method, Yamamoto's causality test, and variance decomposition analysis allowed the authors to find the food insecurity effects of COVID-19 to be more perceptible in upper-middle-income economies than in the least developed countries. In the latter, food security risks attributed to the emergence of the health crisis were mainly related to economic access to adequate food supply (food inflation), whereas in higher-income developing economies, availability-sided food security risks (food trade restrictions and currency depreciation) were more prevalent. The approach presented in this paper contributes to the establishment of a methodology framework that may equip decision-makers with up-to-date estimations of health crisis effects on economic parameters of food availability and access to staples in food-insecure communities.

Input-Based Event-Triggering Consensus of Multiagent Systems Under Denial-of-Service Attacks

Abstract: This paper applies an input-based triggering approach to investigate the secure consensus problem in multiagent systems under denial-of-service (DoS) attacks. The DoS attacks are based on the time-sequence fashion and occur aperiodically in an unknown attack strategy, which can usually damage the control channels executed by an intelligent adversary. A novel event-triggered control scheme on the basis of the relative interagent state is developed under the DoS attacks, by designing a link-based estimator to estimate the relative interagent state between intermitted communication instead of the absolute state. Compared with most of the existing work on the design of the triggering condition related to the state measurement error, the proposed triggering condition is designed based on the control input signal from the view of privacy protection, which can avoid continuous sampling for every agent. Besides, the attack frequency and attack duration of DoS attacks are analyzed and the secure consensus is reachable provided that the attack frequency and attack duration satisfy some certain conditions under the proposed control algorithm. “Zeno phenomenon” does not exhibit by proving that there exist different positive lower bounds corresponding to different link-based triggering conditions. Finally, the effectiveness of the proposed algorithm is verified by a numerical example.

Preparation of a hydrophilic and antibacterial dual function ultrafiltration membrane with quaternized graphene oxide as a modifier

Abstract: In order to improve the anti-biofouling performance of ultrafiltration membrane, quaternized graphene oxide (QGO) was synthesized as a membrane modifier by in-situ growth of quaternary ammonium salt on the graphene oxide surface. A hydrophilic and antibacterial dual functional membrane was prepared with this kind of modifiers by immersion phase inversion method. The modified membrane obviously exhibits enhanced hydrophilicity, antibacterial and mechanical properties than the unmodified Polyvinylidene fluoride (PVDF) membranes. At the same time, it is proved that graphene oxide, as a carrier of quaternary ammonium salt, can significantly reduce the loss of antibacterial substances from the membranes.

Cooperative deformation in high-entropy alloys at ultralow temperatures

Abstract: High-entropy alloys exhibit exceptional mechanical properties at cryogenic temperatures, due to the activation of twinning in addition to dislocation slip. The coexistence of multiple deformation pathways raises an important question regarding how individual deformation mechanisms compete or synergize during plastic deformation. Using in situ neutron diffraction, we demonstrate the interaction of a rich variety of deformation mechanisms in high-entropy alloys at 15 K, which began with dislocation slip, followed by stacking faults and twinning, before transitioning to inhomogeneous deformation by serrations. Quantitative analysis showed that the cooperation of these different deformation mechanisms led to extreme work hardening. The low stacking fault energy plus the stable face-centered cubic structure at ultralow temperatures, enabled by the high-entropy alloying, played a pivotal role bridging dislocation slip and serration. Insights from the in situ experiments point to the role of entropy in the design of structural materials with superior properties.

Fusiform-Like Copper(II)-Based Metal–Organic Framework through Relief Hypoxia and GSH-Depletion Co-Enhanced Starvation and Chemodynamic Synergetic Cancer Therapy

Abstract: The therapeutic effect of traditional chemodynamic therapy (CDT) agents is severely restricted by their weakly acidic pH and glutathione (GSH) overexpression in the tumor microenvironment. Here, fusiform-like copper(II)-based tetrakis(4-carboxy phenyl)porphyrin (TCPP) nanoscale metal-organic frameworks (nMOFs) were designed and constructed for the first time (named PCN-224(Cu)-GOD@MnO2). The coated MnO2 layer can not only avoid conjugation of glucose oxidase (GOD) to damage normal cells but also catalyzes the generation of O2 from H2O2 to enhance the oxidation of glucose (Glu) by GOD, which also provides abundant H2O2 for the subsequent Cu+-based Fenton-like reaction. Meanwhile, the Cu2+ chelated to the TCPP ligand is converted to Cu+ by the excess GSH in the tumor, which reduces the tumor antioxidant activity to improve the CDT effect. Next, the Cu+ reacts with the plentiful H2O2 by enzyme catalysis to produce a toxic hydroxyl radical (•OH), and singlet oxygen (1O2) is synchronously generated from combination with Cu+, O2, and H2O via the Russell mechanism. Furthermore, the nanoplatform can be used for both TCPP-based in vivo fluorescence imaging and Mn2+-induced T1-weighted magnetic resonance imaging. In conclusion, fusiform-like PCN-224(Cu)-GOD@MnO2 nMOFs facilitate the therapeutic efficiency of chemodynamic and starvation therapy via combination with relief hypoxia and GSH depletion after acting as an accurate imaging guide.

Synergy effects on Sn-Cu alloy catalyst for efficient CO2 electroreduction to formate with high mass activity

Abstract: To acquire the synergy effects between Sn and Cu for the jointly high Faradaic efficiency and current density, we develop a novel strategy to design the Sn-Cu alloy catalyst via a decorated co-electrodeposition method for CO2 electroreduction to formate. The Sn-Cu alloy shows high formate Faradaic efficiency of 82.3% ± 2.1% and total C1 products Faradaic efficiency of 90.0% ± 2.7% at −1.14 V vs. reversible hydrogen electrode (RHE). The current density and mass activity of formate reach as high as (79.0 ± 0.4) mA cm−2 and (1490.6 ± 7.5) mA mg−1 at −1.14 V vs. RHE. Theoretical calculations suggest that Sn-Cu alloy can obtain high Faradaic efficiency for CO2 electroreduction by suppressing the competitive hydrogen evolution reaction and that the formate formation follows the path of CO2 → HCOO* → HCOOH. The stepped (2 1 1) surface of Sn-Cu alloy is beneficial towards selective formate production.

An Improved Neural Network Pruning Technology for Automatic Modulation Classification in Edge Devices

Abstract: Automatic modulation classification (AMC) plays an important role in both civilian and military applications. Today, increasingly more researchers apply a deep learning framework in AMC. However, few papers take into account that a typical deep model is difficult to deploy on resource constrained devices. In this paper, we propose a new filter-level pruning technique based on activation maximization (AM) that omits the less important convolutional filter. Compared to other network pruning techniques, the convolutional neural network pruned via the AM method achieves equal or higher classification accuracy in the RadioML2016.10a dataset.

Facile Synthesis of Metal-Organic Framework-Derived CoSe2 Nanoparticles Embedded in the N-Doped Carbon Nanosheet Array and Application for Supercapacitors.

Abstract: Metal-organic framework (MOF)-derived composites of transition metal oxides and porous carbon show great potential for energy storage applications. Selenylation is an effective strategy to improve the electrochemical properties of electrode materials. A facile one-step derivation and selenylation of MOFs is proposed here to obtain CoSe2 nanoparticles embedded into an N-doped carbon skeleton material (CoSe2/NC). Moreover, the composite is directly grown on nickel foam as nanosheet arrays, rather than on other materials as powders. The CoSe2/NC electrode with special construction exhibits a high capacity of 120.2 mA h g-1 at 1 A g-1 and an excellent cyclic ability of 8% loss after 10,000 cycles. An asymmetric supercapacitor CoSe2/NC-NF//AC displays a maximum energy density of 40.9 W h kg-1 at 980 W kg-1. Moreover, the device has demonstrated that it can successfully charge a mobile phone. The outstanding performance indicates promising potential of CoSe2/NC-NF electrodes for supercapacitors.

A heterogeneous interface on NiS@Ni3S2/NiMoO4 heterostructures for efficient urea electrolysis

Abstract: Urea electrolysis is an appealing energy conversion technology to produce hydrogen (H2) and alleviate the problem of urea-rich wastewater treatment concurrently. In particular, electrocatalytic performance can be dramatically enhanced by rationally modulating the surface charge distribution with a well-tuned heterostructure. Herein, a heterostructure is constructed by NiMoO4 nanosheets grown on an interior hollow NiS@Ni3S2 nanorods framework (NiS@Ni3S2/NiMoO4). Density functional theory (DFT) calculations demonstrate that the formed heterojunction structure leads to a tailored surface charge state of NiMoO4, with oxygen as the nucleophilic region and molybdenum as the electrophilic region, which facilitates the decomposition of urea molecules and thus significantly improves hydrogen evolution. As expected, the assembled NiS@Ni3S2/NiMoO4 system substantially expedites urea electrolysis activity with a cell voltage of 1.40 V at 10 mA cm−2, which is 200 mV less than the voltage of an overall water splitting system.

Induction of Planar Sodium Growth on MXene (Ti3C2Tx)-Modified Carbon Cloth Hosts for Flexible Sodium Metal Anodes

Abstract: Sodium (Na) metal batteries have attracted increasing attention and gained rapid development. However, the processing, storing, and application of Na metal anodes are restricted by its inherent stickiness and poor mechanical properties. Herein, an MXene (Ti3C2Tx)-coated carbon cloth (Ti3C2Tx-CC) host is designed and synthesized, which shows a highly metallic conductive and sodiophilic surface. After a thermal infusion treatment, a Na-Ti3C2Tx-CC composite with rigidity and bendability is obtained and employed as a metal anode for Na ion batteries. The Na-Ti3C2Tx-CC electrodes present stable cycling performance and high stripping/plating capacity in both an ether-based (up to 5 mA·h·cm-2) and a carbonate-based (up to 8 mA·h·cm-2) electrolyte. The fundamental protection mechanism of MXene Ti3C2Tx is investigated. Ti3C2Tx efficiently induces Na's initial nucleation and laterally oriented deposition, which effectively avoids the generation of mossy/dendritic Na. The arrangement of Na atoms deposited on the MXene surface inherits the MXene atomic architecture, leading to a smooth "sheet-like" Na surface. Meanwhile, a flexible Na-based Na-Ti3C2Tx-CC∥Na3V2(PO4)3 device is assembled and exhibits capable electrochemical performance.

Event-Based Secure Consensus of Mutiagent Systems Against DoS Attacks

Abstract: This paper studies the problem of event-triggered secure consensus for multiagent systems subject to periodic energy-limited denial-of-service (DoS) attacks, where DoS attacks usually prevent agent-to-agent data transmission. The DoS attacks are assumed to occur periodically based on the time-sequence way and the period of DoS attacks and the uniform lower bound of the communication areas are predetected by some devices. Based on the above assumptions, an event-based protocol consisting of two different measurements corresponding to leader–followers and follower–follower is presented to schedule communications between agents, which can reduce the update frequency of the controller. Then, the stability of the resultant error system is analyzed to derive sufficient conditions of achieving secure consensus by employing the Lyapunov function and the inductive approach. Besides, positive low bounds on any two consecutive intervals of events generated by individual events are calculated to eliminate “Zeno behavior” under the developed triggering condition and event-triggered protocol. Simulation result is provided to verify the theoretical analysis.

Adaptive Fault-Tolerant Prescribed-Time Control for Teleoperation Systems With Position Error Constraints

Abstract: In this article, we present an adaptive prescribed-time control method for a class of nonlinear telerobotic systems with actuator faults and position error constraints. Extended from prescribed-time stability , practically prescribed-time stability (PPTS) is proposed for the first time aiming at stability analysis and control synthesis of nonlinear systems with disturbance and uncertainty. We show that, under the control scheme in the framework of PPTS, the system states are guaranteed to converge to a user-defined set (physically realizable) within user-defined settling time (physically realizable). Based on PPTS, an adaptive fault-tolerant controller is developed by integrating a novel exponential-type barrier Lyapunov function. Rigorous stability analysis based on back-stepping approach proves that, under the proposed control strategy, synchronization errors converge to a user-defined residual-set within predefined settling time and never exceed the prescribed range. Universal performance indexes, including the settling time, residual-set, accuracy, and overshoot, can be user-defined and only dependent on fewer user-defined parameters. Simulation results illustrate the effectiveness of the developed control scheme.

Dynamic Spectrum Interaction of UAV Flight Formation Communication With Priority: A Deep Reinforcement Learning Approach

Abstract: The formation flights of multiple unmanned aerial vehicles (UAV) can improve the success probability of single-machine. Dynamic spectrum interaction solves the problem of the ordered communication of multiple UAVs with limited bandwidth via spectrum interaction between UAVs. By introducing reinforcement learning algorithm, UAVs can continuously obtain the optimal strategy by continuously interacting with the environment. In this paper, two types of UAV formation communication methods are studied. One method allows for information sharing between two UAVs in the same time slot. The other method is the adoption of a dynamic time slot allocation scheme to complete the alternate use of time slots by the UAV to realize information sharing. The quality of experience (QoE) is introduced to evaluate the results of UAV sharing, and the M/G/1 queuing model is used for priority and to evaluate the packet loss of UAV. In terms of algorithms, a combination of deep reinforcement learning (DRL) and the long-short-term memory (LSTM) network is adopted to accelerate the convergence speed of the algorithm. The experimental results show that, compared with the Q-learning and deep Q-network (DQN) methods, the proposed method achieves faster convergence and better performance with respect to the throughput rate.