Shandong Normal University
  • Jinan, Shandong, China
Recent publications
What we concern in this paper is finite-time control of nonlinear impulsive systems involving external disturbance, where practical finite-time and finite-time stabilization are studied with respect to nonvanishing and vanishing disturbance, respectively. A relationship between the finite settling time and the impulsive frequency is presented to show the stabilizing effect of impulses. It is shown that systems subject to nonvanishing disturbance can enter a disturbance-dependent ultimate bound in a finite-time sense, and a relatively smaller bound of settling time is obtained by utilizing stabilizing impulses. Meanwhile, systems subject to vanishing disturbance can achieve finite-time stabilization at the origin. Moreover, compared with the situation without impulses, the corresponding bound of settling time is also smaller. For the sake of illustrating the validity of proposed results, some examples and their simulations are provided.
Automatic seizure detection based on scalp electroencephalogram (EEG) can accelerate the progress of epilepsy diagnosis. Current seizure detection methods based on deep learning usually rely on single convolutional neural network (CNN) or recurrent neural network (RNN) models. In terms of feature extraction, single model often has limitations. Since CNN is good at extracting local features, and Transformer can capture global information, we put forward a seizure detection method based on interactive local and global feature coupling. Local feature and global representation of the EEG are respectively extracted by convolution operation and self-attention mechanism. To make up of the shortcomings of local feature and global representation, a feature coupling block (FCB) is utilized to fuse the two kinds of information in an interactive way. The enhanced feature representation is fed to the classifier for seizure and normal EEG classification. Extensive experiments are conducted on CHB-MIT and Siena scalp EEG datasets. Experimental results demonstrate that the method can effectively perform epileptic seizure detection from the original EEG signals without extra feature extraction.
Edible mushroom polysaccharides, as one of the main biological activities of mushrooms, have anti-tumour, anti-inflammatory, antioxidant, immune regulation and other functions. Especially because of its anti-tumour and immunomodulatory activity, it has been used in the clinical treatment of various diseases. Recent studies have focused on mushroom polysaccharides' functional properties, which may be related to their chemical structures. This review aims to clarify the biological activity of edible mushroom polysaccharides and their medicinal potential in human health and to reveal the relationship between chemical structure and the biological activity of edible mushroom polysaccharides.
This paper studies the input-to-state stability (ISS) and integral input-to-state stability (iISS) of nonlinear impulsive systems in the framework of event-triggered impulsive control (ETIC), where the stabilizing effect of time delays in impulses is fully considered. Some sufficient conditions which can avoid Zeno behavior and guarantee the ISS/iISS property of impulsive systems are proposed, where external inputs are considered in both the continuous dynamics and impulsive dynamics. A novel event-triggered delayed impulsive control (ETDIC) strategy which establishes a relationship among event-triggered parameters, impulse strength and time delays in impulses is presented. It is shown that time delays in impulses can contribute to the stabilization of impulsive systems in ISS/iISS sense. Finally, the effectiveness of the proposed theoretical results is illustrated by two numerical examples.
Pure organic room-temperature phosphorescent (RTP) materials have evoked increasing attention due to their potential application in many fields. However, the preparation of ultralong and color-tunable RTP materials were still facing challenges. Herein, two facile strategies were applied to construct ultralong RTP materials based on non-covalent and covalent linking of sulfanilic acid (SA) on amorphous polyacrylamide (PAM) framework. The hydrogen bonding in PAM/SA and poly(acrylamide-co-4-acrylamidobenzenesulfonic acid) (PAMABS) can effectively help to suppress non-radiative transition, and induce ultralong RTP emission at ambient condition. The RTP emission intensity and lifetime of PAM/SA can be controlled by the molar ratio of acrylamide to SA. Remarkably, PAMABS shows excitation-dependent color-tunable phosphorescence emission. Due to the destructive effect of water on the system rigidity, PAM/SA and PAMABS both exhibit RTP responsiveness to water and heat stimuli. Furthermore, the convenient preparation and excellent properties enable these new organic RTP materials extremely suitable for anti-counterfeiting and information encryption.
Polynucleotide kinase (PNK) involves in various cellular events by regulating phosphorylation processes, and abnormal expression of PNK may induce many human diseases. Herein, we develop a tandem signal amplification strategy for label-free sensing PNK activity in cancer cells. In the presence of PNK, the hairpin probe is phosphorylated to initiate the ligation reaction with the assistance of T4 DNA ligase. Subsequently, a tandem signal amplification can be activated to generate abundant triggers with the ligated sequence as the template and the corresponding 3′-OH end of the 5′- phosphorylated hairpin probe as the primer. Eventually, the addition of SYBR Green II lights up the triggers to produce an enhanced fluorescence signal. Notably, only target PNK can effectively phosphorylate the hairpin probe to initiate the ligation-dependent reaction, endowing this assay with improved specificity. Moreover, the high amplification efficiency of tandem signal amplification endows this assay with enhanced sensitivity. Furthermore, this assay can accurately measure endogenous PNK activity at single-cell level, screen inhibitors, and analyze enzyme kinetic parameters, facilitating PNK-related clinical diagnosis and drug discovery.
Input-to-state stability (ISS) analysis and stabilization are concerned in this paper for switched nonlinear positive systems (SNPS), where the deterministic and random switching are both included. For general SNPS, switched affine nonlinear positive systems (SANPS) and switched linear positive systems (SLPS) with deterministic and some kinds of random ”slow” switching, some criterions on ISS are provided. From the criterions for SANPS and SLPS, the ISS properties can be judged just by the differential, algebraic and switching characteristics of the systems. Further, based on the criterions for SANPS and SLPS, some state feedback controllers are designed such that the closed-loop systems be positive, ISS or ISS in some stochastic senses. Four simulation examples verify the validity of our results.
This paper investigates the problem of event-triggered tracking control for switched networked nonlinear systems with asymmetric time-varying output constraints. To handle the output constraints, an output-dependent generic constraint function is constructed to describe relationship between the output and the performance requirement. Meanwhile, an event-triggering rule is designed to reduce communication frequency between the controller and the actuator, thereby reducing the burden of the network communication. Based on the common Lyapunov function method and event-triggered control strategy, an adaptive control method is designed, which can guarantee that the closed-loop signals are bounded and avoid the Zeno behavior. Different from existing results considering constraints, the proposed scheme not only relaxes the restricted condition of constraint boundaries but also both the cases with and without output constraints can be addressed simultaneously. Furthermore, the stability of the system can be guaranteed by the small-gain technique. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed scheme.
The detection of DNA sequence hybridization has taken on a critical importance for the research of life science, microbiology, and environmental science. In this paper, a D-shaped single mode fiber (SMF) SPR sensor with a composite nanostructure of hyperbolic metamaterials (HMM)/monolayer graphene was developed for DNA detection. The dispersion relation of the Bloch wave in HMM and the energy conversion between modes in plasma resonance were confirmed through calculation and simulation. During the experiment, the metamaterial combined with a monolayer graphene composite structure exhibited the sensitivity and quality factor of 5000 nm/RIU and 40 RIU⁻¹, respectively. The sensor based on the optimal parameters was adopted to detect the hybridization of DNA molecules, and the affinity and reaction rates of DNA molecular hybridization were analyzed based on molecular reaction kinetics. As revealed by the results of this study, the sensor had the advantages of miniaturization, low cost, and specificity detection, which could serve as a novel sensor for DNA hybridization detection from visible light to near infrared region.
A high-performance diode-tandem-pumped actively Q-switched Tm:YAP laser is demonstrated, in which configuration dual Tm:YAP crystals are pumped by two separate diode lasers, respectively. A maximum output power of 10.6 W with corresponding pulse width of 37 ns, pulse energy of 2.12 mJ, and peak power of 57.3 kW is achieved at a pulse repetition rate of 5 kHz. For comparison, an actively Q-switched Tm:YAP laser with a single gain crystal double-end pumped is set up, from which a maximum output power of 6.8 W with a pulse width of 45 ns, a pulse energy of 1.36 mJ and a peak power of 28.3 kW is obtained at the same pulse repetition rate of 5 kHz. The experimental results clearly reveal the effect of diode-tandem-pumping regime on lowering down the thermal load of gain medium.
The development and expansion of the digital economy, including the internet, big data, and cloud computing, provide a new impetus to reaching peak carbon emissions and achieving carbon neutrality. However, the impact and mechanism of the urban digital economy on carbon intensity are still insufficiently characterized. This study confirms a significant inverted U-shaped relationship between them by adding a quadratic term and conducting a U test. When the index of the digital economy exceeds 0.419, it reduces carbon emissions intensity. The empirical results indicate that the digital economy has a nonlinear spatial spillover effect on the carbon emission intensity of adjacent cities presenting a U-shape. The digital economy can not only directly affect carbon emission intensity, but also indirectly affects it by optimizing industrial structure and promoting scientific and technological innovation. The methodology of this paper can be used for future research, and the findings can support the regional development of the digital economy and the formulation of carbon reduction policies.
Molybdenum dioxide nanosheets (MoO2-NSs), as two-dimensional (2D) materials, have attracted broad attention owing to their high damage threshold, good stability, strong localized surface plasmon resonance (LSPR), affordability, and excellent physicochemical properties. In this work, we successfully synthesized high-quality MoO2-NSs through chemical vapor deposition synthesis method and characterized the morphology and structure of the prepared materials in detail. The saturable absorption characteristics of the MoO2-NSs were measured using Z-scan experiments for the first time. Additionally, the compact Q-switched laser and stable mode-locked laser were successfully realized based on a MoO2-NSs saturable absorber (SA). To the best of our knowledge, this is the first presentation of the application of MoO2-NSs SA in the field of ultrafast photonics. These findings indicate that high-quality MoO2-NSs can be an effective optical modulator for generating high-repetition-rate pulsed lasers, and exhibit promising potential applications in mode-locked ultrafast lasers.
In order to find a coordinated approach to support tourism recovery following the impacts of COVID-19, this research examines the experiences of mainland China, the first country whose domestic tourism recovered in the first stage (the first year after the pandemic outbreak). Through the content analysis of tourism policy documents at national, provincial, and city levels, we generated the features of the policy responses from the supply and demand sides, and the policy trends before and after the first peak of the recovery. Next, we summarized the three steps which make up the first stage, and describe the effective policy focus for each step. This process-oriented policy analysis can guide other countries in how to cope with tourism recovery during the first stage.
Early detection and identification of malignant lung nodules improve the survival of lung cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung nodules play an important role in the diagnosis of malignancy. However, the gap between attributes and computation features is the main factor that restricts the performance of computer-aided diagnosis (CAD). Therefore, we propose a Fuse-Long Short-Term Memory-Convolutional Neural Network (F-LSTM-CNN) ensemble learning algorithm which incorporates visual attributes and deep features to classify benign and malignant nodules. First, the attribute features are obtained from clinical information while the deep features of nodules are extracted from the preprocessed computed tomography (CT) images. Second, the Fuse-Convolutional Neural Network (F-CNN) model is proposed for highlighting the essential role of attributes in the classification processing which integrates deep features and attribute features mapped through the transposed convolution. Meanwhile, the Fuse-Long Short-Term Memory (F-LSTM) model is proposed to focus on the specific deep features for classification via the affine transformation of attribute features. Finally, early identification of malignant lung nodules is conducted by fusing the prediction scores of the F-LSTM and F-CNN models. The experiments were conducted on the public lung nodule dataset (LIDC-IDRI) and achieved accuracy, sensitivity, and specificity of 0.955, 1, and 0.937 with an Area under the ROC Curve (AUC) of 0.995 for lung nodule classification. The experiment results show that the proposed F-LSTM-CNN ensemble learning model facilitates the interpretation of diagnostic data and helps radiologists to make decisions in clinical practice.
We demonstrate the construction of a dual-mode biosensor based on fully-π conjugated covalent organic framework (COF) and cobalt oxyhydroxide (CoOOH) nanoflakes for electrochemiluminescent (ECL) and electrochemical sensing of alkaline phosphatase (ALP). The fully-π conjugated COF with sp² carbon-linkage is synthesized through Knoevenagel polycondensation of 2, 5-dimethoxy-terephthalaldehyde (DMTA) and 1,3,5-tris(4-cynomethylphenyl)benzene (TCPB), and it acts as an efficient ECL emitter whose signal is 41 and 125-fold higher than those of TCPB and DMTA. The ECL signal of TCPB-DMTA-COF may be quenched by CoOOH nanoflakes through electrochemiluminescent resonance energy transfer, and meanwhile CoOOH promotes the oxidation of o-phenylenediamine (o-PD) to generate a high differential pulse voltammetry (DPV) signal. When ALP is present, it hydrolyzes L-ascorbic acid-2-phosphate (AAP) to produce L-ascorbic acid (AA). AA can reduce CoOOH to Co²⁺, resulting in the decomposition of the CoOOH nanoflakes and consequently the recovery of ECL signal and the decrease of DPV peak current. This dual-mode biosensor can efficiently eliminate the errors associated with personnel operation and experimental factors, leading to more reliability and accuracy than single-mode biosensor. Moreover, this dual-mode biosensor can be applied for specifically sensing ALP in human serums and screening the inhibitors, with potential applications in biomedical researches.
Knowledge base question answering aims to answer a question over a knowledge base. Multi-hop knowledge base question answering is a challenging task because it requires multi-step reasoning according to the question to get the answer. Existing models infer the answer over a static subgraph or attend to different parts of the question through an intermediate signal. The former obtains limited semantic information, and the latter provides limited reasoning due to the weak supervision signal. In this paper, we eliminate the limitation of static subgraph reasoning by dynamically expanding subgraphs, which connect the question and subgraph to form a joint subgraph. We then adjust the dynamic subgraph to enable reasoning at each step. Specifically, at each step, the question connects different subgraphs, respects the context while paying attention to a specific part of the question, generates a strong intermediate signal, acts on the subsequent reasoning, and finally obtains a correct answer. A large number of experiments on three datasets show that our method performs better than previous state-of-the-art models.
With high nonlinear effect and low band gap value, ZrS2 is a promising material in photovoltaic application. In our work, a ZrS2-polyvinyl alcohol thin film modulator was successfully prepared by liquid phase exfoliation. The modulation depth of ZrS2 saturable absorber is 6.3 % and its saturation intensity is 3.92 MW/cm². Large energy mode-locked phenomenon was obtained in the Er-doped fiber laser with ZrS2 as an optical modulator. When the pump power was 1250 mW, the center wavelength, pulse repetition rate, and maximum pulse energy of the large energy mode-locked were 1531 nm, 604.23 kHz, and 23.65 nJ, respectively. This experiment proves that ZrS2 has excellent nonlinear absorption performance, also provides a reference for the future research of large energy mode-locked based on transition metal dihalogenateds.
Oxidation is an inevitable process for γ-graphyne (γ-GY), a two-dimensional (2D) material of carbon, both in its natural state and during large-scale processing. Understanding the oxidation states within γ-GY is of fundamental importance for further applications. In this work, with density functional theory (DFT) simulations of seven representative oxygen-doped γ-GY structures, we demonstrate that the X-ray photoelectron (XPS) and near-edge X-ray absorption fine-structure (NEXAFS) spectra at the oxygen and carbon K-edges are sensitive for different local structures of oxygen dopants. The theoretical calculation results of γ-GY and seven oxygen-doped γ-GY configurations fit well with the experiment, and all characteristic experimental XPS peaks are assigned. We found that the C 1s ionization potential (IP) of sp²-hybridized carbons is higher than that of sp-hybridized carbons for the pristine γ-GY. By complete and elaborate analysis of the NEXAFS spectrum of each structure at the carbon and oxygen K edges, the seven oxygen-doped γ-GY configurations have been successfully identified. The results can be considered as a benchmark for the determination of oxygen-doped γ-GY configurations, and provide a deep insight into the structure–spectroscopy relationships.
CONTEXT Wheat-maize (W-M) double cropping is the dominant land use system in the North China Plain (NCP). This system has high grain output but suffers from high fertilizer input and nitrogen (N) surplus. Meanwhile, the market demands more protein and oil crops, such as soybean or peanut. OBJECTIVE Here, we assess whether incorporation of legumes into W-M via intercropping with maize can contribute to lower annual N input while maintaining high annual outputs and diversifying products with high yield stability. METHODS We compared yield, yield stability, and profitability of six rotation systems: W-M30 (at the maize inter-plant distance of 30 cm), the density-increased W-M20, wheat-soybean (W-S), wheat-peanut (W-P), and wheat with an intercrop of maize (at the inter-plant distance of 20 cm) and soybean (W-MS) or peanut (W-MP). Four annual N input levels were compared: N0 (no N input), N1 (reduced N input), N2 (target practice), and N3 (current high input). RESULTS AND CONCLUSIONS Results over four years showed that replacing maize by maize/legume intercrops had a similar wheat yield as that of W-M while the N input was intermediate between W-M and W-legume rotations. Total actual/equivalent grain yields and gross margins of W-MS or W-MP were consistently intermediate between W-M and W-legume rotations. Intercropping enhanced the yield and temporal yield stability of maize per plant, with benefits for both yield stability of the intercropping system of maize season and the annual rotation system. Averaged over six rotation systems, increasing N supply increased the annual total actual/equivalent grain yield, gross margin and yield stability to a plateau starting at N1 or N2, without a further significant increase at N3. Specifically, the response of total equivalent yield or gross margin of each annual system to increasing N supply could be fitted by the linear-plateau model. Compared to the response curve of W-M, W-MS and W-S reached the plateau with a lower N input and higher yield and profit, while W-MP and W-P reached the plateau with lower N input but decreased the yield and profit. Compared to W-M with 240–360 kg N/ha/year, W-MS used 210–320 kg N/ha/year saving 11.1–12.5% fertilizer N, while maintaining or improving production by 9.1–13.0%, and improving profitability by 12.1–15.6% and temporal yield stability by 12.8–50.6%. SIGNIFICANCE W-MS diversifies products with lower N input and higher outputs, profitability, and temporal yield stability than conventional W-M, thus is highly recommended towards productive and sustainable agriculture in the NCP.
Wetland conversion to cropland substantially reduces methane (CH 4) emission, turning a source into a sink on many occasions; how various microbial processes contribute to this source-to-sink transition remains elusive. We addressed this issue by examining the net CH 4 flux, CH 4 production potential, CH 4 oxidation potential, and functional genes associated with methanogenesis and methanotrophy in a pristine wetland and a 23-year cultivated cropland in the Sanjiang Plain, China. The study confirmed that wetland conversion to cropland turned a CH 4 source of 44.93 ± 10.17 g CH 4 ⋅m − 2 ⋅yr − 1 to a small CH 4 sink of − 0.056 ± 0.051 g⋅CH 4 m − 2 ⋅yr − 1. The proportion of total CH 4-related genes, methanogenesis genes, as well as the CH 4 production marker genes-mcr were significantly decreased by 24.14 %, 32.10 %, and 97.89 %, respectively in cropland. The proportions of methanotrophic marker genes, pMMO, and the sum of sMMO and pMMO were significantly increased by 48.74 % and 22.79 % after wetland cultivation. The 23-year cultivation yielded suppressing impacts on methanogenesis and mcr genes throughout the four seasons while stimulating effects on the functional genes of sMMO, pMMO, and MMO in spring and summer. The proportions of CH 4-related genes decreased along soil depth in wetland and cropland, while pMMO and MMO slightly increased in the depth of 20-60 cm in cropland. A global synthesis supported this microbial mechanism for the CH 4 source-to-sink transition, indicating the strong methanogenesis suppression and slight methanotrophy enhancement in explaining the source-to-sink transition after wetland conversion to cropland. This mechanism should be incorporated into CH 4 models to predict CH 4 dynamics under land-use change.
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Yu-Zhi Song
  • School of Physics and Electronics
Ma Yinghong
  • School of Management and Engineering
Zhanghua Han
  • School of Physics and Electronics
Yangjian Cai
  • School of Physics and Electronics
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Qingliang Zeng
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