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Abstract In the realm of photovoltaics, organometallic hybridized perovskite solar cells (PSCs) stand out as promising contenders for achieving high‐efficiency photoelectric conversion, owing to their remarkable performance attributes. Nevertheless, defects within the perovskite layer, especially at the perovskite grain boundaries and surface, have a substantial impact on both the overall photoelectric performance and long‐term operational stability of PSCs. To mitigate this challenge, we propose a method for water‐induced condensation polymerization of small molecules involving the incorporation of 1,3‐phenylene diisocyanate (1,3‐PDI) into the perovskite film using an antisolvent technique. Subsequent to this step, the introduction of water triggers the polymerization of [P(1,3‐PDI)], thereby facilitating the in situ passivation of uncoordinated lead defects inherent in the perovskite film. This passivation process demonstrates a notable enhancement in both the efficiency and stability of PSCs. This approach has led to the attainment of a noteworthy power conversion efficiency (PCE) of 24.66% in inverted PSCs. Furthermore, based on the P(1,3‐PDI) modification, these devices maintain 90.15% of their initial efficiency after 5000 h of storage under ambient conditions of 25°C and 50 ± 5% relative humidity. Additionally, even after maximum power point tracking for 1000 h, the PSCs modified with P(1,3‐PDI) sustain 82.05% of the initial PCE. Small molecules can rationally manipulate water and turn harm into benefit, providing new directions and methods for improving the efficiency and stability of PSCs.

Abstract A compact Archimedean spiral antenna with high gain for electrostatic discharge (ESD) detection is investigated. A frustum‐shaped cavity proposed in this work is formed to optimise the maximum antenna gain. Additionally, a helix arm is loaded to enhance antenna gain in lower band. The measured results demonstrate that the proposed antenna, which employs a unidirectional radiation mode, exhibits a maximum antenna gain ranging from −0.74 dBi to 9.46 dBi and a voltage standing wave ratio less than 3 across a frequency range of 0.65–5 GHz. A test system consisted of proposed antenna and a commercial ESD detection antenna is established. The verified results indicate that the proposed antenna has a performance close to the commercial antenna, so that proposed antenna with compact size is preferred to be utilised for ESD detection.

Abstract Forest plantations most likely promote exotic plant invasion. Using an in situ monitoring method, this study investigated the traits correlated with growth and reproduction of an understory invader, Phytolacca americana L., and ecological factors including understory irradiance, soil stoichiometry and microbial patterns associated with these traits in different exotic plantations of Robinia pseudoacacia L. and Pinus thunbergii Parl. at Mount Lao, Qingdao, China. We found that the traits of P. americana underneath the R. pseudoacacia stand might be situated at the fast side of the trait economic spectrum. The R. pseudoacacia stand appeared to “nurse” P. americana. Furthermore, we intended to explain the nurse effects of R. pseudoacacia stands by examining their ecological factors. First, the R. pseudoacacia stand created understory light attenuation, which matched the sciophilous feature of P. americana. Second, the soil beneath the R. pseudoacacia stand might benefit P. americana more since the soil has greater resource availability. Third, a higher microbial diversity was found in the soil derived from P. americana underneath the R. pseudoacacia stand. A greater abundance of plant pathogens was detected in the soil derived from P. americana in the R. pseudoacacia stand, while more abundant mycorrhizal fungi were detected in the P. thunbergii stand. We speculate that plant pathogens can defend P. americana from aggression from other understory competitors. The mycorrhizal fungi in the P. thunbergii stand might benefit P. americana while simultaneously benefiting other understory plants. Intensive competition from other plants might interfere with P. americana. The potential relationships between plant performance and ecological factors may explain the invasion mechanism of P. americana. The present study provides a novel insight on the facilitative effects of exotic tree plantation on an exotic herb through the modification of soil biota, with implications for the biocontrol of invasive species and forest management and conservation.

Abstract Fast screening strategies that enable high‐throughput evaluation and identification of desired variants from diversified enzyme libraries are crucial to tailoring biocatalysts for the synthesis of D‐allulose, which is currently limited by the poor catalytic performance of ketose 3‐epimerases (KEases). Here, the study designs a minimally equipment‐dependent, high‐throughput, and growth‐coupled in vivo screening platform founded on a redesigned D‐allulose‐dependent biosensor system. The genetic elements modulating regulator PsiR expression levels undergo systematic optimization to improve the growth‐responsive dynamic range of the biosensor, which presents ≈30‐fold facilitated growth optical density with a high signal‐to‐noise ratio (1.52 to 0.05) toward D‐allulose concentrations from 0 to 100 mm. Structural analysis and evolutionary conservation analysis of Agrobacterium sp. SUL3 D‐allulose 3‐epimerase (ADAE) reveal a highly conserved catalytic active site and variable hydrophobic pocket, which together regulate substrate recognition. Structure‐guided rational design and directed evolution are implemented using the growth‐coupled in vivo screening platform to reprogram ADAE, in which a mutant M42 (P38N/V102A/Y201L/S207N/I251R) is identified with a 6.28‐fold enhancement of catalytic activity and significantly improved thermostability with a 2.5‐fold increase of the half‐life at 60 °C. The research demonstrates that biosensor‐assisted growth‐coupled evolutionary pressure combined with structure‐guided rational design provides a universal route for engineering KEases.

Abstract Non‐sidelooking airborne radar encounters significant non‐stationary and heterogeneous clutter environments, resulting in a severe shortage of samples. Sparse recovery‐based space‐time adaptive processing (SR‐STAP) methods can achieve good clutter suppression performance with limited samples. Nonetheless, grid‐based SR‐STAP algorithms encounter off‐grid effects in non‐sidelooking arrays, which can severely degrade the clutter suppression performance. In this study, the authors propose a novel gridless SR‐STAP method in the continuous spatial‐temporal domain to address the issue of off‐grid effects. Inspired by the fact that sparse Bayesian learning (SBL) framework implicitly performs a structured covariance matrix estimation, the authors reparameterise its cost function to directly estimate the block‐Toeplitz structured matrix from the measurements in a gridless manner. Since the proposed cost function is non‐convex, we utilise a majorisation‐minimisation‐based iterative procedure to estimate the clutter covariance matrix. Finally, using the standard concept of semidefinite programming, the authors derive a convex gridless implementation of the SBL cost function for uniformly sampled radar systems. Extensive simulation experiments demonstrate the exceptional clutter suppression and target detection performance of the proposed algorithm.

BASP1 is a membrane‐bound protein that plays a promotional or inhibitory role in a variety of tumors; however, its role in gastric cancer (GC) and in the immune microenvironment has not been reported. The objectives of this study were to determine whether BASP1 is a valuable prognostic marker for GC and to explore its role in the immune microenvironment of GC. The expression level of BASP1 in GC was analyzed based on the TCGA dataset and further verified using GSE54129 and GSE161533 datasets, immunohistochemistry, and western blotting. The association between BASP1 and clinicopathological characteristics, as well as its predictive value, were examined using the STAD dataset. Cox regression analysis was performed to determine whether BASP1 can be used as an independent prognostic indicator for GC, and a nomogram was constructed to predict OS. The association between BASP1 and immune cell infiltration, immune checkpoints, and immune cell markers was confirmed by enrichment analysis, as well as analysis based on the TIMER and GEPIA databases. BASP1 was observed to be highly expressed in GC and was associated with a poor prognosis. The expression of BASP1 was positively correlated with the expression of immune checkpoints and immune cell markers, as well as immune cell infiltration. Thus, BASP1 may serve as a standalone prognostic indicator for GC. BASP1 is highly correlated with immune processes, and its expression is positively correlated with the degree of immune cell infiltration, immune checkpoints, and immune cell markers.

Abstract Aim Evaluate the fully online flipped classroom's effects during the pandemic. Design A comparative descriptive study with historical control design. Methods In an internal medicine nursing course, the fully online flipped classroom instruction was used with 53 undergraduates in 2020. Their final examinations were compared with the 50 students taught with traditional offline methods in 2019. Online interactions and students' experiences were described. Pass rates in both classes were over 90% (Χ2 = 0.276, p = 0.60), but the median score in 2019 was higher than in 2020 (Z = −2.491, p = 0.01). There were 996 online interactions and 734 valid interactions in total. All 49 students believed the online flipped classroom schedule was reasonable and all but three said it was helpful. However, 19 students (39%) felt traditional teaching is more effective. Conclusions The fully online flipped classroom method was fairly effective during the pandemic. This model also did increase class participation and sufficient faculty–student interactions in remote education. However, fewer students earned outstanding scores, with possible reasons including the online flipped classroom, lack of clinical practice, stress from COVID‐19 and the shortened exam time. Overall, the method is worth recommending under public health emergencies like COVID‐19, and future research exploring potential concerns about scores is necessary.

Abstract Space‐time adaptive processing (STAP) struggles to effectively suppress clutter in the heterogeneous clutter environment due to the lack of training samples. In order to enhance clutter suppression performance of STAP, a subspace‐weighted mixed‐norm minimisation approach is given. First, a roughly estimated clutter subspace is obtained using the subspace augment (SA) approach. The weight vector is then designed using the association between the dictionary matrix and the noise subspace, allowing the algorithm to penalise sparse coefficients democratically. Finally, in order to solve the subspace‐weighted mixed‐norm minimisation problem, we derive a fast algorithm based on the alternating direction multiplier method (ADMM) framework. The proposed algorithm does not require iteratively updating the weight vector in contrast to the iterative re‐weighted l1 ${l}_{1}$ (IRL1) algorithm. The simulation results demonstrate the effectiveness of the proposed algorithm in terms of computational efficiency and clutter suppression performance.

Abstract The access of large‐scale renewable energy and power electronic equipment to the power grid makes the power source and short‐circuit paths possess time‐varying characteristics when faults occur, which has a serious impact on the traditional protection based on power frequency components. Besides, higher requirements are needed for relay protection in the power grid. The transient fault current contains a large amount of fault information. First, the bus capacitance has a strong reflection effect on the high frequency signal, and there are obvious differences in the high frequency component of the fault current of internal and external faults. Next, a transient quantity algorithm based on sequential overlapping derivative transform is introduced. The algorithm can effectively suppress the low frequency component and enhance the high frequency component in the current, which simply and effectively highlights the difference between the transient current of internal and external faults. Finally, through the ratio of high frequency energy of each outgoing line, the fault direction can be accurately determined, and the transient directional pilot protection can be formed. The accuracy of the protection scheme is verified by a large number of simulation experiments.

Abstract Space‐time adaptive processing with finite samples is supposed to be a crucial technique for airborne radar systems. Inspired by the application of Gaussian prior in sparse Bayesian learning algorithm and the adaptive least absolute shrinkage and selection operator algorithm, a hierarchical Bayesian framework with adaptive Laplace priors is proposed. In this paper, a novel method is applied to avoid the high‐dimension matrix inverse operation in the proposed algorithm. Moreover, in order to apply the method in the complex‐valued domain, the complex‐valued signal is split into two independent variables. Then, the sparse recovery problem in the complex‐valued domain can be transformed into the real‐value domain. Simulation experiments show that the proposed algorithm can achieve great clutter suppression performance and also ensure high computational efficiency.

Abstract Sparse recovery algorithms have been applied to the Space‐time adaptive processing for reducing the requirement of samples over the past 15 years. However, many Sparse recovery algorithms are not robust and need accurate user parameters. Conventional sparse Bayesian learning (SBL) algorithms are insensitivity to user parameters but converge slowly. To remedy the limitation, two iterative reweighted algorithms are proposed based on SBL. In order to minimise the SBL penalty function, we construct its upper‐bounding surrogate function via the concave conjugate function and apply iterative reweighted algorithms to minimise the surrogate function. Theoretical analysis and numerical experiments all exhibit great performance of the proposed algorithms.

The rural infrastructures require inclusiveness in the whole lifecycle (WLC) for the benefits of the society. The theory of inclusive growth has been widely studied since its introduction in the infrastructure system research. However, the majority of the related studies has focused on macro level measurements and no systematic research has been carried out on the microlevel for inclusiveness formation and impact path discovery so that detailed recommendations regarding the process can be formulated. The WLC of infrastructure is a dynamic process, reflected in different stages with various activities and multiple factor groups that connect and influence each other. To address and analyze this dynamic and interdependent process from a micro perspective, this study applies the logical framework method in constructing nine impact paths of rural infrastructure inclusiveness for the WLC, which revealed the influence mechanism of rural infrastructure inclusiveness at the microlevel. According to the results, “project quality” has the most significant influence on the rural infrastructure inclusiveness.

The reservoir of Chang 7 Member of Yanchang Formation in the Ordos Basin is rich in tight oil resources, with well-developed micro-nanopore throats, strong heterogeneity, and complex fluid distribution characteristics. In this paper, a combination of nuclear magnetic resonance and centrifugation experiments is carried out to qualitatively and quantitatively analyze and evaluate the distribution characteristics of the movable fluid in Chang 7 reservoirs in Baibao Block. With different centrifugal forces, the NMR T2 spectrum characteristics of saturated water state and different centrifugal force state can be obtained, and the movable fluid distribution characteristics under the control of different centrifugal forces and different pore throat intervals can be obtained. The research results demonstrate that the NMR T2 spectrum of the Chang 7 tight oil reservoir in the study area presents a double-peak or triple-peak shape. With the increase of centrifugal force, the water saturation value of the corresponding sample gradually decreases. The overall movable fluid saturation ranged from 19.07% to 32.52%, with an average of 26.23% and a low degree of movability. The submicron (0.1~1 μm) and nanoscale (0.075~0.1 μm) pore throats were the main pore throat intervals controlling the movable fluid saturation of the studied samples, accounting for an average of 18.31% and 5.57%, respectively, and micron-scale pore throats (r>1 μm) accounted for an average of 2.35% of the movable fluid distribution.

Abstract To improve the space‐time adaptive processing (STAP) performance of airborne radar in complex environment, a generalised eigenvalue reweighting covariance matrix estimation algorithm called GERCM is proposed here. First, the interference plus noise (IPN) covariance matrix of cell under test (CUT) data is estimated by the selected target‐free training samples around the CUT with the sample covariance matrix method. Then, with the component decompositions of the selected training samples and the assumption of approximately equal subspace, the IPN covariance matrix of CUT data is reformulated by the eigenvector matrix, eigenvalue matrix, and the eigenvalue reweighting vector. Subsequently, based on the modified covariance matching estimation criterion, the eigenvalue reweighting vector is estimated by solving the redesigned convex optimisation problem with the Lagrange dual method. Finally, the STAP weight vector is calculated to process the CUT data. The proposed algorithm can obtain a relatively accurate IPN covariance matrix of CUT data by sufficiently utilising the non‐homogeneous training samples and can effectively protect the moving targets in CUT data, which can be applied to airborne radar with arbitrary array structure and antenna configuration. Simulation results and performance analyses based on the multi‐channel airborne radar measurement data demonstrate the effectiveness of the proposed GERCM algorithm.

Abstract Sparse recovery (SR) based space‐time adaptive processing (STAP) methods have received much attention recently due to their dramatically reduced requirements of training samples. However, most of the existing SR‐STAP algorithms suffer from the off‐grid effect induced by the discretisation of angle‐Doppler plane. To eliminate this effect and improve the performance of clutter suppression, a novel gridless mixed‐norm minimisation (MNM) based STAP algorithm is proposed. Unlike previous grid‐based SR‐STAP methods, the clutter covariance matrix (CCM) is estimated in continuous domain by solving a semidefinite programme (SDP), which is established by utilising the properties of the CCM and the compact formulation of MNM. Furthermore, to reduce the computational burden of solving this SDP, a fast iterative algorithm via the framework of the alternating direction method of multipliers (ADMM) is also derived, where the unknown parameters are iteratively updated with closed‐form expressions. Simulation results show that our proposed algorithm achieves better performance of clutter suppression and target detection with lower computational complexity.

Abstract This paper focuses on finite‐time synchronization and parameters identification in the Markovian switching complex delayed network with multiple weights. Considering the control cost required for network synchronization, finite‐time control technique and pinning control strategy are adopted. Based on these methods, when finite‐time synchronization of the network is achieved, the unknown parameters of the system can also be identified in finite time. In addition, in order to solve the problem of the network performance change caused by network topology switching, an Optimal Nodes Selection Control Strategy (ONSCS) is proposed. On the one hand, finite‐time synchronization and identification of the network can be realized faster, on the other hand, it also further reduces the energy consumption and control cost of the network. Finally, two sets of comparative numerical simulations are given to prove the superiority and applicability of the proposed ONSCS.

Abstract Due to the complexity of real environments, it is hard to detect toxic and harmful gases by sensors. To address such an issue, an artificial olfactory system is promoted, emulating the function of the human nose by means of gas sensors and an inference system. In this work, an artificial olfactory inference system based on memristive devices is developed to classify four gases (ethanol, methane, ethylene, and carbon monoxide) with 10 different concentrations. First, the spike trains converted from signals of the sensor array are inputted to a reservoir computing (RC) system based on volatile memristive devices, which extracts spatiotemporal features; then the features are processed by a classifier based on nonvolatile memristive devices; the output of the classifier indicates the classification result. Moreover, to reduce the device number and the power consumption, three strategies are applied to reduce the extracted features from the RC system. Eventually, the olfactory inference system successfully identifies the gases with a high accuracy of 95%.

Background Insulin receptor substrate‐1 (IRS‐1) rs956115 is associated with vascular risk in patients with coronary artery disease and concomitant diabetes. CYP2C19*2 (rs4244285) modulates clopidogrel response and predicts the outcome of coronary artery disease. This study was designed to explore the association between IRS‐1, CYP2C19*2 genotypes, platelet reactivity, and 1‐year outcome in patients with coronary artery disease undergoing percutaneous coronary intervention. Methods and Results Genotyping was performed using an improved multiplex ligation detection reaction technique. Platelet aggregation was assessed by light transmission aggregometry. Major adverse cardiovascular events were defined as a composite of cardiovascular death, myocardial infarction, and ischemic stroke. A total of 2213 consecutive patients were screened and 1614 were recruited. At 1 month, patients with IRS‐1 CG genotype had significantly lower levels of ADP‐induced platelet aggregation compared with patients with CC homozygotes. Patients with IRS‐1 CG or GG genotype had a 2.09‐fold higher risk of major adverse cardiovascular events compared with those with CC homozygotes (95% CI, 1.04–4.19; P=0.0376). By comparison, patients with CYP2C19*2 GA or AA genotype had higher ADP‐induced platelet aggregation compared with patients with GG homozygotes. Although there was no significant difference in risk of major adverse cardiovascular events between patients with GA/AA and GG genotypes, patients with GA genotype had a 2.19‐fold higher risk than those with GG homozygotes (95% CI, 1.13–4.24; P=0.0200). No interaction between IRS‐1 and CYP2C19*2 genotypes was observed. Conclusions In patients following percutaneous coronary intervention, IRS‐1 GG/CG and CYP2C19*2 GA genotypes were associated with 2.09‐ and 2.19‐fold increased cardiovascular risk, respectively, at 1‐year follow‐up. The association between IRS‐1 genotypes and major adverse cardiovascular events appeared to be independent of known clinical predictors. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01968499.

The advent of the intelligent society leads to the exponential growth of information, imposing urgent requirements in a time‐ and energy‐efficient way to process information where data are generated. This issue can be addressed by the neuromorphic paradigm of computing inspired by biological sensory systems that build up the association between external stimuli and the response of an organism in real‐time; in the paradigm, a neuromorphic system is integrated with sensors to form an artificial sensory system. Herein, a neuromorphic sensory system with integrated capabilities of gas sensing, data storage, and processing is demonstrated. Leaky integrate‐and‐fire (LIF) neurons, the basic computing units in the system, are realized with volatile memristive device Pt/Ag/TaOx/Pt; sensory neurons, i.e., the LIF neurons connected with an array of gas sensors, detect gases and convert the chemical information of gases into neural spikes; synapses based on nonvolatile memristive device Pt/Ta/TaOx/Pt transmit the signals from sensory neurons to relay neurons according to synaptic weights, which are trained by the supervised spike‐rate dependent plasticity; relay neurons then process the signals from the synapses and classify gases. The approach of this work can also be applied to emulate other biological perceptions through the integration with different sensors.

Abstract Water‐responsive (WR) materials that reversibly deform in response to humidity changes show great potential for developing muscle‐like actuators for miniature and biomimetic robotics. Here, it is presented that Bacillus (B.) subtilis’ peptidoglycan (PG) exhibits WR actuation energy and power densities reaching 72.6 MJ m−3 and 9.1 MW m−3, respectively, orders of magnitude higher than those of frequently used actuators, such as piezoelectric actuators and dielectric elastomers. PG can deform as much as 27.2% within 110 ms, and its actuation pressure reaches ≈354.6 MPa. Surprisingly, PG exhibits an energy conversion efficiency of ≈66.8%, which can be attributed to its super‐viscous nanoconfined water that efficiently translates the movement of water molecules to PG's mechanical deformation. Using PG, WR composites that can be integrated into a range of engineering structures are developed, including a robotic gripper and linear actuators, which illustrate the possibilities of using PG as building blocks for high‐efficiency WR actuators.

Abstract To improve the clutter suppression performance of airborne radar in heterogeneous environment, a robust refined training sample reweighting space–time adaptive processing (STAP) method called RRSRW is proposed here. First, some target‐free training samples around the cell under test (CUT) are selected and the corresponding clutter dictionary matrices are constructed using the radar system parameters. Then, the clutter patch amplitudes and array error for selected training samples are simultaneously estimated through the formulated constrained least squares problem. Subsequently, based on the covariance matching estimation criterion, the local weighting coefficients for selected training samples are estimated by the redesigned convex optimisation problem. Finally, the STAP weight vector is calculated to process the CUT data. The proposed method is robust to array error and can effectively protect the moving targets in CUT data, which is free of hyper‐parameters and has global convergence properties. Simulation results demonstrate that the proposed RRSRW method can effectively suppress the strong ground clutter and greatly improve the detection performance of moving targets in heterogeneous environment.

Abstract The cold plate cooling system has become one of the most practical and promising Li‐ion battery thermal management systems for electric vehicles. The existing cold plate has complex structure with high production cost, and the energy consumption is relatively high. In this paper, a detailed optimization study of cavity cold plate is carried out. The heat generation data of the pouch Li‐ion batteries were obtained through experiments, and the data were applied to the finite element method simulation of the cavity cold plate thermal management system. The effects of cavity cold plate thickness (d1), cold plate inlet and outlet width (d2), and inlet coolant mass flow rate on battery temperature and cold plate pressure drop were discussed. The results showed that the optimization allowed the cavity cold plate to control the battery maximum temperature within 40°C and temperature difference within 5°C. Under the same volume of cold plates, the average pressure drop reduction rates of models where Δd (the difference between d1 and d2) is 1 mm are 65% higher than that of the models where d2 is 1 mm. This study has practical significance for improving the design efficiency of cavity cold plate.

Infections caused by antibiotic-resistant bacteria are a major public health threat. The emergence and spread of antibiotic resistance genes (ARGs) in the environment or clinical setting pose a serious threat to human and animal health worldwide. Horizontal gene transfer (HGT) of ARGs is one of the main reasons for the dissemination of antibiotic resistance in vitro and in vivo environments. There is a consensus on the role of mobile genetic elements (MGEs) in the spread of bacterial resistance. Most drug resistance genes are located on plasmids, and the spread of drug resistance genes among microorganisms through plasmid-mediated conjugation transfer is the most common and effective way for the spread of multidrug resistance. Experimental studies of the processes driving the spread of antibiotic resistance have focused on simple in vitro model systems, but the current in vitro protocols might not correctly reflect the HGT of antibiotic resistance genes in realistic conditions. This calls for better models of how resistance genes transfer and disseminate in vivo. The in vivo model can better mimic the situation that occurs in patients, helping study the situation in more detail. This is crucial to develop innovative strategies to curtail the spread of antibiotic resistance genes in the future. This review aims to give an overview of the mechanisms of the spread of antibiotic resistance genes and then demonstrate the spread of antibiotic resistance genes in the in vivo model. Finally, we discuss the challenges in controlling the spread of antibiotic resistance genes and their potential solutions.

This paper proposed a new radar echo simulation method for ultra-low altitude targets in far-field conditions. Based on the electromagnetic (EM) scattering calculation of target and environment, combined with the weighted four-path model, the scattering data of target, environment, and multipath are obtained. The Range-Doppler ring partitioning method is used to determine the size of the minimum resolution units, and then the environment is divided into several scattering elements. By using the method of temporal decomposition, the wide-time pulse is decomposed into a plurality of narrow pulse signals, and the narrow pulses act on scattering elements with different distances and orientations in space. The total echo is obtained by a linear superposition of the responses of each scattering unit. In addition, the numerical results with different parameters, including signal bandwidths, target types, and target height, are simulated and analysed. The simulation results demonstrate that the proposed method can provide a better description of the scattering characteristics of sea-skimming targets in complex scenes in far-field conditions. Meanwhile, it can be applied to the detection and recognition of ultra-low altitude targets above the sea surface.

The problem of generalizing the power option-pricing model to incorporate more empirical features becomes an urgent and necessary event. A new power option pricing method is designed for the financial market uncertainty that simultaneously involves randomness and fuzziness. The randomness in market uncertainty is modeled by a time-fractional diffusion model, which describes trend memory in underlying asset prices. The fuzziness in market uncertainty is characterized by a triangular interval type-2 fuzzy numbers, which better captures the fuzziness of underlying asset prices. Considering the decision-maker’s subjective judgment, we show the price mean value with the possibility-necessity weight and pessimistic-optimistic index under the type-2 fuzzy environment. We develop the power option pricing model with the time-fractional diffusion model and the triangular interval type-2 fuzzy numbers. Furthermore, the analytic solutions of pricing call power option and put power option are obtained and verified by the variational iterative reconstruction method. Our study shows that power option pricing, which adopts the time-fractional model and the triangular interval type-2 fuzzy numbers, can better capture the trend memory and double fuzziness of the real market. In addition, a numerical example is provided to illustrate that the power option means the value is decreasing with respect to the pessimistic-optimistic index and is fluctuating with respect to the possibility-necessity weight index.

At present, aquatic product pollution has become the main root of frequent food safety problems and causes economic losses. Vibrio is one of the main pathogens causing foodborne diseases. In this study, in order to uncover the pollution status of pathogenic Vibrio in the marine products of China, a total of 646 aquatic products were collected and analyzed from 10 coastal cities in China. Five kinds of pathogenic Vibrio were separated from these samples and monitored to explore the relationship between pollution and the pathogen. Real-time fluorescence quantitative PCR was adopted to detect foodborne Vibrio quantitatively in marine aquatic products. Aquatic pathogenic Vibrio was collected in different regions, different types of aquatic products, and different sampling places, and the difference in detection rate was statistically significant through statistical analysis. This study made a frame for the pollution degree of pathogenic Vibrio in marine products in China and established the dominant flora of pathogenic Vibrio in different types of aquatic products, which provides a theoretical basis for food safety supervision departments to take targeted prevention and control measures.

Background. Contralaterally controlled neuromuscular electrical stimulation (CCNMES) is a novel electrical stimulation treatment for stroke; however, reports on the efficacy of CCNMES on lower extremity function after stroke are scarce. Objective. To compare the effects of CCNMES versus NMES on lower extremity function and activities of daily living (ADL) in subacute stroke patients. Methods. Forty-four patients with a history of subacute stroke were randomly assigned to a CCNMES group and a NMES group (n=22 per group). Twenty-one patients in each group completed the study per protocol, with one subject lost in follow-up in each group. The CCNMES group received CCNMES to the tibialis anterior (TA) and the peroneus longus and brevis muscles to induce ankle dorsiflexion motion, whereas the NMES group received NMES. The stimulus current was a biphasic waveform with a pulse duration of 200 μs and a frequency of 60 Hz. Patients in both groups underwent five 15 min sessions of electrical stimulation per week for three weeks. Indicators of motor function and ADL were measured pre- and posttreatment, including the Fugl–Meyer assessment of the lower extremity (FMA-LE) and modified Barthel index (MBI). Surface electromyography (sEMG) assessments included average electromyography (aEMG), integrated electromyography (iEMG), and root mean square (RMS) of the paretic TA muscle. Results. Values for the FMA-LE, MBI, aEMG, iEMG, and RMS of the affected TA muscle were significantly increased in both groups after treatment (p

The key to safe and efficient longwall mining of steeply dipping seams lies in the stability control of the “support-surrounding rock” system. This study analyzes the difficulties encountered when controlling the stability of the support during the longwall mining process of steeply dipping coal seams in terms of the characteristics of the nonuniform filled-in gob using a combination of physical tests, theoretical analyzes, and field measurements. Considering the floor as an elastic foundation, we built a “support-surrounding rock” mechanical model using data obtained on support-surrounding rock systems in different regions and the laws of support motion under different load conditions. Our findings are summarized as follows: first, depending on the angle of the coal seam, the caving gangue rolls (slide) downward along the inclined direction, resulting in the formation of a nonuniform filling zone in the deep gob where the lower, middle, and upper sections are filled, half-filled, and empty, respectively. In addition, an inverted triangular hollow surface is formed on the floor of the gob in the middle and upper sections behind the support. Furthermore, as the angle of the coal seam, length of the working face, and mining height increase, the characteristics of the nonuniform filled-in gob are enhanced. Second, we found that because of the gangue support, the “support-surrounding rock” system is relatively stable in the lower part of the working face; however, in the middle and upper sections of the working face, the contact method and loading characteristics of the support are more complicated, making stability control difficult. Third, the magnitude and direction of the load, action point, and mining height affect the stability of the support to varying degrees, with the tangential load and action position of the roof load having the most significant impacts on the stability of the support. Under loading by the roof, rotation and subsidence of the support inevitably occur, with gradually increasing amplitudes and effects on the intersupport and sliding forces. Finally, we found that overall stability can be achieved by adopting measures involving “sliding advancement of supports” and applying a “down-up” removal order. These research results serve as a significant reference and guidance for longwall mining applications.

This paper proposes an idea of combining the Meyer Shearlet and mathematical morphology to produce the edge detection of pathological sections of the colon. First, the method of constructing a class of sufficiently smooth sigmoid functions along with its relative scale function and Meyer wavelet function is provided in this paper. Based on those, in order to get the new Meyer wavelet function, we use the sigmoid function to construct more general scale functions. Next, taking sufficiently smooth sigmoid functions as examples, combining the relative Meyer wavelet and Shearlet to denoise some pathological sections of the colon leads a decent feedback. At last, this paper provides an improved algorithm for the edge detection of mathematical morphology with the background of multiscale and multistructure. This algorithm is used to carry out the edge detection of images after denoising yields a new edge detection algorithm that fuses the Meyer Shearlet denoising and mathematical morphology. According to the simulation results, the new algorithm is more beneficial for the observation and diagnosis of doctors since the edge noise of the colon pathological image detected by the new algorithm is smaller and provides more continuous and clear lines. Therefore, the fusion algorithm provided in this paper is an effective way to carry out the edge detection of an image.

Based on the data of 3894 companies disclosed in the 2014–2017 Small and Medium Enterprises (SME) Board and Growth Enterprise Market (GEM) Annual Reports, our research evaluates the impacts of the weighted deduction policy for research and development (R&D) expenses on innovation additionality in the “Propensity Score Matching” (PSM) approach, from the moderation perspective of marketization, market competition, and political connections. The empirical findings are as follows: (1) The weighted deduction policy for R&D expenses has a positive effect on the additionality of input and output. The policy has an “additionality effect” on invention patents and utility patents, but it is not significant on appearance patents. (2) Low degree of marketization and high degree of market competition have positive moderating effects on the additionality of input and output. (3) Political connections strengthen the incentive effect of the weighted deduction policy for R&D expenses on the additionality of input and output. From the perspective of additionality, our research results enrich the literature on studies of incentive effects of policy innovation and also provide empirical support for the adjustment of the weighted deduction policy for R&D expenses.

Abstract Aims/Introduction Neonatal diabetes mellitus is created by alterations in the genes responsible for beta‐cell mass and/or function. The present study aimed to evaluate the genetic variants in the insulin gene (INS) in four Chinese infants aged

Abstract Size‐exclusion chromatography (SEC) is a widely adopted method for the isolation of extracellular vesicles (EVs) from complex samples. SEC can efficiently remove high‐abundant proteins, while often requires multiple fractionation operation using diversified column settings. In this study, we aim to establish a simplified SEC method to acquire high quality EVs. In comparison of all three cross‐linked Sepharose resins with the sample types of FBS and human serum (HS), CL‐6B and CL‐4B showed superior performance in regular SEC to CL‐2B in terms of significantly narrower EV and protein peaks, higher resolutions and EV purity. By increasing their bed volumes to 20 ml, the resolutions of CL‐6B and CL‐4B columns could be significantly improved, while the CL‐6B column had the best performance with higher particle yields and tighter EV peaks. With the CL‐6B 20 ml column, we further established a simplified dichotomic SEC method that only requires two bulk elutions to acquire EVs in the Eluate 1 and proteins in the Eluate 2. We further justified that such CL‐6B columns were reusable for at least 10 consecutive times, and the dichotomic SEC was applicable to EV isolations from HS and FBS‐free supernatants of fluorescently labelled and unlabelled SW620 cells. The proteomics analysis implicated that although the two methods had dissimilar abilities in removing different co‐isolating contaminant proteins from EVs, the dichotomic SEC and ultracentrifugation could isolate EVs from human plasma with comparable purity. This dichotomic SEC has its intriguing potential to be used for EV preparation toward clinical testing and/or basic research.

Abstract Background Tumor angiogenesis plays an important role in disease progression, and RhoC has been previously found to be expressed in vascular endothelial cells (VECs); however, its role in tumor angiogenesis requires clarification. This study aimed to explore the effects of RhoC downregulation on the cytoskeleton, pseudopod formation, migration ability, and canalization capacity of myeloma vascular endothelial cells (MVECs) in vitro. Materials and methods The expression of RhoC in MVECs and human umbilical vein endothelial cells (HUVECs) was knocked down by shRNA, and the expression levels of RhoC mRNA were detected by quantitative reverse transcription polymerase chain reaction (qRT‐PCR). The cytoskeletal changes and pseudopods were observed by laser scanning confocal and scanning electron microscopy; VECs were incubated in two‐dimensional Matrigel and three‐dimensional microcarriers to observe tube‐like structures and budding status, respectively. The protein expression of RhoC, phosphorylation of mitogen‐activated protein kinase (p‐MAPK), and Rho‐associated coiled‐coil kinase (ROCK) was determined by Western blotting. The expression of RhoC in VECs was downregulated by RhoC shRNA, thereby decreasing the number of pseudopods, two‐dimensional tube‐like structures, and buds. Results When RhoC was downregulated, the expression levels of ROCK and phosphorylation of MAPK were both decreased (P

Abstract Background Based on previous findings, we hypothesized that Vasohibin 2 (VASH2) protein may induce epithelial‐mesenchymal transition (EMT) of pancreatic cancer (PC) cells by promoting the malignant behaviors of these cells. The present study aimed to test this hypothesis and explore the possible mechanisms involved. Methods The expression of VASH2 in PC tissues and cell lines was detected by quantitative real‐time PCR and Western blot. PC cells with overexpression or knockdown of VASH2 were used to examine the involvement of VASH2 in EMT by detecting the expression of epithelial (E‐cadherin) and mesenchymal (vimentin) markers and EMT‐related transcription factor ZEB1/2, in gemcitabine resistance and tumor cell invasion by apoptosis and invasion assays, and in cancer stem cell‐like phenotypes by detecting the proportion of CD24+CD44+ and side population (SP) cells in PC cells with flow cytometry. The impact of VASH2 overexpression and knockdown on components of the Hedgehog signaling pathway was also assessed. Results We found that VASH2 was highly expressed in PC tissues and cells. It promoted the EMT of PC cells by altering ZEB1/2 expression. VASH2 also stimulated invasion and chemotherapeutic resistance of PC cells and increased the proportion of cancer stem‐like cells in PC cells. VASH2 did so by upregulating the expression of multiple molecules in the Hedgehog signaling pathway of PC cells. Conclusion VASH2 promotes malignant behaviors of PC cells by inducing EMT via activation of the Hedgehog signaling pathway.

Due to the advantages of low porosity, low permeability, high ductility, and excellent capacities for creep and damage self-healing, salt rock is internationally considered as the ideal medium for underground storage of energy and disposal of radioactive waste. As one of the most important mechanical properties of salt rock, creep properties are closely related to the long-term operation stability and safety of salt rock underground storage cavern. A comprehensive review on the creep properties and constitutive model of salt rock is put forward in this paper. The opinions and suggestions on the research priority and direction of salt rock's mechanical properties in the future are put forward: (1) permeability variation of salt rock under the coupling effect of temperature and stress; (2) damage mechanism and evolution process under the effect of creep-fatigue interaction and low frequency cyclic loading; (3) microdeformation mechanisms of salt rock and the relationship between microstructure variations and macrocreep behavior during creep process; (4) the establishment of the creep damage constitutive model with simple form, less parameters, easy application, and considering the damage self-healing ability of salt rock simultaneously.

During the construction of the underpass of a new tunnel, the excavation unloading effect disturbs surrounding rock masses and promotes surrounding rock deformation, inevitably changing stress and displacement in the existing tunnel. Taking Yangtaishan tunnel excavation of Shenzhen Metro Line 6 as an engineering example, effects of excavation programs of left and right lines on the deformation characteristics of newly excavated and existing tunnels were evaluated based on Midas numerical model and priority excavation advantages of the left line were determined. The settlement and horizontal deformation characteristics of the existing tunnel were analyzed using the construction monitoring method. Results showed that maximum settlement and horizontal deformation of the existing tunnel were 1.35 and 0.23 mm, respectively. Settlement of invert and inverted top along axis direction was from growth to decline, and then a V-shaped settlement trough was formed with maximum settlement values of 1.36 and 0.97 mm, respectively. Maximum settlement and uplift of the newly built tunnel appeared on the upper and bottom parts of invert, respectively. In the newly built tunnel segments, the top settlement was dominated and deformation was mainly distributed in both side areas. At the top of the existing tunnel segment, convergence settlement was 3.09 mm and settlement rate was slow first which was accelerated, then stabilized, and finally slowed down again which was opposite to the uplift development trend of the bottom of tunnel segment. The top of the existing tunnel segment showed four settlement stages, slow, rapid, stable, and slow settlement stages. Compared with the right line, preferential excavation of the left line had obvious advantages in terms of tunnel stability. The unloading effect of TBM excavation created vault settlement in the existing tunnels where actual settlement values were 1.12 and 1.13 times, which theoretically calculated settlement. The horizontal deformation of the existing tunnel was varied first linearly and then nonlinearly with maximum deformation in the convergence stage of 1.47 mm.

Loess geological tunnels are characterized by weak geological structure and poor self-stability of surrounding rock, so effectively controlling the excavation face distances of different caverns is of great significance for guiding the safe construction of large-section tunnels. Based on the excavation of large-section loess tunnel from Xi’an Metro Line 4, the optimal excavation face distance is determined based on Midas numerical model. Then, the surface settlement and horizontal deformation are analyzed based on monitoring data, and, finally, the rationality of excavation face distance is verified. The results show that the influence of excavation face distance on surface settlement, vault settlement, and horizontal deformation is consistent. The surface settlement mainly occurs in the range of −20∼20 m from the tunnel centerline and the settlement trough formed has asymmetric characteristics. The vault settlement and horizontal deformation undergo first a rapid settlement and then a slow settlement. The connection between initial support and middle partition is mainly tensile stress and the middle and bottom parts of the supporting structure are mainly compressive stress. Numerical results suggest that the optimal excavation faces distance of L1, L2, and L3 which can be 4, 9, and 9 m, respectively. Construction monitoring data show that the double-sides heading method has a significant effect on surface settlement, vault settlement, and horizontal deformation. The surface settlement occurs within the range of −17∼6 m from the tunnel centerline. The maximum vault settlement and horizontal deformation are 73.00% and 65.50% of the maximum allowable. It can be seen that the actual excavation parameters optimized by Midas numerical model have high reliability.

Abstract Crop yield and economic profitability, both highly dependent on local crop management, soil characteristics, and weather conditions, are among the most influential factors to consider when considering a cropping system. The objective of this study was to compare the economic returns of three different 4‐yr diverse crop rotations with that of a 2‐yr traditional crop rotation in eastern South Dakota. The rotations included were (a) corn (Zea mays L.)–soybean [Glycine max (L.) Merr.]–spring wheat (Triticum aestivum L.)–pea (Pisum sativum L.) (CSSwP), (b) corn–pea–winter wheat–soybean (CPWwS), (c) corn–oat (Avena sativa L.)–winter wheat–soybean (COWwS), and (d) corn–soybean (CS). Results showed that total cost for the CS rotation was 7.2, 14.9, and 18.2% greater than the COWwS, CSSwP, and CPWwS rotations, respectively. Whereas CS rotation had comparable corn yield with CSSwP and COWwS rotations, its soybean yield ranked the lowest among all the rotations. When N fertilizer application fell below the level necessary to achieve for yield maximization, the CS rotation demonstrated a lack of resilience as indicated by a continual decline in economic returns over time. In comparison, the CSSwP rotation demonstrated high resilience to reduced N fertilizer application rate, and its net revenue was the highest among all rotations and surpassed the CS. Our results suggest that extending the traditional CS rotation to the more diversified CSSwP rotation could simultaneously reduce input costs and overreliance on N fertilizer.

Using crude soybean oil (CSO) as fluid and nanomagnetic immobilized phospholipase C (PLC) as fluidizing particles, the Eulerian–Lagrangian fluid-particle two-phase flow model was used to numerically simulate the law of motion of fluidizing particles in the magnetic fluidized bed (MFB). The main parameters were obtained by numerical simulation based on the discrete element method (DEM). The nanomagnetic PLC in the MFB was optimal to the enzymatic reaction by limiting the iteration step size to 3 × 10−5, the boundary condition to 20 × 300 mm, the opening rate to 37.5%, the condition of CSO flow rate to 0.01 m/s, and the magnetic field strength to 0.02T. After 2.0 h of reaction, the amount of residual phosphorus in the oil was 55.73 mg/kg, the content of 1, 2-DAG was 1.42%, and the nanomagnetic enzyme still had 97% relative activity. Hence, these optimal conditions can improve the efficiency and the stability of the nanomagnetic enzymatic reaction.

Aims. Accumulating evidence indicates gut microbiota dysbiosis is involved in metabolic disorders, including prediabetes. The prebiotic inulin has been frequently reported to exert beneficial effects on the host metabolism. Here, we aimed to evaluate whether dietary supplementation with inulin modulates gut microbiota structure in prediabetes, affecting glucose and lipid metabolism. Methods. We performed a prospective single-arm study. A total of 49 subjects with prediabetes (WHO 1999 criteria) were voluntarily enrolled. Each subject received a daily supplement with 15 g of inulin for 6 months. Glucose and lipid metabolic parameters and gut microbiota were analyzed at baseline and at 3 and 6 months after inulin intervention. Intestinal microbiota profile was evaluated using the Illumina MiSeq platform based on V3-V4 bacterial 16S rRNA gene. Results. The mean age of 49 subjects was 56.6 ± 6.9 years and BMI was 25.07 ± 3.02 kg/m2. After 24 weeks of prevention, inulin significantly decreased fasting insulin (2.38 ± 0.50 vs. 2.22 ± 0.62, P=0.03) and 2-hour post-OGTT insulin (4.01 ± 0.77 vs. 3.74 ± 0.76, P=0.02) and improved HOMA-IR (1.05 ± 0.53 vs. 0.85 ± 0.66, P=0.03). Gut microbiota analysis indicated that inulin supplement resulted in an increase in the relative abundance of Actinobacteria, Bifidobacteriales, Bifidobacteriaceae, Lactobacillaceae, Bifidobacterium, Lactobacillus, and Anaerostipes both at 3 and 6 months, while with a decrease in the relative abundance of Alistipes. Spearman correlation analysis revealed altered microbial community was associated with glucose and lipids metabolic parameters. Conclusions. Inulin supplementation improves insulin resistance of prediabetes and exerts beneficial effects on modulating the intestinal microbiota composition. These findings suggest that insulin may be a potentially novel and inexpensive intervention for prediabetes.

Noninvasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) can induce long-term potentiation-like facilitation, but whether the combination of TMS and tDCS has additive effects is unclear. To address this issue, in this randomized crossover study, we investigated the effect of preconditioning with cathodal high-definition (HD) tDCS on intermittent theta burst stimulation- (iTBS-) induced plasticity in the left motor cortex. A total of 24 healthy volunteers received preconditioning with cathodal HD-tDCS or sham intervention prior to iTBS in a random order with a washout period of 1 week. The amplitude of motor evoked potentials (MEPs) was measured at baseline and at several time points (5, 10, 15, and 30 min) after iTBS to determine the effects of the intervention on cortical plasticity. Preconditioning with cathodal HD-tDCS followed by iTBS showed a greater increase in MEP amplitude than sham cathodal HD-tDCS preconditioning and iTBS at each time postintervention point, with longer-lasting after-effects on cortical excitability. These results demonstrate that preintervention with cathodal HD-tDCS primes the motor cortex for long-term potentiation induced by iTBS and is a potential strategy for improving the clinical outcome to guide therapeutic decisions.

Abstract Background Hematopoietic neoplasms with chromosomal translocations involving JAK2 are rare, and most of them show myeloproliferative neoplasm‐associated features, followed by B‐acute lymphoblastic leukemia (B‐ALL). De novo B‐ALL cases with JAK2 rearrangements are suggested to be appropriately considered as BCR‐ABL1‐like B‐ALL, but its partners varied. Methods Fluorescence in situ hybridization (FISH), RNA sequencing (RNA‐Seq), whole‐genome sequencing, and reverse transcription polymerase chain reaction (RT‐PCR) were performed to identify the pathogenic fusion gene in a 29‐year‐old woman with relapsed B‐ALL and rare t(1;9)(p13;p22) translocation. Results We identified RNPC3 as a new JAK2 fusion partner in the patient. She was treated with a combination of chemotherapy and targeted drug ruxolitinib and chimeric antigen receptor T‐cell therapy, but failed to achieve complete remission. She had no chance to undergo allogeneic hematopoietic stem cell transplantation and died of disease progression 7 months after the initial diagnosis. Her clinical course demonstrated that this novel RNPC3‐JAK2 fusion might portend an unfavorable prognosis. Conclusion This finding adds to the expanding compendium of JAK2 fusions found in B‐ALL and suggests the potential need for a diagnostic FISH analysis as well as RNA‐Seq in the appropriate clinical setting.

Abstract Meiosis increases genetic diversity, yet the genome complement needs to be stable to ensure offspring viability. Both small ubiquitin‐like modifier (SUMO) and ubiquitin have been reported to participate in meiotic regulation, yet functions of the SUMO‐ubiquitination crosstalk in meiosis remain unclear. Here, it is reported that a SUMO‐targeted ubiquitin ligase, Slx8p, promotes accurate chromosome segregation during meiosis, since the deletion of SLX8 leads to increased aneuploidy due to a defect in synaptonemal complex (SC) component degradation. Both the RING domain and SUMO interacting motifs of Slx8p are essential for meiotic progression and maintaining spore viability, and the expression of tetraubiquitin fused with SUMO partially rescues meiotic defects in the SLX8‐deletion strain. Furthermore, Slx5p‐Slx8p can directly add ubiquitin to SUMOylated Zip1p and Ecm11p, and forced degradation of Ecm11p partially rescues the sporulation defects of the SLX8 deletion strain. These findings provide a mechanism for SC disassembly and reveal that the crosstalk between SUMOylation and ubiquitination facilitates accurate chromosome segregation by promoting SC component degradation during meiosis.

Two nonidentical dimension Markovian jumping complex networks with stochastic perturbations are taken as objects. The network models under two conditions including single weight and double weights are established, respectively, to study the problem of synchronization and identification. A finite-time projection lag synchronization method is proposed and the unknown parameters of the network are identified. First of all, based on Itô’s formula and the stability theory of finite-time, a credible finite-time adaptive controller is presented to guarantee the synchronization of two nonidentical dimension Markovian jumping complex networks with stochastic perturbations under both conditions. Meanwhile, in order to identify the uncertain parameters of the network with stochastic perturbations accurately, some corresponding sufficient conditions are given. Finally, numerical simulations under two working conditions are given to demonstrate the effectiveness and feasibility of the main theory result.

In order to investigate the aerostatic instability mode and underlying failure mechanism of the new suspension bridge with double main spans, a corresponding program based on aerostatic load increment and two-iteration scheme was developed with considering the effects of aerostatic and geometric nonlinearity. Three double-main-span suspension bridges were taken as a case study to analyze the full range of aerostatic instability with different initial attack angles. Results show that there are two aerostatic instability modes for the double-main-span suspension bridge, one of which is the bilateral antisymmetric instability mode and the other is the single-span instability mode. The critical aerostatic velocity corresponds to the instability mode that occurs first, which is dependent on structural dynamic properties and initial attack angles. In addition, mechanism of the two aerostatic instability modes was discussed in detail.

Aims/Introduction. The aim of the present study was to investigate whether HbA1c was related to clinical outcomes in diabetic patients undergoing CABG surgery. Materials and Methods. A literature search was carried out satisfying the predefined inclusion criteria from Pubmed, Embase, and Cochrane Library. Differences were expressed as odds ratios (ORs) with 95% confidence intervals (CIs) to assess the relationships of preoperative HbA1c levels and clinical prognosis in diabetic patients. Results. 7895 diabetic patients undergoing CABG surgery from eight published studies were finally involved in this meta-analysis. Combined analyses revealed that the higher HbA1c level was significantly associated with increased risks of all-cause mortality (OR 1.56, 95%CI 1.29–1.88), myocardial infarction (OR 2.37, 95%CI 1.21–4.64), and stroke (OR 2.07, 95%CI 1.29–3.32) after CABG surgery. However, there was no significant relationship between HbA1c levels and renal failure (OR 2.08, 95%CI 0.96–4.54) in diabetic patients undergoing CABG surgery. Conclusions. Our meta-analysis demonstrated that the HbA1c level is potentially associated with increased risks of all-cause mortality, myocardial infarction, and stroke in diabetic subjects undergoing CABG surgery. However, further clinical studies with larger sample sizes and longer follow-up period are urgently warranted.