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Abstract Based on high-throughput metabolomics data, the recently introduced inverse differential Jacobian algorithm can infer regulatory factors and molecular causality within metabolic networks close to steady-state. However, these studies assumed perturbations acting independently on each metabolite, corresponding to metabolic system fluctuations. In contrast, emerging evidence puts forward internal network fluctuations, particularly from gene expression fluctuations, leading to correlated perturbations on metabolites. Here, we propose a novel approach that exploits these correlations to quantify relevant metabolic interactions. By integrating enzyme-related fluctuations in the construction of an appropriate fluctuation matrix, we are able to exploit the underlying reaction network structure for the inverse Jacobian algorithm. We applied this approach to a model-based artificial dataset for validation, and to an experimental breast cancer dataset with two different cell lines. By highlighting metabolic interactions with significantly changed interaction strengths, the inverse Jacobian approach identified critical dynamic regulation points which are confirming previous breast cancer studies.

Abstract This study aimed to construct a high-performance prediction and diagnosis model for type 2 diabetic retinopathy (DR) and identify key correlates of DR. This study utilized a cross-sectional dataset of 3,000 patients from the People’s Liberation Army General Hospital in 2021. Logistic regression was used as the baseline model to compare the prediction performance of the machine learning model and the related factors. The recursive feature elimination cross-validation (RFECV) algorithm was used to select features. Four machine learning models, support vector machine (SVM), decision tree (DT), random forest (RF), and gradient boost decision tree (GBDT), were developed to predict DR. The models were optimized using grid search to determine hyperparameters, and the model with superior performance was selected. Shapley-additive explanations (SHAP) were used to analyze the important correlation factors of DR. Among the four machine learning models, the optimal model was GBDT, with predicted accuracy, precision, recall, F1-measure, and AUC values of 0.7883, 0.8299, 0.7539, 0.7901, and 0.8672, respectively. Six key correlates of DR were identified, including rapid micronutrient protein/creatinine measurement, 24-h micronutrient protein, fasting C-peptide, glycosylated hemoglobin, blood urea, and creatinine. The logistic model had 27 risk factors, with an AUC value of 0.8341. A superior prediction model was constructed that identified easily explainable key factors. The number of correlation factors was significantly lower compared to traditional statistical methods, leading to a more accurate prediction performance than the latter.

The human CPAMD8 gene encodes proteins in the A2M/C3 (alpha-2-macroglobulin/complement 3) family, predominantly expressed in the distal tips of the retinal neuroepithelium that form the iris and ciliary body. Mutations in CPAMD8 have been linked to anterior segment dysplasia and congenital glaucoma. Using CRISPR/Cas9 editing, we inserted a 3*EAAAK-EGFP fluorescent tag into the CPAMD8 gene, enabling real-time observation of its expression and providing insights into its biological functions. The resulting gene-edited cell line retained normal stem cell morphology and karyotype, expressed essential pluripotency markers, and exhibited differentiation potential.

This paper primarily investigates the influence of spatial layout on the safety risks associated with urban natural gas pipelines. Drawing from the actual spatial configuration around the pipeline and local climatic characteristics, the study delves into the distribution patterns of natural gas leakage diffusion and explosion accident consequences, considering various factors such as leakage apertures, soil porosity, and spatial layouts. By integrating the outcomes of the consequence analysis, the quantitative risk of urban natural gas pipelines, accounting for the impact of spatial layout, was computed and juxtaposed with the results of traditional two-dimensional risk analysis. The findings underscore that spatial layout exerts a substantial impact on risk distribution, with significantly elevated risk values in more congested spatial layouts. Additionally, the introduction of a barrier along the pipeline leakage path resulted in a 91.4% reduction in risk compared to scenarios without obstruction. It is evident that the spatial layout surrounding the pipeline plays a pivotal role in influencing the distribution of pipeline failure risks, establishing the spatial environment as a critical factor in risk analysis. This study offers valuable insights for urban land planning, safety control line establishment, and related considerations.

Objective: To develop a method for determining the concentration of axitinib in beagle dog plasma and utilize this method to investigate the pharmacokinetics of orally administered axitinib in beagle dogs. Methods: Plasma samples were processed using acetonitrile precipitation and analyzed by UPLC-MS/MS with sunitinib as an internal standard (IS). Chromatographic separation was achieved on a Waters Acquisition UPLC BEH C18 column (50 mm × 2.1 mm, 1.7 μm) with a gradient elution of acetonitrile and 0.1 % formic acid. Mass spectrometry uses an electrospray ion source for positive ion detection in a multiple reaction monitoring mode. The monitored ion transitions for axitinib and sunitinib were m/z 387 → 355.96 and m/z 399.3 → 282.96, respectively. Six beagle dogs were administered 0.33 mg/kg of axitinib orally, and venous blood samples were collected at 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, and 24 h post-dose for pharmacokinetic analysis. Results: The assay demonstrated a linear range of 0.5–100 ng/mL (r2 = 0.9992), and the lower limit of quantification was up to 0.5 ng/mL. Precision, as assessed by relative standard deviation (RSD), was within 8.64 % for both intraday and interday variability. The relative error (RE) for precision from −2.77 %–1.20 %. The recovery rate of the analytes exceeded 85.28 % and the matrix effect was approximately 100 %. Plasma samples maintained stability under various conditions, including room temperature storage for 12 h, processed on an automatic sampler at 4 °C for 6 h, three freeze-thaw cycles, and long-term storage at −80 °C for 60 days. Pharmacokinetic parameters were determined using DAS 2.0 software, revealing a half-life (T1/2) of 6.05 h and an area under the curve (AUC (0 → ∞)) of 97.13 ng h/mL for axitinib. Conclusions: The UPLC-MS/MS method developed in this study offers high specificity, rapid analysis, high recovery, excellent linearity, and minimal plasma volume requirements, making it well-suited for pharmacokinetic and drug interaction studies in beagles dogs.

Abstract The placenta is a unique organ for ensuring normal embryonic growth in the uterine. Here, we found that maternal RNA transcription in Dlk1-Dio3 imprinted domain is essential for placentation. PolyA signals were inserted into Gtl2 to establish a mouse model to prevent the expression of maternal RNAs in the domain. The maternal allele knock-in (MKI) and homozygous (HOMO) placentas showed an expanded junctional zone, reduced labyrinth and poor vasculature impacting both fetal and maternal blood spaces. The MKI and HOMO models displayed dysregulated gene expression in the Dlk1-Dio3 domain. In situ hybridization detected Dlk1, Gtl2, Rtl1, miR-127 and Rian dysregulated in the labyrinth vasculature. MKI and HOMO induced Dlk1 to lose imprinting, and DNA methylation changes of IG-DMR and Gtl2-DMR, leading to abnormal gene expression, while the above changes didn’t occur in paternal allele knock-in placentas. These findings demonstrate that maternal RNAs in the Dlk1-Dio3 domain are involved in placental vasculature, regulating gene expression, imprinting status and DNA methylation.

Abstract Background Missing data is frequently an inevitable issue in cohort studies and it can adversely affect the study's findings. We assess the effectiveness of eight frequently utilized statistical and machine learning (ML) imputation methods for dealing with missing data in predictive modelling of cohort study datasets. This evaluation is based on real data and predictive models for cardiovascular disease (CVD) risk. Methods The data is from a real-world cohort study in Xinjiang, China. It includes personal information, physical examination data, questionnaires, and laboratory biochemical results from 10,164 subjects with a total of 37 variables. Simple imputation (Simple), regression imputation (Regression), expectation-maximization(EM), multiple imputation (MICE) , K nearest neighbor classification (KNN), clustering imputation (Cluster), random forest (RF), and decision tree (Cart) were the chosen imputation methods. Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) are utilised to assess the performance of different methods for missing data imputation at a missing rate of 20%. The datasets processed with different missing data imputation methods were employed to construct a CVD risk prediction model utilizing the support vector machine (SVM). The predictive performance was then compared using the area under the curve (AUC). Results The most effective imputation results were attained by KNN (MAE: 0.2032, RMSE: 0.7438, AUC: 0.730, CI: 0.719-0.741) and RF (MAE: 0.3944, RMSE: 1.4866, AUC: 0.777, CI: 0.769-0.785). The subsequent best performances were achieved by EM, Cart, and MICE, while Simple, Regression, and Cluster attained the worst performances. The CVD risk prediction model was constructed using the complete data (AUC:0.804, CI:0.796-0.812) in comparison with all other models with p

The remediation of paddy soils co-contaminated with As and Cd is tricky. It is difficult to decrease Cd and As availability simultaneously due to their opposite geochemical characteristics. Finding the optimal trade-off relationship between As and Cd availability in paddy soils is a significant task that is necessary to guide the construction of water management measures. This study investigated the dissolution characteristics of As, Cd, Fe, Mn, DOC, DOM, and various As and Cd fractions in soils via the microcosm system and calculated the optimal trade-off value for available As and Cd in porewater. The results showed that the total As in porewater increased rapidly when the soil Eh was reduced to −104 mV. Meanwhile, the total Cd in porewater decreased dramatically when the soil Eh was below 62 mV. Under flooding and drainage conditions, Fe/Mn (oxyhydro)oxides play a vital role in regulating Cd dissolution in paddy soils, while Fe/Mn (oxyhydro)oxides organically bind sulfide together to determine the dissolution of As. Additionally, the optimal pe + pH response to the minimum trade-off value of available As and Cd in porewater was found to be 6.6, which indicates a moderate reduction status. Therefore, further research should apply the optimal pe + pH to construct water management measures to safely utilize co-contaminated paddy fields.

BackgroundThe systemic immuno-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are widely used and have been shown to be predictive indicators of various diseases. Diabetic nephropathy (DN), retinopathy (DR), and peripheral neuropathy (DPN) are the most prominent and common microvascular complications, which have seriously negative impacts on patients, families, and society. Exploring the associations with these three indicators and diabetic microvascular complications are the main purpose.MethodsThere were 1058 individuals with type 2 diabetes mellitus (T2DM) in this retrospective cross-sectional study. SII, NLR, and PLR were calculated. The diseases were diagnosed by endocrinologists. Logistic regression and subgroup analysis were applied to evaluate the association between SII, NLP, and PLR and diabetic microvascular complications.ResultsSII, NLR, and PLR were significantly associated with the risk of DN [odds ratios (ORs): 1.52, 1.71, and 1.60, respectively] and DR [ORs: 1.57, 1.79, and 1.55, respectively] by multivariate logistic regression. When NLR ≥2.66, the OR was significantly higher for the risk of DPN (OR: 1.985, 95% confidence interval: 1.29–3.05). Subgroup analysis showed no significant positive associations across different demographics and comorbidities, including sex, age, hypertension, HbA1c (glycated hemoglobin), and dyslipidemia.ConclusionThis study found a positive relationship between NLR and DN, DR, and DPN. In contrast, SII and PLR were found to be only associated with DN and DR. Therefore, for the diagnosis of diabetic microvascular complications, SII, NLR and PLR are highly valuable.

In recent years, there has been significant research focus on topological states in two-dimensional materials, particularly those exhibiting intrinsic magnetic orderings. In this study, we employ theoretical calculations to uncover the remarkable band topology of monolayer V2Cl3Br3. This two-dimensional compound not only possesses a half-metallic ferromagnetic ground state but also demonstrates exceptional thermodynamic and mechanical stabilities. Notably, we observe clean band crossings with complete spin polarization, which manifest as phase transitions between Weyl semimetal states and quantum anomalous Hall states under different magnetization directions. Both of these topological phases exhibit pronounced edge states. Furthermore, utilizing Monte Carlo simulations with the Heisenberg model, we estimate a high Curie temperature of up to 79.2 K, indicating its potential for spintronic development. Additionally, we analyze the mechanical properties of the material, emphasizing its isotropic mechanical behavior, which offers advantageous features for practical applications. These findings establish the foundation for further exploration of practical applications involving two-dimensional ferromagnetic topological states. Importantly, the identified material candidate can be readily incorporated into experimental preparation, thus accelerating progress in topological quantum applications and the development of half-metallic spintronic devices.

Language immersion has been an emerging educational method for K-12 students to acquire foreign languages. Despite its effectiveness, there are limited teacher education programs designed specifically for language immersion educators. Thus, many language immersion teachers have been applying knowledge learned from general teacher educational programs, which are not designed for language immersion settings, in their daily teaching. Simultaneously, language immersion programs, especially Chinese immersion programs, have identified multiple educational challenges related to curriculum design and content teaching, classroom management, and cross-cultural communications. This study aims to address these challenges from the perceptions of six selected Chinese immersion teachers towards their teacher preparation programs via qualitative in-depth case studies. The participant selection considers various education and teaching backgrounds of Chinese immersion teachers to represent a wide range of perspectives. The results show that the educational philosophy and psychology theories and practices, curriculum and instruction, cross-cultural competence, and practicum in existing preparation programs contribute positively towards immersion teaching in the U.S. However, Chinese immersion teachers demand more social-emotional learning and diversity, equity, and inclusion preparation. Potential solutions to these challenges require synergistic efforts from the current teacher preparation programs, Chinese immersion programs, and policymakers.

Abstract Background The prevalence of microvascular complications in type 2 diabetes mellitus (T2DM) is increasing. The effect of lipid profiles on diabetic microvascular complications remains debated. This research aimed to study the correlation between lipid profiles and microvascular complications. Methods This retrospective cross-sectional study included 1096 T2DM patients. The patients were divided into the control, diabetic retinopathy (DR), nephropathy (DKD), and peripheral neuropathy (DPN) groups based on the existence of corresponding complications. The lipid profiles were analyzed, and the effect on complications was assessed by logistic regression. Results Compared with the control group, the diabetic microvascular complications group had a higher dyslipidemia rate. The rate of high TGs increased significantly with an increasing number of complications. High TG levels contributed to the risk of DKD, DR, and DPN [odds ratios (ORs): 2.447, 2.267, 2.252; 95% confidence interval: 1.648–3.633, 1.406–3.655, 1.472–3.445]. In the age (years) > 55, T2DM duration (years) > 10, and HbA1c (%) ≥ 7 groups, the risk of high TGs was higher for DKD (ORs: 2.193, 2.419, 2.082), DR (ORs: 2.069, 2.317, 1.993), and DPN (ORs: 1.811, 1.405, 1.427). Conclusion High TG levels increase the risk of diabetic microvascular complications, and patients with older age, longer T2DM duration, and higher HbA1c levels are recommended to keep lipid levels more strictly.

One new dimeric cyclohexylethanoid derivative (1) and one new rearranged abietane diterpenoid (2) were isolated from Clerodendrum bungei and C. inerme, respectively, together with 11 known compounds. The structures of the isolated compounds were elucidated by detailed spectroscopic and ECD analyses. The absolute configuration of 2 was unequivocally determined using single-crystal X-ray diffraction analysis. Compound 1 showed the greatest inhibitory effect on NO production in RAW 264.7 murine macrophages induced by lipopolysaccharide (LPS) with the IC50 value of 6.328 µM. Compound 1 also suppressed the proinflammatory cytokines IFN-γ, TNF-α, IL-1β, iNOS and IL-6 mRNA expression, while increased the mRNA expression of the anti-inflammatory cytokines IL-4, IL-10 and Arg-1 through NF-κB signaling pathway. The further experiments confirmed that compound 1 demonstrated the strong in vivo anti-inflammatory effect by reducing mortality, the serum TNF-α, IL-6 and IFN-γ levels, and tissue toxicity in CLP-induced septic mice. Collectively, these findings suggested that compound 1 might serve as a potential anti-inflammatory agent candidate for the sepsis treatment.

In the machining process of 440C stainless steel using ball-end milling, the generation of machined traces is an inevitable outcome. Traditional polishing methods, when applied to the milling surfaces of small conical holes, exhibit significant limitations. However, the application of nanosecond pulsed laser polishing while maintaining dimensional integrity has proven effective in mitigating these issues. The parameters for the laser and scanning strategy were empirically determined through planar experiments. The results showed a reduction in surface roughness to a minimum value, representing a decrease of approximately 41.7%. Further validation experiments were conducted on the ball-milled surface of small conical holes. The rate of roughness reduction in these experiments surpassed that of planar surface polishing with an improvement of approximately 73.6%. The scanning strategy’s applicability was confirmed, and the post-polishing surface morphology was found to be largely in line with the prediction. The remelt layer and heat-affected zone resulting from nanosecond laser polishing were observed to be below 5 μm, significantly preserving the dimensional integrity of the conical hole’s internal surface. Moreover, nanosecond laser polishing was found to substantially enhance the surface hardness of the material, with an increase ranging from 100% to 180%. This study underscores the efficacy of nanosecond laser polishing in enhancing the internal surface of small conical holes, thereby improving the surface properties. Consequently, this method presents a reliable solution for the removal of machined traces from complex internal surfaces.

Abstract Background The prevalence of cardiovascular disease (CVD) is high in China, especially in Northwest China, and dyslipidemia in diabetes is a major factor at risk for CVD. The dyslipidemia prevalence, treatment and control among type 2 diabetes mellitus (T2DM) patients in Northwest China were investigated. Methods In the cross-sectional retrospective research, 1386 medical records of T2DM patients were collected from the Endocrine Department of Tangdu Hospital. And patients’ age, sex, diabetes duration, glycated hemoglobin (HbA1c), complications, lipid levels, and drug use were recorded. The patient characteristics, lipid level and lipid-lowering therapy were analyzed. Results In this study, the dyslipidemia prevalence among T2DM patients was 87.7%, the treatment rate was 68.0%. The overall control rate of low-density lipoprotein cholesterol (LDL-C) was 43.1%, and control rates reached 52.7% for high-risk subjects and 36.1% for very high-risk subjects. The overall control rate of non-high-density lipoprotein cholesterol (non-HDL-C) was 19.8%. HbA1c (%) ≥ 7 was indicated as a major factor predicting failure of LDL-C and non-HDL-C control [odds ratio (OR) 1.521; 2.206, 95% confidence interval (CI) 1.154–2.005; 1.583–3.076)]. Conclusion Among patients with T2DM, it is high prevalence of dyslipidemia and low rate of treatment and control, and higher HbA1c level is the main factor for poor lipid control. It calls for more efforts to promote early screening, prevention and treatment of dyslipidemia for patients, thereby reducing the risk of CVD.

Commercial V2O5-WO3/TiO2 (VWTi) catalysts used in NH3-SCR reaction with varied Zn loading were prepared and then effect of SO2 on Zn-poisoned VWTi catalysts was investigated. Zn could cause the deactivation of VWTi catalysts. Nevertheless, the effect of SO2 on Zn-poisoned VWTi catalysts varied with Zn loading. For Zn-poisoned catalyst with low content of Zn (1.0 wt.%, ZnL), SO2 would promote the activity recovery of the catalyst. However, SO2 had no influence on the Zn-poisoned catalyst with high Zn content (4.0 wt.%, ZnH). The catalyst was characterized by N2 adsorption-desorption, XRD, XPS, SO2-TPD, NH3-TPD, H2-TPR and in situ DRIFTS. Tri-coordinated sulfate species were formed on ZnL sample in the presence of SO2, and the sulfate species could form new Brønsted acid sites, causing the recovery of activity. But ZnSO4 was appeared and no Brønsted acid sites formed on ZnH sample under SO2, thus the activity of ZnH sample changed little.

Direct assessment for internal corrosion of gas pipeline is an important method to assess the internal corrosion of pipelines. In order to improve the applicability and accuracy of direct assessment method for internal corrosion, the influence of CO2 electrochemical corrosion and particle erosion on the internal corrosion of pipeline was studied through electrochemical testing and numerical simulation. At the same time, the influence of pipeline inclination and liquid holdup on electrochemical corrosion was also analyzed. The research results show that: The influence of electrochemical corrosion on the internal corrosion of the gas pipeline is much greater than that of particle erosion, but the particle erosion can accelerate the electrochemical corrosion. Specifically, the greater the inclination of the pipeline, the higher the liquid holdup, and the more serious the corrosion is. In addition, the long uphill section of pipeline with a smaller inclination is prone to corrosion. Thereby, a new direct assessment method for internal corrosion of natural gas pipelines was proposed and applied to a natural gas pipeline in Panjin. The assessment results show that, compared with the original method, this improved method can more accurately identify the location of water accumulation in the pipeline, compare the corrosion risk of each place of water accumulation, and thus provide new theory and technical support for the assessment of internal corrosion in natural gas pipelines. (

The short-wavelength mid-infrared spectral range of the 2 μm waveband has the advantages of low transmission loss and broad gain bandwidth, making it a promising candidate for the next optical fiber communication window. It is thus highly desired to develop high-performance silicon photonic components in this waveband. Here, an efficient dual-layer grating coupler was designed on a 220 nm thick silicon-on-insulator based on raised polysilicon to address the low directionality issue. For the fiber tilted at an angle of 10°, the grating coupler’s simulated coupling efficiency reaches 80.3% (−0.95 dB) at a wavelength of 2002 nm. The 1 dB bandwidth is 66 nm. The structure is completely compatible with the standard silicon photonic fabrication process, making it suitable for large volume fabrication.

The realm of online international Chinese language teaching is undergoing significant transformations propelled by the internet and the pandemic. The digital teaching is the way forward for online international Chinese language teaching. There are significant differences between online international Chinese language teaching and traditional Chinese language teaching. To improve online teaching activities and guide future research, this growing field aims to analyze Chinese international online education research. Specifically, the goal is to develop a sustainable teaching model. By utilizing Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P), the authors analyzed 27 articles proposing a viable teaching model. The review identifies six models of online Chinese language teaching: flipped classroom, APP software, open online platform, online interaction, blended learning, and ChatGPT. The blended learning model is considered the most effective but still faces limitations such as technical issues, demanding teachers, lack of motivation, limited face-to-face interaction, and limited assessment options. Scholars suggest solutions including technical support, teacher training, motivation, improving face-to-face interaction, and using multiple assessment methods. Overall, the blended teaching model has the potential to advance online international Chinese language teaching in the future.

Compound aircraft, merging the advantages of two or more aircraft, is now a promising concept for designing modern aircraft. How to achieve successful docking of two aircraft in flight is an important issue for the applications of vertical compound aircraft. In order to resolve such an issue, this paper proposes a new visual based navigation docking scheme, which is different from rendezvous and docking operations in space applications. The present scheme uses a monocular camera mounted on the chaser aircraft with a certain installation angle to collect the visual features of the target aircraft, then the position and attitude of the landing gear of the target aircraft can be determined. Moreover, a six degrees of freedom docking mechanism mounted on the chaser aircraft is designed to catch hold of the landing gear tires of the target aircraft. In order to avoid undesired collision during the docking process, Z-direction position of the target landing gear is predicted and the proposed Z-direction speed control algorithm is applied to the chaser platform. The robustness of the present scheme has been validated numerically and experimentally by means of a chaser platform and a target platform on the ground testbed. Successful docking of the chaser platform and the target landing gear has been achieved, respectively, when the target platform performs a Z-direction movement and a compound movement.

Slope-stability assessment involves the location of the critical slip surface and the corresponding factor of safety (FOS). Considering force-vector characteristics, the vector sum method was further studied based on the strength reduction definition of the FOS and stress field of slope, and the FOS can be calculated directly by the force limit equilibrium equation on the global sliding direction of the slope. For the sliding direction, it is rigidly proved to be determined only by the sliding shear stress along the slip surface based on the principle of minimum potential energy. Then, two examples with fixed slip surfaces were analyzed and the results were compared with the rigorous Morgenstern–Price method. Finally, two examples from the literature are investigated for searching the critical slip surface using the proposed method and a real-coded genetic algorithm. The calculated results revealed the rationality of the proposed method for both fixed slip surfaces and critical slip surfaces from the literatures in slope stability assessment. This proposed method provides a new path to assess the slope stability, which is worth to be further studied in practical engineering.

Iron phthalocyanine with a 2D structure and symmetric electron distribution around Fe-N4 active sites is not optimal for O2 adsorption and activation. Here, the authors report an axial Fe–O coordination induced electronic localization strategy to enhance oxygen reduction reaction performance.

As the emerging member of zero-dimension transition metal dichalcogenide, WSe2 quantum dots (QDs) have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size. However, low power consumption and high reliability are still challenges for WSe2 QDs-based memristors as synaptic devices. Here, we demonstrate a high-performance, superlow power consumption memristor device with the structure of Ag/WSe2 QDs/La0.3Sr0.7MnO3/SrTiO3. The device displays excellent resistive switching memory behavior with a ROFF/RON ratio of ~5 × 103, power consumption per switching as low as 0.16 nW, very low set, and reset voltage of ~0.52 V and~ -0.19 V with excellent cycling stability, good reproducibility, and decent data retention capability. The superlow power consumption characteristic of the device is further proved by the method of density functional theory calculation. In addition, the influence of pulse amplitude, duration, and interval was studied to gradually modulating the conductance of the device. The memristor has also been demonstrated to simulate different functions of artificial synapses, such as excitatory postsynaptic current, spike timing-dependent plasticity, long-term potentiation, long-term depression, and paired-pulse facilitation. Importantly, digit recognition ability based on the WSe2 QDs device is evaluated through a three-layer artificial neural network, and the digit recognition accuracy after 40 times of training can reach up to 94.05%. This study paves a new way for the development of memristor devices with advanced significance for future low power neuromorphic computing.

In order to solve the problem of low mechanization level of hairy vetch harvesting, a feeding device for an anti-winding hairy vetch harvester was designed. Firstly, the physical properties of hairy vetch stalk were studied. According to the mechanical properties of hairy vetch stalk, the key components of the feeding device were designed and analyzed, the structure and working principle of the feeding device were described. Secondly, the discrete element method was used to simulate and analyze the movement performance of the feeding device. On this basis, the ternary quadratic regression orthogonal rotation combination test was established with the vertical drum, the machine forward speed, and the spiral conveyor speed as the test factors and the stem loss rate as the test index. The simulation results showed that when the vertical drum was 1037.5 r/min, the machine forward speed was 2.76 m/s, the spiral conveyor speed was 348.88 r/min, and the straw loss rate was 2.38%, and the feeding device performs best at this time. Finally, the on-site performance test of the feeding device was carried out. The results showed that: all the test indicators met the requirements of the national standard; the actual cutting width was 1.66 m; the cutting stubble height was 6.41 mm; the over stubble loss rate was 0.45%; the missed cutting loss rate was 0.20%; and the stem loss rate was 3.00%, which verified the rationality of the design of the feeding device. In order to solve the problem of low mechanization level of hairy vetch, which easily becomes entangled in the working process, an anti-winding feeding device for hairy vetch harvesting was designed.

The development of the commercial multi global navigation satellite system (GNSS) dual (multi)-antenna common-clock receiver that uses time-synchronization technology has brought new opportunities for high-precision GNSS-based attitude determination. In this article, for the first time, we present a performance comparison of global positioning system (GPS) L1/Galileo navigation satellite system (Galileo) E1 attitude determination with a common-clock receiver using four different models, i.e., the loosely combined single-differenced (SD-LC) model, the tightly combined single-differenced (SD-TC) model, the loosely combined double-differenced (DD-LC) model, and the tightly combined double-differenced (DD-TC) model. We first introduce the SD-LC, SD-TC, DD-LC, and DD-TC relative positioning models with GPS L1/Galileo E1 observations from a common-clock receiver. Then, we present a performance comparison of the four models in both single-epoch and multi-epoch modes using static data collected with a Trimble BD992 common-clock receiver in terms of the ambiguity dilution of precision (ADOP), the ambiguity resolution (AR) success and failure rates, and the positioning and attitude determination accuracy. In the case of the single-epoch mode, the experimental results revealed that the results of the single-differenced (SD) models were identical to those of double-differenced (DD) models, i.e., the results of SD-LC and SD-TC models were identical to DD-LC and DD-TC models, respectively. Moreover, compared with the loosely combined model (SD-LC/DD-LC), the tightly combined model (SD-TC/DD-TC) delivered a much higher AR success rate and a lower AR failure rate, especially under a high elevation cutoff angle. The AR success rate increased by approximately 35.1% under a 40° elevation cutoff angle, while the AR failure rate decreased by approximately 4.3%. In the case of the multi-epoch mode, the experimental results confirmed the advantages of the tightly combined model over the loosely combined model as well as the SD model over the DD model. Compared with the DD-LC and SD-LC models, the AR success rates of the DD-TC and SD-TC models were improved by approximately 16.7% and 0.6% under a 45° elevation cutoff angle, respectively. The AR failure rates were reduced by approximately 12.4% and 0.3%, respectively. Moreover, compared with the DD-LC and DD-TC models, the AR success rates of the SD-LC and SD-TC models under a 45° elevation cutoff angle were improved by approximately 24.0% and 7.9%, respectively, and the AR failure rates were reduced by approximately 19.9% and 7.8%, respectively. Meanwhile, compared with the DD model, the SD model delivered comparable yaw accuracy and remarkably better pitch accuracy. The pitch accuracy was improved by approximately 65.2–75.0%.

The structural behavior of precast concrete segmental bridges (PCSBs) is affected by the joints between the concrete segments. In this study, a numerical model was established to investigate the direct shear behavior of single-keyed dry joints in PCSBs. The numerical model was validated by the full-scale test results published by the authors. It was found that the numerical results of the joints, such as the ultimate shear load, cracking pattern, and load-displacement curves, matched the test results well. The validated numerical model was further used for extending parametric studies. The factors affecting the shear behavior of single-keyed dry joints include the confining pressure, concrete strength, and key depth. It was found that the ultimate shear capacity increased about 121% when the confining pressure increased from 0.1 to 3.0 MPa, it was very low under confining pressure of 0.1 MPa; it increased about 44% when the concrete strength increased from C40 to C100; it increased about 203% when the key depth increased from 15 to 40 mm. However, the ultimate shear capacity decreased about 20% when the key depth increased from 40 to 60 mm, hence 40 mm was recommended for the design depth of the single-keyed dry joints in PCSBs. Finally, the parametric analysis results were compared with the AASHTO specification. When the key depth was 35, 40 and 45 mm, the AASHTO specification conservatively predict the shear strength capacity of single-keyed dry joints.

Feature selection is an essential step in the preprocessing of data in pattern recognition and data mining. Nowadays, the feature selection problem as an optimization problem can be solved with nature-inspired algorithm. In this paper, we propose an efficient feature selection method based on the cuckoo search algorithm called CBCSEM. The proposed method avoids the premature convergence of traditional methods and the tendency to fall into local optima, and this efficient method is attributed to three aspects. Firstly, the chaotic map increases the diversity of the initialization of the algorithm and lays the foundation for its convergence. Then, the proposed two-population elite preservation strategy can find the attractive one of each generation and preserve it. Finally, Lévy flight is developed to update the position of a cuckoo, and the proposed uniform mutation strategy avoids the trouble that the search space is too large for the convergence of the algorithm due to Lévy flight and improves the algorithm exploitation ability. The experimental results on several real UCI datasets show that the proposed method is competitive in comparison with other feature selection algorithms.

End resistance is a dominant variable in the sinking process of super-sized caisson foundation, which is of great importance to the safe sinking of the caisson foundation. Based on soil excavation process of super large caisson foundation of the main tower of Changtai Yangtze River Bridge, the distribution characteristics and variation of earth pressure under the foot blade was analyzed using 3D finite element method at the first stage of soil excavation. Furthermore, the earth pressure was monitored in real time during soil excavation in order to analyze the influence of soil excavation process on the distribution of earth pressure. The analysis results of engineering practice showed that in the process of soil excavation from inner area to outer area, the end resistance of inner bulkhead and inner partition walls decreased, while the end resistance of outer bulkhead and outer partition walls gradually increased till the soil reached the failure state in the outer bulkhead area. The distribution characteristics and variation of the earth pressure can really reflect overall stress state of caisson foundation, which helps guide the safe sinking by soil excavation.

This systematic review aims to explore social media integration in K-12 foreign language (FL) classrooms in the past decade and discusses the unique challenges of adopting social media in K-12 FL teaching. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and selection criteria, 12 studies between 2010 and 2019 were selected. Adopting a grounded analytical method, this review provides a synthesis of the affordances and challenges of social media integration in K-12 FL education. Based on the data analysis, an effective approach to integrating social media in K-12 FL education is proposed, to connect formal and informal learning environments. This review concludes with suggestions and directions for future research on the integration of social media in K-12 FL classrooms.