Information encryption and anti-counterfeiting play an important role in many aspects of daily life, such as in minimizing economic losses, protecting secure communication and public security, and so on. Owing to the high information capacity and ease of operation, luminescent materials for advanced information encryption and anti-counterfeiting are essential to meet the increasing demand on encryption security. Herein, we summarize two emerging luminescent materials for information encryption and anti-counterfeiting, the AIE materials and room-temperature phosphorescent materials. At last, we discuss the opportunities and anticipations of these two information encryption and anti-counterfeiting materials.

Research on the development of new lightweight Al-Li alloys using selective laser melting pro-cess has great potential for industrial applications. This paper reports on the development of novel aluminum-lithium alloys using selective laser melting technology. Al-Cu-Li-Mg-Ag-Sc-Zr pre-alloyed powders with lithium contents of 1 wt.%, 2 wt.% and 3 wt.%, respectively, were prepared by inert gas atomization. After SLM process optimization, the microstructure and me-chanical properties of the as-formed specimens were investigated. The densification of the three newly developed alloys are 99.51 %, 98.96 % and 92.01 %, respectively. They all have good form-ability, with the lithium loss rate about 15 %. The as-formed alloy with 1% Li content presents good comprehensive properties with a yield strength of 412.6 ± 16.0 MPa, an ultimate tensile strength of 461.1 ± 11.7 MPa, and an elongation of 13.6 ± 1.1%. The three alloys exhibit a layered molten pool stacking morphology and have a typical heterostructure. The columnar crystals and equiaxed fine grains are alternately arranged, and most of the precipitated phases are enriched at the grain boundaries. The change of Li content mainly affects the precipitation of Cu-containing phase. When the Li content is 1 wt.%, there are θ phase, T1 phase and TB phase. When Li increased to 2 wt.%, T1 and T2 phases precipitated together. When Li reaches 3 wt.%, δ' phase precipitates with T2 phase. This study provides useful guidance for the future SLM form-ing of new crack-free and high-strength Al-Li alloys.

As the lifespan of porous asphalt pavement extends, it invariably experiences performance degradation and an increase in tire/pavement noise compared with the original surface when it is newly built. To understand the medium-term performance of porous asphalt pavement during service and reveal the influence of different pavement performance indicators on tire/pavement noise generation, a seven-year continuous observation and data analysis study was conducted. Porous asphalt with different designed material parameters was taken into account, including thin-layer porous asphalt overlay with a maximum nominal aggregate size of 10mm (PUC-10), porous asphalt with a maximum nominal aggregate size of 13mm (PAC-13), and a two-layer porous asphalt incorporating both PUC-10 and PAC-13 (PUC-10+PAC-13). Using automated pavement technology testing equipment, key performance indexes, including damage rate (DR), rut depth (RD), international roughness index (IRI), and sideway force coefficient (SFC), were measured and calculated. The on-board sound intensity (OBSI) method was used to test noise levels in three types of porous asphalt pavement structures and on a dense graded easy compact asphalt concrete (ECA) for comparison. The progressions of the medium-term performances were analyzed according to the measured results. The correlations between tire/pavement noise levels and testing speed, testing lane, pavement structure, and road condition indicators were investigated by regression. The research results revealed that the DR and SFC of the three types of porous asphalt pavement displayed more significant attenuation in the service period, while the IRI and RD showed small changes. Among them, the SFC demonstrated significant attenuation over the first 4 years, decreasing between 13.8% and 17.0%. From the 3-7 years of operation, the transverse crack disease in porous asphalt pavement progressed rapidly. The three porous asphalt pavement structures tested exhibited commendable noise reduction capabilities. Compared to ECA, the OBSI noise levels of these structures were lower by 2.09 dB, 1.53 dB, and 2.88 dB, respectively. Compared to other pavement condition indicators, RD had a more significant impact on the OBSI value of the PUC-10 porous asphalt pavement. For the PUC-10+PAC-13 porous asphalt pavement, there was a significant linear relationship between the OBSI value and SFC, mainly due to polishing of the coarse aggregate surface. It leads to a decrease of the micro-texture, which lies in increasing tire/pavement noise at high-frequency ranges and decreasing SFC. This study will have guiding significance for the research of the attenuated law and durability improvement of porous asphalt tire/pavement noise.

Variety of harmful gases are produced in asphalt mixture after mixing, paving and rolling process. Effective measures must be tak-en to suppress the asphalt pavement in the tunnel due to fire accidents and other toxic gases and fumes, reducing the human health during the construction process. In this study, a flame retardant and smoke suppressant (compound) with Mg(OH)2 as the main component was developed, the flame retardant asphalt mixture and asphalt mastics were prepared to evaluate the flame retard-ant-smoke suppressant properties and performance effects. Firstly, its low and high temperature performances were investigated with the bending beam rheometer (BBR) and dynamic shear rheological (DSR), respectively. Then, the indoor combustion test and the cone calorimeter test were used to evaluate the fire retardant smoke suppression effect of the asphalt mastic. Thirdly, the flame retardant effect of asphalt mastic mixed with the compound was further analyzed by thermogravimetric (TG) test and scanning electron microscopy (SEM). The pyrolysis temperature, mass loss and microscopic state of asphalt surface were used to verify and explain the flame retardant reaction effect and process of the compound. Finally, the asphalt mixture performance was evaluated, as well as the flame retardant smoke suppression effect was verified by asphalt mixture combustion tests. The results showed that the flame retardant smoke suppression time of the flame retardant asphalt mixture was reduced by 66% and the smoke emission area was reduced by 20%. The flame retardant smoke suppression effect of the asphalt mixture was improved by 44%. The flame-retardant and smoke-suppressing compound and the asphalt mixture with the compound prepared in this study meet the asphalt mixture performance and flame retardant smoke suppression function, providing an option for application of fire retardant and smoke-suppressing asphalt pavement materials in tunnels.

This study provides a novel method to prepare metal-ceramic composites from magnetically selected iron ore using microwave heating. By introducing three different microwave susceptors (Activated Carbon, SiC, and a mixture of Activated Carbon and SiC) during the microwave process, effective control of the ratio of metallic and ceramic phases has been achieved easily. The effects of the three susceptors on the microstructure of the metal-ceramics and the related reaction mechanisms were also investigated in detail. The results show that the metal phase (Fe) and ceramic phase (Fe2SiO4, FeAl2O4) can be maintained, but the metal phase to ceramic phase changed significantly. In particular, the microstructures appeared as well-distributed nanosheet structures with diameters of ~400 nm and thicknesses of ~20 nm when SiC was used as the microwave susceptor.

As a member of smart materials, electrorheological elastomers (EREs) formed by pre-treating active electrorheological particles are attracting more and more attention. In this work, four Mg-doped strontium titanate particles with spherical, dendritic, flake-like and pinecone-like morphorlogies were obtained by hydrothermal and low-temperature co-precipitation. XRD, SEM, Raman and FT-IR were used to characterize the obtained products. The results showed that the sizes of Mg-doped strontium titanates are about 1.5‒2.0 μm, and the phase structure are dominated by cubic crystal. These Mg-doped strontium titanates were dispersed in a hydrogel composite elastic medium. Then, Mg-doped strontium titanate/glycerol/gelatin electrorheological composite hydrophilic elastomers were obtained with or without electric field. The electric field response properties of Mg-doped strontium titanate composite elastomers were investigated. It concluded that dendritic Mg-doped strontium titanate composite elastomers is high-performance EREs. And the maximum value of energy storage modulus of Mg-doped strontium titanate composite elastomers has achieved 8.70 MPa. This high electrorheological performance of the products is helpful for their applications in vibration control, force transducers, smart structures, dampers, and other fields.

Fiber distributed optical fiber acoustic sensor (DAS) is generally used in distributed long-distance acoustic/vibration measurement. We found that DAS with excellent performance of low self-noise and anti-fading in combination with the plastic structure in daily life as an acoustic transducer can achieve high-sensitivity acoustic measurement at a single point rather than designing a state-of-the-art acoustic transducer or using special enhanced scattering fiber. The simple acoustic transducer we proposed for DAS can reach the sensitivity level of -106.5dB re. 1rad/μPa at a sensing range of 5.1 km, which can meet many demands on the industrial site.

Endoscopic retrograde cholangiopancreatography (ERCP) is a routinely used therapeutic procedure for the biliary and pancreatic diseases. Population aging may increase the typical indications of ERCP and come with more complexity and difficulties, especially in cannulation. This study aimed to evaluate the incidence, causes, and management of difficult biliary cannulation during ERCP in super-aged patients and the role of difficult cannulation as a risk factor for adverse events. A total of 614 patients, underwent ERCP, were prospectively studied as a cohort and divided into two groups based on their age. There were 146 patients aged 80 years or older in group A and 468 patients aged less than 80 years in group B. The primary outcome measures were the difficulty grade of papilla cannulation, clinical outcomes, and ERCP-related complications in the two groups. The adverse events were analyzed using logistic regression for patient age, co-morbidities, indications, and cannulation difficulty grade variables. There was no difference in the incidence of difficult cannulation between the two groups (32.9% vs. 34.4%, p=0.765) though, as expected, super-aged Group A had a higher prevalence of periampullary diverticulum (29.5% vs. 16.7%, p=0.001). The technical cannulation success rate was (96.6% vs. 96.8%, p= 0.54). All used cannulation techniques in the elderly group were efficient and safe. Logistic regression showed that age ≥80 was not associated with increased adverse events; however, difficult cannulation (adjusted odds ratio [AOR]=3.478; 95% confidence interval [CI]=1.877, 6.442; p<0.001) and CCI ≥2 (AOR=1.824; 95% CI=0.993, 3.349; p=0.045) were more likely to have adverse events. Age ≤65 (AOR=3.460; 95% CI=1.511, 7.922; p=0.003), female gender (AOR=2.362; 95% CI=1.089, 5.124; p=0.030), difficult cannulation (AOR=4.527; 95% CI=2.078, 9.860; p<0.001), and patients with cholangitis (AOR=3.261; 95% CI=1.204, 8.832; p=0.020) were strongly associated with increasing Post-ERCP Pancreatitis (PEP). Advanced age has not proved to be a risk factor of difficult cannulation, and secondary cannulation techniques can be safely and efficaciously utilized for this group. CCI ≥2 and difficult cannulation are associated with increased overall adverse events rate while age ≥80 factor is not.

In this study, we discuss the thermospheric density response to the solar activity and QBO. By using the wavelet power spectrum method, the thermospheric density from 1967 to 2013 shows ~11-year period, semiannual and annual variations, while the seasonal variation is usually more significant under high solar activity conditions. Importantly, we investigate the possible link between the density and the QBO, with the aid of GAMDM model and different density residual method. As a result, the difference between the measured density and empirical model seemingly has QBO signal, but the ratio of them revels that the QBO signal does not exist in the thermospheric density. Comprehensively, we thought the stratospheric QBO cannot impact on the thermosphere, and more data and numerical modeling are needed for further validation.

The paper discusses the classification of fuzzy metrics based on their continuity conditions, dividing them into Erceg, Deng, Yang-Shi, and Chen metrics. It explores the relationships between these types of fuzzy metrics, concluding that a Deng metric in [0,1]-topology must also be Erceg, Chen, and Yang-Shi metrics. The paper also proves that the product of countably many Deng pseudo-metric spaces remains a Deng pseudo-metric space, and demonstrates some σ-locally finite properties of Deng metric space. Additionally, the paper constructs two interrelated mappings based on normal space and concludes that if a [0,1]-topological space is T1 and regular, and its topology has a σ-locally finite base, then it is Deng metrizable, and thus Erceg, Yang-Shi, and Chen metrizable as well.

Based on three-dimensional optical proximity correction (3D OPC), recent advancements in 3D lithography have enabled the high-fidelity customization of 3D micro-optical elements. However, micron-to-millimeter scale structures represented by Fresnel lens design bring more stringent requirements for 3D OPC, which poses significant challenges to the accuracy of models and the efficiency of algorithms. Thus, a lithographic model based on optical imaging and photo-chemical reaction curve is developed in this paper, and a sub-domain division method with a statistics principle is proposed to improve the efficiency and accuracy of 3D OPC. Both the simulation and the experimental results showed the superiority of the proposed 3D OPC method in the fabrication of the Fresnel lenses. The computation memory requirements of the 3D OPC are reduced to below 1 %, and the profile error of the fabricated Fresnel lens reduced 79.98%. Applying the Fresnel lenses to an imaging system, the average peak signal to noise ratio (PSNR) of the image increased by 18.92 %, and the average contrast of the image enhanced by 36 %. We believe the proposed 3D OPC method can be extended to the fabrication of vision-correcting ophthalmological lenses.

The ground surface deformation induced by shield tunnels passing through enclosure structure of existing tunnels is a particular underground construction scenario, which is encountered in Wuhan metro line 12 engineering cases in China. The classic ground deformation theory is difficult to accurately predict this ground deformation. This paper develops a semi-analytical method to predict ground heave considering space effect in this engineering condition. Based on improved ground deformation theory, a novel deformation prediction method of ground and enclosure structure is derived combined with Kirchhoff plate theory. Comparing with field deformation measurements, the maximum difference between measured and calculated deformation is 14.6%, which demonstrating that the proposed method can be used to predict the ground heave induced by shield tunnels passing through the enclosure structure of existing tunnels. The parameters of underground diaphragm wall used in Wuhan metro line 12 are further studied in detail. The results show that the ground heaves have positive correlation with embedded ratio of diaphragm wall, but negative correlation with its elastic modulus and thickness. But the thickness and embedded ratio has a limited effect on ground heaves. This study provides a technical reference for optimization setting of enclosure structure in protecting existing building.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

Objective To observe the effect of roxadustat on blood pressure and micro-inflammatory response in patients with hemodialysis anemia, and to provide a viable technique for the treatment of hemodialysis anemia patients. Methods A total of 100 hemodialysis anemia patients admitted to the Nephrology Department of our hospital from July 2020 to July 2021 were enrolled and randomly divided into an observation group (roxadustat) and a control group (human recombinant erythropoietin (rhEPO). The clinical efficacy, blood lipid metabolism, inflammatory factor levels, iron metabolism-related indicators, blood biochemical indicators, anemia indicators, adverse reactions and blood pressure were recorded and compared. Results There was no significant difference in baseline data and serum indicators (P>0.05). The study group demonstrated superior performance to the control group in terms of clinical efficacy, blood lipid metabolism, inflammatory factor levels, iron metabolism-related indicators, blood biochemical indicators, anemia indicators, adverse reactions and blood pressure (all P<0.05). Conclusion Compared with rhEPO treatment, roxadustat exhibits a promising outcome in treating anemia and has slight impact on blood pressure of patients.

Cadmium(Cd) is a highly toxic and cumulative environmental pollutant. Siderophores are heavy metal chelators with high tolerance to heavy metals such as Cd. Furthermore, ryegrass (Lolium perenne L.) has potential remediation capacity for soils contaminated by heavy metals. Consequently, using ryegrass alongside beneficial soil microorganisms that produce siderophores may be an effective means to remediate soils contaminated with Cd. In this study, Bacillus strains WL1210 and CD303 that were previously isolated from the rhizospheres of Nitraria tangutorum in Wulan and Peganum harmala L in Dachaidan, respectively, both arid sandy environments, were evaluated for heavy metal pollution mitigation. The results indicate that both strains of Bacillus exhibit favorable biological characteristics and stress resistance, and they are both producers of siderophores, which promote the growth of ryegrass under Cd stress.

Monin-Obukhov similarity theory (MOST) overestimates wind shear in some atmospheric stable conditions, i.e. Richardson number $R_f<0.25$. The overestimated wind shear that leads to an under-predicted friction wind speed and a lower ambient turbulence intensity for a given hub-height reference wind speed and a given roughness length, could influence wake modeling of a wind turbine. This work investigates the side effects of the breakdown of MOST on wake modeling under stable conditions and makes some modifications to the flow similarity functions to eliminate these side effects. Based on a field measurement in a wind farm, we firstly show that MOST predicts a larger wind shear for the atmospheric stability parameter $\zeta>0.1$ and proposes new flow similarity functions without constraining $R_f$ to limit the overestimated wind shear by MOST. Next, different turbulence models based on MOST and a modified one based on the new similarity functions are investigated through numerical simulations. These turbulence models are combined with the actuator disk model (AD) and Reynolds-averaged Navier–Stokes equations (RANS) to model wind turbine wakes under stable conditions. As compared to measurements, numerical results show that turbulence models based on MOST result in larger wake deficits and slower wake recovery rate with a square root of the mean-squared-error (RSME) of wake deficit in the range of 0.07-0.18. This overestimated wake effect is improved by applying the new similarity functions and the RSME of wake deficit is averagely reduced by 0.05. Finally, we check the role of the under-predicted turbulence intensity playing in the larger wake deficit predicted by models based MOST. Additional numerical simulations using the modified turbulence model are carried out, in which the roughness length is reduced to impose a hub-height ambient turbulence intensity equivalent to the MOST case. Simulation results show that reducing turbulence intensity enhances wake effects, however, it cannot reproduce the large wake deficit predicted by models based on MOST, which suggests that the overestimated wake effect by MOST could be also related to the overestimated wind shear.

In this paper, we present a groundbreaking methodology in the realm of aspect-level sentiment analysis, which capitalizes on the advanced capabilities of graph-based neural networks. Our approach, distinguished as the Aspect Correlation Graph Network (ACGN), represents a significant departure from conventional models. These traditional models often analyze aspects in isolation, failing to capture the intricate web of sentiment relationships that may exist within a single sentence. ACGN, however, is designed to address this gap by employing a sophisticated bidirectional attention mechanism, integrated with positional encoding. This unique combination not only enhances the model's ability to focus on relevant parts of the sentence but also aids in constructing detailed, aspect-focused representations. These representations are particularly crucial for understanding the nuanced interplay of sentiments associated with different aspects. Central to our model's architecture is the incorporation of a graph convolutional network. This network serves as a pivotal component in mapping and analyzing the complex network of sentiment correlations that can exist among various aspects within sentences. Through this integration, ACGN is able to unearth and interpret the subtle and often overlooked sentiment dynamics that traditional models might miss. Our comprehensive evaluations of the Aspect Correlation Graph Network, conducted using the SemEval 2014 datasets, have yielded promising results. These findings demonstrate a clear and significant advancement over the capabilities of existing models. Particularly, the results underscore the critical importance and utility of recognizing and understanding the connections between sentiments of different aspects in text analysis. This insight opens new avenues in the field of sentiment analysis, suggesting a broader application potential of ACGN in various contexts where understanding nuanced sentiment relationships is key. Overall, our study not only introduces a novel approach in aspect-level sentiment analysis but also sets a new standard for future research in this area. By highlighting the integral role of inter-aspect sentiment connections, ACGN paves the way for more sophisticated and accurate sentiment analysis tools, capable of handling the complexities of natural language with greater finesse and precision.

Open bidding is widely used in Sinopec's material procurement due to its advantages of openness, transparency, and cost savings. However, there have been many complaints about collusive bidding in recent years. Collusive bidding will pose significant challenges to fair competition and increase project costs for material procurement. Therefore, there is an urgent need for an analysis model to identify and prevent the collusive bidding. In this paper, we propose a statistical model for identifying collusive bidding using the coefficient of variation cv, the ratio of high to low average quotation rP and the deviation rate of quotation δ as indicators, based on the statistics of the historical quotations for material A. Through a case study of the framework agreement bidding for material B, we identified the collusion behavior of bidders effectively, thereby verifying the applicability of this statistical model.

Continuous rigid frame bridges across valleys are often at the risk of rockfalls caused by heavy rainfalls, earthquakes and debris flows in a mountainous country. Hollow thin-walled bridge piers (HTWBP) in valleys are exposed to the threat of the impact of accidental rockfalls. In the current research, ANSYS/LS-DYNA is used to establish a high-precision rockfall-HTWBP model. The rockfall-HTWBP model is verified against a scaled impact test of a previous research. A mesh independence test is also performed to obtained an appropriate mesh size. Based on the rockfall-HTWBP model, the impact force, damage and dynamic response characteristics of HTWBP under the rockfall impact are studied. In addition, a damage assessment criteria is proposed based on the response surface model combined with Central Composite Design method and Box-Behnken Design method. The main conclusions are as follows: 1）The impact force of rockfall has a substantial impulse characteristic, and the duration of the impulse load is approximately 0.01s. 2）The impacted surface of the pier is dominated by the final elliptic damage with the conical and strip damage areas as the symmetry axis. The cross-sectional damage mode is compression failure in the impact area and shear failure at the corner. 3）The maximum displacement occurs in the middle height of the pier. The maximum displacement increases with impact height, impact velocity and rockfall diameter and decreases with the uniaxial compressive strength of the concrete. 4) The initial impact velocity and diameter of the rockfall are the most significant parameters affecting the damage indices. In addition, a damage assessment method with a damage zoning diagram based on the response surface method is established for the fast assessment of the damage level of impacted HTWBP.

The need for cross-modal retrieval (CMR) among users is growing because of the swift advancements in computer vision and natural language processing. Promoting home operating systems is greatly aided by the openKylin home operating system. It is focused on enhancing the functionality of the operating system with safe and dependable operating technologies. Practical implications abound for integrating computer vision research into home operating systems. A multimodal retrieval approach based on openKylin is presented to improve the usability of text search graphs, audio, and video. The overview of pertinent domestic and international research is the main topic of this article. This technological advancement. It then offers details on the design, implementation procedure, and final implementation outcomes for demonstration. The works of natural operations show that this strategy has excellent accuracy and performance.

Viruses can infect a cell via one or both routes viz. cell-to-cell (c-c) or cell-free (c-f) . Pathogenesis studies of various viruses, including HIV, have shown that c-c transmission yields a significantly higher infection magnitude than the c-f route. Expectedly, potent antibodies inhibited c-f infection more efficiently than with c-cell transmission. To achieve a one-step, synchronous infection cycle that provides amplified infection, we have studied a consistent and efficient c-c HIV infection model since 1992. H9 cells persistently infected with HTLV-IIIB (H3B cells) and uninfected target CD4+ lymphocyte line (HuT78) were mixed in a ratio of 1:4 respectively. We have recently used this model to produce HIV designer antigens that have been shown to elicit monoclonal as well as polyclonal specific antibodies against novel epitopes that are formed post virus-cell engagement, but prior to fusion. The model can be extended for HIV neutralizing antibody assays or drug inhibitors against high multiplicity of infection.

(1) In recent ten years, with the fast development of digital and engineering manufacturing technology, additive manufacturing has already been more and more widely used in the field of dentistry, from the first personalized surgical guides to the latest personalized restoration crowns and root implants. (2) Especially, the bioprinting of teeth and tissue is of great potential to realize organ regeneration and finally improve the life quality. (3) In this review paper, we firstly presented the workflow of additive manufacturing technology. Then we summarized main applications and recent research progresses of additive manufacturing in dentistry. (4) Lastly, we sketched out some challenges and future directions of additive manufacturing technology in dentistry.

In recent years, there has been significant growth in the ubiquity and popularity of three dimensional(3D) point clouds, with an increasing focus on the classification of 3D point clouds. To extract richer features from point clouds, many researchers have turned their attention to various point set regions and channels within irregular point clouds. However, this approach has limited capability in attending to crucial regions of interest in 3D point clouds and may overlook valuable information from neighboring features during feature aggregation. Therefore, this paper proposes a novel 3D point cloud classification method based on global attention and adaptive graph convolution. The method consists of two main branches: the first branch com-putes attention masks for each point, while the second branch employs adaptive graph convolu-tion to extract global features from the point set. It dynamically learns features based on point interactions, generating adaptive kernels to effectively and precisely capture diverse relationships among points from different semantic parts. Experimental results demonstrate that the proposed model achieves 93.8% in overall accuracy and 90.8% in average accuracy on the ModeNet40 dataset.

Atmospheric stability affects wind turbine wakes significantly. High-fidelity approaches such as large eddy simulations (LES) with the actuator line (AL) model which predicts detailed wake structures, fail to be applied in wind farm engineering applications due to its expensive cost. In order to make wind farm simulations computationally affordable, this paper proposes a new actuator disk model (AD) based on the blade element method (BEM) and combined with Reynolds-averaged Navier–Stokes equations (RANS) to model turbine wakes under different atmospheric stability conditions. In the proposed model, the upstream reference velocity is firstly estimated from the disk averaged velocity based on the one-dimensional momentum theory, and then is used to evaluate the rotor speed to calculate blade element forces. Flow similarity functions based on field measurement are applied to limit wind shear under strongly stable conditions, and turbulence source terms are added to take the buoyant-driven effects into consideration. Results from the new AD model are compared with field measurements and results from the AD model based on the thrust coefficient, the BEM-AD model with classical similarity functions and a high-fidelity LES approach. The results show that the proposed method is better in simulating wakes under various atmospheric stability conditions than the other AD models and has a similar performance to the high-fidelity LES approach however in much lower computational cost.

Reasonable allocation of production plans and saving the overall electricity cost are crucial for large manufacturing conglomerates, which is an effective way for conglomerates to realize open-source and cost-saving. This paper develops an optimization model of off-site industrial production scheduling for enterprises in response to the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's electric power and the difficulty of promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and different electricity prices in different places to optimize the scheduling of industrial production in different places. The model is embedded with two sub-models of the electricity price prediction model and distributed photovoltaic kWh cost model to complete the model parameters, in which the electricity price prediction model utilizes the LSTM neural network. The integrated model is then solved by the particle swarm algorithm. To verify the effectiveness of the model in solving the problem of off-site production scheduling on the demand side of electricity, the research team researched two off-site pharmaceutical factories belonging to the same large pharmaceutical company. Finally, the research data were substituted into the model for solving, and it was concluded that the optimization model could significantly reduce the cost of electricity consumption of the enterprise by about 7.9 %.

In this paper, we delve into the realm of aspect-level sentiment analysis, a sophisticated analytical task focused on pinpointing and interpreting the sentiment directed towards specific elements within a sentence. Traditional methods in this domain, primarily based on neural networks, have often overlooked the critical role of syntactic structures in sentences. To bridge this gap, we have developed the Syntax-Enhanced Sentiment Graph Network (SentiSyn). This pioneering model represents a significant step forward in aspect-level sentiment analysis, bringing to the forefront the utilization of word dependency relationships to enrich sentiment analysis. SentiSyn stands out by its innovative use of a dependency graph, a tool that meticulously maps out the intricate web of syntactic relationships surrounding a target aspect in a sentence. This approach allows SentiSyn to effectively capture and channel sentiment-related characteristics that are deeply rooted in the syntactic context of the aspect target. By doing so, SentiSyn unlocks a deeper understanding of sentiment dynamics in textual content, enabling a more nuanced and accurate sentiment analysis. Our comprehensive experimental evaluation of SentiSyn showcases its remarkable capabilities. When combined with advanced embedding techniques like GloVe and BERT, SentiSyn demonstrates a superior performance edge over several existing sentiment analysis methods. This performance leap is not just incremental; it represents a significant enhancement in the field of sentiment analysis, underscoring the importance of syntactic context in understanding sentiments. Furthermore, our analysis delves into how SentiSyn effectively leverages these embeddings to gain a more profound and contextually rich insight into sentiment dynamics. The results from our tests indicate that SentiSyn, with its unique approach to integrating syntactic structures and advanced embeddings, sets a new benchmark in aspect-level sentiment analysis, offering both enhanced accuracy and deeper sentiment understanding.

According to the development needs of marine seismic station networking, it is necessary to develop a marine seismometer with a networking function to realize quasi-real-time and large-scale long-term observation of undersea seismic signals. This can lay a solid foundation for marine seismic research and research on earth tectonics, activities, and processes. Based on the advantages and disadvantages of the existing observation equipment, this study proposed to develop a new type of the Autonomous Glide Marine Seismometer(AGMS) that can be applied to the global sea area, focusing on the design and study of the main structure of the carrier of the AGMS. The ultimate strength of the ellipsoidal pressure-resistant spherical shell is investigated by using the finite element analysis method. A reasonable finite element analysis model is proposed through comparing the finite element parameter results with the theoretical formulas and relevant specifications. Finally, the design process and strength checking of the pressure-resistant shell of the AGMS are established. These relevant results can also provide a reference for the design of other deep-sea pressure-resistant chambers.

The Station logo is a way for a TV station to claim copyright, which can realize the analysis and understanding of the video by the identification of the station logo, so as to ensure that the broadcasted TV signal will not be illegally interfered. In this paper, we design a station logo detection method based on Convolutional Neural Network by the characteristics of the station, such as small scale-to-height ratio change and relatively fixed position. Firstly, in order to realize the preprocessing and feature extraction of the station data, the video samples are collected, filtered, framed, labeled and processed. Then, the training sample data and the test sample data are divided proportionally to train the station detection model. Finally, the sample is tested to evaluate the effect of the training model in practice. The simulation experiments prove its validity.

The aim of this study was to investigate the physicochemical characterization and biological activities of chitosan (CH) based composite films with the incorporation of chestnut flower essential oil (CFEO). The composite films were prepared by casting method and characterized in terms of structural, morphological and mechanical properties via FT-IR, XRD, UV, SEM and TGA. The results proved the significantly increased water vapor permeability (WVP), heat resistance, antibacterial and antioxidant capabilities of CH-CFEO films. The incorporation of CH and CFEO enhanced the UV blocking, which made the film shield almost all UV light. Films with the tensile strength of 6.37 ± 0.41 MPa and elongation at break of 22.57 ± 0.35% were got with 6 mg mL-1 CFEO. Subsequently, the fruit preservation experiments also confirmed that the composite films could effectively extend the shelf life of bananas through their excellent water vapor and oxygen barrier. These desirable performances enable our newly developed composite films to be a remarkable packaging material to solve the fresh fruit preservation dilemma.

Although the similarity laws were widely used in impact fields, the scaling relations of anisotropic elastic structures often were broken when the geometric distortion (not equal scaling in different spatial directions) and the material distortion (different materials used for scaled model and full-size prototype) were considered. To overcome the difficulty of geometric and material distortion, a directional framework of similarity laws, termed as oriented-density-length-velocity (ODLV) system, is proposed for the anisotropic elastic structure under impact loads. Different from previous similarity law systems using scalar dimensional analysis, the directional similarity law framework mainly considers spatial anisotropy for structural geometry and material parameters. Based on the oriented dimensional analysis and the orthotropic Hooke's law, directional dimensionless numbers and directional scaling relations with geometric power properties for the elastic modulus and the Poisson's ratio are presented systematically. By selecting the dominant material parameters controlling similarity, three important scaling techniques with correction of geometric width and thickness are proposed to compensate for the difficulty of distortion. A clamped square plate with different anisotropic and isotropic elastic materials subjected to dynamic pressure pulse is verified numerically and discussed in detail. The results show that the thin square plate prototype must be scaled to be the thinner/thicker rectangular plate, and the components of displacement, stress and strain between scaled model and full-scale prototype behave good consistency in both spatial and temporal fields.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

BiVO4 powder was synthesized by a simple hydrothermal method. The nanobelts with well dispersed and uniform morphology were synthesized by controlling the temperature. The structure of BiVO4 powder was studied by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The diameter of the nanobelts was about 50 nm. The structure and composition of the nanobelts were studied by X-ray diffraction (XRD), photoluminescence (PL) and X-ray photoelectron spectroscopy (XPS). The absorption intensity of BiVO4 powder in UV-Vis region was compared by UV–vis diffuse reflectance spectroscopy. As a photocatalyst, BiVO4 nanobelts have good photocatalytic ability under visible light irradiation, which is very useful for the treatment of environmental wastewater. The synthesized nanobelts photocatalyst can be reused without destroying its structure. The reusability and chemical stability of photocatalysts are of great significance for practical application.

The stator winding insulation system is the most critical and weak part of the EMU's (electric multiple unit) traction motor. The effective diagnosis for stator ITSC (inter-turn short-circuit) faults can prevent the fault from expanding into phase-to-phase or ground short-circuits. The TCU(traction control unit) controls the traction inverter to output SPWM (sine pulse width modulation) excitation voltage when the traction motor is stationary. Three ITSC fault diagnostic conditions are based on different IGBTs control logic. The Goertzel algorithm is used to calculate the fundamental current amplitude difference Δi and phase angle difference Δθ of equivalent parallel windings under the three diagnostic conditions. The six parameters under the three diagnostic conditions are used as features to establish an ITSC fault diagnostic model based on random forest. The proposed method was validated using a simulation experimental platform for ITSC fault diagnosis of EMU traction motors. The experimental results indicate that the current amplitude features Δi and phase angle features Δθ change obviously with the increase of ITSC fault extent if the ITSC fault occurs at the equivalent parallel windings. The accuracy of the ITSC fault diagnosis model based on the random forest for ITSC fault detection and location both in train and test samples are 100%.

In this paper, a method of direct spinning is proposed for direct spinning of heterogeneous spun wire-blown holes standard parts and the motherboard mounted on the spin board assemblies. The standardization of the spinneret hole was conducive to improving the machining accuracy and efficiency of the pores, and the spinneret holes could be replaced in time when a hole in the spinneret fails. Moreover; on the other hand, according to the needs of the process of spinning, the spinnerets with various cross-sections were combined and installed on the same motherboard for spinning, and the spinning obtained different bionic new functional products. Based on the results, a finite element model of the standard part of the spinneret hole was developed, and the spinnability of the combinable spinnable spinneret board was verified by simulating the melt flow in the spinneret channel through POLYFLOW software. Further, by the processing of the spinneret, the motherboard was installed into a combined spinneret, and the spinneret assembly was installed on the spinning machine for the experiments. Furthermore, the tow section was observed using a microscope, and the results showed the feasibility of the proposed method.

Lithium rich layered oxides (LRLO) are a wide class of innovative active materials for positive electrodes in lithium-ion (LIB) and lithium-metal secondary batteries (LMB). LRLOs are over-stoichiometric layered oxides rich in lithium and manganese, with general formula Li1+xTM1-xO2, where TM is a blend of transition metals comprising Mn (main constituent), Ni, Co, Fe and others. Due to the very variable composition and the extended defectivity their structural identity is still debated among researchers being likely an unresolved hybrid between a monoclinic (mC24) and a hexagonal lattice (hR12). Once casted in composite positive electrode films and assembled in LIBs or LMBs, LRLOs can delivery reversible specific capacities above 220-240 mAhg-1, thus beyond any other available intercalation cathode material for LIBs, with mean working potential above 3.3-3.4 V vs Li for hundreds of cycles in liquid aprotic commercial electrodes. In this review we critically outline the recent advancements in the fundamental understanding of the physico-chemical properties of LRLO as well as the most exciting innovations in their battery performance. We focus in particular on the elusive structural identity of these phases, on the complexity of the reaction mechanism in batteries as well as on practical strategies to minimize or remove cobalt from the lattice while preserving the outstanding performance upon cycling.

This study was conducted to determine the dynamic effects of dietary crude protein (CP) intake on nitrogen (N) balance, ileal amino acid digestibility, and gene expression levels of digestive enzymes at three stages in pigs. In Experiment 1, 18 growing pigs (average body weight (BW) = 9.5 kg) were randomly assigned to one of three treatments (n = 6/treatment group), including normal (20% CP), low (17% CP), and very low (14% CP) protein intake. In Experiment 2, 18 growing pigs (average BW = 30 kg) were allotted randomly to one of three treatments (n = 6/treatment group), including normal (18% CP), low (15% CP), and very low (12% CP) protein intake. In Experiment 3, 18 growing pigs (average BW = 45 kg) were assigned randomly to one of three treatments (n = 6/treatment group), including normal (16% CP), low (13% CP), and very low (10% CP) protein intake. Growing pigs fed the 14% CP and 17% CP diets had lower final BW (P < 0.05) and average daily gain (ADG) (P < 0.05) compared to pigs fed the 20% CP diet. Reducing the dietary CP level from 20 to 14% decreased urinary N excretion by 52.8% (P < 0.001) in Experiment 1. Reducing the dietary CP level from 18 to 12% decreased urinary N excretion by 55.3% (P < 0.001) and reduced fecal N excretion by 34% (P < 0.05) in Experiment 2. Reducing the dietary CP level from 16 to 10% decreased urinary N excretion by 56.4% (P < 0.001) and fecal N excretion by 47.1% (P < 0.001) in Experiment 3. Pigs fed the very low (14%, 12%, and 10% CP) diets showed higher digestibility for CP (P < 0.05), His (P < 0.05), Ile (P < 0.05), Phe (P < 0.05), Thr (P < 0.05), Trp (P < 0.05), Glu (P < 0.05), and Ser (P < 0.05) compared to pigs fed the normal (20%, 18%, and 16% CP) diets among the three experiments. Pigs fed the very low (14%, 12%, and 10% CP) diets showed higher mRNA levels for chymotrypsin C (P < 0.01 in Experiment 1 and 2; P < 0.05 in Experiment 3) compared to pigs fed the normal (20%, 18%, and 16% CP) diets among the three experiments. These results indicated that a reduction in dietary CP by 6% limited the growth performance of growing pigs, and a reduction of dietary CP by 3% supplemented with essential amino acids could reduce the excretion of N into the environment without affecting weight gain.

Examining the soil microbiome structure has a great significance in exploring the mechanism behind plant growth changes due to maize (Zea mays L.) and soybean (Glycine max Merr.) crop rotation. This study explored the effects of soil microbial community structure after soybean and maize crop rotation by designing nine treatments combining three crop rotations (continuous cropping maize or soybean; and maize after soybean) with three fertility treatments (organic compound fertilizer, chemical fertilizer, or without fertilizer). Soil was sampled to 30 cm depth the second year at approximately the middle of the growing season, and was analyzed for physical, chemical, and phospholipid fatty acid (PLFA) profiles. Bacteria was found to be the predominant component of soil microorganisms, which mainly contain the PLFAs i15:0, 16:1 ω 7c, 16:0, 10Me16:0, and 18:1 ω 7c. The concentration of soil gram-negative bacteria from the soybean and maize rotation was less than in soybean continuous cropping when organic fertilizer was applied to both. Crop rotation reduced the percentage of fungi in the soil, among which the effect of organic compound fertilizer application was significantly reduced 24%. The combined crop rotation with organic fertilizer can reduce maximum the percentage of fungi/bacteria. In addition, the content of soil aggregate and organic matter had great influence on gram-positive bacteria and actinomyces, and soil pH had a greater impact on other fungi.

The Internet of Things (IoT) aims to connect all objects and facilitate data interchange, with data accuracy being paramount. While IoT has seen extensive adoption in conventional sectors, its application in the petroleum industry, especially with downhole equipment, poses challenges due to the extreme high-temperature and high-pressure conditions, making accurate measurements elusive. This Paper we aim to enhance the accuracy of downhole pressure measurements in slim-hole drilling parameter monitoring, mitigate the temperature influences on strain gauges, and surmount the intrinsic limitations of the traditional BP neural network, such as sluggish convergence speeds, high sensitivity to initial weights and biases, unstable learning rates, and a tendency to fall into local minima. This study introduces a temperature compensation model using a chaotic-initiated adaptive whale optimization algorithm (C-I-WOA) to optimize a BP neural network, which is henceforth referred to as the C-I-WOA-BP model. Initially, we harnessed chaotic mapping techniques to refine the initialization process of the whale optimization algorithm (WOA) population, thereby bolstering the heterogeneity of the algorithm. Subsequently, we integrated an adaptive weight recalibration mechanism, refined the encompassing methodology of the WOA, and bolstered its capabilities for expansive global scouting and meticulous local refinement in the solution arena. Subsequently, the WOA was used to optimize the weight coefficients of the BP neural network. Finally, we conducted a detailed comparative analysis by juxtaposing the performance metrics of the BP, C-WOA-BP, I-WOA-BP, and C-I-WOA-BP networks. The experimental results indicate that the C-I-WOA-BP model demonstrates faster convergence speed, superior global search capabilities, and enhanced local exploitation potential compared to the other models. Additionally, it provides a more stable and accurate reduction in temperature-induced errors in drilling pressure parameter measurements.

With the development of electricity spot markets, accurate electricity load forecasting enables power generation companies to supply the right amount of electricity, Significantly avoid power waste. As a result, time series forecasting in the field of power can bring significant benefits. Previously, the Informer model successfully introduced the Transformer into long time series forecasting(LTSF) by proposing the ProbSparse self-attention mechanism, which solved the inherent problem of high memory complexity in self-attention. Recent research has further demonstrated the potential of the self-attention for mining complex dependencies. However, the limited amount of historical data has become one of the main challenges in applying deep learning techniques to power LSTF tasks. Previous reserches often add a large number of time covariates to provide more information. In this paper, to address this issue, (i) we design a simple but effective Season-aware Block to enhance the model’s ability to mine artificial prior information in temporal covariates; (ii) we conduct experiments using the provincial power data of Zhejiang Province, China, from 2019 to 2022, and our model outperforms other models, achieving a 19 percent MSE relative improvement; (iii) we conduct ablation experiments to assess the efficacy of the Season-aware Block in extracting temporal periodic features. Furthermore, we elucidate the underlying reasons for the effectiveness of both the self-attention mechanism and the Season-aware Block through visualization experiments.

The construction safety risks (such as landslides or slumps) of the high-fill subgrade are characterized by uncertainty and variability. In order to ensure the construction safety of the high-fill subgrade of the expressway, a comprehensive risk assessment model of high-fill subgrade construction according to the combination weighting method based on game theory was established. Firstly, settlement rate, lateral differential settlement, horizontal displacement at the foot of the slope, deep horizontal displacement, and excess pore pressure were selected as evaluation indicators, and an evaluation index system of high-fill subgrade was constructed. Secondly, the subjective and objective weights were obtained via the analytic hierarchy process and entropy method. Furthermore, the optimized weights were obtained by introducing game theory, and the construction risk of the high-fill subgrade was evaluated and analyzed using the fuzzy comprehensive evaluation method. Finally, based on the high-fill section of the Zhijiang-Tongren Expressway in Hunan Province (China), the evaluation model was validated through field measurement data. The results show that the safety scores obtained using the three methods of analytic hierarchy process, entropy method, and combination weighting method based on game theory are similar. The combination weighting evaluation model can correct the evaluation result error caused by a single weight and avoid information delay caused by the manual processing and analysis of monitoring data. The high-fill subgrade safety evaluation grade based on the combination weighting method and game theory is consistent with the engineering situation, and its fault tolerance range is within 20%. The evaluation model proposed in this study can scientifically and effectively evaluate the safety risks of high-fill subgrade construction, significantly improving the safety and reliability during the construction process.

As a representative of Exponential Organizations, MI went from obscurity to the Fortune 500 in just ten years. Mi's success is inextricably linked to its outstanding business model. This paper summarizes the elements of MI's business model from four perspectives: value proposition, value creation, value delivery, and value capture, as well as its measures for developing into an exponential organization. Expecting to provide theoretical references for the transformation and upgrading of manufacturing organizations.

Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high missed detection rates of offshore ship targets in large-scene SAR images are due to the occlusion of objects or mutual occlusion among targets, especially for small ship targets. To solve this problem, this study proposes a target detection model (TAC_CSAC_Net) that incorporates a multi-attention mechanism for detecting marine vessels in large-scene SAR images. Experiments were conducted on two public datasets, the SAR-Ship-Dataset and high-resolution SAR image dataset (HRSID), with multi-scene and multi-size, and the results showed that the proposed TAC_CSAC_Net model achieves good performance for both small and occluded target detection. Experiments were conducted on a real large-scene dataset, LS-SSDD, to obtain the detection results of subgraphs of the same scene. Quantitative comparisons were made with classical and recently developed deep learning models, and the experiments demonstrated that the proposed model outperformed other models for large-scene SAR image target detection.

One new cassane diterpene possessing an unusual N bridge between C-19 and C-20 named caesalsappanin R (1), as well as another new diterpene caesalsappanin S (2), were isolated from the seeds of Caesalpinia sappan with methanol extract. Their structures were determined by spectroscopic analysis and examined alongside existing data from prior studies. Their biological activities were profiled by their antiplasmodial activity.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

Anomaly detection plays a significant role in helping gas turbines run reliably and economically. Considering collective anomalous data and both sensitivity and robustness of the anomaly detection model, a sequential symbolic anomaly detection method is proposed and applied to the gas turbine fuel system. A structural Finite State Machine is to evaluate posterior probabilities of observing symbolic sequences and most probable state sequences they may locate. Hence an estimating based model and a decoding based model are used to identify anomalies in two different ways. Experimental results indicates that these two models have both ideal performance overall, and estimating based model has a strong ability in robustness, while decoding based model has a strong ability in accuracy, particularly in a certain range of length of sequence. Therefore, the proposed method can well facilitate existing symbolic dynamic analysis based anomaly detection methods especially in gas turbine domain.

Among all the processing technologies of heat-treatable aluminum alloys like 2219 aluminum alloy, using friction stir welding (FSW) as the joining technology and using electromagnetic forming (EMF) for plastic forming technology both have obvious advantages and successful applications. Therefore, there is a broad prospect for the compound technologies which can be used on the 2219 aluminum alloy to manufacture the large-scale thin-wall parts in the astronautic industry. The microstructure and mechanical properties of 2219 aluminum alloy under the process compounded of FSW, heat treatment, and EMF were investigated by means of tensile test, optical microscope (OM), and scanning electron microscope (SEM). The results show that the reduction of strength, which was caused during the FSW process, can be recovered effectively by the post-welding heat treatment composed of solid solution and aging, while the ductility was still reduced after heat treatment. Under the compound technology of FSW, heat treatment, and EMF, the forming limit of 2219 aluminum alloy decreased distinctly due to the poor ductility of the welding joint. A ribbon-pattern, which was formed due to the banded structure caused by FSW process, was found on the fracture surface of welded 2219 aluminum alloy after EMF treatment. During the EMF process, because of the effects of induced eddy current, a unique structure, which was manifested as a molted-surface appearance under the SEM observation, was formed as the material fractured.

This paper studies the integrated design problems of control and guidance with parameter uncertainties, target disturbances, input constraints and actuator faults. Firstly, based on the integrated design idea of the missile guidance and control, the auxiliary variable is used to establish and transform it into a cascade system with input constraints, actuator faults and disturbances of unknown upper bounds. Secondly, the adaptive anti-saturation dynamic surface fault-tolerant controller is designed by using the back-stepping method, adaptive control, auxiliary system and tracking differentiator. By introducing the tracking differentiator and tangent barrier Lyapunov function, the computational explosion problem in the traditional back-stepping method is avoided and the angle of attack can be guaranteed in prospective range, respectively. Finally, the theoretical proof of the designed control strategy is given to ensure that the states of the closed-loop system are bounded. At the same time, the digital simulation of the maneuvering target of different maneuvering forms is carried out, which further illustrate the effectiveness and robustness of the designed control schemes.

Barnyardgrass (Echinochloa spp.) is a prevalent type of weed in rice fields worldwide. Despite the growing knowledge concerning allelopathic interference with barnyardgrass, little is understood regarding the competitive mechanisms between allelopathic rice and herbicide-resistant barnyardgrass at the plant physiological level. In this context, a hydroponic system was employed to investigate the root morphological traits and different phytohormones levels of two rice cultivars, i.e., the allelopathic rice cultivar “PI312777” (PI) and the non-allelopathic rice cultivar “Lemont” (LE), when co-planted with quinclorac-resistant and -susceptible barnyardgrass, respectively. The results showed that the shoot and root biomass were greater in the allelopathic rice cultivar. Moreover, the treatments at the two time points induced an increase in shoot and root biomass of PI when subjected to barnyardgrass stress. In terms of root morphology, PI exhibited significantly higher fine-root length in diameters &lt;0.5 mm, a greater number of root tips, and longer root tips compared to LE. In addition, the levels of different plant hormones, including auxin (IAA), abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA), known for their diverse adaptation strategies to biotic stress, were analysed. The response to quinclorac-resistant barnyardgrass stress was consistent in terms of the content of well-known stress-related hormones, namely SA and JA. The accumulation of SA and JA was observed in both rice cultivars under the stress of quinclorac-resistant barnyardgrass, with higher contents of these hormones in PI than that in LE. The most significant change was observed in IAA and ABA contents in rice, which decreased significantly from 7 days to 14 days under co-culture stress. Additionally, PI contained higher levels of IAA and ABA than LE in the presence of barnyardgrass stress. This research may aid in the development of strategies for reducing the environmental impact of herbicides through the prudent selection of non-chemical herbicide control tactics.

The flowering of Amorphophallus bulbifer plays an important role in its reproduction. The flowers and leaves of A. bulbifer cannot grow at the same time. However, the physiological and molecular mechanisms involved in flower bud and leaf bud formation are still unclear. In this study, the flower buds and leaf buds of A. bulbifer in the early stage of growth were used as research materials, transcriptome and metabolome analyses were carried out, and the soluble sugar and starch contents of A. bulbifer corms were determined. Transcriptome analysis revealed 5 542 differentially expressed genes (DEG) between flower buds and leaf buds, 3 107 of which were upregulated and 2 435 of which were downregulated. Enrichment analysis of the KEGG pathway showed that these differential genes were enriched mainly in the plant hormone signal transduction, DNA replication and fatty acid elongation pathways. Plant hormone signal transduction, DNA replication and fatty acid elongation pathways. A total of 5 296 significant differentially abundant metabolites were screened out by nontargeted metabolomics analysis. The differentially abundant metabolites were functionally classified in the HMDB, and 118 were successfully matched, including 17 that were highly expressed in flower buds. The differentially abundant metabolites in the flower buds were mainly enriched in pathways such as amino acid metabolism, isoquinoline alkaloid biosynthesis and pyrimidine metabolism. Targeted metabolomics analysis revealed that the contents of ABA, ZT and iPA in flower buds were significantly greater than those in leaf buds, while the opposite trend was observed for IAA. The analysis of soluble sugar and starch contents showed that the starch and soluble sugar contents in flower buds were significantly greater than those in leaf buds. The results of this study showed that flower bud development in A. bulbifer was regulated by amino acids, starch, ABA, ZT, iPA, IAA and other hormones. These findings could lead to valuable genetic resources for further study of A. bulbifer flowering and provide a deeper understanding of the molecular basis of A. bulbifer flowering.

Four angucycline glycosides including three new compounds landomycin N (1), galtamycin C (2) and vineomycin D (3), and a known homologue saquayamycin B (4), along with two alkaloids 1-acetyl-β-carboline (5) and indole-3-acetic acid (6), were identified from the fermentation broth of an intertidal sediments derived Streptomyces sp. Their structures were mainly established by IR, HR-ESI-MS, 1D and 2D NMR techniques. Among the isolated angucyclines, saquayamycin B displayed potent cytotoxic activity against hepatoma carcinoma cells HepG-2, SMMC-7721 and plc-prf-5, with IC50 values 0.135, 0.033 and 0.244 μM respectively, superior to positive drug doxorubicin. Saquayamycin B treatment to SMMC-7721 cells led to the typical morphological signs of apoptosis in 4',6-diamidino-2-phenylindole (DAPI) staining experiment.

The genus Amomum encompasses six medicinal species that are extensively utilized and have a significant historical background. Due to their morphological similarities, however, the presence of counterfeit and substandard products remains a challenge. Accurate plant identification is therefore essential to address these issues. This study utilized 11 newly sequenced samples along with extensive data from NCBI to perform molecular identification of these six species. The plastomes of Amomum displayed a typical quadripartite structure with conserved gene content, yet showed independent variations in the SC/IR boundary shifts at both inter- and intra-specific levels. Our approach incorporated ITS, ITS1, ITS2, complete plastomes, matK, rbcL, and psbA-trnH sequences for molecular identification, which effectively differentiated the six medicinal species within the genus Amomum, as confirmed by distance-based and phylogenetic tree analyses. Among these, the ITS, ITS1, and complete plastomes sequences demonstrated the highest identification success rate (3/6), followed by ITS2, matK, and psbA-trnH (1/6). In contrast, rbcL failed to identify any species. This research successfully established a reliable molecular identification method for Amomum plants, to protect wild plant resources and promote the sustainable use of medicinal plants and restrict the exploitation of these resources.

In March 2013, a novel avian influenza A H7N9 virus was emerged in China, which cause rapidly progressive pneumonia and with a high fatality rate. Serologic studies to evaluate neutralizing antibodies of infected patients and birds are invaluable tools for immunogenicity research of H7N9 and epidemiological investigation. Conventional neutralization assays are laborious and time-consuming which also hampered by biosafety requirement. In this study, We construct and produce pseudovirus bearing the full-length hemagglutinin (HA) of H7N9 virus in the Env-defective, luciferase-expressing HIV-1 backbone. The production of lentiviral pseudovirus was analysed by HA gene specific real-time reverse-transcription PCR, transmission electron microscopy (TEM), and Western Blot assay to prove the nucleic acid replication, the morphology of virus, and the expression of HA protein in pseudovirus. After that pseudovirus based inhibition assay was established to detect neutralizing antibodies of a panel of serum samples. Our results demonstrated that H7N9 pseudovirus which had single-cycle infection was generated. By comparing the neutralization antibody titers, pseudovirus based neutralization test could be recognized as an alternative of conventional microneutralization (MN). Hence, we conclude that it is possible to use pseudovirus inhibition assay to screen sera samples, as well as evaluate vaccine-induced neutralizing antibodies against H7N9 virus.

By reviewing the research of development economics in recent years, five key terms of ‘innovation, coordination, green, openness and sharing’ are extracted, corresponding to the five dimensions of the New Development Concept advocated by China. Based on this, an evaluation index system of the development quality of China's fishery industry is constructed. The spatio-temporal characteristics of China's fishery industry development quality were analyzed by using the provincial panel data from 2007 to 2017. The results show that: i) China's fishery industry overall development quality continues to grow, while the variation of provincial quality is also increasing, and the contribution of innovation quality and sharing quality is increasing, becoming an important sub-dimension leading the overall development quality.ii) there is a significant spatial dependence among provincial quality, and the significance is further strengthening. The Hangzhou Bay area and Bohai Bay area have gradually become a dual-core area where the high-quality development of China's fishery industry agglomeration, and the radiation from the dual-core area to the peripheral areas may still be in the process of enhancement. The spatial and temporal distribution of China’s fishery industry development quality keeps the trend of ‘from northeast to southwest’, which is almost parallel to Hu Huanyong line. The gravity center of its distribution is close to the gravity center of Chinese population and economy, and the development quality experienced a process from relatively concentrated to dispersed and then returned to concentrated, and the development speed in the later period was higher than that in the earlier period. iii) Capital accumulation level is the dominant positive influencing factors, while government support level is the dominant negative influencing factors respectively, and both have significant spatial differentiation among provinces.

Intercropping significantly improves land use efficiency and soil fertility. This study examines the impact of three cultivation systems (monoculture sugarcane, peanut-sugarcane and soybean-sugarcane intercropping) on soil properties and diazotrophs. Sugarcane rhizosphere soil was sampled from the farmers’ field. Soil properties and nifH gene abundance were analyzed by high throughput sequencing. Moreover, a total of 436,458 nifH gene sequences were obtained and classified into the 3201 unique operational taxonomic units (OTUs). Maximum unique OTUs resulted with soybean-sugarcane intercropping (<375). The dominant groups across all cultivation were Alpha-proteobacteria and Beta-proteobacteria. On the basis of microbial community structure, intercropping systems were more diverse than monoculture sugarcane. In the genus level, Bradyrhizobium, Burkholderia, Pelomonas, and Sphingomonas were predominant in the intercropping systems. Moreover, diazotrophic bacterial communities of these cultivation systems were positively correlated to the soil pH and soil enzyme protease. Moreover, low available P recovered from intercropping system showed a strong correlation with higher nutrient uptake activity of soil microbes. Based on the results, our investigation concluded that intercropping system caused a positive effect on the growth of diazotrophic bacterial communities and it might boost the soil fertility and this kind of study helps to develop an eco-friendly technology for sustainable sugarcane production.

Motivation: UCSC Xena platform provides huge amounts of processed cancer omics data from big public projects like TCGA or individual reserach groups for enabling unprecedented research opportunities. In 2019, we developed UCSCXenaTools, an R package for retrieval of UCSC Xena data. However, an easier dataset exploration and analysis tool is still lack, especially for researchers without programming experience. Results: We develop UCSCXenaShiny, an R Shiny package to quickly explore, download all datasets from UCSC Xena data hubs. In addiction, a module based analysis framework is constructed to analyze and visualize data. Availability: https://github.com/openbiox/UCSCXenaShiny or https://cran.r-project.org/package=UCSCXenaShiny.

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

During HVDC earth return operation systems, a high magnitude current will be injected into soil through earth electrode, the potential on the surface would change widely and produce unfavorable effects on the AC systems around. This paper presents an effective finite element method (FEM) coupling electric field with thermal field to evaluate the electrical field induced by the injected DC current. Firstly, owe to the characteristic of FEM, this method can consider arbitrary soil and earth electrode structure. Secondly, by setting the electrical and thermal parameters of soil as a function of temperature at the same time, the dynamic coupling process of electric field and thermal field is simulated accurately. Thirdly, to deal with the singular point in FEM subdivision and the huge computation in traditional three-dimensional FEM, the FEM coupling 2-D earth electrode with 3-D soil based on "shell" theory is introduced. Finally, based on the suggested method, the effect of abnormal resistance region (ARR) near DC earth electrode on electric field distribution is analyzed.

Small molecule kinase inhibitors (SMKIs) are one of the heightened concerns in the field of drug research and development. There are seventy-nine (up to July 2023) small molecule kinase inhibitors have been approved by FDA and hundreds kinase inhibitors candidates in clinical trials, which shed light on the treatment of some major diseases. As an important strategy of drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods, such as docking, molecular dynamic, pharmacophore have been applied to the design and optimization of small molecule kinase inhibitors. In the review, we provide an overview of recent advances in CADD and SMKIs; and the application of CADD for discovery of SMKIs.

Microfluidics is facing critical challenges in the quest of miniaturizing, integrating, and automating in vitro diagnostics, including the increasing complexity of assays, the gap between the macroscale world and the microscale devices, and the diverse throughput demands in various clinical settings. Here a “3D extensible” microfluidic design paradigm that consists of a set of basic structures and unit operations was developed for constructing any application-specific assay. Four basic structures- check valve (in), check valve (out), double-check valve (in and out), and on-off valve, were designed to mimic basic acts in biochemical assays. By combining these structures linearly, a series of unit operations can be readily formed. We then proposed a “3D extensible” architecture to fulfill the needs of the function integration, the adaptive “world-to-chip” interface, and the adjustable throughput in the X, Y, and Z directions, respectively. To verify this design paradigm, we developed a fully integrated loop-mediated isothermal amplification microsystem that can directly accept swab samples and detect Chlamydia trachomatis automatically with a sensitivity one order higher than that of the conventional kit. This demonstration validated the feasibility of using this paradigm to develop integrated and automated microsystems in a less risky and more consistent manner.

Polymeric composites such as Poly-ether-ether-ketone (PEEK)/carbon fiber (CF) have been widely utilized due to outstanding performances such as high specific strength and specific modulus. The PEEK/CF components via powder-bed fusion additive manufacturing usually show brittle fracture behaviors induced by their poor interfacial affinity and inner voids. These defects are strongly associated with powder packing quality upon deposition. The particle dynamic model has been widely employed to study the interactions of particle motions. Powder property, bulk material property, and interfacial features of composite powders are key factors in the particle dynamic model. In this work, an efficient and systematic material evaluation is developed for composite powders to investigate their deposition mechanism. The discrete element method is utilized to simulate the dynamic behaviors of PEEK/CF composite powders. The powder properties, bulk material properties, and interfacial features of powders are calibrated and justified by experimental measurement, numerical simulation, and design of experiments. The particle dynamic model can well explain the powder flow behaviors and interactions. It reveals that the addition of short CF particles can assist the flow of PEEK powders and improve the packing quality of the composite powders.

To achieve rapid post-earthquake repair of self-centering ribbed floor flat beam frame structures, a ductile hybrid joint consisting of dog bone weakened energy dissipating steel bars connected to the upper and lower column sections through high-strength threads based on the damage control design concept is proposed. By moving the ductile energy dissipating zone out to the locally weakened section of the energy dissipating steel bars and the locally unbonded prestressed steel bars in the core area, the residual deformation was limited and the seismic performance was improved. Based on the working principle of hybrid joints, low cycle loading tests were conducted on two joint specimens to analyze the influence of lateral prestress on the seismic performance of the hybrid joints. Numerical modeling methods were used to compare the position of the energy-consuming steel bars in the composite layer and the friction performance of joints. The research results indicated that the hybrid joint had stable load-bearing, deformation, and energy dissipation capabilities, with damage primarily concentrated on the energy-consuming steel bars. Even at an inter-story displacement angle of 5.5%, the upper and lower column segments remained elastic. After unloading, the connection seam at the joint was closed, and the self-centering performance was good. When the inter-story displacement angle reached 5.5%, the lateral prestress increased from 150 kN to 250 kN, the ultimate bearing capacity of the joint increased by 16.3%, and the cumulative energy consumption increased by 30.0%. The influence of the friction coefficient of the joint surface on the structural performance was set at a threshold of 0.7. When it was less than the threshold, the ultimate bearing capacity and initial stiffness of the joint increased with an increase in the friction coefficient. After reaching the threshold, the increase in the ultimate bearing capacity of the joint slowed down, and the rate of stiffness degradation gradually accelerated. This joint had excellent seismic performance and can also achieve post-earthquake repair of structures.

Medium-carbon steel is commonly used for the rail, wire ropes, tire cord, cold heading, forging steels, cold finished steel bars, machinable steel and so on. Its fatigue behavior analysis and fatigue life estimation play an important role in the machinery industry. In this paper, the estimation of fatigue life of medium-carbon steel with different surface roughness using established S-N and P-S-N curves is presented. To estimate the fatigue life, the effect of the average surface roughness on the fatigue life of medium-carbon steel has been investigated using 75 fatigue tests in three groups with average surface roughness (Ra): 0.4μm, 0.8μm, and 1.6μm respectively. S-N curves and P-S-N curves have been established based on the fatigue tests. The fatigue life of medium-carbon steel is then estimated based on Tanaka-Mura crack initiation life model, the crack propagation life model using Paris law, and material constants of the S-N curves. 6 more fatigue tests have been conducted to validate the presented fatigue life estimation formulation. The experimental results have shown that the presented model could estimate well the mean fatigue life of medium-carbon steel with different surface roughness

The Gulong shale oil reservoir is formed in freshwater to slightly saline lacustrine basins, mainly consisting of pure shale geological structure, which is quite different from other shale reservoirs around the world. Currently, the development of Gulong shale oil mainly relies on hydraulic fracturing, while the subsequent shut-in period for imbibition has been proven to be an effective method for enhancing shale oil recovery. To clarify the characteristics of fluid occurrence space and the variation of fluid occurrence during saltwater imbibition in Gulong shale, this paper carried out porosity and permeability tests on Gulong shale cores, and analyzed the fluid occurrence space characteristics and imbibition oil recovery based on nuclear magnetic resonance (NMR). In the porosity and permeability tests, the porosity measured by saturation method was calibrated using NMR T2 spectra. Combined with the identification of fractures in shale cores using micro-CT and the analysis of porosity and permeability parameters, it was found that the permeability of shale cores was related to the development of fractures in shale cores. Through the testing and analysis of NMR T1-T2 two-dimensional spectra of the shale cores before and after saturation with oil, it was found that the shale mainly contains heavy oil, light oil, and clay-bound water, and they were distributed in different positions in the T1-T2 spectrum. Finally, the T1-T2 two-dimensional spectra of the shale core at different imbibition stages were analyzed, and it was found that the saltwater mainly entered the minuscule inorganic pores of clay minerals during the imbibition process, and squeezed the larger-sized inorganic pores containing light oil through the hydration expansion effect, thus expelling the light oil from the shale core and achieving the purpose of enhanced oil recovery.

Infrared small target detection (ISTD) plays a crucial role in both civilian and military applications. The detection of small targets against dense cluttered backgrounds remains a challenging task, requiring the collaboration of false alarm source elimination and target detection. Existing approaches primarily focus on modeling targets while often neglecting false alarm sources. To address this limitation, we propose a Target and False Alarm Collaborative Detection Network to leverage the information provided by false alarm sources and the background. Firstly, we introduce a False Alarm Source Estimation Block (FEB) that estimates potential interferences present in the background by extracting features on multiple scales and employing stepwise upsampling for feature fusion. Subsequently, we propose a framework that employs multiple FEBs to eliminate false alarm sources across multiple scales. Finally, a Target Segmentation Block (TSB) is introduced to accurately segment the targets to produce the final detection result. Experiments on public datasets demonstrate that, compared to other methods, our model achieves high accuracy in segmenting targets while being able to extract false alarm sources which can be used for further studies.

Dynamic measurement error correction is an effective method to improve the sensor precision. Dynamic measurement error prediction is an important part of error correction, support vector machine (SVM) is often used to predicting the dynamic measurement error of sensors. Traditionally, the parameters of SVM were always set by manual, which can not ensure the model’s performance. In this paper, a method of SVM based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement error of sensors. Natural selection and Simulated annealing are added in PSO to raise the ability to avoid local optimum. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters, they are the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absoluter percentage error are employed to evaluate the prediction models’ performances. The experiment results show that the NAPSO-SVM has a better prediction precision and a less prediction errors among the three algorithms, and it is an effective method in predicting dynamic measurement errors of sensors.

A series of novel N-n-butyl-1,8-naphthalimide derivatives were synthesized via a three-step reaction involving nucleophilic substitution and acylation. All of the compounds were characterized by IR, ¹H NMR, ¹³C NMR, MS, and elemental analysis, and the crystal structure of N-n-butyl-4-[N’,N’-bis(2`,4`-dichlorobenzoyl)ethylamino]-1,8-naphthalimide was determined. The π-π stacking interactions and hydrogen bonds between the two molecular core planes (naphthalimide ring) and the van der Waals forces between the flexible n-butyl groups resulted in a 3D long-chain structure. The UV-vis and fluorescence properties of the title compounds were investigated. The results indicated that the monosubstituted 1,8-naphthalimide derivatives bearing an electron-donating group on the benzene ring or a structure with a larger conjugative effect exhibited enhanced fluorescence properties.

As an irreplaceable ecological barrier, the ecological conservation developing area (ECDA) is vital for the integrated construction of urban and rural areas, and optimization and adjustment of industrial structure. Developing green agriculture is the foundation and guarantee for improving the rural ecological environment and meeting the increasing needs of farmers′ income. Issued by the Chinese government, No. 1 Central Document stated the necessity of promoting agricultural green development (AGD) and the related technologies in dealing with ecological pressure and resource shortages, especially for large cities like Beijing. However, few empirical studies have conducted on spatiotemporal variations of AGD in ECDA of large cities. Based on the green agricultural traits of Beijing and the accessible data, we evaluate AGD and analyze its spatial and temporal heterogeneity of Beijing ECDA by constructiing a framework with 13 indicators. The weight coefficients of AGD indicators were calculated by the projection pursuit method, with the district panel data from 2006 to 2016. The results demonstrated that energy consumption is a vital factor of green agriculture production, and agricultural output value per unit of the arable land area is the key to the green agricultural revenue. From 2006 to 2016, the AGD index of ECDA had an increasing trend till 2012, followed by a decreasing tendency. The AGD index of the northern region is higher than the southern of ECDA. The obstacle degree model was used to verify AGD limiting factors. They were poor infrastructure, slow agritourism, low labor productivity, and low resource utilization efficiency that varied by districts in ECDA. Given these findings, our study is conducive to the AGD evaluation at the district (county) level for ECDA of large cities and also provides important policy implications.

Drip irrigation systems are becoming more and more mature and are present extensively applied to increase crop yield and water use efficiency in Xinjiang, northwest China. To investigate the effects of irrigation quota on maize growth, the grain yield, and the irrigation water use efficiency (IWUE), a field experiment with four irrigation quotas (T1 4200m3·hm-2, T2 4800m3·hm-2, T3 5400m3·hm-2 and T4 6000m3·hm-2.) were conducted from 2013 to 2021 in Xinjiang China. The re-sults showed significant changes in maize growth, yield, and irrigation water use efficiency in response to different irrigation quotas. The plant height, leaf area index, SPAD, biomass, yield and harvest index of maize at different irrigation quotas all showed a “single peak curve”, and its change was closely related to the irrigation level. The growth index, dry matter accumulation, yield and irrigation water use efficiency with T3 were the highest. The dry matter transfer effi-ciency, contribution of dry matter translocation to grain and the harvest index with T3 showed significant increase of 13.86%, 26.06%, 29.93% and 7.62% compared to T1, respectively. In com-parison to T1, T2 and T4, the yield of T3 increased by 32.17%, 13.54% and 11.27% respectively, and the irrigation water use efficiency (IWUE) increased by 2.80%, 0.93% and 23.63% respectively. The significant correlations established between the maize yield and irrigation quotas could be sim-ulated by kuznets-style relation. The maize yield was negative correlated with irrigation quotas, When the irrigation quota (x) was 5376.73m3·hm-2, the maize yield (y) was 15841.00m3·hm-2. These results demonstrate that the optimized irrigation quota (5400m3·hm-2 treatment) can effectively improve the growth, yield and irrigation water use efficiency of drip irrigation maize in North-west China. In the meanwhile, it can provide theoretical reference and data support for the op-timal irrigation amount of drip irrigation maize in Northwest Xinjiang.

To assure the opacity, an optimal problem is to retain the occurring events sequences as many as possible. Contrary to such problem, the other optimal problem is to preserve the minimal occurring events sequences. In the paper, based on the choosing cost, an optimal opacity-enforcing model is presented to minimize the sum of discount choosing cost, which is not only to preserve the opacity, but also to retain the secret to the maximum. To solve the model, two scenarios on opacity are considered. For the two scenarios, some algorithms are presented to achieve the optimal solution for the model by using the method of dynamic programming. And then, the solutions produced by the algorithms are proved correctly by theoretical proof. Finally, some illustrations for the algorithms are given.

As the most important city in China, Beijing has experienced an economic soar, large-scale population growth and eco-environment changes in recent 20 years.Evaluating climate and human-induced vegetation changes could reveal the relationship of vegetation-climate-human activities and provide important insights for the coordination of economic growth and environmental protection. Based on a long-term MODIS vegetation index dataset, meteorological data (temperature, precipitation) and impervious surface data, the Theil-Sen regression and the Mann-Kendall method are used to estimate vegetation change trend in this study and the residual analysis is utilized to distinguish the impacts of climate factors and human activities on vegetation restoration and degradation from 2000 to 2019 in Beijing. Our results show that the increasing vegetation areas account for 80.2\% of Beijing. The restoration of vegetation is concentrated in the urban core area and mountainous area, while the degradation of vegetation is mainly concentrated in the suburbs. In recent years, the vegetation in most mountainous areas has changed from restoration to significant restoration, indicating that the growth of mountain vegetation has continued to restore. We also found that in the process of urban expansion, vegetation browning occurred in 53.1\% of the urban built-up area, while vegetation greening occurred in the rest part. We concluded that precipitation is the main climatic factor affecting the growth of vegetation in Beijing mountain areas through correlation analysis. Human activities have significantly promoted the vegetation growing in the northern mountainous area thanks to the establishment of environmental protection areas. The negative correlation between vegetation and the impervious surface tends to gradually expand outwards, which is consistent with the trend of urban expansion. The positive correlation region remains stable, but the positive correlation is gradually enhanced. The response of vegetation to urbanization demonstrated a high degree of spatial heterogeneity. These findings indicated that human activities played an increasingly important role in influencing vegetation changes in Beijing.

Solar assisted hybrid cooling systems are promising for the energy saving of refrigeration systems. In most cases, the solar thermal gain is only able to power the heat-driven process of facilities in part of the working period. Therefore, the reduction of compressor power strongly depends upon the duration of heat-driven processes, which has not been addressed properly. Motivated by such knowledge gap, the thermodynamic understanding of solar assisted hybrid cooling systems is deepened through considering the duration in heat-driven processes. Three absorption-compression integrated cooling cycles were taken as examples. It is found that optimal parameters, e.g., inter-stage pressure and temperature, corresponding to various performance indicators trend to be identical, as the duration of heat-driven processes is taken into account. Furthermore, the optimal parameter for different working conditions was obtained. It is displayed that the dimensionless optimal intermediate temperature of layout with the cascade condensation process varies slightly, e.g., 4%, for different conditions. Moreover, the fall of compressor power in entire working periods is nearly independent upon the intermediate temperature. The paper is favorable for the efficient design and operation of solar assisted hybrid cooling systems.

Recently, the outbreak of coronavirus disease 2019 (COVID-19) is threatening human health globally. There is a dire need to find potential therapeutic agents. Angiotensin converting enzyme 2 (ACE2), as an entry receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is considered as potential therapeutic target in COVID-19 pandemic. Here, our bioinformatics analysis revealed that the biological function of ACE2 was correlated with regulation of blood pressure and mediation of SARS-CoV-2 entry into host cells. Ten ACE2 cooperative proteins were identified by using STRING with a high score. ACE2 expressed highly in the small intestine, testis, and kidney. The level of ACE2 expression in tumor tissues varies in different types of cancers compared with that in normal tissues. It was worth noting that the expression level of ACE2 in the tumor has no effect on patient survival. MiRNA hsa-miR-942-5p, and three transcription factors (TFs) including Signal transducer and activator of transcription 4 (STAT4), Estrogen related receptor α (ESRRA), and Signal transducer and activator of transcription 3 (STAT3) were selected as novel ACE2 regulators. Moreover, nine potential therapeutic drugs were predicted by two online databases. Thus, our research may expand the overall view of ACE2 in COVID-19 treatment.

In the study, a new correction method was applied to reduce error during detection on mixed pesticide residue in apples by using Raman spectra. Combined with self-built pesticide residues detection system by Raman spectroscopy and the application of surface enhancement technology, rapid real-time qualitative and quantitative analysis of deltamethrin and acetamiprid residues in apples can be applied effectively. In quantitative analysis, compared with the intensity value of characteristic peaks of single pesticide with same concentration, the intensity value of characteristic peaks of the two pesticides decreased after mixing the pesticides, which interferes the results severely. By comparing the difference in the intensity of characteristic peaks of single and mixed pesticides, a correction method is proposed to eliminate the influence of pesticides mixture. Characteristic peak intensity values of gradient concentration pesticide from 10-1 g•kg-1 to 10-6 g•kg-1 and Lagrangian interpolation are applied in the correction method. And a smooth surface is applied to describe the correction ratio of characteristic peak intensity. Through detecting the characteristic peak intensity values of the mixed pesticide, correction ratio will be obtained. Then real values of the peak intensity of pesticides and the content of each component of the mixed pesticide will be acquired by the correction method. Correlation coefficient of model validation exceeds 0.88 generally and Root Mean Square Error also decreases obviously after correction, which proved the reliability of the method.

In bioinformatics research, traditional machine learning methods have demonstrated efficacy in addressing Euclidean data. However, real-world data often encompasses non-Euclidean forms, such as graph data, which contain intricate structural patterns or high-order relationships that elude conventional machine-learning approaches. Representation learning seeks to derive valuable data representations from enhancing predictive or analytic tasks, capturing vital patterns and structures. This method has proven particularly beneficial in bioinformatics and biomedicine, as it effectively handles high-dimensional, sparse data, detects complex biological patterns, and optimizes predictive performance. In recent years, graph representation learning has become a popular research direction. It embeds graphs into a low-dimensional space while preserving the structural and attribute information of the graph, enabling better feature extraction for downstream tasks. This study extensively reviews representation learning advancements, particularly in the research of representation methods since the emergence of COVID-19. We begin with an analysis and classification of neural network-based language model representation learning techniques as well as graph representation learning methods. Subsequently, we explore their methodological innovations in the context of COVID-19, with a focus on the domains of drugs, public health, and healthcare. Furthermore, we discuss the challenges and opportunities associated with graph representation learning. This comprehensive review presents invaluable insights for researchers as it documents the development of COVID-19 and offers experiential lessons to preempt future infectious diseases. Moreover, this study guides future bioinformatics and biomedicine research methodologies.

Co-free Li-rich oxide is a promising cathode for low cost high energy density Li-ion battery but presents poor cyclic stability. To address this issue, CeO2 is coated on Co-free Li-rich oxide through a low-temperature aged process, resulting in a novel CeO2-coated Li-rich oxide compo-site. Due to the low-temperature aged process, a uniform CeO2 coating layer of 6 nm in thickness is successfully coated on Co-free Li-rich oxide. With this uniform coating, the resulting CeO2-coated Li-rich oxide composite presents improved cyclic stability as well as rate capability as the cathode of Li-ion battery. The capacity retention of the resulting CeO2-coated Li-rich oxide is enhanced from 67% to 85% after 100 cycles and its capacity retention of 5C/0.05C is enhanced from 10% to 23%, compared with the uncoated sample. Such significant improvements enable this low-temperature aged process to be helpful for the practical application of Li-rich oxide materials, not limited to Co-free Li-rich oxide.

The uncertainty in the secondary path of an Active Noise Control (ANC) headphone affects the waterbed effect and stability of the feedback system. This study focuses on the uncertainty of the secondary path when real users wear headphones, and proposes a new uncertainty constraint based on the measured results of the secondary path transfer function under different wearing conditions of dummy head and limited subjects. This constraint and a cascaded second-order infinite impulse response filter with fixed coefficients are used to formulate a control strategic function, which is optimized by the Improved Grey Wolf Optimizer (IGWO) algorithm to obtain the optimal controller with better noise reduction performance. The proposed method and simulation model are validated based on the experimental test results. The results demonstrate that the safety factor and waterbed suppressing factor contained in the proposed uncertainty constraint ensures more stable noise reduction and effective suppression of the waterbed effect for new subjects without a priori data.

A series of novel chiral nonmetallocene pincer-type rare earth metal dialkyl complexes bearing the chiral monoanionic tridentate C2-symmetric 1,3-bis(oxazolinymethylidene)isoindoline (BOXMI) ligand (BOXMI)Ln(CH2SiMe3)2 1-3 (1, Ln = Sc, yield = 57%; 2, Ln = Lu, yield = 55%; 3, Ln = Y, yield = 62%) have been prepared in moderate yields via the acid-base reaction between the BOXMI ligand and rare earth metal tri(trimethylsilylmethyl) complexes. The X-ray diffractions show that both of the complexes 1 and 2 contain one Boxmi ligand and two trimethylsilylmethyl ligands, adopting a distorted-trigonal-bipyramidal configuration. In the presence of cocatalyst such as borate and AlR3, these complexes 1-3 exhibit high activities up to 6.8 × 104 (g of polymer)/(molLn h) and high cis-1,4-selectivities up to 97%) in the polymerization of isoprene in toluene, yielding the cis-1,4-polyisoprenes with high molecular weights (Mn up to 710000 g/mol) and bimodal molecular weight distributions (Mw/Mn = 2.0-4.5).

Trailing oil is the tail section of contamination. There are two main reasons for the formation of trailing oil, one is the effect of laminar flow boundary layer, the other is the outflow of the preceding batch remained in the dead-legs. In the batch transportation of refined oil, under the action of viscous force, the preceding batch forms laminar boundary layer near the pipe wall and stays on the pipe wall, resulting in the phenomenon of contamination trailing and formation of trailing oil. When oil passes through the valve chamber of the oil transportation station, dead-leg will be formed. Due to gravity and convection diffusion, preceding batch flowing from dead-legs will form trailing oil in the pipeline. The phenomenon of trailing oil exists in the process of batch transportation, which will have an effect on the quality of oil. In this paper, Reynolds time-averaged method is used to simulate turbulence.Computational Fluid Dynamics(CFD) software is used to simulate different flow rates and bypass lengths to obtain contamination-related experimental data.Matlab software is used to perform multi-nonlinear regression for the oil substitution time, the length of the bypass and the flow rate. The formula for calculating the length of the trailing oil produced by the dead-leg is obtained. The modified formula for calculating the length of the contamination is obtained by combining the existing formula for calculating the length of the contamination.

Melon pest management relies on the excessive application of pesticides. Reducing pesticide spraying has become a global issue for environmental sustainability and human health. Therefore, developing a new cropping system that is sustainable and eco-friendly is important. This study found that melon seedlings irrigated with ultrafine water containing H2 and O2 (UFW) produced more root hairs, increased shoot height, and produced more flowers than the control irrigated with reverse osmosis (RO) water. Surprisingly, we also discovered that UFW irrigation significantly reduced aphid infestation in melon. Based on cryo-scanning electron microscope (cryo-SEM) observations, UFW treatment enhanced trichome development and prevented aphid infestation. To investigate whether it was H2 or O2 that helped to deter insect infestation, we prepared UF water enrichment of H2 (UF+H2) and O2 (UF+O2) separately and irrigated melons. Cryo-SEM results indicated that both UF+H2 and UF+O2 can increase the density of trichomes in melon leaves and petioles. RT-qPCR showed that UF+H2 significantly increased the gene expression level of the trichome-related gene GLABRA2 (GL2). We planted melons in a plastic greenhouse and irrigated them with ultrafine water enrichment of hydrogen (UF+H2) and oxygen (UF+O2). The SPAD value, photosynthetic parameters, root weight, fruit weight, and fruit sweetness were all better than the control without ultrafine water irrigation. UFW significantly increased trichome development, enhanced insect resistance, and improved fruit traits. This system thus provides useful water management for pest control and sustainable agricultural production.

A typical solid-state quantum sensor can be developed based on negatively charged nitrogen-vacancy (NV-) centers in diamond. The electron spin state of NV- can be controlled and read at room temperature. Through optical detection magnetic resonance (ODMR) technology, temperature measurement inside living cells can be achieved at the nanoscale. The key to ODMR technology is to apply microwave resonance to manipulate the electron spin state of NV-. Therefore, the microwave field characteristics formed near the NV- have a crucial impact on the sensitivity of ODMR measurement. This article mainly focuses on the temperature situation in cellular applications, and simulates the influence of structural parameters of double open loop resonant (DOLR) microwave antennas and broadband large-area (BLA) microwave antennas on the microwave field’s resonance frequency, quality factor Q, magnetic field strength, uniformity, etc. The parameters are optimized to have sufficient bandwidth, high signal-to-noise ratio, low power loss, and high magnetic field strength in the temperature range of 36 ℃ to 42.5 ℃. Finally, the ODMR spectra are used for effect comparison, and the signal-to-noise ratio and Q values of the ODMR spectra are compared when using different antennas. We have provided an optimization method for the design of microwave antennas and it is concluded that the DOLR microwave antenna is more suitable for living cell temperature measurement in our study.

Temporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often could not accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we introduce an Enhanced Residual U-Net architecture for temporal downscaling. The architecture, which incorporates residual blocks, allows for deeper network structures without the risk of overfitting or vanishing gradients, thus capturing more complex temporal dependencies. The U-Net design inherently could capture multi-scale features, making it ideal for simulating various temporal dynamics. Moreover, we implement a flow regularization technique with advection loss to ensure that the model adheres to physical laws governing geophysical fields. Our experimental results across various variables within the ERA5 dataset demonstrate an improvement in downscaling accuracy, outperforming other methods.

Ethylene is an ideal CO2 product in an electrocatalytic CO2 reduction reaction (CO2RR), which has high economic value. In this paper, Al–doped octahedral Cu2O (Al–Cu2O) catalyst was synthesized by a simple wet chemical method. The selectivity of CO2RR products was improved by doping Al onto the surface of octahedral Cu2O by regulating the Al content. The Al–Cu2O was used as an efficient electrocatalyst for CO2RR with selective ethylene production. The Al–Cu2O exhibited a high Faradic efficiency (FEC2H4) of 44.9% at -1.23 V (vs. RHE) in CO2 saturated 0.1 M KHCO3 electrolyte. Charge transferring from Al atom to Cu atom take place after Al doping in Cu2O, thereby optimizing the electronic structure, which facilitates CO2RR to ethylene production. The DFT calculation showed that the Al–Cu2O catalyst can effectively reduce the adsorption energy of the *CHCOH intermediate and promote the mass transfer of charges, thus improving the FEC2H4. After Al doping into Cu2O, the center of d orbitals shift positively, which makes the d–band closer to the Fermi level. Furthermore, the density of electronic states increases, which was conducted to the interaction between Cu atoms and intermediates, thus accelerating the electrochemical CO2 reduction process. This work proved that the metal doping strategy can effectively improve the catalytic properties of Cu2O, thus providing a useful way for CO2 cycling and green production of C2H4.

p-Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking based virtual screening were performed to identify novel potential HPPD inhibitors. The complex based pharmacophore model (CBP) with 0.721 of ROC used for screening compound showed remarkable ability to retrieve known active ligands from decoy molecule. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5(DS 2.5) to discern interactions with key residues at the active site of HPPD. 4 Compounds with top rank in HipHop model and well-known binding model were finally chosen as identification of lead compounds with potentially inhibitory effects on active site of target. The results provided powerful insight to the development of novel HPPD inhibitors herbicides using computational techniques.

In recent years, Chinese manufacturing enterprises compete to chase the wave of "digital revolution", digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises' export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region and industry. In the further study, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises, and form a "masking effect" on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences, and provides certain guidance for enterprises to implement the strategy of digital transformation.

The straightness error of guideway is one of the key indicators of ultra-precision machine, which plays an important role in the machining accuracy of work-piece. In order to measure straightness error of long distance ultra-precision guideway accurately, a splicing measurement for straightness error of guideway using high-precision flat mirror and displacement sensor was proposed in this paper, and the data splicing processing algorithm based on coordinate transformation was studied. Then comparative experiments on splicing measurement and direct measurement of straightness error were carried out on a hydrostatic guideway grinder. The maximum difference between the two measurements was about 0.3μm, which was far less than the straightness error of 5.8μm. The experiment demonstrated the correctness of the proposed splicing measurement method and data processing algorithm. To suppress the influence of straightness error on machining accuracy, a straightness error compensation algorithm based on error rotation transformation and vertical axis position correction was proposed, and the grinding experiment of a plane optics with size of 1400mm×500mm was carried out, whose flatness error after grinding was about 2.98μm. The straightness error of the grinding machine had been well suppressed.

Building energy consumption is the main urban energy consumption component, which mainly serves people-centered work and living energy demands. Based on the physical requirements of humans in urban buildings and to determine the comfortable body temperature in each season, this paper establishes a sizing optimization model of building-type integrated energy systems (IES), where the cooling and heating loads required to maintain indoor somatosensory body comfortable temperature are calculated. Depending on the external energy price, internal power balance and other constraints, the model develops an optimal sizing and capacity panning method of energy conversion and storage unit in a building-type IES with PV generation. The operating principle is described as follows: the PV generation is fully consumed, a gas engine satisfies the electric and thermal base load requirements, while the power system and a heat pump supply the remaining loads. The gas price, peak-valley electricity price gap and heat-topower ratio of gas engines are considered as important factors for the overall techno-economic analysis. The developed method is applied to optimize the economic performance of building-type IES and verified by practical examples. The results show that using the complementary characteristics of different energy conversion units is important to the overall IES cost.

In order to study the crystallinity of different density polyethylenes, the experimental study on the transformation of the conductance mechanism under high electric field was carried out. The X-ray Diffraction(XRD), Different Scanning Calorimeter(DSC), Direct Current(DC) breakdown of Low-density polyethylene(LDPE), Linear low density polyethylene(LLDPE), Medium density polyethylene(MDPE) and High-density polyethylene(HDPE) and the electric field of 5-200kV/mm were tested. Conductivity characteristics experiments, in addition, using the mathematical formula of a variety of conductance mechanisms, the electric field-current density curves of the four kinds of polyethylene were fitted to analyze the conductance transition of the above four kinds of polyethylene in non-ohmic regions under different high field strengths. mechanism. The experimental results show that as the density of polyethylene increases, the crystallinity increases continuously, and the continuous increase of crystallinity causes the electric conduction flow under the same field strength to decrease significantly. The field strength corresponding to the two turning points in the conductance characteristic curve increases simultaneously. Large, the breakdown field strength increases; through analysis, it is found that in the high field, as the electric field increases, the conductance mechanism develops from the ohmic conductance of the low field strength region to the bulk effect of the high field strength region (Poole-Frenkel). Then the electrode effect to the high field strength (Schottky), and the threshold field strength of this conductance mechanism transition increases with the increase of crystallinity.

In-situ grown C_0.3N_0.7Ti and SiC, which derived from non-oxide additives Ti₃SiC₂, are proposed to densify silicon nitride (Si₃N₄) ceramics with enhanced mechanical performance. Remarkable increase of density from 79.20% to 95.48% could be achieved for Si₃N₄ ceramics with 5vol% Ti₃SiC₂. The capillarity of decomposed Si from Ti₃SiC₂, and in-situ reaction between nonstoichiometric TiC_x and Si₃N₄ were believed to be responsible for densification of Si₃N₄ ceramics. An obvious enhancement of flexural strength and fracture toughness for Ti₃SiC₂ doped Si₃N₄ ceramics was observed. The maximum flexural strength of 795 MPa for Si₃N₄ composites with 5vol% Ti₃SiC₂ and maximum fracture toughness of 6.97 MPa^.m^1/2 for Si₃N₄ composites with 20vol% Ti₃SiC₂ are achieved when mixed powders are hot-press sintered at 1700℃. Pull out of elongated Si₃N₄ grains, crack bridging, crack branching and crack deflection were demonstrated to dominate enhance fracture toughness of Si₃N₄ composites.

ALDH+ H1975 lung adenocarcinoma stem cells (LSCs) are a rare cell population identified in lung adenocarcinoma (LUAD). LSCs can self-renew, drive tumor initiation, growth, metastasis, and recurrence, and are also the predominant cause of poor prognosis due to their intrinsic resistance to drugs and chemotherapy. Consequently, LSCs are a promising target for LUAD therapy. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), exert many significant regulatory functions in the pathogenesis of human cancers, showing the necessity for a comprehensive understanding of the mechanisms that underlie lung carcinogenesis. Nonetheless, research on many known transcripts and messenger RNAs (mRNAs) has already generated new information. Unknown biomarkers in ncRNAs and systematic and comprehensive interrelation with unknown ncRNAs and mRNAs may provide further insights into the biology of LUAD. Herein, a set of novel ncRNAs that include miRNAs, lncRNAs, circRNAs, were identified and differentially expressed patterns of ncRNAs and mRNAs in LSCs and ALDH- H1975 LUAD tumor cells (LTCs) were obtained using stringent bioinformatics pipelines. Through a meta-analysis of the identified landscapes, novel competitive endogenous RNA (ceRNA) networks were constructed to reveal the potential molecular mechanisms that regulate the hallmarks of LSCs and LTCs. This study presents a summary of novel ncRNAs and the fundamental roles of differentially expressed ncRNAs implicated in the activity of LSCs and LTCs. In addition, the study also provides a comprehensive resource for the future identification of diagnostic, therapeutic, and prognostic biomarkers in LUAD.

We reported previously that poly (3-hydroxybutyrate) (PHB) oligomer is an effective antimicrobial agent against gram-positive bacteria, gram-negative bacteria, fungi and multi-drug resistant bacteria. In this work, it was further found that polyethylene glycol (PEG) can promote the antimicrobial effect of PHB oligomer synergistically. Three hypothetic mechanisms were proposed, that is, generation of new antimicrobial components, degradation of PHB macromolecules and dissolution/dispersion of PHB oligomer by PEG. With a series of systematic experiments and characterizations of HPLC-MS, it was deducted that dissolution/dispersion of PHB oligomer dominated the synergistic antimicrobial effect between PHB oligomer and PEG. This work demonstrates a way for promoting antimicrobial effect of PHB oligomer and other antimicrobial agents through improving hydrophilicity.

Existing methods enhance mid-low resolution remote sensing ship detection by feeding super-resolved images to the detectors. Although these methods marginally improve the detection accuracy, the correlation between image super-resolution (SR) and ship detection is under-exploited. In this paper, we propose a simple but effective ship detection method called ShipSR-Det, in which both the output image and the intermediate features of the SR module are fed to the detection module. Using the super-resolved feature representation, the potential benefit introduced by image SR can be fully used for ship detection. We apply our method to the SSD and Faster-RCNN detectors and develop ShipSR-SSD and ShipSR-Faster-RCNN, respectively. Extensive ablation studies validate the effectiveness and generality of our method. Moreover, we compare ShipSR-Faster-RCNN with several state-of-the-art ship detection methods. Comparative results on the HRSC2016, DOTA and NWPU VHR-10 datasets demonstrate the superior performance of our proposed method.

The composition and pattern of ecosystems are important factors determining the overall status and spatial differences of ecosystem service functions. However, under the background of differential land policies and ecological protection policies, research on the trend of ecological system pattern changes in the Fenhe River Basin is insufficient. Taking the upper and middle reaches of the Fenhe River Basin as the study area, based on long-term NDVI index and multi-period LUCC remote sensing images, this study used spatial statistics and time trend analysis methods to analyze the spatio-temporal dynamic changes of vegetation, land use, landscape pattern, and explored the impact of major driving factors on ecosystem changes. The results show that: (1) From 2010 to 2020, the vegetation cover in the upper and middle reaches of the Fenhe River Basin increased, with an annual NDVI increment of 0.003 (P<0.001). NDVI showed an increasing trend spatially, with significant statistics (P<0.001) and significant changes (P<0.05) in vegetation in high-altitude mountain areas, and the vegetation cover was mostly forests or grasslands. There was no significant change in vegetation cover in the low-lying urban agglomeration area. (2) From 2010 to 2020, the area of water bodies or wetlands in the study area significantly decreased, with 51.3% converted to arable land and 33.9% transferred to construction land, while only 2.2% remained as water bodies or wetlands. From 2015 to 2020, the trend of water body changes slowed down, with the proportions of conversion to arable land and construction land being 44.0% and 18.4% respectively, while the area of wetlands or water bodies remained at 16.3%. During the period of 2015-2020, the area of water bodies or wetlands converted to other land types increased by more than 14% compared to 2010-2015. This proportion reached more than 30% compared to the 13th Five-year Plan Period. (3) From 2010 to 2020, the spatial changes of landscape diversity (SHDI) and evenness (SHEI) of LUCC showed heterogeneous characteristics. In the high-altitude areas near the river basin boundary, the values of SHDI and SHEI were below 1.0. While in the low-altitude plain areas and urban areas with relatively frequent human activities, the values of SHDI and SHEI were above 1.0, and the values in urban areas could reach above 1.5. The evolution of ecosystem patterns in the upper and middle reaches of the Fenhe River Basin in the past decade has been clarified, providing a scientific basis for the construction and management of ecological environment governance and restoration projects in the Fenhe River Basin, and providing practical references for ecological protection and high-quality development practice in the Yellow River Basin.

Small peptides (SPs), ranging from 5 to 100 amino acids, play integral roles in plants due to their diverse functions. Despite their low abundance and small molecular weight, SPs intricately regulate critical aspects of plant life, including cell division, growth, differentiation, flowering, fruiting, maturation, and stress responses. As vital mediators of intercellular signaling, SPs have garnered significant attention in plant biology research. This comprehensive review delves into SPs' structure, classification, and identification, providing a detailed understanding of their significance. Additionally, we summarize recent findings on the biological functions and signaling pathways of prominent SPs that regulate plant growth and development. The review also offers a forward-looking perspective on future research directions in peptide signaling pathways.

We present a class of efficient parametric closure models for 1D stochastic Burgers equations. Casting it as statistical learning of the flow map, we derive the parametric form by representing the unresolved high wavenumber Fourier modes as functionals of the resolved variables’ trajectory. The reduced models are nonlinear autoregression (NAR) time series models, with coefficients estimated from data by least squares. The NAR models can accurately reproduce the energy spectrum, the invariant densities, and the autocorrelations. Taking advantage of the simplicity of the NAR models, we investigate maximal and optimal space-time reduction. Reduction in space dimension is unlimited, and NAR models with two Fourier modes can perform well. The NAR model’s stability limits time reduction, with a maximal time step smaller than that of the K-mode Galerkin system. We report a potential criterion for optimal space-time reduction: the NAR models achieve minimal relative error in the energy spectrum at the time step where the K-mode Galerkin system’s mean CFL number agrees with the full model’s.

With forty years of developments, bio-macromolecule cryo-electron microscopy has met its revolution of resolution and is playing a very important role in structural biology study. According to different specimen states, cryo-electron microscopy (cryo-EM) involves three specific techniques, single particle analysis (SPA), electron tomography and sub-tomogram averaging, and electron diffraction. All these three techniques have not realized their full potentials of solving structures of bio-macromolecules and therefore need to be developed in the future. In this review, the current existing bottlenecks of cryo-EM SPA are discussed with theoretical analysis, which includes air-water interface during specimen cryo-vitrification, bio-macromolecular conformational heterogeneity, focus gradient within thick specimen, and electron radiation damage. Besides, potential solutions of these bottlenecks are proposed and discussed, which are worthy of further investigations in the future.

In recent years, the taxonomy of the families of Phenuiviridae, Nairoviridae, and Peribunyavidae in Bunyavirales was updated frequently, because many novel viruses in these families have been identified and the species demarcation criteria of these families have been changed. As per these criteria and sequence analysis, we found that the taxonomy of 19 species in these families should be revised. We presented six proposals for optimizing virus species taxonomy using the examples from these families. First, the species demarcation criteria for the same family (e.g., Peribunyavidae) should be unified. Second, the methods and parameters for the taxonomic calculation in the same order (e.g., Bunyavirales) should be unified. Third, virus species taxonomy should be based on phylogenetic relationships, rather than a cutoff value of sequence identities that is a self-contradictory demarcation criterion, although sequence identities aid virus taxonomy greatly. Fourth, virus species taxonomy should be based on the phylogenetic relationship of a key viral gene (e.g., the RdRp gene of Bunyavirales), which is important for the taxonomy of virus recombinants or reassortants. Fifth, a virus can be demarcated without a species before its biomedical significance has been revealed. Sixth, names of all viruses and virus species should be constituted exclusively with common characters (English letters and Arab numbers), to minimize difficulty in spelling and communication. These proposals are rational, flexible, and can accommodate all known viruses. They can also bridge the taxonomy history and the future demands due to their flexibility.

MCrAlX (M: Ni or Co or both, X: minor elements) coatings have been widely used to protect hot components in gas turbines against oxidation and hot corrosion at high temperatures. Understanding the influence of the X-elements on oxidation behaviour is important in the design of durable MCrAlX coatings. In this study, NiCoCrAlX coatings doped with Y+Ru and Ce, respectively, were deposited on Inconel-792 substrate by HVOF. The samples were subjected to isothermal oxidation test in laboratory air at 9000, 1000, 1100 ºC and cyclic oxidation test between 100 ºC and 1100 ºC with 1 hour dwell time at 1100 ºC. It was observed that the coating with Ce shows a much higher oxidation rate than the coating with Y+Ru under both isothermal and cyclic oxidation tests. Besides, β-depletion due to interdiffusion between coating and substrate was significantly lower with Ru addition. Simulations results using both a moving phase boundary model and an established oxidation-diffusion model show that Ru stabilize β grains which reduces β-depletion of coating due to substrate interdiffusion. This paper presents a comprehensive study of the influence of Ce and Ru on oxidation behaviour including investigation of the microstructure evolution influenced by oxidation time at coating surface and coating-substrate interface combining experiment and simulation results.

In the present study, an attempt was made to induce rooting from single-node cuttings of hybrid aspen (Populus tremula L. ×P. tremuloides Michx.) with different concentrations of IAA, IBA and NAA during rooting. Among the three auxins used, NAA showed more effective induction on rooting as compared to IAA and IBA at the whole level. Thereafter, NAA was used further in experiments for anatomical and biochemical investigation. The results showed that it took 12 days from the differentiation of primordium to the appearance of young adventitious roots with NAA application. It was found that endogenous IAA, ZR and GA3 levels increased, but ABA decreased in cuttings with 0.54 mM NAA treatment. In contrast to the endogenous IAA level, NAA had negative effect on IAA-oxidase (IAAO) activity. Similarly, the decreased peroxidase (POD) activity, consistent with down-regulation of expressed levels of POD1 and POD2, was observed in NAA-treated cuttings. Whereas, NAA resulted in a higher activity in polyphenol oxidase (PPO) compared to the control cuttings. Collectively, the study highlighted that 0.54 mM NAA is efficient on rooting in hybrid aspen, and its effect on metabolic changes during rooting is discussed, which provide valuable information for propagating hybrid aspen.

Abstract Background: Numerous studies have demonstrated that the amalgamation of populations belonging to the same breed or closely related breeds leads to enhanced accuracies in genomic predictions (GP). Extensive experimentation with diverse Bayesian and Genome-enabled best linear unbiased prediction (GBLUP) models has been conducted to explore multi-breed genomic selection (GS) in livestock, ultimately establishing they as successful approaches for predicting genomic estimated breeding value (GEBV). This study aimed to examine the efficacy of BayesR and GBLUP model with different weighted genomic relationship matrices (GRM) in making genomic predictions for three distinct beef cattle breeds. Subsequently, we conducted a comparative analysis of the predictive accuracy pertaining to various marker densities and genetic correlations across three distinct beef cattle breeds. This investigation aimed to identify the optimal approach for enhancing the predictive accuracy of multi-breed genomic selection in beef cattle. Results：Genetic relationship matrices revealed moderate similarities between YL and the other breeds, with a striking genetic similarity of 0.87 between WG and HX. In HX cattle, BayesR demonstrated an enhancement in prediction accuracy, achieving 0.52 with HD and 0.46 with WGS, a marked improvement over 0.41 with HD and 0.42 with WGS in GBLUP. In WG and YL breeds, both methods showed comparable accuracies with HD, but BayesR slightly outperformed GBLUP with WGS. Further, multi-breed GS analysis indicated that BayesR consistently surpassed GBLUP in prediction accuracy, particularly with WGS data. For instance, in a combined HX and WG reference population, BayesR achieved a superior accuracy of 0.53 with WGS in HX cattle, a significant enhancement over GBLUP models. The study also underscores the advantage of incorporating multiple breeds in the reference population, which improved prediction accuracy, underscoring the value of broad-based genomic selection strategies. Conclusion: The results show that accuracy of multi-breed genomic predictions was higher with BayesR than with GBLUP, especially for the distantly genetic relationship between reference and validation breeds. Further improvements of multi-breed accuracy of genomic predictions could be achieved by increasing the density of the SNP marker. These findings underscore that BayesR providing a substantial improvement in genomic prediction and the importance of considering genetic relationships in the development of GS strategies for multi-breed cattle populations. Further research is warranted to optimize GRM construction and to explore alternative models for genomic prediction across breeds.