Lithium batteries are widely used due to their advantages such as high energy density, stable performance, low pollution, and long recyclable life. Accurate SOC estimation is important for the use of lithium batteries. To address the problem of low accuracy of SOC estimation by traditional methods, this paper proposes a joint method of fractional order robust unscented Kalman filter (FORUKF) and robust unscented Kalman filter (RUKF) to estimate SOC. The method is based on a fractional order model (FOM) that combines the unscented transformation (UT) technique, the H∞ observer and the joint estimator. Specifically, an adaptive genetic algorithm (AGA) was first used to identify the parameters of the FOM for lithium batteries and to verify the accuracy of the model. Estimation and updating of the ohmic resistance R0 and the capacity QN in the model in real-time by RUKF and then estimation of the SOC by FORUKF. Finally, the accuracy of FORUKF-RUKF was verified under the Federal Urban Driving Schedule (FUDS), US06 Highway Driving Schedule and Beijing Dynamic Stress Test (BJDST). According to the results, the FORUKF-RUKF estimated SOC was found to have better accuracy and robustness than the RUKF, FOUKF and EKF.

The energy transfer process of laser selective melting is very complex. To study the effect of la-ser selective melting on the microstructure and properties of 18Ni-300 martensitic steel, ABAQUS was used to simulate the temperature of laser cladding 18Ni-300 martensitic steel at different time points and different laser power. The results show that the cross-section shape of the molten pool changes from round to oval With the increase of laser power, the higher the peak value of temperature time curve, the greater the temperature gradient; and the laser clad-ding experiment of 18Ni-300 martensitic steel was carried out, and the microstructure and me-chanical properties of the samples under different laser power were analyzed. The results show that with the increase of laser power, the grain size of the cladding layer becomes smaller and the microstructure becomes more compact; the hardness of the side surface of the sample is higher than that of the upper surface, and the tensile strength and elongation show a trend of first increasing and then decreasing.

Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

In order to study the performance of a new type of cement-based grouting material under the coupling effect of freezing-thawing cycle and sulfate attack, experiments were designed and carried out. The damage mechanism of the material under the coupling effect of freezing-thawing and Na2SO4 solution was analyzed by measuring the mass change, relative dynamic elastic modulus, compressive strength loss and microstructure of the new grouting material. With increasing freeze-thaw cycles, mass loss and compres-sive strength loss of the sample in 15% Na2SO4 solution gradually increase, and the relative dynamic elastic modulus gradually decreases. During a 30-cycle freeze-thaw cycle, the mass loss rate, compressive strength loss rate, and relative dynamic elastic modulus of the sample are 4.17%, 24.59%, and 84.3%, respectively, showing good corrosion resistance and frost resistance durability. Microscopic analysis showed that SO42- caused the decomposition of C-S-H gel in the sample and the formation of Gypsum, and the widening of crack width aggravated the internal deterioration, indicating that the material deterioration rate increased under the dual-factor coupling effect.

Large terrestrial carnivores play a crucial role in top-down control within terrestrial ecosystems, maintaining ecosystem stability and biodiversity. However, intense interspecific competition often arises among sympatric large carnivores, leading to population reductions or even extinctions. Spatial partitioning through divergent habitat selection helps mitigate such competition. In Xinlong County, Sichuan Province, we used 293 infrared cameras for monitoring from September to May 2016 and March to October 2022. By employing the Generalized Linear Model (GLM) and the Maximum Entropy Model (MaxEnt), we developed an ensemble model predicting the suitable habitat distribution of leopards (Panthera pardus) and wolves (Canis lupus). We analyzed the main environmental factors influencing habitat selection and the fragmentation of suitable habitats. We found that suitable habitat distribution differed significantly between them. Both species preferred areas with gentle slopes close to settlements. While leopards' habitat selection primarily depended on the distance from settlements, the slope was predominant for wolves. Suitable habitats displayed aggregation, yet wolves exhibited higher fragmentation and more complex patch shapes, indicating greater susceptibility to human activities. These results suggest that sympatric large carnivores, such as leopards and wolves, can reduce spatial competition intensity and promote spatial partitioning by selecting divergent suitable habitats, thereby facilitating species coexistence.

As the application of cyber-physical systems (CPSs) becomes more and more widespread, its security is becoming a focus of attention. Currently, there has been much research on the security defense of the physical layer of the CPS. However, most of the research only focuses on one of the aspects, for example, attack detection, security state estimation or recovery control. Obviously, the effectiveness of security defense targeting only one aspect is limited. Therefore, in this paper, a set of security defense processes is proposed for the case that a CPS containing multiple sensors is subject to three kinds of stealthy attacks (i.e., zero-dynamics attack, covert attack, and replay attack). Firstly, the existing attack detection method based on improved residuals is used to detect stealthy attacks. Secondly, based on the detection results, an optimal state estimation method based on improved Kalman filtering is proposed to estimate the actual state of the system. Then, based on the optimal state, internal model control (IMC) is introduced to complete the recovery control of the system. Finally, the proposed methods are integrated to give a complete security defense process, and the simulation is verified for three kinds of stealthy attacks. The simulation results show that the proposed methods are effective.

Vaccination has proven highly effective against severe acute res-piratory syndrome coronavirus 2 (SARS-CoV-2), but the long-term immunogenicity and the functional preserved im-mune responses of vaccines are needed to inform evolving evi-dence-based guidelines for boosting schedules. We enrolled 205 healthcare workers into a cohort study; all had received three doses of BBIBP-CorV (China Sinopharm Bio-Beijing Company) inactivated vaccine. We assessed SARS-CoV-2 specific binding antibodies, neutralizing antibody, and peripheral T and B cell responses. We demonstrated that more robust antibody re-sponses to SARS-CoV-2 were elicited by booster immunization compared to primary vaccination. Neutralizing antibody titers to SARS-CoV-2 Omicron variant were also efficiently elevated post homologous vaccine booster despite in a lower titer compared to the prototype stain. In addition to S specific humoral and cellular immunity, BBIBP-CorV also induced N-specific antibody and ef-fector T cell responses. The third-dose vaccination led to further expansion of critical polyfunctional T cell responses, likely an essential element for vaccine protection. In particular, a func-tional role for Tfh cell subsets in immunity was suggested by the correlation between both CD4+Tfh and CD8+Tfh with total anti-body, IgG, B cell responses and neutralizing antibodies. Our study details the humoral and cellular responses generated by the BBIBP-CorV booster vaccination in a seven-month follow up study. There is a clear immunologic boosting value of homolo-gous inactivated SARS-CoV-2 vaccine boosters, a consideration for future vaccine strategies.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

Purpose: To clarify the mechanism of state anxiety on intertemporal decision-making, two studies were conducted to investigate the role of trait anxiety and inhibitory control. Study 1 examined the moderating effect of trait anxiety. Study 2 continued to investigate the mediating effect of inhibition control on the basis of study 1. Methods: A total of 266 Chinese college students participated. Participants’ state anxiety, trait anxiety and intertemporal decision-making were measured by questionnaires (scales) respectively. And inhibition control was evaluated by two-choice oddball paradigm. Results: The results of Study 1 indicated that state anxiety could predict intertemporal decision-making and that the moderating effect of trait anxiety on this relationship was significant. Study 2 found that inhibitory control could completely moderate the relationship between state anxiety and intertemporal decision-making and that this indirect effect was affected by trait anxiety. Conclusion: 1)Individuals with higher trait anxiety are more inclined to make more impulsive and intertemporal decisions when they have a high level of state anxiety; 2)state anxiety allows inhibitory control ability to have a further effect on intertemporal decision-making; and 3)the higher trait anxiety in individuals, the stronger mediating effect of inhibitory control on the relationship between state anxiety and intertemporal decision-making.

The mining sector generates a substantial quantity of stone waste and tailings, which constitutes an environmental risk. The most prevalent method for disposing of this industrial waste is dumping, which contributes to soil deterioration and water contamination while acquiring precious land. It can be recycled using a number of processes, such as the promising geopolymerization technique, which transforms waste into value. This study reviews current developments in the manufacturing of mine tailings-based geopolymer composites from industrial waste as a possible sustainable building material. This paper also gives in-depth studies on the characteristics and behaviors of mine tailings composites used in geopolymer manufacturing, including durability, microstructure, thermal and leaching properties. This review also identifies knowledge gaps that must be filled in order to advance mine tailings composites for geopolymers.

Flood forecasting helps anticipate floods and evacuate people, but due to the access of a large number of iot data acquisition devices, the explosive growth of multidimensional data and the increasingly demanding prediction accuracy, classical parameter models and traditional machine learning algorithms are unable to meet the high efficiency and high precision requirements of prediction tasks. In recent years, deep learning algorithms represented by convolutional neural networks, recurrent neural networks and Informer models have achieved fruitful results in time series prediction tasks. The Informer model is used to predict the flood flow of the reservoir. At the same time, the prediction results are compared with the prediction results of the traditional method and the LSTM model, and how to apply the Informer model in the field of flood prediction to improve the accuracy of flood prediction is studied. The data of 28 floods in the Wan 'an Reservoir control basin from May 2014 to June 2020 were used, with areal rainfall in five subzones and outflow from two reservoirs as inputs and flood processes with different sequence lengths as outputs. The results show that the Informer model has good accuracy and applicability in flood forecasting. In the flood forecasting with sequence length of 4, 5 and 6, Informer has higher prediction accuracy, and the prediction accuracy is better than other models under the same sequence length, but the prediction accuracy will decline to a certain extent with the increase of sequence length. The Informer model stably predicts the flood peak better, and its average flood peak difference and average maximum flood peak difference are the smallest. As the length of the sequence increases, the number of fields with a maximum flood peak difference less than 15% increases, and the maximum flood peak difference decreases. Therefore, the Informer model can be used as one of the better flood forecasting methods, and it provides a new forecasting method and scientific decision-making basis for reservoir flood control.

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics, and thermodynamic parameters of peanut shell using TGA under atmospheric air. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1. Pre-exponential factors using FWO range from 2.19×106 to 8.06×107 s–1, and for KAS range from9.72×105 to 2.25×107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤ ±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

The conversion of CO2 into more synthetically flexible CO is an effective and potential method for CO2 remediation, utilization and carbon emission reduction. In this paper, the reaction of carbon-carbon dioxide (Boudouard reaction) was performed in a microwave fixed bed reactor using semi-coke (SC) as both the microwave absorber and reactant and was systematically compared with that heated in a conventional thermal field. The effects of the heating source, SC particle size, CO2 flow rate and additives on CO2 conversion and CO output were investigated. By microwave heating (MWH), CO2 conversion reached more than 99 %, while by conventional heating (CH), the maximum conversion of CO2 was approximately 29% at 900 °C. Meanwhile, for the reaction with 5 wt% Barium Carbonate added as a promoter, the reaction temperature was significantly reduced to 750 °C with almost quantitative conversion of CO2. Further kinetic calculations showed that the apparent activation energy of the reaction under microwave heating was 46.3 kJ/mol, which was only one-third of that observed under conventional heating. The microwave-assisted Boudouard reaction with catalytic barium carbonate is a promising method for carbon dioxide utilization.

The application of 3D LiDAR technology has become increasingly extensive in tunnel monitoring due to the large density and high accuracy of the acquired spatial data. The proposed processing method aims at circle tunnels and provides a clear workflow to automatically process raw point data and easily interpretable results to analyze tunnel health state. The proposed automatic processing method employs a series of algorithms to extract point cloud of a single tunnel segment without obvious noise from entire raw tunnel point cloud mainly by three steps: axis acquisition, segments extraction and denoising. Tunnel axis is extracted by fitting boundaries of the tunnel point cloud rejection in plane with RANSAC algorithm. With guidance of axis, the entire preprocessed tunnel point cloud is segmented by equal division to get a section of tunnel point cloud which corresponds to a single tunnel segment. Then the noise in every single point cloud segment is removed by clustering algorithm twice, based on distance and intensity. Finally, clean point clouds of tunnel segments are processed by effective deformation extraction processor to get ovality and three-dimensional deformation nephogram.

Currently, the number of lightning casualties and casualty rates have significantly reduced in developed countries, but there has been no significant reduction in developing countries. On the one hand, this is due to the high frequency of lightning; on the other hand, the vulnerability of people in developing countries is also an influencing factor. Through case analysis and summary, this paper expounds on lightning injury’s mechanism and clinical manifestations. It points out that lightning injury is mainly related to heart problems and the impact on the nervous system, rather than burns, which usually cause fewer consequences. Medical treatment needs to pay attention to the order and principles of treatment. Implementing CPR and auxiliary AED is the most effective way to save lives. Attention should be paid to the practical and effective treatment and nursing of lightning stroke sequelae. Finally, combined with the situation of lightning casualties in china, the existing problems are put forward during the process of early treatment, post-hospital treatment, and nursing observation, which provides an objective basis for the cognition of the scientific nature of the lightning injury.

Ultra-thin Fe–6.5wt.%Si ribbons with 35 μm in thickness were prepared by melt-spinning. The magnetic properties were investigated before and after annealing 1000 ºC. DC properties and low-frequency (400 Hz ~ 10 kHz) iron losses have significantly improved after heat treatment. A simplified formula based on Steinmetz law which can be used to predict the AC iron loss is presented. According to the results of some iron losses data, a simplified formula has been determined, and the extent of AC iron losses can be predicted. The results obtained from the formula predict AC iron loss to a good degree. The method developed in this work could be extended to other magnetic materials for predicting AC iron loss with greater ease.

From a scientific standpoint, both temporal and spatial variables must be examined when developing programs for training various soccer scoring techniques (SSTs), but a review of current literature reveals that existing scientific studies have overlooked this combinatory influence. Consequently, there is no reliable theory on temporal-spatial identification when evaluating scoring opportunities. Quantified by using biomechanical modeling, anthropometry, and SSTs found in FIFA Puskás Award (121 nominated goals between 2009 and 2020), it is found that players’ proprioceptive/effective shooting volume (i.e. players’ attack space) could be sevenfold the currently-practiced shooting volume. The ignorance of some SSTs’ training leads to the underuse of the potential shooting volume. These overlooked SSTs are airborne and/or acrobatic techniques, perceived as high-risk and low-reward. Relying on the talent of an athlete to improvise on the fly can hardly be considered as a viable coaching strategy. Therefore, for developing science-based SST training regimes, groundbreaking studies are needed to: 1) expand the perception of shooting volume, and 2) entrain one-touch-shot techniques (airborne/acrobatic) within this volume, in short, Focusing-on-Time-in-Space. Whence, the new temporal-spatial theory could guide future researches and develop novel training programs. An increase of airborne/acrobatic goals would ultimately further enhance the excitement of the game.

In the end, this paper analyzed the economy from the investment in plant construction, raw material collection, product production and product sales. The resulting products include pyrolytic carbon, pyrolytic oil, pyrolysis gas. The results showed that when the treatment scale was 1 ton h−1, the pyrolysis plants with three loading modes will always be in a state of loss during the 20-year running time. When the processing scale was 9 ton h−1, the pyrolysis plant can be profitable in the first year. In the sensitivity analysis, the influence of three pyrolysis products on the total return on investment was explored. The results showed that the price change of pyrolysis oil has the greatest influence on the total return on investment (Total ROI) under the three loading methods, The price change of pyrolysis gas has minimal impact on the Total ROI. This study provides basic data and basis for the commercialization of coal-biomass co-pyrolysis technology and investment in plant construction.

The creep behaviors of TA2 and R60702 at low and intermediate temperature were presented and discussed in this paper. Experimental results indicated that an apparent threshold stress exhibited in the creep deformation of R60702. Meanwhile, the primary creep phase was found as the main pattern in the room temperature creep behavior of TA2. Compared with exponential law, the power law has been proved to be a proper constitutive model in the description of primary creep phase. It also showed that θ projection method had its significant advantage in the evaluation of accelerated creep stage. Thus, a composite model which combined power law with θ projection method was applied in the creep curves evaluation at low and intermediate temperature. Based on the multiaxial creep deformation results, the model was modified and discussed. A linear relationship existed between composite model parameters and applied load. Finally, the creep life could be accurately predicted and the composite model method is suitable for application in low and intermediate temperature creep life analysis.

(1) Background: Bacterial reinfection and root fracture are the main culprits related to root canal treatment failure. This study aimed to assess the utility of quercetin solution as an adjunctive endodontic irrigant that strengthen root canal dentin with commitment anti-biofilm activity and bio-safety. (2) Methods: Based on a noninvasive dentin infection model, dentin tubules infected with Enterococcus faecalis (E. faecalis) were irrigated with sterile water (control group), and 0, 1, 2, 4 wt% quercetin-containing ethanol solutions. The live and dead bacteria proportions within E. fae-calis biofilms were analyzed using confocal laser scanning microscopy (CLSM). Elastic modulus and hydroxyproline release and X-ray photoelectron spectroscopy (XPS) characterization was tested on irrigant-treated demineralized dentin to evaluate irrigants’ biostability. The cytotoxicity of irrigants was tested by CCK-8 assay. (3) Results: Quercetin increased the proportion of dead bacteria volumes within E. faecalis, and improved the flexural strength of dentin collagen com-pared to control group. The XPS characterization revealed an increase in C-O peak area under both C1s and O1s narrow-scan spectra. The CCK-8 assay confirmed no cytotoxicity of quercetin solutions. (4) Conclusions: Quercetin exhibited anti-biofilm activity, collagen-stabilizing effect as well as cytocompatibility, supporting quercetin as a potential candidate for endodontic irrigant.

This study takes a two-echelon agricultural products supply chain (APSC) composed of an agricultural product processor (processor) and an agricultural product supermarket (supermarket) as the research object. In order to ensure the stable supply of high-quality agricultural products, this paper considers both fairness concern and corporate social responsibility (CSR), and establishes four Stackelberg game models with or without considering fairness concern and CSR, and obtains the influence mechanism of fairness concern and CSR on bilateral quality efforts in APSC through comparative analysis and numerical analysis. Research shows that the supermarket’s fairness concern can take the role of "profit distribution mechanism", but it is not conducive to improving bilateral quality efforts resulting in the inability to improve market demand, and it is not conducive to improving the utility of the supply chain system and consumer surplus; both members of APSC sharing CSR can not only improve the quality of agricultural products and promote the expansion of market demand, but also can achieve Pareto improvement of both profit of all members and supply chain system. Besides, The CSR shared by both members has a greater impact on bilateral quality efforts decision than the supermarket’s fairness concern, and thus the positive effect of CSR can overcome the negative effect of supermarket’s fairness concern.

That how to improve the sensitivity and the detection ability of the Large-caliber sensor is critical to satisfy the requirement of heavy vehicle wear condition monitoring. In this paper, we introduced the LC resonance principle to the design of sensor with large flow channel (7mm). The resonant exciting coil increases the impedance change of the exciting circuit caused by wear particles which magnify the current difference between the two exciting coils and improve the sensitivity of the sensor. The resonant induction coil greatly suppresses the interference signals and magnifies the weak induced electromotive force which is beneficial to enhance the detection ability. In order to boost the detectability for different materials particles, a phase controlled variable-frequency exciting system (PCVFES) was adopted to automatically switch the exciting frequency between 284kHz for ferromagnetic particles and 420KHz for non-ferromagnetic particles. For the weak signal detection, based on the essential characteristic of the signal, we apply a simpler method that modified lock-in amplifier (MLIA) rather than the conventional algorithms (Wavelet transform, EMD). Results show that using these methods the sensitivity and the detection ability of the sensor are significantly improved and the 75μm iron particles and 220μm copper particles were successfully detected which realizes the initial abnormal wear monitoring for the large flow project.

In this study we used a non-autonomous Chua’s Circuit, and the fractional Lorenz chaos system together with a detection method from Extension theory to analyze the voltage signals. The measured bearing signals by acceleration sensor were introduced into the master and slave systems through a Chua’s Circuit. In a chaotic system minor differences can cause significant changes that generate dynamic errors, and extension matter-element models can be used to judge the bearing conditions. Extension theory can be used to establish classical and sectional domains using the dynamic errors of the fault conditions. The results obtained were compared with those from Discrete Fourier Transform analysis, Wavelet analysis and an integer order chaos system. The diagnostic ratio showed the fractional order master and slave chaos system calculations. The results show that the method presented in this paper is very suitable for monitoring the operational state of ball bearing system to be superior to the other methods. The diagnosis ratio was better and there were other significant advantages such as low cost and few.

Network Embedding (NE) is an important method to learn the representations of network via a low-dimensional space. Conventional NE models focus on capturing the structure information and semantic information of vertices while neglecting such information for edges. In this work, we propose a novel NE model named BimoNet to capture both the structure and semantic information of edges. BimoNet is composed of two parts, i.e., the bi-mode embedding part and the deep neural network part. For bi-mode embedding part, the first mode named add-mode is used to express the entity-shared features of edges and the second mode named subtract-mode is employed to represent the entity-specific features of edges. These features actually reflect the semantic information. For deep neural network part, we firstly regard the edges in a network as nodes, and the vertices as links, which will not change the overall structure of the whole network. Then we take the nodes' adjacent matrix as the input of the deep neural network as it can obtain similar representations for nodes with similar structure. Afterwards, by jointly optimizing the objective function of these two parts, BimoNet could preserve both the semantic and structure information of edges. In experiments, we evaluate BimoNet on three real-world datasets and task of relation extraction, and BimoNet is demonstrated to outperform state-of-the-art baseline models consistently and significantly.

Although the Orthotropic steel decks (OSDs) have been widely used in the construction of long-span bridges, there are frequently reported fatigue cracks after years of operation, and the bridge deck overlay also presents severe damage due to OSD crack-induced stiffness reduction. The ultra-high performance concrete (UHPC), recognized as the most innovative cementitious composites and the next generation of high-performance materials, shows high strength, ductility, toughness and well performance on durability. After its first application to the OSD bridge in early 2000s, the orthotropic Steel-UHPC composite deck has been comprehensively studied worldwide. This review will summarize some important studies and findings on behavior and fatigue performance of orthotropic steel-UHPC composite deck. The existing studies and engineering application indicate that such deck system presents good bending behavior and high fatigue performance. The failure mode of shear studs in UHPC layer is dominated by shear fractures. The cracking of UHPC layer shall consider the superposition effect of stress from both the whole bridge structure and local decks. While some reasonable structural details in the traditional OSD may not work for the orthotropic steel-UHPC composite deck. It is recommended to evaluate the stress behavior and structural parameters, as well as fatigue life by conducting the field test under in-service traffic conditions.

Abstract：The brain often switches freely between focused attention and divergent thinking, and the default mode network (DMN) is activated during brain rest. The discovery, function and characteristics of default mode network all indicate that learning does not stop when the brain "rests". Mental disease can lead to dysfunctional default mode networks, which affects learning adversely. Therefore, default mode network plays an important role in learning. Neural activities such as β-wave rhythm regulation, "subconscious" divergence mode initiation, hippocampal function and neural replay occur during default mode, which also explain that "rest" promotes learning. This paper reveals the role and neural mechanism of default mode network in learning from the neural level, discusses the essential role default mode network plays in learning, and default mode network enables rest to promote learning.

Traditional lithium-ion batteries cannot meet the high flexibility and bendability requirements of modern flexible electronic devices due to the limitations of their electrode materials. Therefore, the development of high-performance flexible energy storage devices is of great significance for promoting flexible electronics. In recent years, one-dimensional flexible fiber lithium-ion batteries have been rapidly developed due to the advantages of high flexibility and bendability. However, it is still a big challenge to realize 1D flexible fiber lithium-ion batteries with excellent electro-chemical properties and good mechanical performance. In this work, a reduced graphene ox-ide-based printing ink is proposed to fabricate flexible Li4Ti5O12/graphene fiber electrodes through a 3D printing assembly strategy. It is noteworthy that the green reducing agent vitamin C was used to reduce graphene oxide in one step, which improved the conductivity of the fiber elec-trode. Furthermore, a 3D conductive network is constructed inside the fiber electrodes due to the high specific surface area of reduced graphene oxide, which enhances the electronic conductivity and ion mobility. The fiber electrode not only has good mechanical performance, but also has ex-cellent electrochemical properties. Equally important, the method is simple and efficient, and the working environment is flexible. It can precisely control the shape, size and structure of the one-dimensional fiber flexible electrode, which is of great significance for the development of fu-ture flexible electronic devices.

Given the documented wave-induced damage of elevated coastal decks during extreme natural hazards (e.g. hurricanes) in the last two decades, it is of utmost significance to decipher the wave-structure-interaction of complex deck geometries and quantify the associated loads. Therefore, this study focuses on the assessment of solitary wave impact on open-girder decks that allow the air to escape from the sides. To this end, an arbitrary Lagrangian-Eulerian (ALE) numerical method with a multi-phase compressible formulation is used for the development of three-dimensional hydrodynamic models, which are validated against a large-scale experimental dataset of a coastal deck. Using the validated model as a baseline, a parametric investigation of different deck geometries with a varying number of girders Ng and three different widths, was conducted. The results reveal that the Ng of a superstructure has a complex role and that for small wave heights the horizontal and uplift forces increase with the Ng, while for large waves the opposite happens. If the Ng is small the wave particles accelerate after the initial impact on the offshore girder leading to a more violent slamming on the onshore part of the deck and larger pressures and forces, however, if Ng is large then unsynchronized eddies are formed in each chamber, which dissipate energy and apply out-of-phase pressures that result in multiple but weaker impacts on the deck. The decomposition of the total loads into slamming and quasi-static components, reveals surprisingly consistent trends for all the simulated waves, which facilitates the development of predictive load equations. These new equations, which are a function of Ng and are limited by the ratio of the wavelength to the deck width, provide more accurate predictions than existing empirical methods, and are expected to be useful to both engineers and researchers working towards the development of resilient coastal infrastructure.

Paraphrase generation is an important yet challenging task in NLP. Neural network-based approaches have achieved remarkable success in sequence-to-sequence(seq2seq) learning. Previous paraphrase generation work generally ignores syntactic information regardless of its availability, with the assumption that neural nets could learn such linguistic knowledge implicitly. In this work we make an endeavor to probe into the efficacy of explicit syntactic information for the task of paraphrase generation. Syntactic information can appear in the form of dependency trees which could be easily acquired from off-the-shelf syntactic parsers. Such tree structures could be conveniently encoded via graph convolutional networks(GCNs) to obtain more meaningful sentence representations, which could improve generated paraphrases. Through extensive experiments on four paraphrase datasets with different sizes and genres, we demonstrate the utility of syntactic information in neural paraphrase generation under the framework of seq2seq modeling. Specifically, our GCN-enhanced models consistently outperform their syntax-agnostic counterparts in multiple evaluation metrics.

Mode locked pulse generation has been reported using both active and passive mode locking schemes. Active mode locking technique has been proven to be an effective way to generate high-repetition-rate pulses by incorporating a modulator inside the laser cavity. Compared to actively mode locked lasers, passively mode locked lasers can generate pulse train at ultrashort pulse width but with relatively lower repetition rate. Thus, it is a brilliant idea to build a hybrid mode locked system combining both active and passive mode lockers. In this review, several hybrid mode locked fiber ring laser systems are discussed and summarized. Hybrid mode locking is a promising method to generate high speed ultrashort optical pulses for fiber-optic telecommunication system.

With the great development of intelligent transportation systems (ITS), travel time prediction has attracted the attentions of many researchers and a large number of prediction methods have been developed. However, as an unavoidable topic, the predictability of travel time series is the basic premise for travel time prediction has received less attention than the methodology. Based on the analysis of the complexity of travel time series, this paper defines travel time predictability to express the probability of correct travel time prediction and proposes an entropy-based method to measure the upper bound of travel time predictability. Multiscale entropy is employed to quantify the complexity of travel time series, and the relationships between entropy and the upper bound of travel time predictability are presented. Empirical studies are made with vehicle trajectory data in an express road section. The effectiveness of time scales, tolerance, and series length to entropy and travel time predictability are analysis, and some valuable suggestions about the accuracy of travel time predictability are discussed. Finally, the comparisons between travel time predictability and actual prediction results from two prediction models, ARIMA and BPNN, are conducted. Experimental results demonstrate the validity and reliability of the proposed travel time predictability.

This paper has designed a four-channel wide dynamic microwave rectifier circuit for the shortcomings of uneven output voltage of each branch of the multi-channel rectification technology. A voltage-doubling rectifier circuit with identical structure was used in each branch. The four rectifier branches shared the same load at the output terminal, allowing the rectifier circuit to have an RF-DC conversion efficiency greater than 50% over the input power range from 12mW to 274mW, widened by 274% compared to a single channel. Not only the advantages of multi-channel technology with wide dynamics were retained, but also the output voltage was highly consistent and could be directly output in parallel without complex power electronics conversion.

The branch prediction units (BPUs) generally have security vulnerabilities, which can be used by attackers to obtain the execution status, jump directions, and jump address of conditional branches, and the existing protection methods cannot defend against these attacks. Therefore, this article proposes a hardware security protection method for conditional branches of embedded systems. This method calculates the number of updates to the branch target buffer (BTB). When it exceeds the threshold, BTB is locked to prevent attackers from analyzing the execution status of branches based on the time difference of whether BTB is updated. Moreover, the hybrid physical unclonable function (PUF) circuit is designed to provide confidentiality protection for the jump directions, jump addresses, and their indexes, preventing attackers from stealing these critical data. If these mechanism fails and attackers successfully tamper with conditional branches, this paper proposes a control flow integrity (CFI) protection mechanism based on branch labels to timely detect tampering with instruction codes, jump addresses, and jump directions. The proposed method is implemented and tested on FPGA. The experimental results show that this method can achieve fine-grained security protection for conditional branches, with about 5.4% resource overhead and less than 5.5% performance overhead.

Microsoft has implemented several measures to defend against macro viruses, including the use of Anti-malware Scan Interface (AMSI) and automatic macro blocking. Nevertheless, evidence shows that threat actors have found ways to bypass these mechanisms. As a result, phishing emails continue to apply malicious macros as their essential attack vector. In this paper, we analyze 77 obfuscation features from the attacker’s point of view and extract 46 suspicious keywords in macro. We first combine the above two types of features to train machine learning models on a public dataset. Then, we carry out the same experiment on self-constructed dataset, a collection of newly discovered samples, to see if our proposed method could discover the unseen malicious macros. Experimental results demonstrate that, comparing with the existing researches, our proposed method has a higher detection rate and better consistency. Furthermore, ensemble multi-classifiers with distinct feature selection further improve the detection performance.

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

With the changing relationship between urban and rural areas in China, the rural areas are experiencing rapid social transformation. To ensure successful implementation of the rural revitalization strategy, land consolidation has become a major measure of rural economic reform. Existing research focuses on quantitative studies exploring the relationship between land consolidation and rural economic development, but there is a lack of studies on the relationship between land consolidation and social change. In this study, Jin’an Village is selected as the research area, using semi-structured interviews and semi-participatory observation to obtain original materials, aiming to make a detailed description of the specific practice of land consolidation, and to analyze the impact of land consolidation on the transformation of rural social consciousness. The study found that rural land consolidation involves villagers in the land consolidation process, which can effectively stimulate villagers’ participation in public affairs. Concurrently, the interaction between villagers and outside investors disrupts the conventional socialization model in rural areas and motivates villagers to act in accordance with contractual agreements. The conclusion is that land consolidation in rural areas can enhance the political democracy and legal consciousness of local villagers, which can lead to a change in local social consciousness. Our findings also emphasize the crucial necessity to grant rural villagers with improved accessibility to professional services and information, coupled with the continued promotion of land consolidation to advance modernization in these areas.

China’s greenhouse industry has thousands of years of development history, although the development of modern greenhouses has come late. After decades of development of China, its greenhouse industry is in the forefront of the world. China’s greenhouse industry is experiencing rapid development, transformation and upgrading. China ranks first in the world in terms of greenhouse area, used mainly for vegetable cultivation and plays an important role in the utilization of agricultural resources and food production. In 2023, the cumulative area of new greenhouses nationwide was 1835.87 million ha. In this paper we present the latest developments in the greenhouse sector. More specifically, we present a greenhouse market development overview, the greenhouse production, the greenhouse industry, and technology development. Current problems are underpinned, development opportunities and prospects are analyzed, and measures and specific proposals are detailed for the technological development of the greenhouse sector both for increasing product quantity and quality.

Directional solidification experiments were carried out to investigate the effect of micro-alloying element Sn and magnetic field on the solidification of Al-Bi immiscible alloys. Experimental results show that the size distribution of the dispersed particles in the low-speed solidified Al-3.4wt%Bi alloy presents two peaks, while it only shows one peak when solidified at a relatively high speed. The addition of Sn not only can enhance the nucleation rate and the number density of the Bi-rich droplets in the sample, but also decrease the Marangoni migration velocity and the axial resultant velocity of minority phase droplets in front of the solidification interface. Thereby it promotes the formation of Al-Bi alloys with a well-dispersed microstructure. A static magnetic with the strength of 0.2T increase the number density of the dispersed particles and decrease the average size and the size distribution width of the dispersed particles. Under the effect of Sn addition and static magnetic field, the average radius of the dispersed particles <R> and the solidification velocity V_0 satisfy <R>∝〖V_0〗^(-1/3) when the alloy was solidified at a relatively low velocity, <R> and V_0 satisfy <R>∝〖V_0〗^(-1/2) when the alloy is solidified at a high velocity.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate the tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) the tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving the tour routes, the transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

We found an important fact that the beam footprint line of Ping will intersect with the real water depth when the initial incidence angle is about 45°, and sound velocity error hardly has an effect on it. This is contrary to our previous experience that the soundings of the central beam of multi-beam bathymetric system (MBS) is the most accurate. Firstly, the influence of sound velocity errors on central beam and seafloor topography distortion was analyzed. Secondly, the process of proving this fact was given, and the topography correction method was proposed by compensating the sound velocity profile area (SVP area). Finally, we showed in the first simulation of four type errors in SVPs that this fact is verified. The topography correction method used in the second simulation to correct the topography distortion of the first simulation is also verified.

With the accelerating urbanization process, the population increasingly concentrates in urban areas. In view of the special situation in China and a series of problems in the process of rapid urbanization, there were no reasonable measures for optimizing the population pattern. This study explored the distribution pattern of the Chinese population and proposed an optimization plan for the population distribution using GIS analysis. The main findings were as follows. (1) From 2010 to 2015, the distribution of population density in China presented a pattern of high in the southeast and low in the northwest based on the county-level administrative regions. The population still showed a tendency to migrate to the southeast of the country based on the “Hu Huanyong Line”. (2) There was a great difference in the land use efficiency in terms of population and economic production in China. The economic concentration in China was higher than the population concentration. In the areas where population and economic production were aggregated, GDP per capita and land use efficiency were higher. (3) Based on the land use efficiency in terms of population and economic production, the optimized urbanization plan of “1+4+11” for China’s urbanization was put forward, namely, one national-level aggregated area of population and economic production, 4 regional-level aggregated areas of population and economic production, and 11 local regionally aggregated areas of population and economic production. This optimization plan for urbanization represents an attempt to explore the direction of China’s urbanization, and it can be used to optimize the spatial development pattern and provide scientific guidance for the new urbanization plan.

Aiming at the prediction of environmental vibrations induced by elevated high-speed railway, a machine-learning method is developed by combining random forest algorithm and Bayesian optimization, which using the dataset from on-site experiments . When it comes to achieving a rapid and effective prediction of environmental vibration, there is few research on com-parisons and verifications of different algorithms, and neither on parameter tuning and optimi-zation of machine learning algorithms. In this paper, a field experiment is firstly carried out to measure the ground vibrations caused by high-speed trains running on bridge, and then the en-vironmental vibration characteristics are analyzed in view of ground accelerations and weighted vibration levels. Subsequently, three machine-learning algorithms of linear regression, support vector machine and random forest are developed by using experimental database, and their prediction performance are discussed. Finally, two optimization models for the hyperparameter set of random forest algorithm are further compared. It turns out that the integrated random forest algorithm has higher accuracy in predicting environmental vibration than linear regression and support vector machine; the Bayesian optimization has excellent performance and high efficiency in achieving efficient and in-depth optimization of parameters, and can be combined with the RF machine learning algorithm to effectively predict the environmental vibrations induced by the high-speed railway.

Intelligent ship technology is currently an international research hotspot, and model predictive control is widely used in the path-tracking control of intelligent vehicles. To construct an intelligent ship anti-disturbance path-tracking control method, firstly, an environmental disturbance model was constructed with the actual meteorological data of the target sea area. Secondly, the Fossen ship equation of motion is linearized and discretized as the ship motion model. Thirdly, the expression of the prediction equation is derived from the ship motion model. Fourthly, the cost function is constructed by using the polar diameter and polar angle values of the ship. Fifth, the power function in the cost function is replaced with an exponential function to obtain an improved cost function. Sixthly, according to the Lyapunov theory and the MPC terminal constraint theory, the stability of the improved cost function is verified. Seventh, different test paths are set up, the environmental disturbance model is taken as the external disturbance, the ship motion model, the prediction equation, and the improved cost function are used to design the anti-disturbance path-tracking control algorithm according to the model prediction control idea for simulation experiments. Finally, different MATLAB simulation results show that the improved cost function can resist disturbance of the external wave, current, and wind, and effectively track the target path. Therefore, this study provides a reference for improving the navigation safety of ship path-tracking.

High-rise building fires pose a serious threat to the lives and property safety of the people. The lack of reliable and accurate positioning means is one of the main difficulties faced by rescue. In the absence of prior knowledge of the high-rise building fire environment, the coverage deployment of mobile base stations is a challenging problem that has not received much attention in the literature. This paper studies the problem of autonomous optimal deployment of base stations in high-rise building fire environment based on UAV group. A novel problem formulation is proposed that solves the non line of sight (NLOS) positioning problem in complex unknown environment. The purpose of this paper is to realize the coverage and deployment of mobile base stations in complex and unknown fire environment. The NLOS positioning problem in the fire field environment is turned into the line of sight (LOS) positioning problem through the optimization algorithm. And there are more than three LOS base stations nearby any point in the fire field. A control law which is formulated in a mathematically precise problem statement is developed that guarantees to meet mobile base stations deployment goal and to avoid collision. Finally, positioning accuracy of our method and that of common method were compared. The simulation result showed that the positioning accuracy of simulated firefighter in the fire field environment was improved greatly.

Cloud-based CNC is an emerging paradigm of Industry 4.0 where computer numerical control (CNC) functionalities are moved to the cloud and provided to manufacturing machines as a service. Among many benefits, C-CNC allows manufacturing machines to leverage advanced control algorithms running on cloud computers to boost their performance at low cost, without need for major hardware upgrades. However, a fundamental challenge of C-CNC is how to guarantee safety and reliability of machine control given variable Internet quality of service, especially on public Internet networks. We propose a three-tier redundant architecture to address this challenge. We then prototype tier one of the architecture on a 3D printer successfully controlled via C-CNC over public Internet connections, and discuss follow-on research opportunities.

Mineral identification is an important part of geological analysis. Traditional identification methods rely on either the experiences of the appraisers or the various measuring instruments and the methods are either easily influenced by the experiences or need too much work. To solve the above problems, there have been studies using image recognition and intelligent algorithms to identify minerals. But the current studies can not identify many minerals, and the accuracy is low. To increase the number of identified mineral categories and the accuracy, we proposed the method that uses both the mineral images and the Mohs hardness in the deep neural networks to identify the minerals. The experimental results showed that the method can reach 94.0% Top-1 accuracy and 99.9% Top-5 accuracy for 28 common minerals. The model that combines image and Mohs hardness together can identify more minerals and increase the accuracy using less training data.

A novel electrospun nanofiber was developed using polyamide-6 (PA) and ε-poly-L-lysine (PL). PA is a popular textile polymer having desirable mechanical and thermal properties, chemical stability, and biocompatibility. However, PA nanofibers are prone to bacterial growth and user discomfort. PL, a natural homopolyamide, is non-toxic, antimicrobial, and hydrophilic but lacks spinnability due to its low molecular weight. Given its similar backbone structure as PA, with an additional amino side chain, PL was integrated with PA to develop multifunctional nanofibers. This study explores a simple, scalable method to obtain PL nanofibers by utilizing the structurally similar PA as the base. The goal was to enhance the functionality of PA by addressing its drawbacks. The study demonstrates spinnability of varying concentrations of PL with base PA while exploring compositions with higher PL concentrations than previously reported. Electrospinning parameters were studied to optimize the nanofiber properties. The effects of PL addition on morphology, hydrophilicity, thermal stability, mechanical performance, and long-term antimicrobial activity of nanofibers were evaluated. The inclusion of PL in PA-based nanofibers resulted in super hydrophilicity, increased tensile strength, and efficient antimicrobial properties with long-term stability. These enhanced characteristics hold promise for the composite nanofiber’s application in medical and protective textiles.

At different heat treatment temperatures, the hardness and flexural strength of M2 high-speed steel selective laser melting (SLM) parts show mixed trends. When the heat treatment temperature is 260°C, the hardness and flexural strength of the M2 high-speed steel SLM part are decreased, but the hardness difference between the upper and lower surfaces of the M2 high-speed steel SLM part is also reduced. When the heat treatment temperature is 560°C, the hardness and flexural strength of the M2 high-speed steel SLM part are almost close to that of the original M2 high-speed steel SLM part, and the performance gradient in the sample is improved, and the overall structure is uniform. When the subsequent heat treatment temperature is 860 °C, the hardness of the SLM parts reaches a minimum, with an average value of 24 HRC. However, the flexural strength exceeds that of the original SLM parts. Moreover, the microstructure of the sample is uniform, which significantly improves the anisotropy of performance.

Jumping side volley has created breathtaking moments and cherished memories for us. Regrettably, a scientific study on the skill has not been found in literature. Relying on talent of athletes to improvise on the fly can hardly be considered a viable learning strategy. This study targets to fill the gap by quantifying factors contributing to develop its coaching method. Using 3D motion capture (12-cameras, 200Hz) and full-body biomechanical modeling, our study aimed to identify elements that govern entrainment of the skill by examining jumping, kicking and falling phases of its execution. Given the rarity of players who have acquired this skill, we found five subjects for the study. Twenty-three trials were captured and quantified. The results unveil the following key elements: 1) the control of trunk rotation during the jumping, 2) the angle between thighs upon take-off, 3) the whip-like control of the kicking leg during airborne, 4) timing between ball motion and limbs’ coordination, and 5) damping mechanism during falling. An accurate kick can only be achieved through repetitive training. This underlines the need for athletes to master a safe landing technique that minimizes risk of injury during practice. Therefore, training should begin with learning a safe falling technique.

Formaldehyde (HCHO), an indoor volatile organic compound, is seriously harmful to human health. Therefore, green and effective decomposition of HCHO is essential. TiO₂ has been employed for the degradation of HCHO via photocatalytic generation of reactive oxygen species (ROS) (O^2-, ·OH), yet the low specific surface area of crystalline TiO₂ depressed the catalytic performance. Herein, we prepared TiO₂ aerogels with high specific surface area and high porosity by sol-gel method, and added PVA to introduce flexible molecular chains for pore size regulation. The photocatalytic performance test verifies that the pore size of TiO₂ aerogel is one of the important factors for HCHO decomposition. Notably, through the establishment of theoretical model and calculation, we validated that the efficiency of HCHO decomposition is related to the oxygen pressure in the pores of TiO₂ aerogel, and the oxygen pressure is inversely proportional to the pore size. Accordingly, the optimal pore size of TiO₂ aerogel for the photocatalytic HCHO decomposition is 2 nm~10 nm. This study provides a theoretical idea for TiO₂ aerogels in the decomposition reaction of HCHO, which is expected to inspire more breakthroughs in the study of TiO₂ aerogels for green chemistry.

Formaldehyde (HCHO), an indoor volatile organic compound, is seriously harmful to human health. Therefore, green and effective decomposition of HCHO is essential. TiO2 has been employed for the degradation of HCHO via photocatalytic generation of reactive oxygen species (ROS) (O2-, ·OH), yet the low specific surface area of crystalline TiO2 depressed the catalytic performance. Herein, we prepared TiO2 aerogels with high specific surface area and high porosity by sol-gel method, and added PVA to introduce flexible molecular chains for pore size regulation. The photocatalytic performance test verifies that the pore size of TiO2 aerogel is one of the important factors for HCHO decomposition. Notably, through the establishment of theoretical model and calculation, we validated that the efficiency of HCHO decomposition is related to the oxygen pressure in the pores of TiO2 aerogel, and the oxygen pressure is inversely proportional to the pore size. Accordingly, the optimal pore size of TiO2 aerogel for the photocatalytic HCHO decomposition is 2 nm-10 nm. This study provides a theoretical idea for TiO2 aerogels in the decomposition reaction of HCHO, which is expected to inspire more breakthroughs in the study of TiO2 aerogels for green chemistry.

The ability to handle spatiotemporal information makes contribution for improving the prediction performance of machine RUL. However, most existing models for spatiotemporal information processing are not only complex in structure but also lack adaptive feature extraction capabilities. Therefore, a lightweight operator with adaptive spatiotemporal information extraction ability named Involution GRU (Inv-GRU) is proposed for aero-engine RUL prediction. Involution, the adaptive feature extraction operator, is replaced by the information connection in the gated recurrent unit for obtaining the adaptively spatiotemporal information extraction ability and reducing the parameters. Thus, Inv-GRU can well extract the degradation information the of aero-engine. Then for RUL prediction task, the Inv-GRU based deep learning (DL) framework is firstly constructed, where features extracted by Inv-GRU and several human-made features are separately processed to generate the health indicators (HIs) from multi-raw data of aero-engines. Finally, fully connection layers are adopted are adopted to reduce dimension and regress RUL based on the generated HIs. By applying the Inv-GRU based DL framework to the Commercial Modular Aero Propulsion System Simulation (C-MAPSS) datasets, successful predictions of aero-engines RUL have been achieved. Comparative analysis reveals that the proposed model exhibits superior overall prediction performance compared to recent public methods.

The host-guest inclusion strategy has potential to surpass the limitations of energy density and suboptimal performances of single explosives. The guest molecules can not only enhance the detonation performance of host explosives but can also enhance their stability. Therefore, the deeply analysis the role of guest influence on the pyrolysis decomposition of the host-guest explosive is necessary. The whole decomposition reaction stage of CL-20/H2O, CL-20/CO2, CL-20/N2O, CL-20/NH2OH was calculated by ReaxFF-MD. The incorporation of CO2, N2O and NH2OH significantly increase the energy levels of CL-20. However, different guest has little influence on the initial decomposition paths of CL-20. The Ea1 and Ea2 values of CL-20/CO2, CL-20/N2O, CL-20/NH2OH systems are higher than the CL-20/H2O system. Clearly, incorporation of CO2, N2O, NH2OH can inhibit the initial decomposition and intermediate decomposition stage of CL-20/H2O. Guest molecules get heavily involved in the reaction and influence on the reaction rate. k1 of CL-20/N2O and CL-20/NH2OH systems are significantly larger than that of CL-20/H2O at high temperatures. k1 of CL-20/CO2 system is much complex, which can be affected deeply by temperatures. k2 of CL-20/CO2, CL-20/N2O system is significantly smaller than that of CL-20/H2O at high temperatures. k2 of CL-20/NH2OH system is little difference at high temperatures. For the CL-20/CO2 system, the k3 value of CO2 is slight higher than that for CL-20/H2O, CL-20/N2O, CL-20/NH2OH systems, while the k3 values of N2 and H2O are slight smaller than that for CL-20/H2O, CL-20/N2O, CL-20/NH2OH systems. For the CL-20/N2O system, the k3 value of CO2 is slight smaller than that for CL-20/H2O, CL-20/CO2, CL-20/NH2OH systems. For the CL-20/NH2OH system, the k3 value of H2O is slight larger than that for CL-20/H2O, CL-20/CO2, CL-20/N2O systems. These mechanisms revealed that CO2, N2O and NH2OH molecules inhibit the early stages of the initial decomposition of CL-20, and play an important role for the decomposition subsequently.

Based on data from the Yunnan Province farm household survey, we examine the effect of rural land rights policy on farmers’ income. The regression results show that right significantly raises the total income of farmers, with farm income serving as the primary source of total income. After performing numerous robustness tests, using instrumental variables to handle endogeneity and arriving at the same conclusion, the result is still valid. According to the heterogeneity analysis, in the sample of households with long-term migrant workers, the confirmation of rural land rights significantly increases total and nonfarm income while decreasing farm income. Furthermore, total income includes nonfarm income, which reflects the effect of different farmers' optimal labor allocation based on the external market environment. According to the impact mechanism anal-ysis, right can increase farmers' total income by promoting land transfer, and farmers in less developed areas are more willing to increase their income by land transfer out.

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature (LST), SUHI and urban design factors were achieved by using Landsat satellite data, GIS database and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that in the summer daytime under the clear sky condition, the LST varied greatly from 26 °C to 40 °C and the SUHI changed in a wide range of -6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZ of LCZs 1-5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.697, RMSE of 1.21 °C, and the d value of 0.81 for the model of LCZs 1-5, and the values of 0.666, 1.66 °C, and 0.76 for the model of the mixed LCZ, indicating that the models can predict the changes of SUHI with LCZs to a large and satisfactory extent. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs in the largely urbanized cities, and provides information beneficial to the urban designs and regenerations in the humid subtropical region.

In this paper, we propose a novel network representation learning model TransPath to encode heterogeneous information networks (HINs). Traditional network representation learning models aim to learn the embeddings of a homogeneous network. TransPath is able to capture the rich semantic and structure information of a HIN via meta-paths. We take advantage of the concept of translation mechanism in knowledge graph which regards a meta-path, instead of an edge, as a translating operation from the first node to the last node. Moreover, we propose a user-guided meta-path sampling strategy which takes users' preference as a guidance, which could explore the semantics of a path more precisely, and meanwhile improve model efficiency via the avoidance of other noisy and meaningless meta-paths. We evaluate our model on two large-scale real-world datasets DBLP and YELP, and two benchmark tasks similarity search and node classification. We observe that TransPath outperforms other state-of-the-art baselines consistently and significantly.

List-only entity linking is the task of mapping ambiguous mentions in texts to target entities in a group of entity lists. Different from traditional entity linking task, which leverages rich semantic relatedness in knowledge bases to improve linking accuracy, list-only entity linking can merely take advantage of co-occurrences information in entity lists. State-of-the-art work utilizes co-occurrences information to enrich entity descriptions, which are further used to calculate local compatibility between mentions and entities to determine results. Nonetheless, entity coherence is also deemed to play an important part in entity linking, which is yet currently neglected. In this work, in addition to local compatibility, we take into account global coherence among entities. Specifically, we propose to harness co-occurrences in entity lists for mining both explicit and implicit entity relations. The relations are then integrated into an entity graph, on which Personalized PageRank is incorporated to compute entity coherence. The final results are derived by combining local mention-entity similarity and global entity coherence. The experimental studies validate the superiority of our method. Our proposal not only improves the performance of list-only entity linking, but also opens up the bridge between list-only entity linking and conventional entity linking solutions.

Controlling the selectivity of detonation initiation reaction of explosive is a Holy Grail, and it seems to be an “idiot's daydream”, by strengthening external electric field, to reduce the explosive sensitivity. The effects of external electric fields on the initiation reactions in NH2NO2∙∙∙NH3, a model system of the nitroamine explosive with alkaline additive, were investigated at the MP2/6-311++G(2d,p) and CCSD/6-311++G(2d,p) level. The concerted effect in the intermolecular hydrogen exchange is characterized by an index of the imaginary vibrations. Due to the weakened concerted effects by the electric field along the −x-direction opposite to the “reaction axis”, the dominant reaction changes from the hydrogen exchange to 1,3-intramolecular hydrogen transference with the increase of the field strengths. Furthermore, the stronger the field strengths, the higher the barrier heights become, indicating the lower sensitivities. Therefore, by strengthening the field strength and adjusting the orientation between the field and “reaction axis”, not only can the reaction selectivity be controlled, but also the sensitivity can be reduced, in particular under a super-strong field. Thus, a traditional concept, which the explosive is dangerous under the super-strong external electric field, is broken theoretically. Compared to the neutral medium, the low sensitivity of the explosive with alkaline can be achieved under the stronger field. Employing atoms in molecules, reduced density gradient and surface electrostatic potentials, the origin of the reaction selectivity and sensitivity change is revealed. This work provides a new idea to the technical improvement for adding the external electric field into the explosive system.

Aspergillus montevidensis is an important domesticated fungus that has been applied to produce many traditional fermented foods under high osmotic conditions. However, the detailed mechanisms of tolerance to osmotic stress remain largely unknown. Here, we construct a target-deleted strain (ΔLeuRS) of A. montevidensis and found that the ΔLeuRS mutants grew slowly and suppressed the development of the cleistothecium compared to the wide-type strains (WT) under salt-stressed conditions. Furthermore, differentially expressed genes (P<0.0001) governed by LeuRS were involved in salt tolerance, ABC transporter, amino acid metabolism, sugar metabolism, and reproduction process. The ΔLeuRS strains compared to WT strains under short- and long-term salinity stress especially altered accumulation levels of metabolites, such as amino acids and derivatives, carbohydrates, organic acids, and fatty acids. The study provides new insights into the underlying mechanisms of salinity tolerance and lays a foundation for favor improvement of foods fermented with A. montevidensis.

Acid in-situ leaching (ISL) is a common approach to the recovery of uranium in the subsurface. As some toxic and harmful substances might be produced by the chemical reactions among the injected sulphuric acid, the groundwater, and the porous media during leaching processes, the pollution control of the mining plan for ISL is important. In this study, a three-dimensional reactive transport modeling (3DRTM) was applied to decide the pollution control mining plan, considering the partial penetration through wellbore in confined aquifer and complex chemical reactions between main minerals. Based on the 3DRTM, different pumping ratio and non-uniform injection schemes were compared. The results show that the preferential pollution control mining plan is non-uniform injection ratio equal 0.1. By analyzing the characteristics of water table and streamline, it is concluded that the scheme has a strong hydraulic capture effect. In this scheme, the concentration of UO22+, H+, SO42- obtained by 3DRTM is lower. The inner well injection rate is 194.09 m3/d, the outer well injection rate is 158.89 m3/d, and the pumping rate is 264.00 m3/d. A reasonable suggestion is to adopt non-uniform injection mining mode in ISL.

In order to further reduce the emissivity of the hydrophobic low infrared emissivity composite coating and improve the mechanical properties of the coating, the dispersant, adhesion enhancer, and defoamer were used to improve the dispersion state of the fillers, the interface structure, and the surface state of the hydrogen silicone oil modified polyurethane/Al composite coating. The effects of dispersant, adhesion enhancer, and defoamer on the micro-structure, emissivity, glossiness, hydrophobic property, and mechanical properties of the coating were systematically studied. The results show that the polycarboxylate anionic dispersant can obviously improve the dispersion state of flake Al powder and nano-SiO2 in the coating, so that the infrared emissivity of the coating can be reduced, and the coating can have higher hydrophobic and mechanical properties. The bonding strength between the resin matrix and the metal substrate of the coating can be significantly improved by the adhesion enhancer through the bridging action, so that the adhesion strength and impact strength of the coating can be significantly improved. The defoamer can significantly reduce the pores in the coating, so that the surface state of the coating can be significantly improved, and the mechanical properties of the coating can be significantly improved. The coating has the best emissivity (0.527), glossiness (4.3), adhesion strength (grade 1), impact strength (40 kg.cm), and hydrophobic property (water contact angle (WCA) is 140o) when the amount of dispersant, adhesion enhancer, and defoamer is 5 wt%, 4 wt%, and 1 wt%, respectively.

This paper investigates the problem of cooperative standoff tracking using multiple fixed-wing unmanned aerial vehicles (UAVs) with control input constraints. In order to achieve accurate target tracking in the presence of unknown background wind and target motion, a coordinated standoff target tracking algorithm is proposed. The objective of the research is to steer multiple UAVs to fly a circular orbit around a moving target with prescribed intervehicle angular spacing. To achieve this goal, two control laws are proposed, including relative range regulation and space phase separation. On one hand, a heading rate control law based on Lyapunov guidance vector field is proposed. The convergence analysis show that the UAVs can asymptotically converge to a desired circular orbit around the target, regardless of their initial position and heading. Through rigorous theoretical proof, it is concluded that the command signal of the proposed heading rate controller will not violate the boundary constraint on heading rate. On the other hand, a temporal phase is introduced to represent the phase separation and avoid discontinuity of the wrapped space phase angle. On this basis, a speed controller is developed to achieve equal phase separation. The proposed airspeed controller met the requirement of airspeed constraint. In addition, to improve the robustness of the aircraft during target tracking, an estimator is developed to estimate the composition velocity of the unknown wind and target motion. The proposed estimator uses the offset vector between the UAV’s actual flight path and the desired orbit which is defined by Lyapunov guidance vector field to estimate the composition velocity. The stability of the estimator is proved. Simulations are conducted under different scenarios to demonstrate the effectiveness of the proposed cooperative standoff target tracking algorithm. The simulation results of indicate that, the temporal-phase-based speed controller can achieve fast convergence speed and small phase separation error. Additionally, the composition velocity estimator exhibits fast response speed and high estimation accuracy.

Analytical mechanics is the most basic discipline. The basic principles of analytical mechanics should also be applicable to general deformed objects. However, the virtual displacement principle proposed by analytical mechanics is only applicable to particle systems and rigid body systems, but not to general deformed objects. In this paper, the generalized virtual displacement principle of general deformed objects (such as, elastic objects, plastic objects, elasto-platic objects and flexible objects etc ) is derived by the method of analytical mechanics, which is also applicable to particle systems and rigid body systems. First of all, according to the method of analytical mechanics, the external force, internal force, constraint reaction force and elastic recovery force of the deformed object system under the equilibrium state are analyzed, and the concepts of virtual displacement, ideal constraint and virtual work are introduced, and the generalized virtual displacement principle (also called generalized virtual work principle) of deformed objects is proposed; secondly, vector form, coordinate component form and generalized coordinate form of generalized virtual displacement principle of deformed object are given; thirdly, as the application of the principle, the virtual displacement principle of deformed objects in plane polar coordinate system, space cylindrical coordinate system and spherical coordinate system is given; finally, a brief conclusion is drawn. This work unifies the virtual displacement principle of elastic object, plastic, elastoplastic etc deformed object systems and rigid object systems with the basic method of analytical mechanics. It is a basic principle for dealing with the static problems of deformed objects. This work also lays a foundation for the further study of the dynamics of deformed object systems.

Acute ischemic strokes are the third leading cause of death and the leading cause of neurological disability worldwide. The oxygen and glucose deprivation associated with ischemic strokes not only leads to neuronal cell death, but also increases the inflammatory response and decreases functional output of the brain. The only intervention approved by US Federal Drug and Food Administration for treatment of ischemic strokes is tissue plasminogen activator (tPA), however, such treatment can only be given within 4.5 hours of the onset of stroke-like symptoms. This narrow time-range limits its application, and it also might induce detrimental rather than beneficial effects to stroke patients by treatment of the tPA. In order to reduce the infarct volume of an acute ischemic stroke while increasing the time period for treatment, emerging therapies reveal great potential by targeting inflammation, growth factors, ion channels, and neurotransmitter receptors with monoclonal antibody (MAB). With successfully application in the treatment of cancer patient by MAB, in this review, we will focus on recent advances on stroke therapy by using MAB on the treatment of stroke by targeting inflammation, growth factors, ion channels, and neurotransmitter receptors. Therefore, developing specific MAB targeting the signaling pathway of stroke will contribute to stroke therapy.

Underwater wireless optical communication (UWOC) is acknowledged as a useful way to transmit data in ocean for short distance application. Carrying UWOC device on mobile platform is quite practical in ocean engineering, which is helpful to exploit its advantages. In application, such platform needs camera to observe surroundings and guide its action. Since the majority of ocean is always dark, active illumination is necessary to imaging. Once UWOC worked in such environment, its performance is affected by the illumination light noise. In this paper, we study the influence of underwater LED illumination on bidirectional UWOC with Monte Carlo method. We simulate forward noise from the LED illumination to the opposite receiver in the cooperative terminal, and the backscattering noise on the adjacent receiver in the same terminal. The results show that the forward noise is reduced with the increase of absorption coefficient, scattering coefficient, transmitting distance, and separated distance between receiver and the optical axis of LED. But it becomes greater with FOV of receiver. The backscattering noise is reduced with the increase of absorption coefficient and separated distance between receiver and LED. But it becomes greater with FOV and scattering coefficient, while it has little relation with transmitting distance. In order to reduce such two kind noises, besides inserting optical filter in the receivers and narrow their field, the optical axis of LED light should keep away from the receivers. The results in this paper is helpful for UWOC application.

This pioneering study presents an in-depth biomechanical examination of soccer's diving header, aiming to quantify its impact on ball speed enhancement (BSE) and effective offensive range (EOR). Despite the diving header's widespread acclaim and historical significance, there remains a dearth of scientific scrutiny into its biomechanical intricacies. Employing an innovative research design featuring a static hanging ball at varied offensive distances and heights, the study replicates diverse header scenarios. The results of 3D motion quantification have shown that a physically excellent player (identified through the maximal standing long jump test) could reach an EOR around 2.64 times his body height. Furthermore, the study unveils that proficient players could attain BSE surpassing 9 m/s, signifying the diving header's heightened efficacy compared to traditional heading techniques, which could only result in 4.5 m/s. Correlation analyses unveil noteworthy relationships, highlighting the pivotal role of head speed at impact and the influence of minimizing speed-drop and temporal disparities for amplified effectiveness. Considerations for optimizing diving header execution are introduced, emphasizing the necessity for targeted training programs. Despite acknowledged limitations inherent to its pilot nature, this exploration furnishes foundational knowledge to guide subsequent research and practical applications, providing valuable insights into soccer training and skill development through a biomechanical lens.

Objective: To explore the inflammatory markers for the development of obliterative bronchiolitis (OB) after adenovirus infection in children. Methods: In this retrospective study, the medical data of 62 children with adenovirus pneumonia treated in our hospital between February 2020 and November 2021 were collected and assigned to an OB group (n = 30) or non-OB group (n = 32) according to the presence of OB. Clinical characteristics of patients included gender, age, prematurity, underlying disease, length of hospitalization, type of adenovirus infection, ventilator use, length of ventilator use, and laboratory index levels. Results: Children with OB were associated with higher serum ferritin levels versus those without (P < 0.05). There were no significant differences in the immunoglobulin E (IgE), interleukin-6 (IL-6), partial arterial pressure of oxygen (PaO₂), D-dimer, lactate dehydrogenase (LDH), and lymphocyte absolute values between the two groups of children (P > 0.05). Logistic multifactorial regression analysis revealed that the length of ventilator use and serum ferritin level were inflammatory markers for the development of OB in children with adenovirus pneumonia. Conclusion: The length of ventilator use and serum ferritin levels are inflammatory markers for the development of OB after adenovirus infection in children, and timely measurement of the above indicators in children is instrumental in predicting the prognosis of children.

Due to the highly nonlinear, multi-stage, and strongly time-varying marine lysozyme fermentation process, it is difficult to assure the stability and prediction accuracy of the traditional single global soft sensor model on a global scale. This study innovatively proposed a soft sensor model based on an improved seagull optimization algorithm (ISOA) combined with Gaussian process regression (GPR) weighted ensemble learning. First, the sample data set is divided into multiple local sample subsets by the improved density peak clustering algorithm (ADPC). Second, the Gaussian process regression model is optimally altered with an improved seagull optimization algorithm for the purpose of establishing the corresponding sub-prediction model. Finally, the prediction model's fusion strategy is ultimately determined depending on the degree of connection between the test samples and a subset of local pieces. Simulation results show that the proposed soft sensor model, which searches GPR based on ISOA and combines various sub-models, can predict the key biochemical parameters of the marine lysozyme fermentation process better with less prediction error under the condition of fewer training data, and it can be expanded to the soft sensor models of general nonlinear systems, according to simulation results.

We report an all-optical radio-frequency (RF) spectrum analyzer with a bandwidth greater than 5 terahertz (THz), based on a 50-cm long spiral waveguide in a CMOS-compatible high-index doped silica platform. By carefully mapping out the dispersion profile of the waveguides for different thicknesses, we identify the optimal design to achieve near zero dispersion in the C-band. To demonstrate the capability of the RF spectrum analyzer, we measure the optical output of a femtosecond fiber laser with an ultrafast optical RF spectrum in the terahertz regime.

Segmental bone defects caused by trauma, infection, tumor resection or osteoporotic fractures present significant surgical treatment challenges. Host bone autograft is considered the gold standard to restore function but comes with the cost of harvest site comorbidity. Allograft bone is a secondary option but has its own limitations in incorporation with host bone as well as cost. Therefore, developing new bone tissue engineering strategies to treat bone defects is critically needed. In the past three decades, the use of stem cells delivered with different scaffolds or growth factors for bone tissue engineering has made tremendous progress. Many varieties of stem cells have been isolated from different tissues for use in bone tissue engineering. This review summarizes the progress in using different postnatal stem cells including bone marrow mesenchymal stem cells, muscle-derived stem cells, adipose-derived stem cells, dental pulp stem cells/periodontal ligament stem cells, periosteum stem cells, umbilical cord-derived stem cells, peripheral blood stem cells and urine-derived stem cells for bone tissue engineering and repair. This review also summarizes the progress using exosomes or extracellular vesicles delivered with various scaffolds for bone repair. The advantages and disadvantages of each type of stem cell are also discussed and explained in detail. It is hopeful in the future that these preclinical results will translate into new therapies for bone defect repair.

A series of precise data consisting of zircon U–Pb ages, whole-rock geochemistry and Sr–Nd–Hf isotope compositions from the Huhetaoergai granitic pluton was collected in this study and combined with data from the western Huhetaoergai, Zhuxiaogubuhe and Yagan granitic plutons to constrain the petrogenesis and tectonic setting of granitic plutons in the northern Ya-Gan fault zone, North Alxa, China. The Huhetaoergai pluton is composed of hornblende diorite, medium- to coarse-grained biotite adamellite and coarse-grained biotite adamellite with K-feldspar megacrysts. The U–Pb zircon ages of biotite adamellite are 220.5 ± 1.9 Ma and 226.5 ± 2.4 Ma. These granitoids are I-type granites with highly radiogenic initial ⁸⁷Sr/⁸⁶Sr of 0.708085–0.735470, negative eNd(t) average values of −2.98–3.23 and high eHf(t) of 9–11.05. These features indicate the granitoids were formed from magmas generated from juvenile crust. We speculate that the granitoids of the Huhetaoergai pluton were emplaced during an episode of intense intraplate orogenic movement evolution in an extrusional setting after a period of extensional postcollisional intraplate evolution.

The orthogonal matrix with cube be symmetric is a common class of matrices with important properties. We pay attention to this kind of matrices. By using the close relationship between the eigenvalues of a matrix and the trace of its power, we obtain the algorithm for its all possible different eigenvalues and multiplicities. The calculation formula is expressed only by the trace of a matrix and its power, avoiding solving the characteristic polynomial. The method is simple and practical. Furthermore, a new essential characterization for the sum of orthogonal matrix pairs being orthogonal is given as well.

The boundary layer height (BLH) distinguishes the interface between the lower and free atmosphere, which is a key variable in numerical simulation, aerosol, and environmental pollution studies. Thus, the goal of this work is to propose a novel method conjuncting with numerical regularization to analyze climate characteristics of the marine boundary layer height (MBLH) using 2007-2011 GPS-RO data from the COSMIC mission. While traditionally, the difference method has been used to achieve this aim, herein, we propose an innovative method, in which the bending angle profile gradient was calculated using the numerical regulation method where the regulation parameters are determined by the double-parameter model function method. Then, the MBLH was determined by employing the maximum gradient method to ascertain the height corresponding to the smallest gradient. The results show a correlation between currents and the MBLH—a relationship that has not been previously demonstrated. A low MBLH is associated with seasons and regions where cold ocean currents are prevailing; whereas a high MBLH is observed in the seasons and places where warm currents are prevailing. This correlation was validated by comparing the obtained results with different occultation data—i.e., atmprf and echprf—which also established that atmprf is more sensitive to convective cloud top capture. In seas with active convection, the armprf calculated bending angle is higher than that from echprf. Subsequently, the standard deviation was used to express the MBLH confidence level. The results show that the MBLH standard deviation is highest in low latitudes and lowest in the middle and high latitudes. Furthermore, we analyzed the interannual MBLH variation trend, which displayed a seasonal variation and spatial distribution corresponding with the current and subsolar point. Finally, we conducted a case study in the South China Sea, and identified a distinctive seasonal change and downward trend.

The three-dimensional morphology of frictional sub-surfaces holds significant importance for studying tribological issues. However, the uniformity of horizontal datum in 3D scanning is limited for curved surfaces, resulting in the inability to obtain accurate contour characterization parameters from the scanning results. This study aims to address this issue by constructing regular surface equations and normalizing the 3D profiler scanning results. By fitting the data, a "plane" surface representative of the surface features is obtained, and the paper demonstrates this approach on the surface morphology of different worn parts in the frictional area of spherical bearings located in the specific environment of the Three Gorges gate. The results indicate that the obtained "plane" effectively reconstructs the three-dimensional morphology map of the regular surface. Moreover, this reconstructed plane not only clearly illustrates the surface characteristics but also provides the foundation for analyzing the wear mechanism.

Multi-cameras system is widely applied in 3D computer vision especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-cameras system are critical to the accuracy of vision measurement and the key is to find an appropriate calibration target. In this paper, a high-precision camera calibration method for multi-cameras system based on transparent glass checkerboard and ray tracing is described, which is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera is obtained by Zhang’s calibration method. Then, multiple cameras capture several images from the front and back of the glass checkerboard with different orientations, and all images contain distinct grid corners. As the cameras on one side are not affected by the refraction of glass checkerboard, extrinsic parameters can be directly calculated. However, the cameras on another side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce calibration error. A multi-cameras calibration method using refractive projection model and ray tracing is developed to eliminate this error. Furthermore, both synthetic and real data are employed to validate the proposed approach. The experimental results of refractive calibration show that the error of the 3D reconstruction is smaller than 0.2 mm, the relative errors of both rotation and translation are less than 0.014%, and the mean and standard deviation of reprojection error of 4-cameras system are 0.00007 and 0.4543 pixel. The proposed method is flexible, high accurate, and simple to carry out.

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of April 17, 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

In the pursuit of China’s dual carbon goals, identifying spatio-temporal changes in industrial carbon emission efficiency and their influencing factors in cities at different stages of development is the key to effective formulation of countermeasures to promote the low-carbon transformation of Chinese national industry and achieve high-quality economic development. In this study, we used balanced panel data of 270 Chinese cities from 2005 to 2020 as a research object: (1) to show spatio-temporal evolution patterns in urban industrial carbon emission efficiency; (2) to analyze the aggregation characteristics of industrial carbon emission efficiency in Chinese cities using Global Moran's I statistics; and (3) to use the hierarchical regression model for panel data to assess the non-linear impact of the digital economy on the industrial carbon emission efficiency of cities. The results show the following: (1) the industrial carbon emission efficiency of Chinese cities exhibited an upward trend from 2005 to 2020, with a spatial distribution pattern of high in the south and low in the north; (2) China's urban industrial carbon emission efficiency is characterized by significant spatial autocorrelation, with increasing and stabilizing correlation, and a relatively fixed pattern of spatial agglomeration; (3) there is a significant inverted-U-shaped relationship between the digital economy and the industrial carbon emission efficiency of cities. The digital economy increases carbon emissions and inhibits industrial carbon-emission efficiency in the early stages of development, but inhibits carbon emissions and promotes industrial carbon emission efficiency in mature developmental stages. Therefore, cities at all levels should reduce pollution and carbon emissions from high-energy-consuming and high-polluting enterprises, gradually reduce carbon-intensive industries, and accelerate the digital transformation and upgrading of enterprises. Western, central and eastern regions especially should seek to promote the sharing of innovation resources, strengthen exchanges and interactions relating to scientific and technological innovation, and jointly explore coordinated development routes for the digital economy.

The current methods for lightning risk warnings that are based on atmospheric electric field (AEF) data have a tendency to rely on single features, which results in low robustness and efficiency. Additionally, there is a lack of research on cancelling warning signals, contributing to the high false alarm rate (FAR) of these methods. To overcome these limitations, this study proposes a lightning risk warning method that incorporates enhanced empirical Wavelet transform-Adaptive Savitzky Gorey filter (EEWT-ASG) and one-dimensional morphology, using time-frequency domain features obtained through the Wavelet transform (WT). The proposed method achieved a probability of detection (POD) of 77.11%, miss alarm rate (MAR) of 22.89%, FAR of 40.19%, and critical success index (CSI) of 0.51, as evaluated on 83 lightning processes. This method can issue a warning signal up to 22 minutes in advance for lightning processes.

In order to improve the performance of the draft tube in hydraulic turbine, a multi–objective optimization method for the draft tube is developed by combining the design of experiment (DOE), the radial basis function (RBF) and the non–dominated sorting genetic algorithm (NSGA–II) in this paper. The geometrical design variables of the median section in the draft tube and the cross section in its exit diffuser are considered as design parameters in this optimization, which objective function is to maximize the pressure recovery factor (Cp) and minimize the energy loss coefficient (ζ). The limited numbers of design matrix required for the shape optimization of the draft tube is generated by optimal Latin hypercube (OLH) method of the DOE technique, of which performances are evaluated through computational fluid dynamic (CFD) numerical simulation. For reducing of the computational consumption, the approximate model is used based on the RBF. The Pareto optimal solutions are finally performed using the NSGA–II for obtaining the best geometrical parameters of the draft tube. The optimization result of the draft tube shows a marked performance improvement over the original, which verifies the theoretical validity and feasibility of the proposed method in this paper.

Diamond-like carbon (DLC) films have a promising tribological application in green precision manufacturing, but their toughness represents a serious issue in the way of their application perspective. The film thickness is on the micrometer scale and makes conventional methods unsuitable for its toughness characterization. The absence of an accepted method for characterizing the DLC toughness has hindered the related research on the development of toughening methods and understanding the mechanism. This work intends to explore a relatively simple and acceptable characterization method to measure the film toughness. Moreover, toughening mechanisms of DLC films are proposed during the characterization to reveal the toughening mechanism. The toughness can be fully characterized through combining impact toughness and scratch toughness. The impact toughness can be obtained by observing the size of the indentation and the crack state around the indentation in the impact experiment. The scratch toughness could be assessed by combining the scratch morphology and Crack Propagation Resistance (CPRS). The improvement of film toughness should be carried out from two aspects: preventing microcrack initiation and suppressing crack propagation. Appropriate doping of non-carbide metal particles can effectively improve the toughness of the film, and there are seven main factors affecting the toughening of the film. Five toughening mechanisms of non-carbide metals from film preparation to test stage are revealed during the investigation of the change patterns.

The phycobilisome (PBS) is the major light-harvesting apparatus in cyanobacteria and red algae, a large multi-subunit protein complex of several megadaltons that is found on the stromal side of thylakoid membranes in orderly arrays. Chromophore lyases catalyse the thioether bond between apoproteins and phycobilins of PBSs. Depending on the species, composition, spatial assembly and, especially, the functional tuning of different phycobiliproteins mediated by linker proteins, PBSs can absorb light between 450 and 650 nm, making them efficient and versatile light-harvesting systems. However, basic research and technological innovations are needed, not only to understand their role in photosynthesis but also to realise the potential applications of PBSs. Synthetic biology provides an innovative approach to expand our understanding of the distinctive properties that make the PBS such an efficient light-harvesting system and to explore its heterologous synthesis, photosynthetic functions and potential medical applications. Focusing on these topics, this review describes the essential components needed for PBS assembly, the functional basis of PBS photosynthesis and the applications of phycobiliproteins. Moreover, key technical challenges for heterologous biosynthesis of phycobiliproteins in chassis cells are discussed.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

The structure characterization of two new polysaccharides from Agrocybe aegerita (AA-P) and Hygrophorus olivaceoalbus (HO-P) by HPGPC, GC-MS, NMR and FT-IR indicated that AA-P was composed of Galactose, Glucose and Arabinose, in the ratio of 3:2:1. Its skeleton structure was consisted of (1→4)-Arap, (1→4,6)-Glup and (1→6)-Galp with one branched chain. The HO-P was consisted of mannose, galactose and glucose in a ratio of 1:1:2. Its skeleton structure was consisted of (1→6)-Galactose residues, (→1)-glucose residues, (1→4)-glucose residues and (1→4,6)-D-mannose residues. There were two branched chains connected to the main chain. AA-P and HO-P had the best stimulation effect on B cells and RAW264.7 cells, respectively, and could both mainly by impacting and reducing G0/G1 phase which lead to a significant proliferation of B cells, T cells and RAW264.7 cells. In addition, AA-P and HO-P could significantly promote the secretion of TNF-α from T cells, the secretion of IgA, IgD, IgE, IgG and IgM from B cells, and the secretion of TNF-α from RAW264.7 cells, but neither of them could impact the secretion of IL-1β from RAW264.7 cells.

The increased cultivation of Cannabis sativa L. in North America, represented by high Δ9-tetrahydrocannabinol-containing (high-THC) cannabis genotypes and low THC-containing hemp genotypes, has been impacted by an increasing number of plant pathogens. These include fungi which destroy roots, stems and leaves, in some cases causing a build-up of populations and mycotoxins in the inflorescences that can negatively impact quality. Viroids and viruses have also increased in prevalence and severity and can reduce plant growth and product quality. Rapid diagnosis of the occurrence and spread of these pathogens is critical. Techniques in the area of molecular diagnostics have been applied to study these pathogens in both cannabis and hemp. These include polymerase chain reaction (PCR)-based technologies, including RT-PCR, multiplex RT-PCR, RT-qPCR, and ddPCR, as well as whole genome sequencing (NGS) and bioinformatics. In this study, examples of how these technologies have enhanced the rapidity and sensitivity of pathogen diagnosis on cannabis and hemp will be illustrated. These molecular tools have also enabled studies on the diversity and origins of specific pathogens, specifically viruses and viroids, and these will be illustrated. Comparative studies on the genomics and metabolomics of healthy and diseased plants are urgently needed to provide insight into their impact on quality and composition of cannabis and hemp-derived products. Management of these pathogens will require monitoring of their spread and survival using the appropriate technologies to allow accurate detection, followed by appropriate implementation of disease control measures.

This study used a two-stage network data envelopment analysis model to measure the water use efficiency of 108 cities in the Yangtze River Economic Belt in the initial water use and wastewater treatment phases from 2009 to 2019. We used the Dagum Gini coefficient to decompose the urban water use efficiency of six major urban clusters in the Yangtze River Economic Belt. We also used σ convergence and β convergence types to test the convergence characteristics of urban water use efficiency of six major urban clusters in the Yangtze River Economic Belt. This study found that the overall low level of water use efficiency in cities in the Yangtze River Economic Zone mainly stems from the low level of water use efficiency in the wastewater treatment stage. The 108 cities in the Yangtze River Economic Zone are divided into four types based on the average values of water use efficiency in the initial use and wastewater treatment phases; the highest number of cities are in the double-low category, with low average values of water use efficiency in the initial use and wastewater treatment phases. During the study period, spatial differences in urban water use efficiency in the Yangtze River Economic Zone narrowed, with the differences stemming mainly from hyperdensity, followed by intra- and inter-regional differences. Meanwhile, there is convergence in urban water use efficiency in the Yangtze River Economic Belt; significant β convergence in the urban agglomerations of the Yangtze River Delta, Jianghuai, middle reaches of the Yangtze River, Chengdu–Chongqing, and Central Yunnan; and insignificant β convergence in the Central Qian urban agglomeration. After considering control factors, such as industrial structure, financial development level, environmental regulation, economic development level, and science and education development level, the water use efficiency of the six major urban clusters in the Yangtze River Economic Belt converges faster, but the influence of these control factors on the water use efficiency of each urban cluster is heterogeneous. Research results have reference value for the development of improvement strategies on differentiated urban water use efficiency in the Yangtze River Economic Belt.

Much has been explored in the individual health issue, and most of them adopt the objective data such as laboratory tests or health services utilization to analyze individual health assessment. However, the factors influencing individuals in self‐assessed health is still unclean. The study considers that self‐assessed health is viewed as catalyst in health management and explores various dimensions associated with self‐assessed health. Totally, 800 participants who were randomly sampled from the citizen of Porter County, Indiana completed the Needs Assessment Citizen Survey in 2007.After adjustment for age, gender, education, income, and health coverage, life quality (β=1.5538, sdandard erro of β=0.8404), and Medicaid assistance (β= -0.7715, sdandard erro of β= 0.3958) are the main determinants of individuals’ self‐assessed health. The results suggest that public health officials should consider improving citizens’ self-assessed health by providing good living and socio-economic environment.

In response to reducing the energy cost of unmanned surface vehicles (USVs) while overcoming the low accuracy problem in surface target detection, a lightweight detection algorithm with multi-scale feature fusion is proposed. Based on the popular one-stage lightweight Yolov7-tiny target detection model, a lightweight extraction module is designed first by introducing the multiscale residual module to reduce the number of parameters and computational complexity while improving accuracy. The Mish and SiLU activation functions are used to enhance network feature extraction. Second, the path aggregation network employs coordinate convolution to strengthen spatial information perception. Finally, the dynamic head, which is based on the at-tention mechanism, improves the representation ability of object detection heads without any computational overhead. According to the experimental findings, the proposed model has 22.1% fewer parameters than the original model, 15% fewer GFLOPs, a 6.2% improvement in [email protected], a 4.3% rise in [email protected]:0.95, and it satisfies the real-time criteria. According to the research, the suggested lightweight water surface detection approach includes a lighter model, a simpler computational architecture, more accuracy, and a wide range of generalizability. It performs bet-ter in a variety of difficult water surface circumstances.

The morphological transformation of an arched ribbon driven by torsion is a scientific problem that is connected with daily life and requires thorough analysis. An arched ribbon can achieve an instantaneous high speed through energy transformation and then return to the original shape of the structure. In this paper, based on the characteristics of the ribbon structure, the dynamic mathematical model of the arched ribbon driven by torsion is established from the Kirchhoff rod equation. The variations of the Euler angle of each point on the center line of the ribbon with the arc coordinate s and the rotation angle of the supports $\phi$ was examined. The relationship between the internal force distribution of each point in the direction of $\hat{d}_{a}$ and the material, cross-sectional properties, and rotation angle of the supports was obtained. We used ABAQUS, a nonlinear finite element analysis tool, to simulate the morphological transformations of the ribbons, verified our theory with simulation results, and reproduced the experimental results of Sano. Furthermore, we redefined the concept of the ``critical flipping point'' of Sano. In this paper, the dimensional analysis method was used to fit the simulation data. The following relationship between the critical width $ w ^{*} $, thickness h, and the radius R of the ribbon with different cross sections was obtained: $w^{*}=A\cdot R\left(h/R\right)^{0.6}$, where A is 3.19 for rectangular cross sections and 3.06 for elliptical cross sections. By analyzing the simulation data, we determined the variation behavior of the out-of-plane deflection of the center point of the ribbon with the radius R, width w, and thickness h. Our research has guiding significance for understanding and designing arched ribbons driven by torsion, and the results can be applied to problems of different scales.

Why are pieces of spaghetti generally broken into three to ten segments instead of two as one thinks? How can one obtain the desired number of fracture segments? For these problems, in this paper a strand of spaghetti is considered an elastic rod, and the finite-element software ABAQUS is used to simulate the detailed fracture dynamics of the elastic rod. By changing the size (length and diameter) of the rod, the relevant data on the fracture limit curvature and the number of fractured segments of the elastic rod are obtained. The ABAQUS simulation results confirm the scientific judgment of B. Audoly and S. Neukirch (Fragmentation of rods by cascading cracks: Why spaghetti does not break in half. Phys Rev Lett 95: 095505). Using dimensional analysis to fit the finite-element data, two relations of the elastic rod fracture dynamics are obtained: (1) the relationship between the fracture limit curvature and the diameter, and (2) the relationship between the number of fracture segments and the diameter-length ratio. Results reveal that when the length is constant, the larger the diameter (the smaller the diameter-length ratio D/L), the smaller the limit curvature; and the larger the diameter-length ratio D/L, the fewer the number of fractured segments. The relevant formulations can be used to obtain the desired number of broken segments of spaghetti by changing the diameter-to-length ratio.

Why do stretched rubber bands not hit the hand after ejection? What is the mechanism behind the rubber band ejection dynamics? These questions represent a fascinating scientific problem. Because the size of a rubber band in the circumferential direction is much larger than that in the other two directions of its cross-section, we regard the rubber band as a slender beam and establish a mathematical model of the dynamics of the rubber band stretching and ejection. Furthermore, we obtain the dependence of the dynamic curvature of the rubber band on the arc length and time. We used the finite element software ABAQUS to simulate the dynamic process of a rubber band stretching and ejection. The simulation results and dimensional analysis were performed to examine the effect of the bending elastic rebound velocity. The mathematical model and simulation results revealed that the relationship between the curvature and time at the end of the rubber band ($s =0$) was as follows: $\kappa\sim t^{-{1}/{2}}$. This research has guiding significance for the design of rubber bands as elastic energy storage devices.

Fresh water springs are unique natural resources in Florida, currently under threat from increasing groundwater pumping and pollution resulting from a variety of sources. This paper estimates current recreation benefits from visiting springs using the travel cost method and elicits residents’ willingness to contribute for springs restoration using the contingent valuation method. It further compares the performance of count data models correcting for endogenous stratification and truncation, and finds that the annual consumer surplus per person per trip is between $20 and $43. Furthermore, visitors are willing to contribute $12 to $14 per person per trip for springs restoration without reducing trip demand.

A millimeter-wave microstrip leaky-wave antenna array based on the substrate-integrated waveguide (SIW) and the complementary split-ring resonator (CSRR) is proposed in this paper. The slow wave characteristics of the SIW are enhanced by etching two rows of symmetrical CSRR-type slots on the surface of the SIW layer. The magnetic coupling between the CSRR-SIW layer and equally spaced circular patches array on the upper layer realizes the radiation of electromagnetic energy. In the 23~30 GHz (relative bandwidth 26.4%) operating frequency band, the horizontal polarization radiation beam scanning from -62° to -2° is realized, with a peak gain of 9.6~11.7 dBi, and the cross-polarization ratio is more than 43.8 dB.

Search for appropriate materials with favorable staggered energy band arrangements is important and of great challenge to fabricate Z-scheme photocatalysts with high activity in visible light. In this study, we demonstrated a facile and feasible strategy to construct highly active organic-inorganic Z-scheme hybrids (P-BMO) with linear pyrene-based conjugated polymer (P17-E) and Bi₂MoO₆ via in-situ palladium-catalyzed cross-coupling reaction. Characterization results revealed C-O chemical bond formed at the heterointerface between P17-E and Bi₂MoO₆ after in-situ polycondensation and endowed the hybrids with observably improved photogenerated carries transfer capability. Visible light driven photocatalytic removal of ciprofloxacin and Cr(VI) were significantly enhanced after the incorporation of P17-E into Bi₂MoO₆ whether with the morphology of nanosheets, nanobelts or microspheres. Moreover, this P-BMO hybrids were also found to exhibit sustainable excellent photocatalytic performance after four runs of photocatalytic evaluation test, suggesting its high activity and stability. To better eliminate the redox ability enhancement of P-BMO, a reasonable Z-scheme electrons transferring mechanism between P17-E and Bi₂MoO₆ was proposed and proved by the determination of •O₂^– and •OH and Pt nanoparticles photodeposition experiments. This work might provide a viable source and insight into the design of Z-scheme photocatalysts with excellent redox ability for environmental remediation.

The separation of Li+ and [Bmim]+(1-Butyl-3-methylimidazolium) by electrically driven membrane technology was studied. The effects of the types and modification processes of cation exchange membranes, current density, total cation concentration, temperature, and anion types on separation efficiency were investigated. The results indicated that it is feasible to achieve efficient separation of Li+ and [Bmim]+ using the selectivity of cation exchange membranes under electric field. Membrane CMX and the modified membrane A and B which obtained from the CMX showed obvious selective of Li+ from [Bmim]+. When the current density is 5 mA/cm2 and the feed concentrations of Li+ and [Bmim]+ are 0.3 mol/L and 0.2 mol/L, the selective transport coefficient of the modified membrane B can reach 6.2 in the first 120 minutes of the process. Reducing current density and increasing total cation concentration can improve separation efficiency. Lowering the temperature can improve the separation effect, but improvement is not obviously. Changing the anion of the feed from chloride ion to acetate has no effect on the separation.

In order to properly cover different scenarios, radiation patterns of antennas should be accordingly adjusted before fabrication. However, most antennas are unable to provide both broadside beam and designable conical beam which are usually-used radiation patterns for radio coverage. In this paper, a planar Circular Polarized (CP) annular Leaky-Wave Antenna (LWA) with conical beam is proposed, which is realized on annular Substrate-Integrated Waveguide (SIW). Broadside beam or conical beam could be easily obtained by fabricating the LWA with modified structural parameters. The central operating band is 5.8 GHz. The LWA allows only the -1th spatial harmonic to radiate, while the fundamental wave and other spatial harmonics are suppressed in slow wave mode. In order to validate the design effectiveness, two examples for broadside beam and conical beam radiation are fabricated and measured. The measurement results show good agreement with the simulation results. The proposed LWA presents a promising radiation performance and is a good candidate for wireless communication applications.

By constructing a static map, the library robot can navigate and access documents autonomously, which greatly improves efficiency; however, for libraries where shelves can be moved, map changes do not allow for direct navigation, and also sensors such as radar and camera are relatively expensive, so we propose a low-cost navigation algorithm based on real-time ranging data and map matrices, and designed a mobile archive access robot. In order to obtain real-time distance data, nine near/long range sensors were mounted on the chassis and a composite digital filtering algorithm was designed based on different moving area characteristics; then the access task matrix and map matrix were designed based on the archive access task and the location characteristics of the archive shelf placement, the robot can rely on the range data to update the map matrix during the moving process, complete its own positioning, and use the task matrix The robot can use the task matrix to complete autonomous navigation and access to multiple files. Experiments show that the filtered positioning accuracy can reach 1cm, while the robot can move to the target shelf autonomously, which is more practical and less costly.

This paper reports the effect of as-deposited surface condition on the fatigue strength in an additive manufactured titanium alloy Ti-6Al-4V (WAAM Ti64). First, local stress concentration caused by the surface waviness was quantified by a metrology technique followed by numerical modelling. Fatigue tests were conducted under bending load with the as-deposited surface being under tensile cyclic stress. The applicability of two predictive methods was studied and compared with the fatigue test results. The traditional notch stress method overestimated the fatigue strength by a factor of 1.5 at a given life; the poor agreement with the test is attributed to the crack propagation from the waviness being dominant in the bending test, i.e., the crack initiation stage was short, hence the local stress method is unsuitable. The fracture mechanics approach has delivered good predictions at every applied stress levels. The method treats a waviness trough as an initial crack. This approach is suitable for predicting the fatigue life in materials built by wire based directed energy deposition processes.

The current spreading novel coronavirus SARS-CoV-2 is highly infectious and pathogenic and has attracted global attention. Recent studies have found that SARS-CoV-2 and SARS-CoV share around 80% of homology and use the same cell entry receptor, ACE2. These inspired us to study other receptors of SARS-CoV, which may be used for SARS-CoV-2 binding as well. In this study, we screened the gene expression of three receptors (ACE2, DC-SIGN and L-SIGN) in four datasets of normal lung tissue from lung adenocarcinoma patients and two single-cell RNA sequencing datasets from normal lung and bronchial epithelial cells separately. No significant difference in gene expression of these three receptors were found between gender groups (male vs female). We found higher gene expression of DC-SIGN in elder with age>60 and higher gene expression of L-SIGN in Caucasian than Asian. Similar to ACE2, we observed significantly higher DC-SIGN gene expression in the lungs of smokers, especially former smokers. However, smokers upregulate ACE2 and DC-SIGN gene expression in different cell types. In the whole lung, ACE2 is actively expressed in remodeled Alveolar Type II cells of former smokers, while DC-SIGN is largely expressed in monocytes of former smokers and dendritic cells of current smokers. In bronchial epithelium, no obvious gene expression of DC-SIGN and L-SIGN was observed while ACE2 was found to be actively expressed in goblet cells of current smokers and club cells of non-smokers. In conclusion, our findings may indicate that smokers, especially former smokers, and people over 60 have higher risk and are more susceptible to SARS-CoV-2 infection. Also, this study provides hints on possible SARS-CoV-2 pathogenicity mechanisms in lung infection.

The liquid-vapor phase change lattice Boltzmann method is used to investigate the pinning-depinning mechanism of the contact line during droplet evaporation on the stripe-patterned surfaces in 3D space. Considering the curvature of the contact line and the direction of the unbalanced Young’s force, the local force balance theory near the stripe boundary is proposed to explain the steady state of the droplets on the stripe-patterned surfaces. An equation is proposed to evaluate the characteristic contact angle of the stabilized droplets. During the evaporation of the droplet, the stick-slip-jump behavior and the CCR-Mixed-CCA mode can be well captured by the lattice Boltzmann simulation. When the contact line is pinned to the stripe boundary, the contact line in the direction perpendicular to the stripes is slowly moving while the curvature of the contact line is gradually increasing. The gradually increasing curvature of the contact line accelerates the movement of the contact line, and the final contact line is detached from the stripe boundary. The research results provide theoretical support and guidance for the design, improvement and application of patterned surfaces in the field of micro-fluidic and evaporation heat transfer.

Fully mechanized mining face production involves complex geological conditions; mining pressure; gas, water, fire and other mining environments. The working face needs a shearer, hydraulic support, a scraper conveyor and other equipment for coordination. The deep integration of intelligent technology with factors such as "humans, machines, the environment, and management" in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for coal mining robot technology systems, including single robots, robotized equipment, robot clusters and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve customized research and development and standardized production of various types of robots. A specific analysis was conducted on the research progress of common key technologies such as explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mine robot research and development is proposed. Moreover, robotic mining systems should be promoted to enhance the overall intelligence level and mining efficiency of mining equipment. To develop human‒machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots. The digital twinning of the entire mine robot system should be accelerated, the normalized operation level of coal mine robots should be improved, research on coal mining robots, support robots, and transportation robots should be carried out, intelligence should be achieved in fully mechanized mining faces, and equipment support for fewer and unmanned fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization has been summarized, and the technical and engineering feasibility of the coal mining machine population has been verified.