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Vehicle ad hoc networks (VANETs) are special wireless networks which help vehicles to obtain continuous and stable communication. Pseudonym revocation, as a vital security mechanism, is able to protect legal vehicles in VANETs. However, existing pseudonym-revocation schemes suffer from the issues of low certificate revocation list (CRL) generation and update efficiency, along with high CRL storage and transmission costs. In order to solve the above issues, this paper proposes an improved Morton-filter-based pseudonym-revocation scheme for VANETs (IMF-PR). IMF-PR establishes a new distributed CRL management mechanism to maintain a low CRL distribution transmission delay. In addition, IMF-PR improves the Morton filter to optimize the CRL management mechanism so as to improve CRL generation and update efficiency and reduce the CRL storage overhead. Moreover, CRLs in IMF-PR store illegal vehicle information based on an improved Morton filter data structure to improve the compress ratio and the query efficiency. Performance analysis and simulation experiments showed that IMF-PR can effectively reduce storage by increasing the compression gain and reducing transmission delay. In addition, IMF-PR can also greatly improve the lookup and update throughput on CRLs.

With the development of Intelligent Transportation Systems (ITS), Vehicular Ad hoc Networks (VANETs) have become a research hotspot in recent years. However, the vehicle communication system is vulnerable, resulting in threats to the privacy of users. This paper proposes a secure and efficient identity-based anonymous authentication scheme and uses pseudonyms to enhance the privacy protection of vehicle users. By improving the existing vehicle public key infrastructure and introducing Bloom filter to compress the Certificate Revocation List (CRL), the efficient pseudonym revocation scheme is then presented under the premise of ensuring user privacy. This scheme is able to perform batch pseudonym revocation and keep the pseudonym unlinkable. The security analysis shows that the proposed scheme is able to meet the security and privacy requirements in VANETs and CRL distribution.

Privacy disclosure has become a key challenge in vehicular ad hoc networks (VANETs). Although IEEE, ERSI, etc. suggest that a pseudonym-based scheme is a solution, how to support pseudonym management and vehicle authentication is still an open issue. In this paper, a secure VANETs authentication scheme (PAS) is proposed, where software-defined network (SDN) is integrated as a suitable infrastructure to support anonymous authentication and pseudonym management, while removing the requirement for pseudonym certification in the dynamic VANETs environment. The security and performance analysis indicate that PAS is able protect the privacy of vehicles and has a high efficiency.

In vehicular ad hoc networks (VANETs), pseudonym change is considered as the vital mechanism to support vehicles’ anonymity. Due to the complicated road conditions and network environment, it is a challenge to design an efficient and adaptive pseudonym change protocol. In this paper, a pseudonym change protocol for location privacy preserving (PCP) is proposed. We first present the requirements of pseudonym change in different scenarios. According to variable network states and road conditions, vehicles are able to take different pseudonym change strategies to resist the tracking by global passive adversaries. Furthermore, the registration protocol, authentication protocol, pseudonym issuance protocol, and pseudonym revocation protocol are introduced for the pseudonym management mechanism. As a consequence, it is not feasible for global passive adversaries to track a vehicle for a long time and obtain the trajectory of the vehicle. The analysis results show that the security and performance of PCP are improved compared with the traditional ones.

Jasmonates (JAs) regulate the defense of biotic and abiotic stresses, growth, development, and many other important biological processes in plants. The comprehensive proteomic profiling of plants under JAs treatment provides insights into the regulation mechanism of JAs. Isobaric tags for relative and absolute quantification (iTRAQ)-based quantitative proteomic analysis was performed on the Arabidopsis wild type (Ws) and JA synthesis deficiency mutant opr3-1. The effects of exogenous MeJA treatment on the proteome of opr3-1, which lacks endogenous JAs, were investigated. A total of 3683 proteins were identified and 126 proteins were differentially regulated between different genotypes and treatment groups. The functional classification of these differentially regulated proteins showed that they were involved in metabolic processes, responses to abiotic stress or biotic stress, the defense against pathogens and wounds, photosynthesis, protein synthesis, and developmental processes. Exogenous MeJA treatment induced the up-regulation of a large number of defense-related proteins and photosynthesis-related proteins, it also induced the down-regulation of many ribosomal proteins in opr3-1. These results were further verified by a quantitative real-time PCR (qRT-PCR) analysis of 15 selected genes. Our research provides the basis for further understanding the molecular mechanism of JAs’ regulation of plant defense, photosynthesis, protein synthesis, and development.

Abstract Background The metabolic score for visceral fat (METS-VF) quantifies the cumulative burden of visceral and intra-abdominal adipose tissues. However, the relationship between the METS-VF and carotid atherosclerosis (CAS) has not been extensively explored. Therefore, this study aimed to investigate the association between the METS-VF and CAS. Methods This cross-sectional study enrolled 7089 Chinese adults who underwent physical examinations at the Zhenhai Lianhua Hospital, Zhejiang, China, in 2020. Multivariable logistic regression analysis was used to explore the linear relationship between METS-VF and CAS. Generalised additive models (GAM) were employed to evaluate potential nonlinear associations. The inflection points of METS-VF were determined using segmented logistic regression analysis optimised for maximum likelihood ratios and recursive algorithms. Results Multivariable logistic regression analysis revealed a positive correlation between METS-VF and CAS (odds ratio [OR]: 1.824, 95% confidence interval [CI]: 1.753–1.899; P

The natural disasters faced by modern urban systems are complex, with multiple disaster-causing factors coexisting and secondary disasters occurring concurrently. With emergency management moving towards smart, natural disaster response has shifted from emergency-centered response to pre-disaster prevention. How to improve the government's natural disaster emergency preparedness has become an important issue that needs to be addressed. Based on the TOE (Technology-Organization-Environment) framework, the fsQCA method was used to explore the improvement path of emergency preparedness capacity of 10 pilot units in China to deal with natural disasters in 2020. Analyze the group effects and interrelationships of technology level, simultaneous supporting facilities, organizational construction, financial investment, external pressure, and social repercussions. The results show that: there exist four conditional groupings of high emergency preparedness in two modes. Two modes are organization-environment dual-drive and technology-organization-environment triple-drive, which have multiple concurrencies and follow the principle of consistent results. There are substitution effects in the conditional groupings of high emergency preparedness. There are causal asymmetries in the conditional groupings of high emergency preparedness and non-high emergency preparedness. This study aims to explore the smart emergency preparedness of ten pilot and to provide ideas for the overall development of “smart emergency response” and the improvement of emergency preparedness for natural disasters.

Abstract The multi‐layer screen is the key component in the large synchronous generator end zone. The leakage flux, losses, and temperature of end components are significantly affected by the thickness of multi‐layer screen in the synchronous generator. To investigate the influence of multi‐layer screen thickness on the end leakage flux, losses, and temperature in the synchronous generator end zone, 1407MVA nuclear power synchronous generator is studied. Three‐dimensional transient electromagnetic field model of synchronous generator end zone is established. Three‐dimensional transient electromagnetic field in the end zone of 1407MVA synchronous generator with the multi‐layer screen is calculated based on the novel iterative method. The flux density of end components is compared and studied in the end zone under the variation of multi‐layer screen thickness. Influence of the different thicknesses of multi‐layer screen on the losses of the shield plate, screen, finger plate, and stator end core is researched. The losses of end components obtained from 3D end electromagnetic field calculation are applied to the end zone as the heat source in the three‐dimensional fluid and thermal coupled field. The temperature distribution of the end components is determined. The accuracy of the calculated results is validated by the experimental values.

This study explores the application effect of the new non-isocyanate polyurethane curing agent on the rapid curing mechanism and bearing characteristics of piles in beach foundations. Through laboratory tests and field tests, the effects of the curing agent on the physical and mechanical properties of sand were systematically analyzed, including compressive strength, shear strength, and elastic modulus, and the effects of water content and cement–sand mass ratio on the properties of sand after curing were investigated. The results show that introducing a curing agent significantly improves the mechanical properties of sand, and the cohesion and internal friction angle increase exponentially with the sand mass ratio. In addition, the increase in water content leads to a decrease in the strength of solidified sand, and the microstructure analysis reveals the change in the bonding effect between the solidified gel and the sand particles. The field static load tests of single piles and pile groups verify the effectiveness of the rapid solidification pile in beach foundations and reveal the significant influence of pile length and pile diameter on the bearing capacity. This study provides a theoretical basis and technical support for the rapid solidification and reinforcement of tidal flat foundations and provides important guidance for related engineering applications.

ABSTRACTWC-Al2O3-graphene composite powder was synthesized by ultrasonic treatment and ball milling, then consolidated by hot pressing sintering (HPS). For potential applications, the friction coefficient and wear resistance of the sintered bulks at different temperatures (room temperature, 200, 400, and 600°C) were investigated. The wear tracks were characterized by scanning electron microscope, energy dispersive spectroscopy and Raman spectroscopy, X-ray photoelectron spectroscopy, respectively. The results show that the friction coefficient decreases and the wear rate increases with the increase of temperature, mainly because oxidization wear occurs on the wear surface of WC-Al2O3-graphene composite under high temperature. The main wear mechanism is the destruction and formation of tribochemical compacted layer. Graphene reduces the wear rate of WC-Al2O3-graphene composite under high tampere. The reason is that graphene reduces oxidation wear by blocking or absorbing oxygen; moreover, graphene reduces the cycle frequency of damage and reconstruction of tribochemical compacted layer by reducing the peeling of it.

Boolean operations on geometric models are important in numerical simulation and serve as essential tools in the fields of computer-aided design and computer graphics. The accuracy of these operations is heavily influenced by finite precision arithmetic, a commonly employed technique in geometric calculations, which introduces numerical approximations. To ensure robustness in Boolean operations, numerical methods relying on rational numbers or geometric predicates have been developed. These methods circumvent the accumulation of rounding errors during computation, thus preserving accuracy. Nonetheless, it is worth noting that these approaches often entail more intricate operation rules and data structures, consequently leading to longer computation times. In this paper, we present a straightforward and robust method for performing Boolean operations on both closed and open triangulated surfaces. Our approach aims to eliminate errors caused by floating-point operations by relying solely on entity indexing operations, without the need for coordinate computation. By doing so, we ensure the robustness required for Boolean operations. Our method consists of two main stages: (1) Firstly, candidate triangle intersection pairs are identified using an octree data structure, and then parallel algorithms are employed to compute the intersection lines for all pairs of triangles. (2) Secondly, closed or open intersection rings, sub-surfaces, and sub-blocks are formed, which is achieved entirely by cleaning and updating the mesh topology without geometric solid coordinate computation. Furthermore, we propose a novel method based on entity indexing to differentiate between the union, subtraction, and intersection of Boolean operation results, rather than relying on inner and outer classification. We validate the effectiveness of our method through various types of Boolean operations on triangulated surfaces.

Numerous software packages have emerged to implement the SPH method and are being used for the analysis of various scientific and engineering problems. Nevertheless, few efforts have been made to develop packages of SPH by considering both the efficiency and readability in balance. Considering efficiency and readability, we designed and developed a Julia-based open-source package of parallel SPH called juSPH. We described juSPH regarding the SPH methodology, software architecture, and software functionalities, and verified the accuracy and evaluated the efficiency by modeling a dam-break experiment. Furthermore, the modular structure of juSPH makes the code easily readable and facilitates further development.

BackgroundThe over-the-scope clip (OTSC) is an innovative device and has been successfully used in endoscopic treatment, however, there is a lack of clinical data from China. The aim of this study is to investigate the OTSC applications in the treatment of upper non-variceal gastrointestinal bleeding (UNVGIB), perforations, and fistulas in China.MethodsIn total, 80 patients were treated with one OTSC respectively as first-line therapy in our endoscopy center between January 2016 and November 2020. Among them, 41 patients had UNVGIB, 34 patients had perforations, and five patients had fistulas. The technical and clinical success rates were used to assess the efficacy of OTSC on the above diseases. In addition, we compared the hemostatic efficacy of OTSC with the standard endoscopic therapy in ulcer bleeding and Dieulafoy's lesion by propensity score matching analysis.ResultsIn general, the OTSCs were applied successfully in all patients and achieved 100% (80/80) technical success. The clinical success of all patients was 91.3% (73/80). Among 41 patients with UNVGIB, the clinical success was 85.4% (35/41); 6 patients presented with recurrence. For patients of Dieulafoy's lesion and under antithrombotic therapy, we found that OTSC treatment had both efficient and reliable hemostasis effects. In addition, according to the characteristics of ulcers, site of bleeding lesion, and Blatchford score, all patients received similar and reliable clinical success rates. After propensity score matching, we found that OTSC treatment had low rebleeding rates when compared with standard endoscopic therapy in both Dieulafoy's lesion (15.0 vs 30.0%) and ulcer bleeding (17.6 vs 29.4%). Among 34 patients with perforations, the clinical success was 100% (34/34). Among five patients with fistulas, only one patient failed in maintaining the OTSC before esophageal fistula healing, and the clip achieved an overall clinical success of 80% (4/5).ConclusionThe OTSC represents a safe and effective endoscopic therapy for UNVGIB, perforations, and fistulas as first-line treatment, especially for Dieulafoy's lesion or patients under antithrombotic therapy for UNVGIB, etc. However, OTSC application in these specific lesions or patients lacks adequate evidence as first-line treatment. Therefore, further larger sample and multi-center clinical trials are required to improve its indications in clinical treatment.

In this study, ethylene glycol diglycidyl ether (EGDE) and melamine (ME) were used to prepare a spherical composite material CMC-LTO-EGDE-ME through the strategy of cross-linking reaction of biodegradable sodium carboxymethyl cellulose (CMC) with Li2TiO3 (LTO) to improve the cycle stability of the adsorption-desorption for lithium recovery. In the geothermal water at 333.15°K, the adsorption capacity of the spherical composite adsorbent for lithium-ion is 12.02 mg/g, and the adsorption equilibrium time is 8 h. There is a good selectivity of Li+ (Kd = 3.7 × 103) and high separation factors between Li+ and Na+, K+, Cs+ and Ca2+ (between 39.17 and 181.97). Studies on adsorption kinetics and adsorption isotherm showed that composite material’s adsorption process was obtained from the pseudosecond-order kinetics and the molecular diffusion model. It was found that the composite material has broad applications in lithium recovery from geothermal water.

The brake system is a key component to ensuring the safe driving and riding comfort of the vehicle, and the friction between the brake disc and the friction plate is the main source of vibration and noise. Therefore, in order to improve the stability of the braking system and reduce the generation of vibration, a six-degree-of-freedom nonlinear dynamics model was established, and using the Stribeck friction model and related parameters, the dynamic equation was solved by the Runge-Kutta method. The bifurcation diagram, Lyapunov diagram, time domain diagram, frequency spectrum diagram, and phase plane diagram of the brake pad and brake disc during friction braking were obtained, and the vibration characteristics of both under different braking pressure, braking speed, brake pad support stiffness, and brake disc support stiffness were analyzed. The results show that brake pressure is an important factor in triggering nonlinear vibration; increasing the braking speed will increase the amplitude of vibration, but will shorten the time to enter the stable motion state, and increasing the support stiffness brake pad and disc will reduce the amplitude of system vibration.

The accurate classification of traffic data is challenging for network management and security, especially in imbalanced situations. The limitation of the existing convolutional neural networks is that they have problems such as overfitting, instability, and poor generalization when used to classify imbalanced datasets. In this paper, we propose a new imbalanced encrypted traffic classification model. The proposed model is based on the improved convolutional block attention module (CBAM) and re-weighted cross-entropy focal loss (CEFL) function. The model exploits the redefined imbalance degree to construct a weight function, which is used to reassign the weights of the categories. The improved CBAM based on the redefined imbalance degree can make the model pay more attention to the characteristics of the minority samples, and increase the representation ability of these samples. The re-weighted CEFL loss function can be used to expand the effective loss gap between minority and majority samples. The method is validated on the public ISCX Tor 2016 dataset. The experimental results show that the performance of the new classification model is better than the baseline methods, and the proposed method can remarkably push the precision of the minority categories to 93.28% (14.63%↑), recall to 91.71% (16.98%↑), and F1 score to 92.49% (16.23%↑).

The remote sensing satellite constellation based on micro-satellites is an important means to construct a global and all-sky earth observation system in the future. Therefore, realizing the recognition of aircraft activities on video micro-satellites is a key technology that needs to be solved urgently. In this paper, an efficient algorithm for aircraft activity recognition that can be deployed on video micro-satellites was proposed. First, aircraft detection was performed on the first incoming remote sensing image using a robust DCNN-based object detection model. Then, a multi-target tracking model incorporating geospatial information was built for aircraft tracking and activity recognition. The algorithm was deployed on an embedded AI computer which was a COTS component. The algorithm was verified using remote sensing videos from commercial micro-satellites. Experimental results show that the algorithm can process aircraft targets of different sizes, and is equally effective even with complex environmental backgrounds, lighting conditions, and various movements of the aircraft, such as turning, entering, and exiting. Based on aircraft tracking results and geospatial information, the motion speed of each aircraft can be obtained, and its activity can be divided into parking, taxiing, or flying. The scheme proposed in this paper has good application prospects in the realization of on-orbit event recognition in micro-satellites with limited computing and memory resources.

In this paper, a parallel Smoothed Finite Element Method (S-FEM) package epSFEM using incremental theory to solve elastoplastic problems is developed by employing the Julia language on a multicore CPU. The S-FEM, a new numerical method combining the Finite Element Method (FEM) and strain smoothing technique, was proposed by Liu G.R. in recent years. The S-FEM model is softer than the FEM model for identical grid structures, has lower sensitivity to mesh distortion, and usually produces more accurate solutions and a higher convergence speed. Julia, as an efficient, user-friendly and open-source programming language, balances computational performance, programming difficulty and code readability. We validate the performance of the epSFEM with two sets of benchmark tests. The benchmark results indicate that (1) the calculation accuracy of epSFEM is higher than that of the FEM when employing the same mesh model; (2) the commercial FEM software requires 10,619 s to calculate an elastoplastic model consisting of approximately 2.45 million triangular elements, while in comparison, epSFEM requires only 5876.3 s for the same computational model; and (3) epSFEM executed in parallel on a 24-core CPU is approximately 10.6 times faster than the corresponding serial version.

The rational use of a large amount of straw produced from grain fields is an important issue in major grain-producing areas. On the other hand, due to the long-term preferential applications of chemical fertilizers, soil organic carbon (SOC) content, soil fertility and organic matter levels have decreased, and the soil physical-chemical properties have deteriorated in protected agricultural facilities. In this study, a wet crop, taro (Colocasia esculenta (L.) Schott) and the straw of two main crops [wheat (Triticum aestivum L.) and rice (Oryza sativa L.)] were selected to investigate the effect of row-surface straw mulching on taro yields and soil chemical properties. The results showed that nearly all wheat straw and 74% of rice straw decomposed in one season under wet conditions. Straw mulching significantly increased the taro yield, increased the levels of SOC, soil rapid available nitrogen, phosphorus and potassium, and improved the activities of sucrase and phosphatase in the soil. We conclude that row-surface straw mulching t of wet crops could not only improve the soil properties and crop yields in the protected facility but could also consume considerable straw (wheat: 14,250 kg/ha, rice: 111,00 kg/ha), and the method applied in other areas with similar conditions.

The outcomes of double-bundle anterior cruciate ligament (ACL) reconstruction leave room for improvement. We hope to augment double-bundle ACL reconstruction with the reconstruction of an ACL-mimicking anterolateral structure (ALS). Thus, we would like to introduce a combined double-bundle ACL reconstruction and ACL-mimicking ALS reconstruction technique. The main indication for this technique is ACL injury with a high degree of pivot shift test, general laxity, or near critical value of the posterior tibial slope. The main steps in this technique include preparation of an isolated graft for the anteromedial bundle of the ACL and a combined graft for the posterolateral bundle of the ACL and ALS, creation of three tibial tunnels and two femoral tunnels, graft placement, and final graft fixation at an adjustable loop. We have obtained promising clinical outcomes with this technique and consider that this report will provide new options in ACL reconstruction.

The stock market is known for its extreme complexity and volatility, and people are always looking for an accurate and effective way to guide stock trading. Long short-term memory (LSTM) neural networks are developed by recurrent neural networks (RNN) and have significant application value in many fields. In addition, LSTM avoids long-term dependence issues due to its unique storage unit structure, and it helps predict financial time series. Based on LSTM and an attention mechanism, a wavelet transform is used to denoise historical stock data, extract and train its features, and establish the prediction model of a stock price. We compared the results with the other three models, including the LSTM model, the LSTM model with wavelet denoising and the gated recurrent unit(GRU) neural network model on S&P 500, DJIA, HSI datasets. Results from experiments on the S&P 500 and DJIA datasets show that the coefficient of determination of the attention-based LSTM model is both higher than 0.94, and the mean square error of our model is both lower than 0.05.

A method for measuring pork freshness based on images and the EfficientNet framework was established. A total of 2 500 images of pork with different freshness were collected as original dataset and processed by image enhancement to construct a new dataset of 60 000 images. First, EfficientNet was trained with the CIFAR-10 dataset to determine the basic structure and initial weights of the model. Then, the model was trained and improved using the constructed dataset to make the model suitable for five classification problems. Finally, the established model was tested, verified, and compared with the current mainstream convolutional neural network (CNN) models of Alexnet, VGG16 and ResNet50. The results showed that the average correct recognition rate of the EfficientNet model was as high as 98.62%, which was significantly better than that of the Alexnet, VGG16 and ResNet50 models. The correct recognition rate of the EfficientNetB2 model was 99.22%, and the training time was only 157 min. The comprehensive performance of the EfficientNetB2 model was the best, making it the most suitable method for pork freshness identification. In order to improve its generalization ability, the optimizer algorithm of the EfficientNetB2 model was improved, and the performances of stochastic gradient descent (SGD), adaptive moment estimation (Adam), root mean square propagation (RMSProp) and rectified adaptive moment estimation (RAdam) were compared. The results showed that the RAdam optimizer failed to further improve the accuracy of the model but instead helped to improve its generalization capability, which will of practical significance for engineering applications.